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Validation of 3D ultrasound: CT registration of prostate images
NASA Astrophysics Data System (ADS)
Firle, Evelyn A.; Wesarg, Stefan; Karangelis, Grigoris; Dold, Christian
All over the world 20% of men are expected to develop prostate cancer sometime in his life. In addition to surgery - being the traditional treatment for cancer - the radiation treatment is getting more popular. The most interesting radiation treatment regarding prostate cancer is Brachytherapy radiation procedure. For the safe delivery of that therapy imaging is critically important. In several cases where a CT device is available a combination of the information provided by CT and 3D Ultrasound (U/S) images offers advantages in recognizing the borders of the lesion and delineating the region of treatment. For these applications the CT and U/S scans should be registered and fused in a multi-modal dataset. Purpose of the present development is a registration tool (registration, fusion and validation) for available CT volumes with 3D U/S images of the same anatomical region, i.e. the prostate. The combination of these two imaging modalities interlinks the advantages of the high-resolution CT imaging and low cost real-time U/S imaging and offers a multi-modality imaging environment for further target and anatomy delineation. This tool has been integrated into the visualization software "InViVo" which has been developed over several years in Fraunhofer IGD in Darmstadt.
Algorithm of pulmonary emphysema extraction using thoracic 3D CT images
NASA Astrophysics Data System (ADS)
Saita, Shinsuke; Kubo, Mitsuru; Kawata, Yoshiki; Niki, Noboru; Nakano, Yasutaka; Ohmatsu, Hironobu; Tominaga, Keigo; Eguchi, Kenji; Moriyama, Noriyuki
Recently, due to aging and smoking, emphysema patients are increasing. The restoration of alveolus which was destroyed by emphysema is not possible, thus early detection of emphysema is desired. We describe a quantitative algorithm for extracting emphysematous lesions and quantitatively evaluate their distribution patterns using low dose thoracic 3-D CT images. The algorithm identified lung anatomies, and extracted low attenuation area (LAA) as emphysematous lesion candidates. Applying the algorithm to thoracic 3-D CT images and then by follow-up 3-D CT images, we demonstrate its potential effectiveness to assist radiologists and physicians to quantitatively evaluate the emphysematous lesions distribution and their evolution in time interval changes.
Computation of tooth axes of existent and missing teeth from 3D CT images.
Wang, Yang; Wu, Lin; Guo, Huayan; Qiu, Tiantian; Huang, Yuanliang; Lin, Bin; Wang, Lisheng
Orientations of tooth axes are important quantitative information used in dental diagnosis and surgery planning. However, their computation is a complex problem, and the existing methods have respective limitations. This paper proposes new methods to compute 3D tooth axes from 3D CT images for existent teeth with single root or multiple roots and to estimate 3D tooth axes from 3D CT images for missing teeth. The tooth axis of a single-root tooth will be determined by segmenting the pulp cavity of the tooth and computing the principal direction of the pulp cavity, and the estimation of tooth axes of the missing teeth is modeled as an interpolation problem of some quaternions along a 3D curve. The proposed methods can either avoid the difficult teeth segmentation problem or improve the limitations of existing methods. Their effectiveness and practicality are demonstrated by experimental results of different 3D CT images from the clinic.
In vivo 3D PIXE-micron-CT imaging of Drosophila melanogaster using a contrast agent
NASA Astrophysics Data System (ADS)
Matsuyama, Shigeo; Hamada, Naoki; Ishii, Keizo; Nozawa, Yuichiro; Ohkura, Satoru; Terakawa, Atsuki; Hatori, Yoshinobu; Fujiki, Kota; Fujiwara, Mitsuhiro; Toyama, Sho
In this study, we developed a three-dimensional (3D) computed tomography (CT) in vivo imaging system for imaging small insects with micrometer resolution. The 3D CT imaging system, referred to as 3D PIXE-micron-CT (PIXEμCT), uses characteristic X-rays produced by ion microbeam bombardment of a metal target. PIXEμCT was used to observe the body organs and internal structure of a living Drosophila melanogaster. Although the organs of the thorax were clearly imaged, the digestive organs in the abdominal cavity could not be clearly discerned initially, with the exception of the rectum and the Malpighian tubule. To enhance the abdominal images, a barium sulfate powder radiocontrast agent was added. For the first time, 3D images of the ventriculus of a living D. melanogaster were obtained. Our results showed that PIXEμCT can provide in vivo 3D-CT images that reflect correctly the structure of individual living organs, which is expected to be very useful in biological research.
Accuracy of volume measurement using 3D ultrasound and development of CT-3D US image fusion algorithm for prostate cancer radiotherapy
Baek, Jihye; Huh, Jangyoung; Hyun An, So; Oh, Yoonjin; Kim, Myungsoo; Kim, DongYoung; Chung, Kwangzoo; Cho, Sungho; Lee, Rena
Purpose: To evaluate the accuracy of measuring volumes using three-dimensional ultrasound (3D US), and to verify the feasibility of the replacement of CT-MR fusion images with CT-3D US in radiotherapy treatment planning. Methods: Phantoms, consisting of water, contrast agent, and agarose, were manufactured. The volume was measured using 3D US, CT, and MR devices. A CT-3D US and MR-3D US image fusion software was developed using the Insight Toolkit library in order to acquire three-dimensional fusion images. The quality of the image fusion was evaluated using metric value and fusion images. Results: Volume measurement, using 3D US, shows a 2.8 {+-} 1.5% error, 4.4 {+-} 3.0% error for CT, and 3.1 {+-} 2.0% error for MR. The results imply that volume measurement using the 3D US devices has a similar accuracy level to that of CT and MR. Three-dimensional image fusion of CT-3D US and MR-3D US was successfully performed using phantom images. Moreover, MR-3D US image fusion was performed using human bladder images. Conclusions: 3D US could be used in the volume measurement of human bladders and prostates. CT-3D US image fusion could be used in monitoring the target position in each fraction of external beam radiation therapy. Moreover, the feasibility of replacing the CT-MR image fusion to the CT-3D US in radiotherapy treatment planning was verified.
ERIC Educational Resources Information Center
Hastings, S. K.
Discusses 3 D imaging as it relates to digital representations in virtual library collections. Highlights include X-ray computed tomography (X-ray CT); the National Science Foundation (NSF) Digital Library Initiatives; output peripherals; image retrieval systems, including metadata; and applications of 3 D imaging for libraries and museums. (LRW)
3D CT-Video Fusion for Image-Guided Bronchoscopy
Higgins, William E.; Helferty, James P.; Lu, Kongkuo; Merritt, Scott A.; Rai, Lav; Yu, Kun-Chang
Bronchoscopic biopsy of the central-chest lymph nodes is an important step for lung-cancer staging. Before bronchoscopy, the physician first visually assesses a patient's three-dimensional (3D) computed tomography (CT) chest scan to identify suspect lymph-node sites. Next, during bronchoscopy, the physician guides the bronchoscope to each desired lymph-node site. Unfortunately, the physician has no link between the 3D CT image data and the live video stream provided during bronchoscopy. Thus, the physician must essentially perform biopsy blindly, and the skill levels between different physicians differ greatly. We describe an approach that enables synergistic fusion between the 3D CT data and the bronchoscopic video. Both the integrated planning and guidance system and the internal CT-video registration and fusion methods are described. Phantom, animal, and human studies illustrate the efficacy of the methods. PMID:18096365
TBIdoc: 3D content-based CT image retrieval system for traumatic brain injury
NASA Astrophysics Data System (ADS)
Li, Shimiao; Gong, Tianxia; Wang, Jie; Liu, Ruizhe; Tan, Chew Lim; Leong, Tze Yun; Pang, Boon Chuan; Lim, C. C. Tchoyoson; Lee, Cheng Kiang; Tian, Qi; Zhang, Zhuo
Traumatic brain injury (TBI) is a major cause of death and disability. Computed Tomography (CT) scan is widely used in the diagnosis of TBI. Nowadays, large amount of TBI CT data is stacked in the hospital radiology department. Such data and the associated patient information contain valuable information for clinical diagnosis and outcome prediction. However, current hospital database system does not provide an efficient and intuitive tool for doctors to search out cases relevant to the current study case. In this paper, we present the TBIdoc system: a content-based image retrieval (CBIR) system which works on the TBI CT images. In this web-based system, user can query by uploading CT image slices from one study, retrieval result is a list of TBI cases ranked according to their 3D visual similarity to the query case. Specifically, cases of TBI CT images often present diffuse or focal lesions. In TBIdoc system, these pathological image features are represented as bin-based binary feature vectors. We use the Jaccard-Needham measure as the similarity measurement. Based on these, we propose a 3D similarity measure for computing the similarity score between two series of CT slices. nDCG is used to evaluate the system performance, which shows the system produces satisfactory retrieval results. The system is expected to improve the current hospital data management in TBI and to give better support for the clinical decision-making process. It may also contribute to the computer-aided education in TBI.
Evaluation of accuracy of 3D reconstruction images using multi-detector CT and cone-beam CT
Kim, Mija; YI, Won-Jin; Heo, Min-Suk; Lee, Sam-Sun; Choi, Soon-Chul
Purpose This study was performed to determine the accuracy of linear measurements on three-dimensional (3D) images using multi-detector computed tomography (MDCT) and cone-beam computed tomography (CBCT). Materials and Methods MDCT and CBCT were performed using 24 dry skulls. Twenty-one measurements were taken on the dry skulls using digital caliper. Both types of CT data were imported into OnDemand software and identification of landmarks on the 3D surface rendering images and calculation of linear measurements were performed. Reproducibility of the measurements was assessed using repeated measures ANOVA and ICC, and the measurements were statistically compared using a Student t-test. Results All assessments under the direct measurement and image-based measurements on the 3D CT surface rendering images using MDCT and CBCT showed no statistically difference under the ICC examination. The measurements showed no differences between the direct measurements of dry skull and the image-based measurements on the 3D CT surface rendering images (P>.05). Conclusion Three-dimensional reconstructed surface rendering images using MDCT and CBCT would be appropriate for 3D measurements. PMID:22474645
3D segmentation and image annotation for quantitative diagnosis in lung CT images with pulmonary lesions
NASA Astrophysics Data System (ADS)
Li, Suo; Zhu, Yanjie; Sun, Jianyong; Zhang, Jianguo
Pulmonary nodules and ground glass opacities are highly significant findings in high-resolution computed tomography (HRCT) of patients with pulmonary lesion. The appearances of pulmonary nodules and ground glass opacities show a relationship with different lung diseases. According to corresponding characteristic of lesion, pertinent segment methods and quantitative analysis are helpful for control and treat diseases at an earlier and potentially more curable stage. Currently, most of the studies have focused on two-dimensional quantitative analysis of these kinds of deceases. Compared to two-dimensional images, three-dimensional quantitative analysis can take full advantage of isotropic image data acquired by using thin slicing HRCT in space and has better quantitative precision for clinical diagnosis. This presentation designs a computer-aided diagnosis component to segment 3D disease areas of nodules and ground glass opacities in lung CT images, and use AIML (Annotation and image makeup language) to annotate the segmented 3D pulmonary lesions with information of quantitative measurement which may provide more features and information to the radiologists in clinical diagnosis.
Imaging Properties of 3D Printed Materials: Multi-Energy CT of Filament Polymers.
Shin, James; Sandhu, Ranjit S; Shih, George
Clinical applications of 3D printing are increasingly commonplace, likewise the frequency of inclusion of 3D printed objects on imaging studies. Although there is a general familiarity with the imaging appearance of traditional materials comprising common surgical hardware and medical devices, comparatively less is known regarding the appearance of available 3D printing materials in the consumer market. This work detailing the CT appearance of a selected number of common filament polymer classes is an initial effort to catalog these data, to provide for accurate interpretation of imaging studies incidentally or intentionally including fabricated objects. Furthermore, this information can inform the design of image-realistic tissue-mimicking phantoms for a variety of applications, with clear candidate material analogs for bone, soft tissue, water, and fat attenuation.
Segmentation of brain blood vessels using projections in 3-D CT angiography images.
Babin, Danilo; Vansteenkiste, Ewout; Pizurica, Aleksandra; Philips, Wilfried
Segmenting cerebral blood vessels is of great importance in diagnostic and clinical applications, especially in quantitative diagnostics and surgery on aneurysms and arteriovenous malformations (AVM). Segmentation of CT angiography images requires algorithms robust to high intensity noise, while being able to segment low-contrast vessels. Because of this, most of the existing methods require user intervention. In this work we propose an automatic algorithm for efficient segmentation of 3-D CT angiography images of cerebral blood vessels. Our method is robust to high intensity noise and is able to accurately segment blood vessels with high range of luminance values, as well as low-contrast vessels.
Computer-aided diagnosis for osteoporosis using chest 3D CT images
NASA Astrophysics Data System (ADS)
Yoneda, K.; Matsuhiro, M.; Suzuki, H.; Kawata, Y.; Niki, N.; Nakano, Y.; Ohmatsu, H.; Kusumoto, M.; Tsuchida, T.; Eguchi, K.; Kaneko, M.
The patients of osteoporosis comprised of about 13 million people in Japan and it is one of the problems the aging society has. In order to prevent the osteoporosis, it is necessary to do early detection and treatment. Multi-slice CT technology has been improving the three dimensional (3-D) image analysis with higher body axis resolution and shorter scan time. The 3-D image analysis using multi-slice CT images of thoracic vertebra can be used as a support to diagnose osteoporosis and at the same time can be used for lung cancer diagnosis which may lead to early detection. We develop automatic extraction and partitioning algorithm for spinal column by analyzing vertebral body structure, and the analysis algorithm of the vertebral body using shape analysis and a bone density measurement for the diagnosis of osteoporosis. Osteoporosis diagnosis support system obtained high extraction rate of the thoracic vertebral in both normal and low doses.
SU-E-J-209: Verification of 3D Surface Registration Between Stereograms and CT Images
Han, T; Gifford, K; Smith, B; Salehpour, M
Purpose: Stereography can provide a visualization of the skin surface for radiation therapy patients. The aim of this study was to verify the registration algorithm in a commercial image analysis software, 3dMDVultus, for the fusion of stereograms and CT images. Methods: CT and stereographic scans were acquired of a head phantom and a deformable phantom. CT images were imported in 3dMDVultus and the surface contours were generated by threshold segmentation. Stereograms were reconstructed in 3dMDVultus. The resulting surfaces were registered with Vultus algorithm and then exported to in-house registration software and compared with four algorithms: rigid, affine, non-rigid iterative closest point (ICP) and b-spline algorithm. RMS (root-mean-square residuals of the surface point distances) error between the registered CT and stereogram surfaces was calculated and analyzed. Results: For the head phantom, the maximum RMS error between registered CT surfaces to stereogram was 6.6 mm for Vultus algorithm, whereas the mean RMS error was 0.7 mm. For the deformable phantom, the maximum RMS error was 16.2 mm for Vultus algorithm, whereas the mean RMS error was 4.4 mm. Non-rigid ICP demonstrated the best registration accuracy, as the mean of RMS errors were both within 1 mm. Conclusion: The accuracy of registration algorithm in 3dMDVultus was verified and exceeded RMS of 2 mm for deformable cases. Non-rigid ICP and b-spline algorithms improve the registration accuracy for both phantoms, especially in deformable one. For those patients whose body habitus deforms during radiation therapy, more advanced nonrigid algorithms need to be used.
Improving Low-dose Cardiac CT Images based on 3D Sparse Representation
NASA Astrophysics Data System (ADS)
Shi, Luyao; Hu, Yining; Chen, Yang; Yin, Xindao; Shu, Huazhong; Luo, Limin; Coatrieux, Jean-Louis
Cardiac computed tomography (CCT) is a reliable and accurate tool for diagnosis of coronary artery diseases and is also frequently used in surgery guidance. Low-dose scans should be considered in order to alleviate the harm to patients caused by X-ray radiation. However, low dose CT (LDCT) images tend to be degraded by quantum noise and streak artifacts. In order to improve the cardiac LDCT image quality, a 3D sparse representation-based processing (3D SR) is proposed by exploiting the sparsity and regularity of 3D anatomical features in CCT. The proposed method was evaluated by a clinical study of 14 patients. The performance of the proposed method was compared to the 2D spares representation-based processing (2D SR) and the state-of-the-art noise reduction algorithm BM4D. The visual assessment, quantitative assessment and qualitative assessment results show that the proposed approach can lead to effective noise/artifact suppression and detail preservation. Compared to the other two tested methods, 3D SR method can obtain results with image quality most close to the reference standard dose CT (SDCT) images.
Improving Low-dose Cardiac CT Images based on 3D Sparse Representation
Shi, Luyao; Hu, Yining; Chen, Yang; Yin, Xindao; Shu, Huazhong; Luo, Limin; Coatrieux, Jean-Louis
Cardiac computed tomography (CCT) is a reliable and accurate tool for diagnosis of coronary artery diseases and is also frequently used in surgery guidance. Low-dose scans should be considered in order to alleviate the harm to patients caused by X-ray radiation. However, low dose CT (LDCT) images tend to be degraded by quantum noise and streak artifacts. In order to improve the cardiac LDCT image quality, a 3D sparse representation-based processing (3D SR) is proposed by exploiting the sparsity and regularity of 3D anatomical features in CCT. The proposed method was evaluated by a clinical study of 14 patients. The performance of the proposed method was compared to the 2D spares representation-based processing (2D SR) and the state-of-the-art noise reduction algorithm BM4D. The visual assessment, quantitative assessment and qualitative assessment results show that the proposed approach can lead to effective noise/artifact suppression and detail preservation. Compared to the other two tested methods, 3D SR method can obtain results with image quality most close to the reference standard dose CT (SDCT) images. PMID:26980176
Improving Low-dose Cardiac CT Images based on 3D Sparse Representation.
Shi, Luyao; Hu, Yining; Chen, Yang; Yin, Xindao; Shu, Huazhong; Luo, Limin; Coatrieux, Jean-Louis
Cardiac computed tomography (CCT) is a reliable and accurate tool for diagnosis of coronary artery diseases and is also frequently used in surgery guidance. Low-dose scans should be considered in order to alleviate the harm to patients caused by X-ray radiation. However, low dose CT (LDCT) images tend to be degraded by quantum noise and streak artifacts. In order to improve the cardiac LDCT image quality, a 3D sparse representation-based processing (3D SR) is proposed by exploiting the sparsity and regularity of 3D anatomical features in CCT. The proposed method was evaluated by a clinical study of 14 patients. The performance of the proposed method was compared to the 2D spares representation-based processing (2D SR) and the state-of-the-art noise reduction algorithm BM4D. The visual assessment, quantitative assessment and qualitative assessment results show that the proposed approach can lead to effective noise/artifact suppression and detail preservation. Compared to the other two tested methods, 3D SR method can obtain results with image quality most close to the reference standard dose CT (SDCT) images.
3D visualization of biomedical CT images based on OpenGL and VRML techniques
NASA Astrophysics Data System (ADS)
Yin, Meng; Luo, Qingming; Xia, Fuhua
Current high-performance computers and advanced image processing capabilities have made the application of three- dimensional visualization objects in biomedical computer tomographic (CT) images facilitate the researches on biomedical engineering greatly. Trying to cooperate with the update technology using Internet, where 3D data are typically stored and processed on powerful servers accessible by using TCP/IP, we should hold the results of the isosurface be applied in medical visualization generally. Furthermore, this project is a future part of PACS system our lab is working on. So in this system we use the 3D file format VRML2.0, which is used through the Web interface for manipulating 3D models. In this program we implemented to generate and modify triangular isosurface meshes by marching cubes algorithm. Then we used OpenGL and MFC techniques to render the isosurface and manipulating voxel data. This software is more adequate visualization of volumetric data. The drawbacks are that 3D image processing on personal computers is rather slow and the set of tools for 3D visualization is limited. However, these limitations have not affected the applicability of this platform for all the tasks needed in elementary experiments in laboratory or data preprocessed.
GPU-Based 3D Cone-Beam CT Image Reconstruction for Large Data Volume
Zhao, Xing; Hu, Jing-jing; Zhang, Peng
Currently, 3D cone-beam CT image reconstruction speed is still a severe limitation for clinical application. The computational power of modern graphics processing units (GPUs) has been harnessed to provide impressive acceleration of 3D volume image reconstruction. For extra large data volume exceeding the physical graphic memory of GPU, a straightforward compromise is to divide data volume into blocks. Different from the conventional Octree partition method, a new partition scheme is proposed in this paper. This method divides both projection data and reconstructed image volume into subsets according to geometric symmetries in circular cone-beam projection layout, and a fast reconstruction for large data volume can be implemented by packing the subsets of projection data into the RGBA channels of GPU, performing the reconstruction chunk by chunk and combining the individual results in the end. The method is evaluated by reconstructing 3D images from computer-simulation data and real micro-CT data. Our results indicate that the GPU implementation can maintain original precision and speed up the reconstruction process by 110–120 times for circular cone-beam scan, as compared to traditional CPU implementation. PMID:19730744
Pore detection in Computed Tomography (CT) soil 3D images using singularity map analysis
NASA Astrophysics Data System (ADS)
Sotoca, Juan J. Martin; Tarquis, Ana M.; Saa Requejo, Antonio; Grau, Juan B.
X-ray Computed Tomography (CT) images have significantly helped the study of the internal soil structure. This technique has two main advantages: 1) it is a non-invasive technique, i.e., it doesńt modify the internal soil structure, and 2) it provides a good resolution. The major disadvantage is that these images are sometimes low-contrast in the solid/pore interface. One of the main problems in analyzing soil structure through CT images is to segment them in solid/pore space. To do so, we have different segmentation techniques at our disposal that are mainly based on thresholding methods in which global or local thresholds are calculated to separate pore space from solid space. The aim of this presentation is to develop the fractal approach to soil structure using "singularity maps" and the "Concentration-Area (CA) method". We will establish an analogy between mineralization processes in ore deposits and morphogenesis processes in soils. Resulting from this analogy a new 3D segmentation method is proposed, the "3D Singularity-CA" method. A comparison with traditional 3D segmentation methods will be performed to show the main differences among them.
CT image artifacts from brachytherapy seed implants: A postprocessing 3D adaptive median filter
Basran, Parminder S.; Robertson, Andrew; Wells, Derek
Purpose: To design a postprocessing 3D adaptive median filter that minimizes streak artifacts and improves soft-tissue contrast in postoperative CT images of brachytherapy seed implantations. Methods: The filter works by identifying voxels that are likely streaks and estimating more reflective voxel intensity by using voxel intensities in adjacent CT slices and applying a median filter over voxels not identified as seeds. Median values are computed over a 5x5x5 mm region of interest (ROI) within the CT volume. An acrylic phantom simulating a clinical seed implant arrangement and containing nonradioactive seeds was created. Low contrast subvolumes of tissuelike material were also embedded in the phantom. Pre- and postprocessed image quality metrics were compared using the standard deviation of ROIs between the seeds, the CT numbers of low contrast ROIs embedded within the phantom, the signal to noise ratio (SNR), and the contrast to noise ratio (CNR) of the low contrast ROIs. The method was demonstrated with a clinical postimplant CT dataset. Results: After the filter was applied, the standard deviation of CT values in streak artifact regions was significantly reduced from 76.5 to 7.2 HU. Within the observable low contrast plugs, the mean of all ROI standard deviations was significantly reduced from 60.5 to 3.9 HU, SNR significantly increased from 2.3 to 22.4, and CNR significantly increased from 0.2 to 4.1 (all P<0.01). The mean CT in the low contrast plugs remained within 5 HU of the original values. Conclusion: An efficient postprocessing filter that does not require access to projection data, which can be applied irrespective of CT scan parameters has been developed, provided the slice thickness and spacing is 3 mm or less.
Segmentation of bone structures in 3D CT images based on continuous max-flow optimization
NASA Astrophysics Data System (ADS)
Pérez-Carrasco, J. A.; Acha-Piñero, B.; Serrano, C.
In this paper an algorithm to carry out the automatic segmentation of bone structures in 3D CT images has been implemented. Automatic segmentation of bone structures is of special interest for radiologists and surgeons to analyze bone diseases or to plan some surgical interventions. This task is very complicated as bones usually present intensities overlapping with those of surrounding tissues. This overlapping is mainly due to the composition of bones and to the presence of some diseases such as Osteoarthritis, Osteoporosis, etc. Moreover, segmentation of bone structures is a very time-consuming task due to the 3D essence of the bones. Usually, this segmentation is implemented manually or with algorithms using simple techniques such as thresholding and thus providing bad results. In this paper gray information and 3D statistical information have been combined to be used as input to a continuous max-flow algorithm. Twenty CT images have been tested and different coefficients have been computed to assess the performance of our implementation. Dice and Sensitivity values above 0.91 and 0.97 respectively were obtained. A comparison with Level Sets and thresholding techniques has been carried out and our results outperformed them in terms of accuracy.
Micro-CT images reconstruction and 3D visualization for small animal studying
NASA Astrophysics Data System (ADS)
Gong, Hui; Liu, Qian; Zhong, Aijun; Ju, Shan; Fang, Quan; Fang, Zheng
A small-animal x-ray micro computed tomography (micro-CT) system has been constructed to screen laboratory small animals and organs. The micro-CT system consists of dual fiber-optic taper-coupled CCD detectors with a field-of-view of 25x50 mm2, a microfocus x-ray source, a rotational subject holder. For accurate localization of rotation center, coincidence between the axis of rotation and centre of image was studied by calibration with a polymethylmethacrylate cylinder. Feldkamp"s filtered back-projection cone-beam algorithm is adopted for three-dimensional reconstruction on account of the effective corn-beam angle is 5.67° of the micro-CT system. 200x1024x1024 matrix data of micro-CT is obtained with the magnification of 1.77 and pixel size of 31x31μm2. In our reconstruction software, output image size of micro-CT slices data, magnification factor and rotation sample degree can be modified in the condition of different computational efficiency and reconstruction region. The reconstructed image matrix data is processed and visualization by Visualization Toolkit (VTK). Data parallelism of VTK is performed in surface rendering of reconstructed data in order to improve computing speed. Computing time of processing a 512x512x512 matrix datasets is about 1/20 compared with serial program when 30 CPU is used. The voxel size is 54x54x108 μm3. The reconstruction and 3-D visualization images of laboratory rat ear are presented.
A universal approach for automatic organ segmentations on 3D CT images based on organ localization and 3D GrabCut
NASA Astrophysics Data System (ADS)
Zhou, Xiangrong; Ito, Takaaki; Zhou, Xinxin; Chen, Huayue; Hara, Takeshi; Yokoyama, Ryujiro; Kanematsu, Masayuki; Hoshi, Hiroaki; Fujita, Hiroshi
This paper describes a universal approach to automatic segmentation of different internal organ and tissue regions in three-dimensional (3D) computerized tomography (CT) scans. The proposed approach combines object localization, a probabilistic atlas, and 3D GrabCut techniques to achieve automatic and quick segmentation. The proposed method first detects a tight 3D bounding box that contains the target organ region in CT images and then estimates the prior of each pixel inside the bounding box belonging to the organ region or background based on a dynamically generated probabilistic atlas. Finally, the target organ region is separated from the background by using an improved 3D GrabCut algorithm. A machine-learning method is used to train a detector to localize the 3D bounding box of the target organ using template matching on a selected feature space. A content-based image retrieval method is used for online generation of a patient-specific probabilistic atlas for the target organ based on a database. A 3D GrabCut algorithm is used for final organ segmentation by iteratively estimating the CT number distributions of the target organ and backgrounds using a graph-cuts algorithm. We applied this approach to localize and segment twelve major organ and tissue regions independently based on a database that includes 1300 torso CT scans. In our experiments, we randomly selected numerous CT scans and manually input nine principal types of inner organ regions for performance evaluation. Preliminary results showed the feasibility and efficiency of the proposed approach for addressing automatic organ segmentation issues on CT images.
Integration of 3D anatomical data obtained by CT imaging and 3D optical scanning for computer aided implant surgery
Background A precise placement of dental implants is a crucial step to optimize both prosthetic aspects and functional constraints. In this context, the use of virtual guiding systems has been recognized as a fundamental tool to control the ideal implant position. In particular, complex periodontal surgeries can be performed using preoperative planning based on CT data. The critical point of the procedure relies on the lack of accuracy in transferring CT planning information to surgical field through custom-made stereo-lithographic surgical guides. Methods In this work, a novel methodology is proposed for monitoring loss of accuracy in transferring CT dental information into periodontal surgical field. The methodology is based on integrating 3D data of anatomical (impression and cast) and preoperative (radiographic template) models, obtained by both CT and optical scanning processes. Results A clinical case, relative to a fully edentulous jaw patient, has been used as test case to assess the accuracy of the various steps concurring in manufacturing surgical guides. In particular, a surgical guide has been designed to place implants in the bone structure of the patient. The analysis of the results has allowed the clinician to monitor all the errors, which have been occurring step by step manufacturing the physical templates. Conclusions The use of an optical scanner, which has a higher resolution and accuracy than CT scanning, has demonstrated to be a valid support to control the precision of the various physical models adopted and to point out possible error sources. A case study regarding a fully edentulous patient has confirmed the feasibility of the proposed methodology. PMID:21338504
A positioning QA procedure for 2D/2D (kV/MV) and 3D/3D (CT/CBCT) image matching for radiotherapy patient setup.
Guan, Huaiqun; Hammoud, Rabih; Yin, Fang-Fang
A positioning QA procedure for Varian's 2D/2D (kV/MV) and 3D/3D (planCT/CBCT) matching was developed. The procedure was to check: (1) the coincidence of on-board imager (OBI), portal imager (PI), and cone beam CT (CBCT)'s isocenters (digital graticules) to a linac's isocenter (to a pre-specified accuracy); (2) that the positioning difference detected by 2D/2D (kV/MV) and 3D/3D(planCT/CBCT) matching can be reliably transferred to couch motion. A cube phantom with a 2 mm metal ball (bb) at the center was used. The bb was used to define the isocenter. Two additional bbs were placed on two phantom surfaces in order to define a spatial location of 1.5 cm anterior, 1.5 cm inferior, and 1.5 cm right from the isocenter. An axial scan of the phantom was acquired from a multislice CT simulator. The phantom was set at the linac's isocenter (lasers); either AP MV/R Lat kV images or CBCT images were taken for 2D/2D or 3D/3D matching, respectively. For 2D/2D, the accuracy of each device's isocenter was obtained by checking the distance between the central bb and the digital graticule. Then the central bb in orthogonal DRRs was manually moved to overlay to the off-axis bbs in kV/MV images. For 3D/3D, CBCT was first matched to planCT to check the isocenter difference between the two CTs. Manual shifts were then made by moving CBCT such that the point defined by the two off-axis bbs overlay to the central bb in planCT. (PlanCT can not be moved in the current version of OBI1.4.) The manual shifts were then applied to remotely move the couch. The room laser was used to check the accuracy of the couch movement. For Trilogy (or Ix-21) linacs, the coincidence of imager and linac's isocenter was better than 1 mm (or 1.5 mm). The couch shift accuracy was better than 2 mm.
Automatic 3D pulmonary nodule detection in CT images: A survey.
Valente, Igor Rafael S; Cortez, Paulo César; Neto, Edson Cavalcanti; Soares, José Marques; de Albuquerque, Victor Hugo C; Tavares, João Manuel R S
This work presents a systematic review of techniques for the 3D automatic detection of pulmonary nodules in computerized-tomography (CT) images. Its main goals are to analyze the latest technology being used for the development of computational diagnostic tools to assist in the acquisition, storage and, mainly, processing and analysis of the biomedical data. Also, this work identifies the progress made, so far, evaluates the challenges to be overcome and provides an analysis of future prospects. As far as the authors know, this is the first time that a review is devoted exclusively to automated 3D techniques for the detection of pulmonary nodules from lung CT images, which makes this work of noteworthy value. The research covered the published works in the Web of Science, PubMed, Science Direct and IEEEXplore up to December 2014. Each work found that referred to automated 3D segmentation of the lungs was individually analyzed to identify its objective, methodology and results. Based on the analysis of the selected works, several studies were seen to be useful for the construction of medical diagnostic aid tools. However, there are certain aspects that still require attention such as increasing algorithm sensitivity, reducing the number of false positives, improving and optimizing the algorithm detection of different kinds of nodules with different sizes and shapes and, finally, the ability to integrate with the Electronic Medical Record Systems and Picture Archiving and Communication Systems. Based on this analysis, we can say that further research is needed to develop current techniques and that new algorithms are needed to overcome the identified drawbacks.
Reconstruction of 4D-CT from a Single Free-Breathing 3D-CT by Spatial-Temporal Image Registration
Wu, Guorong; Wang, Qian; Lian, Jun; Shen, Dinggang
In the radiation therapy of lung cancer, a free-breathing 3D-CT image is usually acquired in the treatment day for image-guided patient setup, by registering with the free-breathing 3D-CT image acquired in the planning day. In this way, the optimal dose plan computed in the planning day can be transferred onto the treatment day for cancer radiotherapy. However, patient setup based on the simple registration of the free-breathing 3D-CT images of the planning and the treatment days may mislead the radiotherapy, since the free-breathing 3D-CT is actually the mixed-phase image, with different slices often acquired from different respiratory phases. Moreover, a 4D-CT that is generally acquired in the planning day for improvement of dose planning is often ignored for guiding patient setup in the treatment day. To overcome these limitations, we present a novel two-step method to reconstruct the 4D-CT from a single free-breathing 3D-CT of the treatment day, by utilizing the 4D-CT model built in the planning day. Specifically, in the first step, we proposed a new spatial-temporal registration algorithm to align all phase images of the 4D-CT acquired in the planning day, for building a 4D-CT model with temporal correspondences established among all respiratory phases. In the second step, we first determine the optimal phase for each slice of the free-breathing (mixed-phase) 3D-CT of the treatment day by comparing with the 4D-CT of the planning day and thus obtain a sequence of partial 3D-CT images for the treatment day, each with only the incomplete image information in certain slices; and then we reconstruct a complete 4D-CT for the treatment day by warping the 4D-CT of the planning day (with complete information) to the sequence of partial 3D-CT images of the treatment day, under the guidance of the 4D-CT model built in the planning day. We have comprehensively evaluated our 4D-CT model building algorithm on a public lung image database, achieving the best registration
Construction of Realistic Liver Phantoms from Patient Images using 3D Printer and Its Application in CT Image Quality Assessment.
Leng, Shuai; Yu, Lifeng; Vrieze, Thomas; Kuhlmann, Joel; Chen, Baiyu; McCollough, Cynthia H
The purpose of this study is to use 3D printing techniques to construct a realistic liver phantom with heterogeneous background and anatomic structures from patient CT images, and to use the phantom to assess image quality with filtered backprojection and iterative reconstruction algorithms. Patient CT images were segmented into liver tissues, contrast-enhanced vessels, and liver lesions using commercial software, based on which stereolithography (STL) files were created and sent to a commercial 3D printer. A 3D liver phantom was printed after assigning different printing materials to each object to simulate appropriate attenuation of each segmented object. As high opacity materials are not available for the printer, we printed hollow vessels and filled them with iodine solutions of adjusted concentration to represent enhance levels in contrast-enhanced liver scans. The printed phantom was then placed in a 35×26 cm oblong-shaped water phantom and scanned repeatedly at 4 dose levels. Images were reconstructed using standard filtered backprojection and an iterative reconstruction algorithm with 3 different strength settings. Heterogeneous liver background were observed from the CT images and the difference in CT numbers between lesions and background were representative for low contrast lesions in liver CT studies. CT numbers in vessels filled with iodine solutions represented the enhancement of liver arteries and veins. Images were run through a Channelized Hotelling model observer with Garbor channels and ROC analysis was performed. The AUC values showed performance improvement using the iterative reconstruction algorithm and the amount of improvement increased with strength setting.
Construction of realistic liver phantoms from patient images using 3D printer and its application in CT image quality assessment
NASA Astrophysics Data System (ADS)
Leng, Shuai; Yu, Lifeng; Vrieze, Thomas; Kuhlmann, Joel; Chen, Baiyu; McCollough, Cynthia H.
The purpose of this study is to use 3D printing techniques to construct a realistic liver phantom with heterogeneous background and anatomic structures from patient CT images, and to use the phantom to assess image quality with filtered back-projection and iterative reconstruction algorithms. Patient CT images were segmented into liver tissues, contrast-enhanced vessels, and liver lesions using commercial software, based on which stereolithography (STL) files were created and sent to a commercial 3D printer. A 3D liver phantom was printed after assigning different printing materials to each object to simulate appropriate attenuation of each segmented object. As high opacity materials are not available for the printer, we printed hollow vessels and filled them with iodine solutions of adjusted concentration to represent enhance levels in contrast-enhanced liver scans. The printed phantom was then placed in a 35×26 cm oblong-shaped water phantom and scanned repeatedly at 4 dose levels. Images were reconstructed using standard filtered back-projection and an iterative reconstruction algorithm with 3 different strength settings. Heterogeneous liver background were observed from the CT images and the difference in CT numbers between lesions and background were representative for low contrast lesions in liver CT studies. CT numbers in vessels filled with iodine solutions represented the enhancement of liver arteries and veins. Images were run through a Channelized Hotelling model observer with Garbor channels and ROC analysis was performed. The AUC values showed performance improvement using the iterative reconstruction algorithm and the amount of improvement increased with strength setting.
Novel and powerful 3D adaptive crisp active contour method applied in the segmentation of CT lung images.
Rebouças Filho, Pedro Pedrosa; Cortez, Paulo César; da Silva Barros, Antônio C; C Albuquerque, Victor Hugo; R S Tavares, João Manuel
The World Health Organization estimates that 300 million people have asthma, 210 million people have Chronic Obstructive Pulmonary Disease (COPD), and, according to WHO, COPD will become the third major cause of death worldwide in 2030. Computational Vision systems are commonly used in pulmonology to address the task of image segmentation, which is essential for accurate medical diagnoses. Segmentation defines the regions of the lungs in CT images of the thorax that must be further analyzed by the system or by a specialist physician. This work proposes a novel and powerful technique named 3D Adaptive Crisp Active Contour Method (3D ACACM) for the segmentation of CT lung images. The method starts with a sphere within the lung to be segmented that is deformed by forces acting on it towards the lung borders. This process is performed iteratively in order to minimize an energy function associated with the 3D deformable model used. In the experimental assessment, the 3D ACACM is compared against three approaches commonly used in this field: the automatic 3D Region Growing, the level-set algorithm based on coherent propagation and the semi-automatic segmentation by an expert using the 3D OsiriX toolbox. When applied to 40 CT scans of the chest the 3D ACACM had an average F-measure of 99.22%, revealing its superiority and competency to segment lungs in CT images.
Piecewise-diffeomorphic image registration: application to the motion estimation between 3D CT lung images with sliding conditions.
Risser, Laurent; Vialard, François-Xavier; Baluwala, Habib Y; Schnabel, Julia A
In this paper, we propose a new strategy for modelling sliding conditions when registering 3D images in a piecewise-diffeomorphic framework. More specifically, our main contribution is the development of a mathematical formalism to perform Large Deformation Diffeomorphic Metric Mapping registration with sliding conditions. We also show how to adapt this formalism to the LogDemons diffeomorphic registration framework. We finally show how to apply this strategy to estimate the respiratory motion between 3D CT pulmonary images. Quantitative tests are performed on 2D and 3D synthetic images, as well as on real 3D lung images from the MICCAI EMPIRE10 challenge. Results show that our strategy estimates accurate mappings of entire 3D thoracic image volumes that exhibit a sliding motion, as opposed to conventional registration methods which are not capable of capturing discontinuous deformations at the thoracic cage boundary. They also show that although the deformations are not smooth across the location of sliding conditions, they are almost always invertible in the whole image domain. This would be helpful for radiotherapy planning and delivery.
Three-dimensional analysis of alveolar bone resorption by image processing of 3-D dental CT images
NASA Astrophysics Data System (ADS)
Nagao, Jiro; Kitasaka, Takayuki; Mori, Kensaku; Suenaga, Yasuhito; Yamada, Shohzoh; Naitoh, Munetaka
We have developed a novel system that provides total support for assessment of alveolar bone resorption, caused by periodontitis, based on three-dimensional (3-D) dental CT images. In spite of the difficulty in perceiving the complex 3-D shape of resorption, dentists assessing resorption location and severity have been relying on two-dimensional radiography and probing, which merely provides one-dimensional information (depth) about resorption shape. However, there has been little work on assisting assessment of the disease by 3-D image processing and visualization techniques. This work provides quantitative evaluation results and figures for our system that measures the three-dimensional shape and spread of resorption. It has the following functions: (1) measures the depth of resorption by virtually simulating probing in the 3-D CT images, taking advantage of image processing of not suffering obstruction by teeth on the inter-proximal sides and much smaller measurement intervals than the conventional examination; (2) visualizes the disposition of the depth by movies and graphs; (3) produces a quantitative index and intuitive visual representation of the spread of resorption in the inter-radicular region in terms of area; and (4) calculates the volume of resorption as another severity index in the inter-radicular region and the region outside it. Experimental results in two cases of 3-D dental CT images and a comparison of the results with the clinical examination results and experts' measurements of the corresponding patients confirmed that the proposed system gives satisfying results, including 0.1 to 0.6mm of resorption measurement (probing) error and fairly intuitive presentation of measurement and calculation results.
Pulmonary nodule classification based on CT density distribution using 3D thoracic CT images
NASA Astrophysics Data System (ADS)
Kawata, Yoshiki; Niki, Noboru; Ohamatsu, Hironobu; Kusumoto, Masahiko; Kakinuma, Ryutaro; Mori, Kiyoshi; Yamada, Kozo; Nishiyama, Hiroyuki; Eguchi, Kenji; Kaneko, Masahiro; Moriyama, Noriyuki
Computer-aided diagnosis (CAD) has been investigated to provide physicians with quantitative information, such as estimates of the malignant likelihood, to aid in the classification of abnormalities detected at screening of lung cancers. The purpose of this study is to develop a method for classifying nodule density patterns that provides information with respect to nodule statuses such as lesion stage. This method consists of three steps, nodule segmentation, histogram analysis of CT density inside nodule, and classifying nodules into five types based on histogram patterns. In this paper, we introduce a two-dimensional (2-D) joint histogram with respect to distance from nodule center and CT density inside nodule and explore numerical features with respect to shape and position of the joint histogram.
Patient specific respiratory motion modeling using a limited number of 3D lung CT images.
Cui, Xueli; Gao, Xin; Xia, Wei; Liu, Yangchuan; Liang, Zhiyuan
To build a patient specific respiratory motion model with a low dose, a novel method was proposed that uses a limited number of 3D lung CT volumes with an external respiratory signal. 4D lung CT volumes were acquired for patients with in vitro labeling on the upper abdominal surface. Meanwhile, 3D coordinates of in vitro labeling were measured as external respiratory signals. A sequential correspondence between the 4D lung CT and the external respiratory signal was built using the distance correlation method, and a 3D displacement for every registration control point in the CT volumes with respect to time can be obtained by the 4D lung CT deformable registration. A temporal fitting was performed for every registration control point displacements and an external respiratory signal in the anterior-posterior direction respectively to draw their fitting curves. Finally, a linear regression was used to fit the corresponding samples of the control point displacement fitting curves and the external respiratory signal fitting curve to finish the pulmonary respiration modeling. Compared to a B-spline-based method using the respiratory signal phase, the proposed method is highly advantageous as it offers comparable modeling accuracy and target modeling error (TME); while at the same time, the proposed method requires 70% less 3D lung CTs. When using a similar amount of 3D lung CT data, the mean of the proposed method's TME is smaller than the mean of the PCA (principle component analysis)-based methods' TMEs. The results indicate that the proposed method is successful in striking a balance between modeling accuracy and number of 3D lung CT volumes.
Adapted morphing model for 3D volume reconstruction applied to abdominal CT images
NASA Astrophysics Data System (ADS)
Fadeev, Aleksey; Eltonsy, Nevine; Tourassi, Georgia; Martin, Robert; Elmaghraby, Adel
The purpose of this study was to develop a 3D volume reconstruction model for volume rendering and apply this model to abdominal CT data. The model development includes two steps: (1) interpolation of given data for a complete 3D model, and (2) visualization. First, CT slices are interpolated using a special morphing algorithm. The main idea of this algorithm is to take a region from one CT slice and locate its most probable correspondence in the adjacent CT slice. The algorithm determines the transformation function of the region in between two adjacent CT slices and interpolates the data accordingly. The most probable correspondence of a region is obtained using correlation analysis between the given region and regions of the adjacent CT slice. By applying this technique recursively, taking progressively smaller subregions within a region, a high quality and accuracy interpolation is obtained. The main advantages of this morphing algorithm are 1) its applicability not only to parallel planes like CT slices but also to general configurations of planes in 3D space, and 2) its fully automated nature as it does not require control points to be specified by a user compared to most morphing techniques. Subsequently, to visualize data, a specialized volume rendering card (TeraRecon VolumePro 1000) was used. To represent data in 3D space, special software was developed to convert interpolated CT slices to 3D objects compatible with the VolumePro card. Visual comparison between the proposed model and linear interpolation clearly demonstrates the superiority of the proposed model.
Registration of 2D x-ray images to 3D MRI by generating pseudo-CT data
NASA Astrophysics Data System (ADS)
van der Bom, M. J.; Pluim, J. P. W.; Gounis, M. J.; van de Kraats, E. B.; Sprinkhuizen, S. M.; Timmer, J.; Homan, R.; Bartels, L. W.
Spatial and soft tissue information provided by magnetic resonance imaging can be very valuable during image-guided procedures, where usually only real-time two-dimensional (2D) x-ray images are available. Registration of 2D x-ray images to three-dimensional (3D) magnetic resonance imaging (MRI) data, acquired prior to the procedure, can provide optimal information to guide the procedure. However, registering x-ray images to MRI data is not a trivial task because of their fundamental difference in tissue contrast. This paper presents a technique that generates pseudo-computed tomography (CT) data from multi-spectral MRI acquisitions which is sufficiently similar to real CT data to enable registration of x-ray to MRI with comparable accuracy as registration of x-ray to CT. The method is based on a k-nearest-neighbors (kNN)-regression strategy which labels voxels of MRI data with CT Hounsfield Units. The regression method uses multi-spectral MRI intensities and intensity gradients as features to discriminate between various tissue types. The efficacy of using pseudo-CT data for registration of x-ray to MRI was tested on ex vivo animal data. 2D-3D registration experiments using CT and pseudo-CT data of multiple subjects were performed with a commonly used 2D-3D registration algorithm. On average, the median target registration error for registration of two x-ray images to MRI data was approximately 1 mm larger than for x-ray to CT registration. The authors have shown that pseudo-CT data generated from multi-spectral MRI facilitate registration of MRI to x-ray images. From the experiments it could be concluded that the accuracy achieved was comparable to that of registering x-ray images to CT data.
Clinical Application of Solid Model Based on Trabecular Tibia Bone CT Images Created by 3D Printer
Cho, Jaemo; Park, Chan-Soo; Kim, Yeoun-Jae
Objectives The aim of this work is to use a 3D solid model to predict the mechanical loads of human bone fracture risk associated with bone disease conditions according to biomechanical engineering parameters. Methods We used special image processing tools for image segmentation and three-dimensional (3D) reconstruction to generate meshes, which are necessary for the production of a solid model with a 3D printer from computed tomography (CT) images of the human tibia's trabecular and cortical bones. We examined the defects of the mechanism for the tibia's trabecular bones. Results Image processing tools and segmentation techniques were used to analyze bone structures and produce a solid model with a 3D printer. Conclusions These days, bio-imaging (CT and magnetic resonance imaging) devices are able to display and reconstruct 3D anatomical details, and diagnostics are becoming increasingly vital to the quality of patient treatment planning and clinical treatment. Furthermore, radiographic images are being used to study biomechanical systems with several aims, namely, to describe and simulate the mechanical behavior of certain anatomical systems, to analyze pathological bone conditions, to study tissues structure and properties, and to create a solid model using a 3D printer to support surgical planning and reduce experimental costs. These days, research using image processing tools and segmentation techniques to analyze bone structures to produce a solid model with a 3D printer is rapidly becoming very important. PMID:26279958
Adaptive Iterative Dose Reduction Using Three Dimensional Processing (AIDR3D) Improves Chest CT Image Quality and Reduces Radiation Exposure
Yamashiro, Tsuneo; Miyara, Tetsuhiro; Honda, Osamu; Kamiya, Hisashi; Murata, Kiyoshi; Ohno, Yoshiharu; Tomiyama, Noriyuki; Moriya, Hiroshi; Koyama, Mitsuhiro; Noma, Satoshi; Kamiya, Ayano; Tanaka, Yuko; Murayama, Sadayuki
Objective To assess the advantages of Adaptive Iterative Dose Reduction using Three Dimensional Processing (AIDR3D) for image quality improvement and dose reduction for chest computed tomography (CT). Methods Institutional Review Boards approved this study and informed consent was obtained. Eighty-eight subjects underwent chest CT at five institutions using identical scanners and protocols. During a single visit, each subject was scanned using different tube currents: 240, 120, and 60 mA. Scan data were converted to images using AIDR3D and a conventional reconstruction mode (without AIDR3D). Using a 5-point scale from 1 (non-diagnostic) to 5 (excellent), three blinded observers independently evaluated image quality for three lung zones, four patterns of lung disease (nodule/mass, emphysema, bronchiolitis, and diffuse lung disease), and three mediastinal measurements (small structure visibility, streak artifacts, and shoulder artifacts). Differences in these scores were assessed by Scheffe's test. Results At each tube current, scans using AIDR3D had higher scores than those without AIDR3D, which were significant for lung zones (p<0.0001) and all mediastinal measurements (p<0.01). For lung diseases, significant improvements with AIDR3D were frequently observed at 120 and 60 mA. Scans with AIDR3D at 120 mA had significantly higher scores than those without AIDR3D at 240 mA for lung zones and mediastinal streak artifacts (p<0.0001), and slightly higher or equal scores for all other measurements. Scans with AIDR3D at 60 mA were also judged superior or equivalent to those without AIDR3D at 120 mA. Conclusion For chest CT, AIDR3D provides better image quality and can reduce radiation exposure by 50%. PMID:25153797
Measurement of spiculation index in 3D for solitary pulmonary nodules in volumetric lung CT images
NASA Astrophysics Data System (ADS)
Dhara, Ashis Kumar; Mukhopadhyay, Sudipta; Alam, Naved; Khandelwal, Niranjan
In this paper a differential geometry based method is proposed for calculating surface speculation of solitary pulmonary nodule (SPN) in 3D from lung CT images. Spiculation present in SPN is an important shape feature to assist radiologist for measurement of malignancy. Performance of Computer Aided Diagnostic (CAD) system depends on the accurate estimation of feature like spiculation. In the proposed method, the peak of the spicules is identified using the property of Gaussian and mean curvature calculated at each surface point on segmented SPN. Once the peak point for a particular SPN is identified, the nearest valley points for the corresponding peak point are determined. The area of cross-section of the best fitted plane passing through the valley points is the base of that spicule. The solid angle subtended by the base of spicule at peak point and the distance of peak point from nodule base are taken as the measures of spiculation. The speculation index (SI) for a particular SPN is the weighted combination of all the spicules present in that SPN. The proposed method is validated on 95 SPN from Imaging Database Resources Initiative (IDRI) public database. It has achieved 87.4% accuracy in calculating quantified spiculation index compared to the spiculation index provided by radiologists in IDRI database.
A strain energy filter for 3D vessel enhancement with application to pulmonary CT images.
Xiao, Changyan; Staring, Marius; Shamonin, Denis; Reiber, Johan H C; Stolk, Jan; Stoel, Berend C
The traditional Hessian-related vessel filters often suffer from detecting complex structures like bifurcations due to an over-simplified cylindrical model. To solve this problem, we present a shape-tuned strain energy density function to measure vessel likelihood in 3D medical images. This method is initially inspired by established stress-strain principles in mechanics. By considering the Hessian matrix as a stress tensor, the three invariants from orthogonal tensor decomposition are used independently or combined to formulate distinctive functions for vascular shape discrimination, brightness contrast and structure strength measuring. Moreover, a mathematical description of Hessian eigenvalues for general vessel shapes is obtained, based on an intensity continuity assumption, and a relative Hessian strength term is presented to ensure the dominance of second-order derivatives as well as suppress undesired step-edges. Finally, we adopt the multi-scale scheme to find an optimal solution through scale space. The proposed method is validated in experiments with a digital phantom and non-contrast-enhanced pulmonary CT data. It is shown that our model performed more effectively in enhancing vessel bifurcations and preserving details, compared to three existing filters.
3D texture analysis of solitary pulmonary nodules using co-occurrence matrix from volumetric lung CT images
NASA Astrophysics Data System (ADS)
Dhara, Ashis Kumar; Mukhopadhyay, Sudipta; Khandelwal, Niranjan
In this paper we have investigated a new approach for texture features extraction using co-occurrence matrix from volumetric lung CT image. Traditionally texture analysis is performed in 2D and is suitable for images collected from 2D imaging modality. The use of 3D imaging modalities provide the scope of texture analysis from 3D object and 3D texture feature are more realistic to represent 3D object. In this work, Haralick's texture features are extended in 3D and computed from volumetric data considering 26 neighbors. The optimal texture features to characterize the internal structure of Solitary Pulmonary Nodules (SPN) are selected based on area under curve (AUC) values of ROC curve and p values from 2-tailed Student's t-test. The selected texture feature in 3D to represent SPN can be used in efficient Computer Aided Diagnostic (CAD) design plays an important role in fast and accurate lung cancer screening. The reduced number of input features to the CAD system will decrease the computational time and classification errors caused by irrelevant features. In the present work, SPN are classified from Ground Glass Nodule (GGN) using Artificial Neural Network (ANN) classifier considering top five 3D texture features and top five 2D texture features separately. The classification is performed on 92 SPN and 25 GGN from Imaging Database Resources Initiative (IDRI) public database and classification accuracy using 3D texture features and 2D texture features provide 97.17% and 89.1% respectively.
Algorithm of pulmonary emphysema extraction using thoracic 3-D CT images
NASA Astrophysics Data System (ADS)
Saita, Shinsuke; Kubo, Mitsuru; Kawata, Yoshiki; Niki, Noboru; Nakano, Yasutaka; Ohmatsu, Hironobu; Tominaga, Keigo; Eguchi, Kenji; Moriyama, Noriyuki
Emphysema patients have the tendency to increase due to aging and smoking. Emphysematous disease destroys alveolus and to repair is impossible, thus early detection is essential. CT value of lung tissue decreases due to the destruction of lung structure. This CT value becomes lower than the normal lung- low density absorption region or referred to as Low Attenuation Area (LAA). So far, the conventional way of extracting LAA by simple thresholding has been proposed. However, the CT value of CT image fluctuates due to the measurement conditions, with various bias components such as inspiration, expiration and congestion. It is therefore necessary to consider these bias components in the extraction of LAA. We removed these bias components and we proposed LAA extraction algorithm. This algorithm has been applied to the phantom image. Then, by using the low dose CT(normal: 30 cases, obstructive lung disease: 26 cases), we extracted early stage LAA and quantitatively analyzed lung lobes using lung structure.
Self-calibration of cone-beam CT geometry using 3D-2D image registration.
Ouadah, S; Stayman, J W; Gang, G J; Ehtiati, T; Siewerdsen, J H
Robotic C-arms are capable of complex orbits that can increase field of view, reduce artifacts, improve image quality, and/or reduce dose; however, it can be challenging to obtain accurate, reproducible geometric calibration required for image reconstruction for such complex orbits. This work presents a method for geometric calibration for an arbitrary source-detector orbit by registering 2D projection data to a previously acquired 3D image. It also yields a method by which calibration of simple circular orbits can be improved. The registration uses a normalized gradient information similarity metric and the covariance matrix adaptation-evolution strategy optimizer for robustness against local minima and changes in image content. The resulting transformation provides a 'self-calibration' of system geometry. The algorithm was tested in phantom studies using both a cone-beam CT (CBCT) test-bench and a robotic C-arm (Artis Zeego, Siemens Healthcare) for circular and non-circular orbits. Self-calibration performance was evaluated in terms of the full-width at half-maximum (FWHM) of the point spread function in CBCT reconstructions, the reprojection error (RPE) of steel ball bearings placed on each phantom, and the overall quality and presence of artifacts in CBCT images. In all cases, self-calibration improved the FWHM-e.g. on the CBCT bench, FWHM = 0.86 mm for conventional calibration compared to 0.65 mm for self-calibration (p < 0.001). Similar improvements were measured in RPE-e.g. on the robotic C-arm, RPE = 0.73 mm for conventional calibration compared to 0.55 mm for self-calibration (p < 0.001). Visible improvement was evident in CBCT reconstructions using self-calibration, particularly about high-contrast, high-frequency objects (e.g. temporal bone air cells and a surgical needle). The results indicate that self-calibration can improve even upon systems with presumably accurate geometric calibration and is
Self-calibration of cone-beam CT geometry using 3D-2D image registration
NASA Astrophysics Data System (ADS)
Ouadah, S.; Stayman, J. W.; Gang, G. J.; Ehtiati, T.; Siewerdsen, J. H.
Robotic C-arms are capable of complex orbits that can increase field of view, reduce artifacts, improve image quality, and/or reduce dose; however, it can be challenging to obtain accurate, reproducible geometric calibration required for image reconstruction for such complex orbits. This work presents a method for geometric calibration for an arbitrary source-detector orbit by registering 2D projection data to a previously acquired 3D image. It also yields a method by which calibration of simple circular orbits can be improved. The registration uses a normalized gradient information similarity metric and the covariance matrix adaptation-evolution strategy optimizer for robustness against local minima and changes in image content. The resulting transformation provides a 'self-calibration' of system geometry. The algorithm was tested in phantom studies using both a cone-beam CT (CBCT) test-bench and a robotic C-arm (Artis Zeego, Siemens Healthcare) for circular and non-circular orbits. Self-calibration performance was evaluated in terms of the full-width at half-maximum (FWHM) of the point spread function in CBCT reconstructions, the reprojection error (RPE) of steel ball bearings placed on each phantom, and the overall quality and presence of artifacts in CBCT images. In all cases, self-calibration improved the FWHM—e.g. on the CBCT bench, FWHM = 0.86 mm for conventional calibration compared to 0.65 mm for self-calibration (p < 0.001). Similar improvements were measured in RPE—e.g. on the robotic C-arm, RPE = 0.73 mm for conventional calibration compared to 0.55 mm for self-calibration (p < 0.001). Visible improvement was evident in CBCT reconstructions using self-calibration, particularly about high-contrast, high-frequency objects (e.g. temporal bone air cells and a surgical needle). The results indicate that self-calibration can improve even upon systems with presumably accurate geometric calibration and is
A Registration Method Based on Contour Point Cloud for 3D Whole-Body PET and CT Images
Yang, Qiyao; Wang, Zhiguo; Zhang, Guoxu
The PET and CT fusion image, combining the anatomical and functional information, has important clinical meaning. An effective registration of PET and CT images is the basis of image fusion. This paper presents a multithread registration method based on contour point cloud for 3D whole-body PET and CT images. Firstly, a geometric feature-based segmentation (GFS) method and a dynamic threshold denoising (DTD) method are creatively proposed to preprocess CT and PET images, respectively. Next, a new automated trunk slices extraction method is presented for extracting feature point clouds. Finally, the multithread Iterative Closet Point is adopted to drive an affine transform. We compare our method with a multiresolution registration method based on Mattes Mutual Information on 13 pairs (246~286 slices per pair) of 3D whole-body PET and CT data. Experimental results demonstrate the registration effectiveness of our method with lower negative normalization correlation (NC = −0.933) on feature images and less Euclidean distance error (ED = 2.826) on landmark points, outperforming the source data (NC = −0.496, ED = 25.847) and the compared method (NC = −0.614, ED = 16.085). Moreover, our method is about ten times faster than the compared one. PMID:28316979
Supervised recursive segmentation of volumetric CT images for 3D reconstruction of lung and vessel tree.
Li, Xuanping; Wang, Xue; Dai, Yixiang; Zhang, Pengbo
Three dimensional reconstruction of lung and vessel tree has great significance to 3D observation and quantitative analysis for lung diseases. This paper presents non-sheltered 3D models of lung and vessel tree based on a supervised semi-3D lung tissues segmentation method. A recursive strategy based on geometric active contour is proposed instead of the "coarse-to-fine" framework in existing literature to extract lung tissues from the volumetric CT slices. In this model, the segmentation of the current slice is supervised by the result of the previous one slice due to the slight changes between adjacent slice of lung tissues. Through this mechanism, lung tissues in all the slices are segmented fast and accurately. The serious problems of left and right lungs fusion, caused by partial volume effects, and segmentation of pleural nodules can be settled meanwhile during the semi-3D process. The proposed scheme is evaluated by fifteen scans, from eight healthy participants and seven participants suffering from early-stage lung tumors. The results validate the good performance of the proposed method compared with the "coarse-to-fine" framework. The segmented datasets are utilized to reconstruct the non-sheltered 3D models of lung and vessel tree.
3D electron density imaging using single scattered x rays with application to breast CT and mammographic screening
NASA Astrophysics Data System (ADS)
van Uytven, Eric Peter
Screening mammography is the current standard in detecting breast cancer. However, its fundamental disadvantage is that it projects a 3D object into a 2D image. Small lesions are difficult to detect when superimposed over layers of normal tissue. Commercial Computed Tomography (CT) produces a true 3D image yet has a limited role in mammography due to relatively low resolution and contrast. With the intent of enhancing mammography and breast CT, we have developed an algorithm which can produce 3D electron density images using a single projection. Imaging an object with x rays produces a characteristic scattered photon spectrum at the detector plane. A known incident beam spectrum, beam shape, and arbitrary 3D matrix of electron density values enable a theoretical scattered photon distribution to be calculated. An iterative minimization algorithm is used to make changes to the electron density voxel matrix to reduce regular differences between the theoretical and the experimentally measured distributions. The object is characterized by the converged electron density image. This technique has been validated in simulation using data produced by the EGSnrc Monte Carlo code system. At both mammographic and CT energies, a scanning polychromatic pencil beam was used to image breast tissue phantoms containing lesion-like inhomogeneities. The resulting Monte Carlo data is processed using a Nelder-Mead iterative algorithm (MATLAB) to produce the 3D matrix of electron density values. Resulting images have confirmed the ability of the algorithm to detect various 1x1x2.5 mm3 lesions with calcification content as low as 0.5% (p<0.005) at a dose comparable to mammography.
US-CT 3D dual imaging by mutual display of the same sections for depicting minor changes in hepatocellular carcinoma.
Fukuda, Hiroyuki; Ito, Ryu; Ohto, Masao; Sakamoto, Akio; Otsuka, Masayuki; Togawa, Akira; Miyazaki, Masaru; Yamagata, Hitoshi
The purpose of this study was to evaluate the usefulness of ultrasound-computed tomography (US-CT) 3D dual imaging for the detection of small extranodular growths of hepatocellular carcinoma (HCC). The clinical and pathological profiles of 10 patients with single nodular type HCC with extranodular growth (extranodular growth) who underwent a hepatectomy were evaluated using two-dimensional (2D) ultrasonography (US), three-dimensional (3D) US, 3D computed tomography (CT) and 3D US-CT dual images. Raw 3D data was converted to DICOM (Digital Imaging and Communication in Medicine) data using Echo to CT (Toshiba Medical Systems Corp., Tokyo, Japan), and the 3D DICOM data was directly transferred to the image analysis system (ZioM900, ZIOSOFT Inc., Tokyo, Japan). By inputting the angle number (x, y, z) of the 3D CT volume data into the ZioM900, multiplanar reconstruction (MPR) images of the 3D CT data were displayed in a manner such that they resembled the conventional US images. Eleven extranodular growths were detected pathologically in 10 cases. 2D US was capable of depicting only 2 of the 11 extranodular growths. 3D CT was capable of depicting 4 of the 11 extranodular growths. On the other hand, 3D US was capable of depicting 10 of the 11 extranodular growths, and 3D US-CT dual images, which enable the dual analysis of the CT and US planes, revealed all 11 extranodular growths. In conclusion, US-CT 3D dual imaging may be useful for the detection of small extranodular growths.
Regularization Designs for Uniform Spatial Resolution and Noise Properties in Statistical Image Reconstruction for 3D X-ray CT
Cho, Jang Hwan; Fessler, Jeffrey A.
Statistical image reconstruction methods for X-ray computed tomography (CT) provide improved spatial resolution and noise properties over conventional filtered back-projection (FBP) reconstruction, along with other potential advantages such as reduced patient dose and artifacts. Conventional regularized image reconstruction leads to spatially variant spatial resolution and noise characteristics because of interactions between the system models and the regularization. Previous regularization design methods aiming to solve such issues mostly rely on circulant approximations of the Fisher information matrix that are very inaccurate for undersampled geometries like short-scan cone-beam CT. This paper extends the regularization method proposed in [1] to 3D cone-beam CT by introducing a hypothetical scanning geometry that helps address the sampling properties. The proposed regularization designs were compared with the original method in [1] with both phantom simulation and clinical reconstruction in 3D axial X-ray CT. The proposed regularization methods yield improved spatial resolution or noise uniformity in statistical image reconstruction for short-scan axial cone-beam CT. PMID:25361500
Regularization designs for uniform spatial resolution and noise properties in statistical image reconstruction for 3-D X-ray CT.
Cho, Jang Hwan; Fessler, Jeffrey A
Statistical image reconstruction methods for X-ray computed tomography (CT) provide improved spatial resolution and noise properties over conventional filtered back-projection (FBP) reconstruction, along with other potential advantages such as reduced patient dose and artifacts. Conventional regularized image reconstruction leads to spatially variant spatial resolution and noise characteristics because of interactions between the system models and the regularization. Previous regularization design methods aiming to solve such issues mostly rely on circulant approximations of the Fisher information matrix that are very inaccurate for undersampled geometries like short-scan cone-beam CT. This paper extends the regularization method proposed in to 3-D cone-beam CT by introducing a hypothetical scanning geometry that helps address the sampling properties. The proposed regularization designs were compared with the original method in with both phantom simulation and clinical reconstruction in 3-D axial X-ray CT. The proposed regularization methods yield improved spatial resolution or noise uniformity in statistical image reconstruction for short-scan axial cone-beam CT.
Combining Population and Patient-Specific Characteristics for Prostate Segmentation on 3D CT Images.
Ma, Ling; Guo, Rongrong; Tian, Zhiqiang; Venkataraman, Rajesh; Sarkar, Saradwata; Liu, Xiabi; Tade, Funmilayo; Schuster, David M; Fei, Baowei
Prostate segmentation on CT images is a challenging task. In this paper, we explore the population and patient-specific characteristics for the segmentation of the prostate on CT images. Because population learning does not consider the inter-patient variations and because patient-specific learning may not perform well for different patients, we are combining the population and patient-specific information to improve segmentation performance. Specifically, we train a population model based on the population data and train a patient-specific model based on the manual segmentation on three slice of the new patient. We compute the similarity between the two models to explore the influence of applicable population knowledge on the specific patient. By combining the patient-specific knowledge with the influence, we can capture the population and patient-specific characteristics to calculate the probability of a pixel belonging to the prostate. Finally, we smooth the prostate surface according to the prostate-density value of the pixels in the distance transform image. We conducted the leave-one-out validation experiments on a set of CT volumes from 15 patients. Manual segmentation results from a radiologist serve as the gold standard for the evaluation. Experimental results show that our method achieved an average DSC of 85.1% as compared to the manual segmentation gold standard. This method outperformed the population learning method and the patient-specific learning approach alone. The CT segmentation method can have various applications in prostate cancer diagnosis and therapy.
Combining population and patient-specific characteristics for prostate segmentation on 3D CT images
NASA Astrophysics Data System (ADS)
Ma, Ling; Guo, Rongrong; Tian, Zhiqiang; Venkataraman, Rajesh; Sarkar, Saradwata; Liu, Xiabi; Tade, Funmilayo; Schuster, David M.; Fei, Baowei
Prostate segmentation on CT images is a challenging task. In this paper, we explore the population and patient-specific characteristics for the segmentation of the prostate on CT images. Because population learning does not consider the inter-patient variations and because patient-specific learning may not perform well for different patients, we are combining the population and patient-specific information to improve segmentation performance. Specifically, we train a population model based on the population data and train a patient-specific model based on the manual segmentation on three slice of the new patient. We compute the similarity between the two models to explore the influence of applicable population knowledge on the specific patient. By combining the patient-specific knowledge with the influence, we can capture the population and patient-specific characteristics to calculate the probability of a pixel belonging to the prostate. Finally, we smooth the prostate surface according to the prostate-density value of the pixels in the distance transform image. We conducted the leave-one-out validation experiments on a set of CT volumes from 15 patients. Manual segmentation results from a radiologist serve as the gold standard for the evaluation. Experimental results show that our method achieved an average DSC of 85.1% as compared to the manual segmentation gold standard. This method outperformed the population learning method and the patient-specific learning approach alone. The CT segmentation method can have various applications in prostate cancer diagnosis and therapy.
Combining Population and Patient-Specific Characteristics for Prostate Segmentation on 3D CT Images
Ma, Ling; Guo, Rongrong; Tian, Zhiqiang; Venkataraman, Rajesh; Sarkar, Saradwata; Liu, Xiabi; Tade, Funmilayo; Schuster, David M.; Fei, Baowei
Prostate segmentation on CT images is a challenging task. In this paper, we explore the population and patient-specific characteristics for the segmentation of the prostate on CT images. Because population learning does not consider the inter-patient variations and because patient-specific learning may not perform well for different patients, we are combining the population and patient-specific information to improve segmentation performance. Specifically, we train a population model based on the population data and train a patient-specific model based on the manual segmentation on three slice of the new patient. We compute the similarity between the two models to explore the influence of applicable population knowledge on the specific patient. By combining the patient-specific knowledge with the influence, we can capture the population and patient-specific characteristics to calculate the probability of a pixel belonging to the prostate. Finally, we smooth the prostate surface according to the prostate-density value of the pixels in the distance transform image. We conducted the leave-one-out validation experiments on a set of CT volumes from 15 patients. Manual segmentation results from a radiologist serve as the gold standard for the evaluation. Experimental results show that our method achieved an average DSC of 85.1% as compared to the manual segmentation gold standard. This method outperformed the population learning method and the patient-specific learning approach alone. The CT segmentation method can have various applications in prostate cancer diagnosis and therapy. PMID:27660382
Bone canalicular network segmentation in 3D nano-CT images through geodesic voting and image tessellation
NASA Astrophysics Data System (ADS)
Zuluaga, Maria A.; Orkisz, Maciej; Dong, Pei; Pacureanu, Alexandra; Gouttenoire, Pierre-Jean; Peyrin, Françoise
Recent studies emphasized the role of the bone lacuno-canalicular network (LCN) in the understanding of bone diseases such as osteoporosis. However, suitable methods to investigate this structure are lacking. The aim of this paper is to introduce a methodology to segment the LCN from three-dimensional (3D) synchrotron radiation nano-CT images. Segmentation of such structures is challenging due to several factors such as limited contrast and signal-to-noise ratio, partial volume effects and huge number of data that needs to be processed, which restrains user interaction. We use an approach based on minimum-cost paths and geodesic voting, for which we propose a fully automatic initialization scheme based on a tessellation of the image domain. The centroids of pre-segmented lacunæ are used as Voronoi-tessellation seeds and as start-points of a fast-marching front propagation, whereas the end-points are distributed in the vicinity of each Voronoi-region boundary. This initialization scheme was devised to cope with complex biological structures involving cells interconnected by multiple thread-like, branching processes, while the seminal geodesic-voting method only copes with tree-like structures. Our method has been assessed quantitatively on phantom data and qualitatively on real datasets, demonstrating its feasibility. To the best of our knowledge, presented 3D renderings of lacunæ interconnected by their canaliculi were achieved for the first time.
Local plate/rod descriptors of 3D trabecular bone micro-CT images from medial axis topologic analysis
Peyrin, Francoise; Attali, Dominique; Chappard, Christine; Benhamou, Claude Laurent
Purpose: Trabecular bone microarchitecture is made of a complex network of plate and rod structures evolving with age and disease. The purpose of this article is to propose a new 3D local analysis method for the quantitative assessment of parameters related to the geometry of trabecular bone microarchitecture. Methods: The method is based on the topologic classification of the medial axis of the 3D image into branches, rods, and plates. Thanks to the reversibility of the medial axis, the classification is next extended to the whole 3D image. Finally, the percentages of rods and plates as well as their mean thicknesses are calculated. The method was applied both to simulated test images and 3D micro-CT images of human trabecular bone. Results: The classification of simulated phantoms made of plates and rods shows that the maximum error in the quantitative percentages of plate and rods is less than 6% and smaller than with the structure model index (SMI). Micro-CT images of human femoral bone taken in osteoporosis and early or advanced osteoarthritis were analyzed. Despite the large physiological variability, the present method avoids the underestimation of rods observed with other local methods. The relative percentages of rods and plates were not significantly different between osteoarthritis and osteoporotic groups, whereas their absolute percentages were in relation to an increase of rod and plate thicknesses in advanced osteoarthritis with also higher relative and absolute number of nodes. Conclusions: The proposed method is model-independent, robust to surface irregularities, and enables geometrical characterization of not only skeletal structures but entire 3D images. Its application provided more accurate results than the standard SMI on simple simulated phantoms, but the discrepancy observed on the advanced osteoarthritis group raises questions that will require further investigations. The systematic use of such a local method in the characterization of
Efficient 3D texture feature extraction from CT images for computer-aided diagnosis of pulmonary nodules
NASA Astrophysics Data System (ADS)
Han, Fangfang; Wang, Huafeng; Song, Bowen; Zhang, Guopeng; Lu, Hongbing; Moore, William; Liang, Zhengrong; Zhao, Hong
Texture feature from chest CT images for malignancy assessment of pulmonary nodules has become an un-ignored and efficient factor in Computer-Aided Diagnosis (CADx). In this paper, we focus on extracting as fewer as needed efficient texture features, which can be combined with other classical features (e.g. size, shape, growing rate, etc.) for assisting lung nodule diagnosis. Based on a typical calculation algorithm of texture features, namely Haralick features achieved from the gray-tone spatial-dependence matrices, we calculated two dimensional (2D) and three dimensional (3D) Haralick features from the CT images of 905 nodules. All of the CT images were downloaded from the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI), which is the largest public chest database. 3D Haralick feature model of thirteen directions contains more information from the relationships on the neighbor voxels of different slices than 2D features from only four directions. After comparing the efficiencies of 2D and 3D Haralick features applied on the diagnosis of nodules, principal component analysis (PCA) algorithm was used to extract as fewer as needed efficient texture features. To achieve an objective assessment of the texture features, the support vector machine classifier was trained and tested repeatedly for one hundred times. And the statistical results of the classification experiments were described by an average receiver operating characteristic (ROC) curve. The mean value (0.8776) of the area under the ROC curves in our experiments can show that the two extracted 3D Haralick projected features have the potential to assist the classification of benign and malignant nodules.
Twin robotic x-ray system for 2D radiographic and 3D cone-beam CT imaging
NASA Astrophysics Data System (ADS)
Fieselmann, Andreas; Steinbrener, Jan; Jerebko, Anna K.; Voigt, Johannes M.; Scholz, Rosemarie; Ritschl, Ludwig; Mertelmeier, Thomas
In this work, we provide an initial characterization of a novel twin robotic X-ray system. This system is equipped with two motor-driven telescopic arms carrying X-ray tube and flat-panel detector, respectively. 2D radiographs and fluoroscopic image sequences can be obtained from different viewing angles. Projection data for 3D cone-beam CT reconstruction can be acquired during simultaneous movement of the arms along dedicated scanning trajectories. We provide an initial evaluation of the 3D image quality based on phantom scans and clinical images. Furthermore, initial evaluation of patient dose is conducted. The results show that the system delivers high image quality for a range of medical applications. In particular, high spatial resolution enables adequate visualization of bone structures. This system allows 3D X-ray scanning of patients in standing and weight-bearing position. It could enable new 2D/3D imaging workflows in musculoskeletal imaging and improve diagnosis of musculoskeletal disorders.
2D and 3D Terahertz Imaging and X-Rays CT for Sigillography Study
NASA Astrophysics Data System (ADS)
Fabre, M.; Durand, R.; Bassel, L.; Recur, B.; Balacey, H.; Bou Sleiman, J.; Perraud, J.-B.; Mounaix, P.
Seals are part of our cultural heritage but the study of these objects is limited because of their fragility. Terahertz and X-Ray imaging are used to analyze a collection of wax seals from the fourteenth to eighteenth centuries. In this work, both techniques are compared in order to discuss their advantages and limits and their complementarity for conservation state study of the samples. Thanks to 3D analysis and reconstructions, defects and fractures are detected with an estimation of their depth position. The path from the parchment tongue inside the seals is also detected.
2D and 3D Terahertz Imaging and X-Rays CT for Sigillography Study
NASA Astrophysics Data System (ADS)
Fabre, M.; Durand, R.; Bassel, L.; Recur, B.; Balacey, H.; Bou Sleiman, J.; Perraud, J.-B.; Mounaix, P.
Seals are part of our cultural heritage but the study of these objects is limited because of their fragility. Terahertz and X-Ray imaging are used to analyze a collection of wax seals from the fourteenth to eighteenth centuries. In this work, both techniques are compared in order to discuss their advantages and limits and their complementarity for conservation state study of the samples. Thanks to 3D analysis and reconstructions, defects and fractures are detected with an estimation of their depth position. The path from the parchment tongue inside the seals is also detected.
Iterative Mesh Transformation for 3D Segmentation of Livers with Cancers in CT Images
Lu, Difei; Wu, Yin; Harris, Gordon; Cai, Wenli
Segmentation of diseased liver remains a challenging task in clinical applications due to the high inter-patient variability in liver shapes, sizes and pathologies caused by cancers or other liver diseases. In this paper, we present a multi-resolution mesh segmentation algorithm for 3D segmentation of livers, called iterative mesh transformation that deforms the mesh of a region-of-interest (ROI) in a progressive manner by iterations between mesh transformation and contour optimization. Mesh transformation deforms the 3D mesh based on the deformation transfer model that searches the optimal mesh based on the affine transformation subjected to a set of constraints of targeting vertices. Besides, contour optimization searches the optimal transversal contours of the ROI by applying the dynamic-programming algorithm to the intersection polylines of the 3D mesh on 2D transversal image planes. The initial constraint set for mesh transformation can be defined by a very small number of targeting vertices, namely landmarks, and progressively updated by adding the targeting vertices selected from the optimal transversal contours calculated in contour optimization. This iterative 3D mesh transformation constrained by 2D optimal transversal contours provides an efficient solution to a progressive approximation of the mesh of the targeting ROI. Based on this iterative mesh transformation algorithm, we developed a semi-automated scheme for segmentation of diseased livers with cancers using as little as five user-identified landmarks. The evaluation study demonstrates that this semiautomated liver segmentation scheme can achieve accurate and reliable segmentation results with significant reduction of interaction time and efforts when dealing with diseased liver cases. PMID:25728595
Iterative mesh transformation for 3D segmentation of livers with cancers in CT images.
Lu, Difei; Wu, Yin; Harris, Gordon; Cai, Wenli
Segmentation of diseased liver remains a challenging task in clinical applications due to the high inter-patient variability in liver shapes, sizes and pathologies caused by cancers or other liver diseases. In this paper, we present a multi-resolution mesh segmentation algorithm for 3D segmentation of livers, called iterative mesh transformation that deforms the mesh of a region-of-interest (ROI) in a progressive manner by iterations between mesh transformation and contour optimization. Mesh transformation deforms the 3D mesh based on the deformation transfer model that searches the optimal mesh based on the affine transformation subjected to a set of constraints of targeting vertices. Besides, contour optimization searches the optimal transversal contours of the ROI by applying the dynamic-programming algorithm to the intersection polylines of the 3D mesh on 2D transversal image planes. The initial constraint set for mesh transformation can be defined by a very small number of targeting vertices, namely landmarks, and progressively updated by adding the targeting vertices selected from the optimal transversal contours calculated in contour optimization. This iterative 3D mesh transformation constrained by 2D optimal transversal contours provides an efficient solution to a progressive approximation of the mesh of the targeting ROI. Based on this iterative mesh transformation algorithm, we developed a semi-automated scheme for segmentation of diseased livers with cancers using as little as five user-identified landmarks. The evaluation study demonstrates that this semi-automated liver segmentation scheme can achieve accurate and reliable segmentation results with significant reduction of interaction time and efforts when dealing with diseased liver cases.
A visual data-mining approach using 3D thoracic CT images for classification between benign and malignant pulmonary nodules
NASA Astrophysics Data System (ADS)
Kawata, Yoshiki; Niki, Noboru; Ohamatsu, Hironobu; Kusumoto, Masahiko; Kakinuma, Ryutaro; Mori, Kiyoshi; Yamada, K.; Nishiyama, Hiroyuki; Eguchi, Kenji; Kaneko, Masahiro; Moriyama, Noriyuki
This paper presents a visual data-mining approach to assist physicians for classification between benign and malignant pulmonary nodules. This approach retrieves and displays nodules which exhibit morphological and internal profiles consistent to the nodule in question. It uses a three-dimensional (3-D) CT image database of pulmonary nodules for which diagnosis is known. The central module in this approach makes possible analysis of the query nodule image and extraction of the features of interest: shape, surrounding structure, and internal structure of the nodules. The nodule shape is characterized by principal axes, while the surrounding and internal structure is represented by the distribution pattern of CT density and 3-D curvature indexes. The nodule representation is then applied to a similarity measure such as a correlation coefficient. For each query case, we sort all the nodules of the database from most to less similar ones. By applying the retrieval method to our database, we present its feasibility to search the similar 3-D nodule images.
Towards real-time 3D US to CT bone image registration using phase and curvature feature based GMM matching.
Brounstein, Anna; Hacihaliloglu, Ilker; Guy, Pierre; Hodgson, Antony; Abugharbieh, Rafeef
In order to use pre-operatively acquired computed tomography (CT) scans to guide surgical tool movements in orthopaedic surgery, the CT scan must first be registered to the patient's anatomy. Three-dimensional (3D) ultrasound (US) could potentially be used for this purpose if the registration process could be made sufficiently automatic, fast and accurate, but existing methods have difficulties meeting one or more of these criteria. We propose a near-real-time US-to-CT registration method that matches point clouds extracted from local phase images with points selected in part on the basis of local curvature. The point clouds are represented as Gaussian Mixture Models (GMM) and registration is achieved by minimizing the statistical dissimilarity between the GMMs using an L2 distance metric. We present quantitative and qualitative results on both phantom and clinical pelvis data and show a mean registration time of 2.11 s with a mean accuracy of 0.49 mm.
3D segmentation of abdominal aorta from CT-scan and MR images.
Duquette, Anthony Adam; Jodoin, Pierre-Marc; Bouchot, Olivier; Lalande, Alain
We designed a generic method for segmenting the aneurismal sac of an abdominal aortic aneurysm (AAA) both from multi-slice MR and CT-scan examinations. It is a semi-automatic method requiring little human intervention and based on graph cut theory to segment the lumen interface and the aortic wall of AAAs. Our segmentation method works independently on MRI and CT-scan volumes and has been tested on a 44 patient dataset and 10 synthetic images. Segmentation and maximum diameter estimation were compared to manual tracing from 4 experts. An inter-observer study was performed in order to measure the variability range of a human observer. Based on three metrics (the maximum aortic diameter, the volume overlap and the Hausdorff distance) the variability of the results obtained by our method is shown to be similar to that of a human operator, both for the lumen interface and the aortic wall. As will be shown, the average distance obtained with our method is less than one standard deviation away from each expert, both for healthy subjects and for patients with AAA. Our semi-automatic method provides reliable contours of the abdominal aorta from CT-scan or MRI, allowing rapid and reproducible evaluations of AAA.
Pancreas segmentation from 3D abdominal CT images using patient-specific weighted subspatial probabilistic atlases
NASA Astrophysics Data System (ADS)
Karasawa, Kenichi; Oda, Masahiro; Hayashi, Yuichiro; Nimura, Yukitaka; Kitasaka, Takayuki; Misawa, Kazunari; Fujiwara, Michitaka; Rueckert, Daniel; Mori, Kensaku
Abdominal organ segmentations from CT volumes are now widely used in the computer-aided diagnosis and surgery assistance systems. Among abdominal organs, the pancreas is especially difficult to segment because of its large individual differences of the shape and position. In this paper, we propose a new pancreas segmentation method from 3D abdominal CT volumes using patient-specific weighted-subspatial probabilistic atlases. First of all, we perform normalization of organ shapes in training volumes and an input volume. We extract the Volume Of Interest (VOI) of the pancreas from the training volumes and an input volume. We divide each training VOI and input VOI into some cubic regions. We use a nonrigid registration method to register these cubic regions of the training VOI to corresponding regions of the input VOI. Based on the registration results, we calculate similarities between each cubic region of the training VOI and corresponding region of the input VOI. We select cubic regions of training volumes having the top N similarities in each cubic region. We subspatially construct probabilistic atlases weighted by the similarities in each cubic region. After integrating these probabilistic atlases in cubic regions into one, we perform a rough-to-precise segmentation of the pancreas using the atlas. The results of the experiments showed that utilization of the training volumes having the top N similarities in each cubic region led good results of the pancreas segmentation. The Jaccard Index and the average surface distance of the result were 58.9% and 2.04mm on average, respectively.
Efficient and robust 3D CT image reconstruction based on total generalized variation regularization using the alternating direction method.
Chen, Jianlin; Wang, Linyuan; Yan, Bin; Zhang, Hanming; Cheng, Genyang
Iterative reconstruction algorithms for computed tomography (CT) through total variation regularization based on piecewise constant assumption can produce accurate, robust, and stable results. Nonetheless, this approach is often subject to staircase artefacts and the loss of fine details. To overcome these shortcomings, we introduce a family of novel image regularization penalties called total generalized variation (TGV) for the effective production of high-quality images from incomplete or noisy projection data for 3D reconstruction. We propose a new, fast alternating direction minimization algorithm to solve CT image reconstruction problems through TGV regularization. Based on the theory of sparse-view image reconstruction and the framework of augmented Lagrange function method, the TGV regularization term has been introduced in the computed tomography and is transformed into three independent variables of the optimization problem by introducing auxiliary variables. This new algorithm applies a local linearization and proximity technique to make the FFT-based calculation of the analytical solutions in the frequency domain feasible, thereby significantly reducing the complexity of the algorithm. Experiments with various 3D datasets corresponding to incomplete projection data demonstrate the advantage of our proposed algorithm in terms of preserving fine details and overcoming the staircase effect. The computation cost also suggests that the proposed algorithm is applicable to and is effective for CBCT imaging. Theoretical and technical optimization should be investigated carefully in terms of both computation efficiency and high resolution of this algorithm in application-oriented research.
Tracking time interval changes of pulmonary nodules on follow-up 3D CT images via image-based risk score of lung cancer
NASA Astrophysics Data System (ADS)
Kawata, Y.; Niki, N.; Ohmatsu, H.; Kusumoto, M.; Tsuchida, T.; Eguchi, K.; Kaneko, M.; Moriyama, N.
In this paper, we present a computer-aided follow-up (CAF) scheme to support physicians to track interval changes of pulmonary nodules on three dimensional (3D) CT images and to decide the treatment strategies without making any under or over treatment. Our scheme involves analyzing CT histograms to evaluate the volumetric distribution of CT values within pulmonary nodules. A variational Bayesian mixture modeling framework translates the image-derived features into an image-based risk score for predicting the patient recurrence-free survival. Through applying our scheme to follow-up 3D CT images of pulmonary nodules, we demonstrate the potential usefulness of the CAF scheme which can provide the trajectories that can characterize time interval changes of pulmonary nodules.
Automated torso organ segmentation from 3D CT images using structured perceptron and dual decomposition
NASA Astrophysics Data System (ADS)
Nimura, Yukitaka; Hayashi, Yuichiro; Kitasaka, Takayuki; Mori, Kensaku
This paper presents a method for torso organ segmentation from abdominal CT images using structured perceptron and dual decomposition. A lot of methods have been proposed to enable automated extraction of organ regions from volumetric medical images. However, it is necessary to adjust empirical parameters of them to obtain precise organ regions. This paper proposes an organ segmentation method using structured output learning. Our method utilizes a graphical model and binary features which represent the relationship between voxel intensities and organ labels. Also we optimize the weights of the graphical model by structured perceptron and estimate the best organ label for a given image by dynamic programming and dual decomposition. The experimental result revealed that the proposed method can extract organ regions automatically using structured output learning. The error of organ label estimation was 4.4%. The DICE coefficients of left lung, right lung, heart, liver, spleen, pancreas, left kidney, right kidney, and gallbladder were 0.91, 0.95, 0.77, 0.81, 0.74, 0.08, 0.83, 0.84, and 0.03, respectively.
NASA Astrophysics Data System (ADS)
Carson, Jeffrey J. L.; Roumeliotis, Michael; Chaudhary, Govind; Stodilka, Robert Z.; Anastasio, Mark A.
Our group has concentrated on development of a 3D photoacoustic imaging system for biomedical imaging research. The technology employs a sparse parallel detection scheme and specialized reconstruction software to obtain 3D optical images using a single laser pulse. With the technology we have been able to capture 3D movies of translating point targets and rotating line targets. The current limitation of our 3D photoacoustic imaging approach is its inability ability to reconstruct complex objects in the field of view. This is primarily due to the relatively small number of projections used to reconstruct objects. However, in many photoacoustic imaging situations, only a few objects may be present in the field of view and these objects may have very high contrast compared to background. That is, the objects have sparse properties. Therefore, our work had two objectives: (i) to utilize mathematical tools to evaluate 3D photoacoustic imaging performance, and (ii) to test image reconstruction algorithms that prefer sparseness in the reconstructed images. Our approach was to utilize singular value decomposition techniques to study the imaging operator of the system and evaluate the complexity of objects that could potentially be reconstructed. We also compared the performance of two image reconstruction algorithms (algebraic reconstruction and l1-norm techniques) at reconstructing objects of increasing sparseness. We observed that for a 15-element detection scheme, the number of measureable singular vectors representative of the imaging operator was consistent with the demonstrated ability to reconstruct point and line targets in the field of view. We also observed that the l1-norm reconstruction technique, which is known to prefer sparseness in reconstructed images, was superior to the algebraic reconstruction technique. Based on these findings, we concluded (i) that singular value decomposition of the imaging operator provides valuable insight into the capabilities of
Parametric modeling of the intervertebral disc space in 3D: application to CT images of the lumbar spine.
Korez, Robert; Likar, Boštjan; Pernuš, Franjo; Vrtovec, Tomaž
Gradual degeneration of intervertebral discs of the lumbar spine is one of the most common causes of low back pain. Although conservative treatment for low back pain may provide relief to most individuals, surgical intervention may be required for individuals with significant continuing symptoms, which is usually performed by replacing the degenerated intervertebral disc with an artificial implant. For designing implants with good bone contact and continuous force distribution, the morphology of the intervertebral disc space and vertebral body endplates is of considerable importance. In this study, we propose a method for parametric modeling of the intervertebral disc space in three dimensions (3D) and show its application to computed tomography (CT) images of the lumbar spine. The initial 3D model of the intervertebral disc space is generated according to the superquadric approach and therefore represented by a truncated elliptical cone, which is initialized by parameters obtained from 3D models of adjacent vertebral bodies. In an optimization procedure, the 3D model of the intervertebral disc space is incrementally deformed by adding parameters that provide a more detailed morphometric description of the observed shape, and aligned to the observed intervertebral disc space in the 3D image. By applying the proposed method to CT images of 20 lumbar spines, the shape and pose of each of the 100 intervertebral disc spaces were represented by a 3D parametric model. The resulting mean (±standard deviation) accuracy of modeling was 1.06±0.98mm in terms of radial Euclidean distance against manually defined ground truth points, with the corresponding success rate of 93% (i.e. 93 out of 100 intervertebral disc spaces were modeled successfully). As the resulting 3D models provide a description of the shape of intervertebral disc spaces in a complete parametric form, morphometric analysis was straightforwardly enabled and allowed the computation of the corresponding
Estimation of aortic valve leaflets from 3D CT images using local shape dictionaries and linear coding
NASA Astrophysics Data System (ADS)
Liang, Liang; Martin, Caitlin; Wang, Qian; Sun, Wei; Duncan, James
Aortic valve (AV) disease is a significant cause of morbidity and mortality. The preferred treatment modality for severe AV disease is surgical resection and replacement of the native valve with either a mechanical or tissue prosthetic. In order to develop effective and long-lasting treatment methods, computational analyses, e.g., structural finite element (FE) and computational fluid dynamic simulations, are very effective for studying valve biomechanics. These computational analyses are based on mesh models of the aortic valve, which are usually constructed from 3D CT images though many hours of manual annotation, and therefore an automatic valve shape reconstruction method is desired. In this paper, we present a method for estimating the aortic valve shape from 3D cardiac CT images, which is represented by triangle meshes. We propose a pipeline for aortic valve shape estimation which includes novel algorithms for building local shape dictionaries and for building landmark detectors and curve detectors using local shape dictionaries. The method is evaluated on real patient image dataset using a leave-one-out approach and achieves an average accuracy of 0.69 mm. The work will facilitate automatic patient-specific computational modeling of the aortic valve.
Geometry-based vs. intensity-based medical image registration: A comparative study on 3D CT data.
Savva, Antonis D; Economopoulos, Theodore L; Matsopoulos, George K
Spatial alignment of Computed Tomography (CT) data sets is often required in numerous medical applications and it is usually achieved by applying conventional exhaustive registration techniques, which are mainly based on the intensity of the subject data sets. Those techniques consider the full range of data points composing the data, thus negatively affecting the required processing time. Alternatively, alignment can be performed using the correspondence of extracted data points from both sets. Moreover, various geometrical characteristics of those data points can be used, instead of their chromatic properties, for uniquely characterizing each point, by forming a specific geometrical descriptor. This paper presents a comparative study reviewing variations of geometry-based, descriptor-oriented registration techniques, as well as conventional, exhaustive, intensity-based methods for aligning three-dimensional (3D) CT data pairs. In this context, three general image registration frameworks were examined: a geometry-based methodology featuring three distinct geometrical descriptors, an intensity-based methodology using three different similarity metrics, as well as the commonly used Iterative Closest Point algorithm. All techniques were applied on a total of thirty 3D CT data pairs with both known and unknown initial spatial differences. After an extensive qualitative and quantitative assessment, it was concluded that the proposed geometry-based registration framework performed similarly to the examined exhaustive registration techniques. In addition, geometry-based methods dramatically improved processing time over conventional exhaustive registration.
Anatomy of hepatic arteriolo-portal venular shunts evaluated by 3D micro-CT imaging.
Kline, Timothy L; Knudsen, Bruce E; Anderson, Jill L; Vercnocke, Andrew J; Jorgensen, Steven M; Ritman, Erik L
The liver differs from other organs in that two vascular systems deliver its blood - the hepatic artery and the portal vein. However, how the two systems interact is not fully understood. We therefore studied the microvascular geometry of rat liver hepatic artery and portal vein injected with the contrast polymer Microfil(®). Intact isolated rat livers were imaged by micro-CT and anatomic evidence for hepatic arteriolo-portal venular shunts occurring between hepatic artery and portal vein branches was found. Simulations were performed to rule out the possibility of the observed shunts being artifacts resulting from image blurring. In addition, in the case of specimens where only the portal vein was injected, only the portal vein was opacified, whereas in hepatic artery injections, both the hepatic artery and portal vein were opacified. We conclude that mixing of the hepatic artery and portal vein blood can occur proximal to the sinusoidal level, and that the hepatic arteriolo-portal venular shunts may function as a one-way valve-like mechanism, allowing flow only from the hepatic artery to the portal vein (and not the other way around).
Automated detection of retinal cell nuclei in 3D micro-CT images of zebrafish using support vector machine classification
NASA Astrophysics Data System (ADS)
Ding, Yifu; Tavolara, Thomas; Cheng, Keith
Our group is developing a method to examine biological specimens in cellular detail using synchrotron microCT. The method can acquire 3D images of tissue at micrometer-scale resolutions, allowing for individual cell types to be visualized in the context of the entire specimen. For model organism research, this tool will enable the rapid characterization of tissue architecture and cellular morphology from every organ system. This characterization is critical for proposed and ongoing "phenome" projects that aim to phenotype whole-organism mutants and diseased tissues from different organisms including humans. With the envisioned collection of hundreds to thousands of images for a phenome project, it is important to develop quantitative image analysis tools for the automated scoring of organism phenotypes across organ systems. Here we present a first step towards that goal, demonstrating the use of support vector machines (SVM) in detecting retinal cell nuclei in 3D images of wild-type zebrafish. In addition, we apply the SVM classifier on a mutant zebrafish to examine whether SVMs can be used to capture phenotypic differences in these images. The longterm goal of this work is to allow cellular and tissue morphology to be characterized quantitatively for many organ systems, at the level of the whole-organism.
An innovative strategy for the identification and 3D reconstruction of pancreatic cancer from CT images.
Marconi, S; Pugliese, L; Del Chiaro, M; Pozzi Mucelli, R; Auricchio, F; Pietrabissa, A
We propose an innovative tool for Pancreatic Ductal AdenoCarcinoma 3D reconstruction from Multi-Detector-Computed Tomography. The tumor mass is discriminated from health tissue, and the resulting segmentation labels are rendered preserving information on different hypodensity levels. The final 3D virtual model includes also pancreas and main peri-pancreatic vessels, and it is suitable for 3D printing. We performed a preliminary evaluation of the tool effectiveness presenting ten cases of Pancreatic Ductal AdenoCarcinoma processed with the tool to an expert radiologist who can correct the result of the discrimination. In seven of ten cases, the 3D reconstruction is accepted without any modification, while in three cases, only 1.88, 5.13, and 5.70 %, respectively, of the segmentation labels are modified, preliminary proving the high effectiveness of the tool.
Detection accuracy of condylar bony defects in Promax 3D cone beam CT images scanned with different protocols
Zhang, Z-L; Cheng, J-G; Li, G; Shi, X-Q; Zhang, J-Z; Zhang, Z-Y; Ma, X-C
Objectives: To investigate and compare the detection accuracy of bony defects on the condylar surface of the temporomandibular joint (TMJ) in cone beam CT (CBCT) images scanned with standard and large view protocols on the same machine. Methods: 21 dry human skulls with 42 TMJs were scanned with the large view and standard view protocols of the CBCT scanner Promax 3D (Planmeca, Helsinki, Finland). Seven observers evaluated all the images for the presence or absence of defects on the surface of the condyle. Using the macroscopic examination of condylar defects as the gold standard, receiver operating characteristic (ROC) analysis was performed. Results: Macroscopic examination revealed that, of the 42 condyles, 18 were normal and 24 had a defect on the surface of the condyles. Areas under the ROC curves for the large view and the standard view group of CBCT images were 0.739 and 0.720, respectively, and no significant difference was found between the two groups of images (p = 0.902). Neither the interobserver nor the intraobserver variability were significant. Conclusions: The two scanning protocols provided by the CBCT scanner Promax 3D were reliable and comparable with detection of condylar defects. PMID:23420852
Registration of 2D C-Arm and 3D CT Images for a C-Arm Image-Assisted Navigation System for Spinal Surgery
Chang, Chih-Ju; Lin, Geng-Li; Tse, Alex; Chu, Hong-Yu; Tseng, Ching-Shiow
C-Arm image-assisted surgical navigation system has been broadly applied to spinal surgery. However, accurate path planning on the C-Arm AP-view image is difficult. This research studies 2D-3D image registration methods to obtain the optimum transformation matrix between C-Arm and CT image frames. Through the transformation matrix, the surgical path planned on preoperative CT images can be transformed and displayed on the C-Arm images for surgical guidance. The positions of surgical instruments will also be displayed on both CT and C-Arm in the real time. Five similarity measure methods of 2D-3D image registration including Normalized Cross-Correlation, Gradient Correlation, Pattern Intensity, Gradient Difference Correlation, and Mutual Information combined with three optimization methods including Powell's method, Downhill simplex algorithm, and genetic algorithm are applied to evaluate their performance in converge range, efficiency, and accuracy. Experimental results show that the combination of Normalized Cross-Correlation measure method with Downhill simplex algorithm obtains maximum correlation and similarity in C-Arm and Digital Reconstructed Radiograph (DRR) images. Spine saw bones are used in the experiment to evaluate 2D-3D image registration accuracy. The average error in displacement is 0.22 mm. The success rate is approximately 90% and average registration time takes 16 seconds. PMID:27018859
Use of the FLUKA Monte Carlo code for 3D patient-specific dosimetry on PET-CT and SPECT-CT images.
Botta, F; Mairani, A; Hobbs, R F; Vergara Gil, A; Pacilio, M; Parodi, K; Cremonesi, M; Coca Pérez, M A; Di Dia, A; Ferrari, M; Guerriero, F; Battistoni, G; Pedroli, G; Paganelli, G; Torres Aroche, L A; Sgouros, G
Patient-specific absorbed dose calculation for nuclear medicine therapy is a topic of increasing interest. 3D dosimetry at the voxel level is one of the major improvements for the development of more accurate calculation techniques, as compared to the standard dosimetry at the organ level. This study aims to use the FLUKA Monte Carlo code to perform patient-specific 3D dosimetry through direct Monte Carlo simulation on PET-CT and SPECT-CT images. To this aim, dedicated routines were developed in the FLUKA environment. Two sets of simulations were performed on model and phantom images. Firstly, the correct handling of PET and SPECT images was tested under the assumption of homogeneous water medium by comparing FLUKA results with those obtained with the voxel kernel convolution method and with other Monte Carlo-based tools developed to the same purpose (the EGS-based 3D-RD software and the MCNP5-based MCID). Afterwards, the correct integration of the PET/SPECT and CT information was tested, performing direct simulations on PET/CT images for both homogeneous (water) and non-homogeneous (water with air, lung and bone inserts) phantoms. Comparison was performed with the other Monte Carlo tools performing direct simulation as well. The absorbed dose maps were compared at the voxel level. In the case of homogeneous water, by simulating 10(8) primary particles a 2% average difference with respect to the kernel convolution method was achieved; such difference was lower than the statistical uncertainty affecting the FLUKA results. The agreement with the other tools was within 3–4%, partially ascribable to the differences among the simulation algorithms. Including the CT-based density map, the average difference was always within 4% irrespective of the medium (water, air, bone), except for a maximum 6% value when comparing FLUKA and 3D-RD in air. The results confirmed that the routines were properly developed, opening the way for the use of FLUKA for patient-specific, image
Use of the FLUKA Monte Carlo code for 3D patient-specific dosimetry on PET-CT and SPECT-CT images*
Botta, F; Mairani, A; Hobbs, R F; Vergara Gil, A; Pacilio, M; Parodi, K; Cremonesi, M; Coca Pérez, M A; Di Dia, A; Ferrari, M; Guerriero, F; Battistoni, G; Pedroli, G; Paganelli, G; Torres Aroche, L A; Sgouros, G
Patient-specific absorbed dose calculation for nuclear medicine therapy is a topic of increasing interest. 3D dosimetry at the voxel level is one of the major improvements for the development of more accurate calculation techniques, as compared to the standard dosimetry at the organ level. This study aims to use the FLUKA Monte Carlo code to perform patient-specific 3D dosimetry through direct Monte Carlo simulation on PET-CT and SPECT-CT images. To this aim, dedicated routines were developed in the FLUKA environment. Two sets of simulations were performed on model and phantom images. Firstly, the correct handling of PET and SPECT images was tested under the assumption of homogeneous water medium by comparing FLUKA results with those obtained with the voxel kernel convolution method and with other Monte Carlo-based tools developed to the same purpose (the EGS-based 3D-RD software and the MCNP5-based MCID). Afterwards, the correct integration of the PET/SPECT and CT information was tested, performing direct simulations on PET/CT images for both homogeneous (water) and non-homogeneous (water with air, lung and bone inserts) phantoms. Comparison was performed with the other Monte Carlo tools performing direct simulation as well. The absorbed dose maps were compared at the voxel level. In the case of homogeneous water, by simulating 108 primary particles a 2% average difference with respect to the kernel convolution method was achieved; such difference was lower than the statistical uncertainty affecting the FLUKA results. The agreement with the other tools was within 3–4%, partially ascribable to the differences among the simulation algorithms. Including the CT-based density map, the average difference was always within 4% irrespective of the medium (water, air, bone), except for a maximum 6% value when comparing FLUKA and 3D-RD in air. The results confirmed that the routines were properly developed, opening the way for the use of FLUKA for patient-specific, image
Use of the FLUKA Monte Carlo code for 3D patient-specific dosimetry on PET-CT and SPECT-CT images
NASA Astrophysics Data System (ADS)
Botta, F.; Mairani, A.; Hobbs, R. F.; Vergara Gil, A.; Pacilio, M.; Parodi, K.; Cremonesi, M.; Coca Pérez, M. A.; Di Dia, A.; Ferrari, M.; Guerriero, F.; Battistoni, G.; Pedroli, G.; Paganelli, G.; Torres Aroche, L. A.; Sgouros, G.
Patient-specific absorbed dose calculation for nuclear medicine therapy is a topic of increasing interest. 3D dosimetry at the voxel level is one of the major improvements for the development of more accurate calculation techniques, as compared to the standard dosimetry at the organ level. This study aims to use the FLUKA Monte Carlo code to perform patient-specific 3D dosimetry through direct Monte Carlo simulation on PET-CT and SPECT-CT images. To this aim, dedicated routines were developed in the FLUKA environment. Two sets of simulations were performed on model and phantom images. Firstly, the correct handling of PET and SPECT images was tested under the assumption of homogeneous water medium by comparing FLUKA results with those obtained with the voxel kernel convolution method and with other Monte Carlo-based tools developed to the same purpose (the EGS-based 3D-RD software and the MCNP5-based MCID). Afterwards, the correct integration of the PET/SPECT and CT information was tested, performing direct simulations on PET/CT images for both homogeneous (water) and non-homogeneous (water with air, lung and bone inserts) phantoms. Comparison was performed with the other Monte Carlo tools performing direct simulation as well. The absorbed dose maps were compared at the voxel level. In the case of homogeneous water, by simulating 108 primary particles a 2% average difference with respect to the kernel convolution method was achieved; such difference was lower than the statistical uncertainty affecting the FLUKA results. The agreement with the other tools was within 3-4%, partially ascribable to the differences among the simulation algorithms. Including the CT-based density map, the average difference was always within 4% irrespective of the medium (water, air, bone), except for a maximum 6% value when comparing FLUKA and 3D-RD in air. The results confirmed that the routines were properly developed, opening the way for the use of FLUKA for patient-specific, image
Effects of x-ray and CT image enhancements on the robustness and accuracy of a rigid 3D/2D image registration.
Kim, Jinkoo; Yin, Fang-Fang; Zhao, Yang; Kim, Jae Ho
A rigid body three-dimensional/two-dimensional (3D/2D) registration method has been implemented using mutual information, gradient ascent, and 3D texturemap-based digitally reconstructed radiographs. Nine combinations of commonly used x-ray and computed tomography (CT) image enhancement methods, including window leveling, histogram equalization, and adaptive histogram equalization, were examined to assess their effects on accuracy and robustness of the registration method. From a set of experiments using an anthropomorphic chest phantom, we were able to draw several conclusions. First, the CT and x-ray preprocessing combination with the widest attraction range was the one that linearly stretched the histograms onto the entire display range on both CT and x-ray images. The average attraction ranges of this combination were 71.3 mm and 61.3 deg in the translation and rotation dimensions, respectively, and the average errors were 0.12 deg and 0.47 mm. Second, the combination of the CT image with tissue and bone information and the x-ray images with adaptive histogram equalization also showed subvoxel accuracy, especially the best in the translation dimensions. However, its attraction ranges were the smallest among the examined combinations (on average 36 mm and 19 deg). Last the bone-only information on the CT image did not show convergency property to the correct registration.
A fast rigid-registration method of inferior limb X-ray image and 3D CT images for TKA surgery
NASA Astrophysics Data System (ADS)
Ito, Fumihito; O. D. A, Prima; Uwano, Ikuko; Ito, Kenzo
In this paper, we propose a fast rigid-registration method of inferior limb X-ray films (two-dimensional Computed Radiography (CR) images) and three-dimensional Computed Tomography (CT) images for Total Knee Arthroplasty (TKA) surgery planning. The position of the each bone, such as femur and tibia (shin bone), in X-ray film and 3D CT images is slightly different, and we must pay attention how to use the two different images, since X-ray film image is captured in the standing position, and 3D CT is captured in decubitus (face up) position, respectively. Though the conventional registration mainly uses cross-correlation function between two images,and utilizes optimization techniques, it takes enormous calculation time and it is difficult to use it in interactive operations. In order to solve these problems, we calculate the center line (bone axis) of femur and tibia (shin bone) automatically, and we use them as initial positions for the registration. We evaluate our registration method by using three patient's image data, and we compare our proposed method and a conventional registration, which uses down-hill simplex algorithm. The down-hill simplex method is an optimization algorithm that requires only function evaluations, and doesn't need the calculation of derivatives. Our registration method is more effective than the downhill simplex method in computational time and the stable convergence. We have developed the implant simulation system on a personal computer, in order to support the surgeon in a preoperative planning of TKA. Our registration method is implemented in the simulation system, and user can manipulate 2D/3D translucent templates of implant components on X-ray film and 3D CT images.
3D imaging of lung tissue by confocal microscopy and micro-CT
NASA Astrophysics Data System (ADS)
Kriete, Andres; Breithecker, Andreas; Rau, Wigbert D.
Two complementary techniques for the imaging of tissue subunits are discussed. A computer guided light microscopic imaging technique is described first, which confocally resolves thick serial sections axially. The lateral area of interest is increased by scanning a mosaic of images in each plane. Subsequently, all images are fused digitally to form a highly resolved volume exhibiting the fine structure of complete respiratory units of lung. A different technique described is based on microtomography. This method allows to image volumes up to 3x3x3 cm at a resolution of up to 7 microns. Due to the lack of strong density differences, a contrast enhancement procedure is introduced which makes this technique applicable for the imaging of lung tissue. Imaging, visualization and analysis described here are parts of an ongoing project to model structure and to simulate function of tissue subunits and complete organs.
Three-dimensional image technology in forensic anthropology: Assessing the validity of biological profiles derived from CT-3D images of the skeleton
NASA Astrophysics Data System (ADS)
Garcia de Leon Valenzuela, Maria Julia
This project explores the reliability of building a biological profile for an unknown individual based on three-dimensional (3D) images of the individual's skeleton. 3D imaging technology has been widely researched for medical and engineering applications, and it is increasingly being used as a tool for anthropological inquiry. While the question of whether a biological profile can be derived from 3D images of a skeleton with the same accuracy as achieved when using dry bones has been explored, bigger sample sizes, a standardized scanning protocol and more interobserver error data are needed before 3D methods can become widely and confidently used in forensic anthropology. 3D images of Computed Tomography (CT) scans were obtained from 130 innominate bones from Boston University's skeletal collection (School of Medicine). For each bone, both 3D images and original bones were assessed using the Phenice and Suchey-Brooks methods. Statistical analysis was used to determine the agreement between 3D image assessment versus traditional assessment. A pool of six individuals with varying experience in the field of forensic anthropology scored a subsample (n = 20) to explore interobserver error. While a high agreement was found for age and sex estimation for specimens scored by the author, the interobserver study shows that observers found it difficult to apply standard methods to 3D images. Higher levels of experience did not result in higher agreement between observers, as would be expected. Thus, a need for training in 3D visualization before applying anthropological methods to 3D bones is suggested. Future research should explore interobserver error using a larger sample size in order to test the hypothesis that training in 3D visualization will result in a higher agreement between scores. The need for the development of a standard scanning protocol focusing on the optimization of 3D image resolution is highlighted. Applications for this research include the possibility
High-accuracy 3D image-based registration of endoscopic video to C-arm cone-beam CT for image-guided skull base surgery
NASA Astrophysics Data System (ADS)
Mirota, Daniel J.; Uneri, Ali; Schafer, Sebastian; Nithiananthan, Sajendra; Reh, Douglas D.; Gallia, Gary L.; Taylor, Russell H.; Hager, Gregory D.; Siewerdsen, Jeffrey H.
Registration of endoscopic video to preoperative CT facilitates high-precision surgery of the head, neck, and skull-base. Conventional video-CT registration is limited by the accuracy of the tracker and does not use the underlying video or CT image data. A new image-based video registration method has been developed to overcome the limitations of conventional tracker-based registration. This method adds to a navigation system based on intraoperative C-arm cone-beam CT (CBCT), in turn providing high-accuracy registration of video to the surgical scene. The resulting registration enables visualization of the CBCT and planning data within the endoscopic video. The system incorporates a mobile C-arm, integrated with an optical tracking system, video endoscopy, deformable registration of preoperative CT with intraoperative CBCT, and 3D visualization. Similarly to tracker-based approach, the image-based video-CBCT registration the endoscope is localized with optical tracking system followed by a direct 3D image-based registration of the video to the CBCT. In this way, the system achieves video-CBCT registration that is both fast and accurate. Application in skull-base surgery demonstrates overlay of critical structures (e.g., carotid arteries) and surgical targets with sub-mm accuracy. Phantom and cadaver experiments show consistent improvement of target registration error (TRE) in video overlay over conventional tracker-based registration-e.g., 0.92mm versus 1.82mm for image-based and tracker-based registration, respectively. The proposed method represents a two-fold advance-first, through registration of video to up-to-date intraoperative CBCT, and second, through direct 3D image-based video-CBCT registration, which together provide more confident visualization of target and normal tissues within up-to-date images.
Automatic segmentation of solitary pulmonary nodules based on local intensity structure analysis and 3D neighborhood features in 3D chest CT images
NASA Astrophysics Data System (ADS)
Chen, Bin; Kitasaka, Takayuki; Honma, Hirotoshi; Takabatake, Hirotsugu; Mori, Masaki; Natori, Hiroshi; Mori, Kensaku
This paper presents a solitary pulmonary nodule (SPN) segmentation method based on local intensity structure analysis and neighborhood feature analysis in chest CT images. Automated segmentation of SPNs is desirable for a chest computer-aided detection/diagnosis (CAS) system since a SPN may indicate early stage of lung cancer. Due to the similar intensities of SPNs and other chest structures such as blood vessels, many false positives (FPs) are generated by nodule detection methods. To reduce such FPs, we introduce two features that analyze the relation between each segmented nodule candidate and it neighborhood region. The proposed method utilizes a blob-like structure enhancement (BSE) filter based on Hessian analysis to augment the blob-like structures as initial nodule candidates. Then a fine segmentation is performed to segment much more accurate region of each nodule candidate. FP reduction is mainly addressed by investigating two neighborhood features based on volume ratio and eigenvector of Hessian that are calculates from the neighborhood region of each nodule candidate. We evaluated the proposed method by using 40 chest CT images, include 20 standard-dose CT images that we randomly chosen from a local database and 20 low-dose CT images that were randomly chosen from a public database: LIDC. The experimental results revealed that the average TP rate of proposed method was 93.6% with 12.3 FPs/case.
Automated torso organ segmentation from 3D CT images using conditional random field
NASA Astrophysics Data System (ADS)
Nimura, Yukitaka; Hayashi, Yuichiro; Kitasaka, Takayuki; Misawa, Kazunari; Mori, Kensaku
This paper presents a segmentation method for torso organs using conditional random field (CRF) from medical images. A lot of methods have been proposed to enable automated extraction of organ regions from volumetric medical images. However, it is necessary to adjust empirical parameters of them to obtain precise organ regions. In this paper, we propose an organ segmentation method using structured output learning which is based on probabilistic graphical model. The proposed method utilizes CRF on three-dimensional grids as probabilistic graphical model and binary features which represent the relationship between voxel intensities and organ labels. Also we optimize the weight parameters of the CRF using stochastic gradient descent algorithm and estimate organ labels for a given image by maximum a posteriori (MAP) estimation. The experimental result revealed that the proposed method can extract organ regions automatically using structured output learning. The error of organ label estimation was 6.6%. The DICE coefficients of right lung, left lung, heart, liver, spleen, right kidney, and left kidney are 0.94, 0.92, 0.65, 0.67, 0.36, 0.38, and 0.37, respectively.
Automatic localization of target vertebrae in spine surgery using fast CT-to-fluoroscopy (3D-2D) image registration
NASA Astrophysics Data System (ADS)
Otake, Y.; Schafer, S.; Stayman, J. W.; Zbijewski, W.; Kleinszig, G.; Graumann, R.; Khanna, A. J.; Siewerdsen, J. H.
Localization of target vertebrae is an essential step in minimally invasive spine surgery, with conventional methods relying on "level counting" - i.e., manual counting of vertebrae under fluoroscopy starting from readily identifiable anatomy (e.g., the sacrum). The approach requires an undesirable level of radiation, time, and is prone to counting errors due to the similar appearance of vertebrae in projection images; wrong-level surgery occurs in 1 of every ~3000 cases. This paper proposes a method to automatically localize target vertebrae in x-ray projections using 3D-2D registration between preoperative CT (in which vertebrae are preoperatively labeled) and intraoperative fluoroscopy. The registration uses an intensity-based approach with a gradient-based similarity metric and the CMA-ES algorithm for optimization. Digitally reconstructed radiographs (DRRs) and a robust similarity metric are computed on GPU to accelerate the process. Evaluation in clinical CT data included 5,000 PA and LAT projections randomly perturbed to simulate human variability in setup of mobile intraoperative C-arm. The method demonstrated 100% success for PA view (projection error: 0.42mm) and 99.8% success for LAT view (projection error: 0.37mm). Initial implementation on GPU provided automatic target localization within about 3 sec, with further improvement underway via multi-GPU. The ability to automatically label vertebrae in fluoroscopy promises to streamline surgical workflow, improve patient safety, and reduce wrong-site surgeries, especially in large patients for whom manual methods are time consuming and error prone.
A novel 3D graph cut based co-segmentation of lung tumor on PET-CT images with Gaussian mixture models
NASA Astrophysics Data System (ADS)
Yu, Kai; Chen, Xinjian; Shi, Fei; Zhu, Weifang; Zhang, Bin; Xiang, Dehui
Positron Emission Tomography (PET) and Computed Tomography (CT) have been widely used in clinical practice for radiation therapy. Most existing methods only used one image modality, either PET or CT, which suffers from the low spatial resolution in PET or low contrast in CT. In this paper, a novel 3D graph cut method is proposed, which integrated Gaussian Mixture Models (GMMs) into the graph cut method. We also employed the random walk method as an initialization step to provide object seeds for the improvement of the graph cut based segmentation on PET and CT images. The constructed graph consists of two sub-graphs and a special link between the sub-graphs which penalize the difference segmentation between the two modalities. Finally, the segmentation problem is solved by the max-flow/min-cut method. The proposed method was tested on 20 patients' PET-CT images, and the experimental results demonstrated the accuracy and efficiency of the proposed algorithm.
Automatic organ localizations on 3D CT images by using majority-voting of multiple 2D detections based on local binary patterns and Haar-like features
NASA Astrophysics Data System (ADS)
Zhou, Xiangrong; Yamaguchi, Shoutarou; Zhou, Xinxin; Chen, Huayue; Hara, Takeshi; Yokoyama, Ryujiro; Kanematsu, Masayuki; Fujita, Hiroshi
This paper describes an approach to accomplish the fast and automatic localization of the different inner organ regions on 3D CT scans. The proposed approach combines object detections and the majority voting technique to achieve the robust and quick organ localization. The basic idea of proposed method is to detect a number of 2D partial appearances of a 3D target region on CT images from multiple body directions, on multiple image scales, by using multiple feature spaces, and vote all the 2D detecting results back to the 3D image space to statistically decide one 3D bounding rectangle of the target organ. Ensemble learning was used to train the multiple 2D detectors based on template matching on local binary patterns and Haar-like feature spaces. A collaborative voting was used to decide the corner coordinates of the 3D bounding rectangle of the target organ region based on the coordinate histograms from detection results in three body directions. Since the architecture of the proposed method (multiple independent detections connected to a majority voting) naturally fits the parallel computing paradigm and multi-core CPU hardware, the proposed algorithm was easy to achieve a high computational efficiently for the organ localizations on a whole body CT scan by using general-purpose computers. We applied this approach to localization of 12 kinds of major organ regions independently on 1,300 torso CT scans. In our experiments, we randomly selected 300 CT scans (with human indicated organ and tissue locations) for training, and then, applied the proposed approach with the training results to localize each of the target regions on the other 1,000 CT scans for the performance testing. The experimental results showed the possibility of the proposed approach to automatically locate different kinds of organs on the whole body CT scans.
Detecting Radiation-Induced Injury Using Rapid 3D Variogram Analysis of CT Images of Rat Lungs
Jacob, Richard E.; Murphy, Mark K.; Creim, Jeffrey A.; Carson, James P.
Rationale and Objectives To investigate the ability of variogram analysis of octree-decomposed CT images and volume change maps to detect radiation-induced damage in rat lungs. Materials and Methods The lungs of female Sprague-Dawley rats were exposed to one of five absorbed doses (0, 6, 9, 12, or 15 Gy) of gamma radiation from a Co-60 source. At 6 months post-exposure, pulmonary function tests were performed and 4DCT images were acquired using a respiratory-gated microCT scanner. Volume change maps were then calculated from the 4DCT images. Octree decomposition was performed on CT images and volume change maps, and variogram analysis was applied to the decomposed images. Correlations of measured parameters with dose were evaluated. Results The effects of irradiation were not detectable from measured parameters, indicating only mild lung damage. Additionally, there were no significant correlations of pulmonary function results or CT densitometry with radiation dose. However, the variogram analysis did detect a significant correlation with dose in both the CT images (r=−0.57, p=0.003) and the volume change maps (r=−0.53, p=0.008). Conclusion This is the first study to utilize variogram analysis of lung images to assess pulmonary damage in a model of radiation injury. Results show that this approach is more sensitive to detecting radiation damage than conventional measures such as pulmonary function tests or CT densitometry. PMID:24029058
Fusion of cone-beam CT and 3D photographic images for soft tissue simulation in maxillofacial surgery
NASA Astrophysics Data System (ADS)
Chung, Soyoung; Kim, Joojin; Hong, Helen
During maxillofacial surgery, prediction of the facial outcome after surgery is main concern for both surgeons and patients. However, registration of the facial CBCT images and 3D photographic images has some difficulties that regions around the eyes and mouth are affected by facial expressions or the registration speed is low due to their dense clouds of points on surfaces. Therefore, we propose a framework for the fusion of facial CBCT images and 3D photos with skin segmentation and two-stage surface registration. Our method is composed of three major steps. First, to obtain a CBCT skin surface for the registration with 3D photographic surface, skin is automatically segmented from CBCT images and the skin surface is generated by surface modeling. Second, to roughly align the scale and the orientation of the CBCT skin surface and 3D photographic surface, point-based registration with four corresponding landmarks which are located around the mouth is performed. Finally, to merge the CBCT skin surface and 3D photographic surface, Gaussian-weight-based surface registration is performed within narrow-band of 3D photographic surface.
The effect of spatial micro-CT image resolution and surface complexity on the morphological 3D analysis of open porous structures
Pyka, Grzegorz; Kerckhofs, Greet
In material science microfocus X-ray computed tomography (micro-CT) is one of the most popular non-destructive techniques to visualise and quantify the internal structure of materials in 3D. Despite constant system improvements, state-of-the-art micro-CT images can still hold several artefacts typical for X-ray CT imaging that hinder further image-based processing, structural and quantitative analysis. For example spatial resolution is crucial for an appropriate characterisation as the voxel size essentially influences the partial volume effect. However, defining the adequate image resolution is not a trivial aspect and understanding the correlation between scan parameters like voxel size and the structural properties is crucial for comprehensive material characterisation using micro-CT. Therefore, the objective of this study was to evaluate the influence of the spatial image resolution on the micro-CT based morphological analysis of three-dimensional (3D) open porous structures with a high surface complexity. In particular the correlation between the local surface properties and the accuracy of the micro-CT-based macro-morphology of 3D open porous Ti6Al4V structures produced by selective laser melting (SLM) was targeted and revealed for rough surfaces a strong dependence of the resulting structure characteristics on the scan resolution. Reducing the surface complexity by chemical etching decreased the sensitivity of the overall morphological analysis to the spatial image resolution and increased the detection limit. This study showed that scan settings and image processing parameters need to be customized to the material properties, morphological parameters under investigation and the desired final characteristics (in relation to the intended functional use). Customization of the scan resolution can increase the reliability of the micro-CT based analysis and at the same time reduce its operating costs. - Highlights: • We examine influence of the image resolution
SU-C-201-06: Utility of Quantitative 3D SPECT/CT Imaging in Patient Specific Internal Dosimetry of 153-Samarium with GATE Monte Carlo Package
Fallahpoor, M; Abbasi, M; Sen, A; Parach, A; Kalantari, F
Purpose: Patient-specific 3-dimensional (3D) internal dosimetry in targeted radionuclide therapy is essential for efficient treatment. Two major steps to achieve reliable results are: 1) generating quantitative 3D images of radionuclide distribution and attenuation coefficients and 2) using a reliable method for dose calculation based on activity and attenuation map. In this research, internal dosimetry for 153-Samarium (153-Sm) was done by SPECT-CT images coupled GATE Monte Carlo package for internal dosimetry. Methods: A 50 years old woman with bone metastases from breast cancer was prescribed 153-Sm treatment (Gamma: 103keV and beta: 0.81MeV). A SPECT/CT scan was performed with the Siemens Simbia-T scanner. SPECT and CT images were registered using default registration software. SPECT quantification was achieved by compensating for all image degrading factors including body attenuation, Compton scattering and collimator-detector response (CDR). Triple energy window method was used to estimate and eliminate the scattered photons. Iterative ordered-subsets expectation maximization (OSEM) with correction for attenuation and distance-dependent CDR was used for image reconstruction. Bilinear energy mapping is used to convert Hounsfield units in CT image to attenuation map. Organ borders were defined by the itk-SNAP toolkit segmentation on CT image. GATE was then used for internal dose calculation. The Specific Absorbed Fractions (SAFs) and S-values were reported as MIRD schema. Results: The results showed that the largest SAFs and S-values are in osseous organs as expected. S-value for lung is the highest after spine that can be important in 153-Sm therapy. Conclusion: We presented the utility of SPECT-CT images and Monte Carlo for patient-specific dosimetry as a reliable and accurate method. It has several advantages over template-based methods or simplified dose estimation methods. With advent of high speed computers, Monte Carlo can be used for treatment planning
Correlative 3D-imaging of Pipistrellus penis micromorphology: Validating quantitative microCT images with undecalcified serial ground section histomorphology.
Herdina, Anna Nele; Plenk, Hanns; Benda, Petr; Lina, Peter H C; Herzig-Straschil, Barbara; Hilgers, Helge; Metscher, Brian D
Detailed knowledge of histomorphology is a prerequisite for the understanding of function, variation, and development. In bats, as in other mammals, penis and baculum morphology are important in species discrimination and phylogenetic studies. In this study, nondestructive 3D-microtomographic (microCT, µCT) images of bacula and iodine-stained penes of Pipistrellus pipistrellus were correlated with light microscopic images from undecalcified surface-stained ground sections of three of these penes of P. pipistrellus (1 juvenile). The results were then compared with µCT-images of bacula of P. pygmaeus, P. hanaki, and P. nathusii. The Y-shaped baculum in all studied Pipistrellus species has a proximal base with two club-shaped branches, a long slender shaft, and a forked distal tip. The branches contain a medullary cavity of variable size, which tapers into a central canal of variable length in the proximal baculum shaft. Both are surrounded by a lamellar and a woven bone layer and contain fatty marrow and blood vessels. The distal shaft consists of woven bone only, without a vascular canal. The proximal ends of the branches are connected with the tunica albuginea of the corpora cavernosa via entheses. In the penis shaft, the corpus spongiosum-surrounded urethra lies in a ventral grove of the corpora cavernosa, and continues in the glans under the baculum. The glans penis predominantly comprises an enlarged corpus spongiosum, which surrounds urethra and baculum. In the 12 studied juvenile and subadult P. pipistrellus specimens the proximal branches of the baculum were shorter and without marrow cavity, while shaft and distal tip appeared already fully developed. The present combination with light microscopic images from one species enabled a more reliable interpretation of histomorphological structures in the µCT-images from all four Pipistrellus species.
Evaluation of the combined effects of target size, respiratory motion and background activity on 3D and 4D PET/CT images
NASA Astrophysics Data System (ADS)
Park, Sang-June; Ionascu, Dan; Killoran, Joseph; Mamede, Marcelo; Gerbaudo, Victor H.; Chin, Lee; Berbeco, Ross
Gated (4D) PET/CT has the potential to greatly improve the accuracy of radiotherapy at treatment sites where internal organ motion is significant. However, the best methodology for applying 4D-PET/CT to target definition is not currently well established. With the goal of better understanding how to best apply 4D information to radiotherapy, initial studies were performed to investigate the effect of target size, respiratory motion and target-to-background activity concentration ratio (TBR) on 3D (ungated) and 4D PET images. Using a PET/CT scanner with 4D or gating capability, a full 3D-PET scan corrected with a 3D attenuation map from 3D-CT scan and a respiratory gated (4D) PET scan corrected with corresponding attenuation maps from 4D-CT were performed by imaging spherical targets (0.5-26.5 mL) filled with 18F-FDG in a dynamic thorax phantom and NEMA IEC body phantom at different TBRs (infinite, 8 and 4). To simulate respiratory motion, the phantoms were driven sinusoidally in the superior-inferior direction with amplitudes of 0, 1 and 2 cm and a period of 4.5 s. Recovery coefficients were determined on PET images. In addition, gating methods using different numbers of gating bins (1-20 bins) were evaluated with image noise and temporal resolution. For evaluation, volume recovery coefficient, signal-to-noise ratio and contrast-to-noise ratio were calculated as a function of the number of gating bins. Moreover, the optimum thresholds which give accurate moving target volumes were obtained for 3D and 4D images. The partial volume effect and signal loss in the 3D-PET images due to the limited PET resolution and the respiratory motion, respectively were measured. The results show that signal loss depends on both the amplitude and pattern of respiratory motion. However, the 4D-PET successfully recovers most of the loss induced by the respiratory motion. The 5-bin gating method gives the best temporal resolution with acceptable image noise. The results based on the 4D
An Optimized Spline-Based Registration of a 3D CT to a Set of C-Arm Images.
Jonić, S; Thévenaz, P; Zheng, G; Nolte, L-P; Unser, M
We have developed an algorithm for the rigid-body registration of a CT volume to a set of C-arm images. The algorithm uses a gradient-based iterative minimization of a least-squares measure of dissimilarity between the C-arm images and projections of the CT volume. To compute projections, we use a novel method for fast integration of the volume along rays. To improve robustness and speed, we take advantage of a coarse-to-fine processing of the volume/image pyramids. To compute the projections of the volume, the gradient of the dissimilarity measure, and the multiresolution data pyramids, we use a continuous image/volume model based on cubic B-splines, which ensures a high interpolation accuracy and a gradient of the dissimilarity measure that is well defined everywhere. We show the performance of our algorithm on a human spine phantom, where the true alignment is determined using a set of fiducial markers.
Detecting Radiation-Induced Injury Using Rapid 3D Variogram Analysis of CT Images of Rat Lungs
Jacob, Rick E.; Murphy, Mark K.; Creim, Jeffrey A.; Carson, James P.
A new heterogeneity analysis approach to discern radiation-induced lung damage was tested on CT images of irradiated rats. The method, combining octree decomposition with variogram analysis, demonstrated a significant correlation with radiation exposure levels, whereas conventional measurements and pulmonary function tests did not. The results suggest the new approach may be highly sensitive for assessing even subtle radiation-induced changes
Determination of 3D location and rotation of lumbar vertebrae in CT images by symmetry-based auto-registration
NASA Astrophysics Data System (ADS)
Vrtovec, Tomaž; Likar, Boštjan; Pernuš, Franjo
Quantitative measurement of vertebral rotation is important in surgical planning, analysis of surgical results, and monitoring of the progression of spinal deformities. However, many established and newly developed techniques for measuring axial vertebral rotation do not exploit three-dimensional (3D) information, which may result in virtual axial rotation because of the sagittal and coronal rotation of vertebrae. We propose a novel automatic approach to the measurement of the location and rotation of vertebrae in 3D without prior volume reformation, identification of appropriate cross-sections or aid by statistical models. The vertebra under investigation is encompassed by a mask in the form of an elliptical cylinder in 3D, defined by its center of rotation and the rotation angles. We exploit the natural symmetry of the vertebral body, vertebral column and vertebral canal by dividing the vertebral mask by its mid-axial, mid-sagittal and mid-coronal plane, so that the obtained volume pairs contain symmetrical parts of the observed anatomy. Mirror volume pairs are then simultaneously registered to each other by robust rigid auto-registration, using the weighted sum of absolute differences between the intensities of the corresponding volume pairs as the similarity measure. The method was evaluated on 50 lumbar vertebrae from normal and scoliotic computed tomography (CT) spinal scans, showing relatively large capture ranges and distinctive maxima at the correct locations and rotation angles. The proposed method may aid the measurement of the dimensions of vertebral pedicles, foraminae and canal, and may be a valuable tool for clinical evaluation of the spinal deformities in 3D.
Cardiac image reconstruction on a 16-slice CT scanner using a retrospectively ECG-gated multicycle 3D back-projection algorithm
NASA Astrophysics Data System (ADS)
Shechter, Gilad; Naveh, Galit; Altman, Ami; Proksa, Roland M.; Grass, Michael
Fast 16-slice spiral CT delivers superior cardiac visualization in comparison to older generation 2- to 8-slice scanners due to the combination of high temporal resolution along with isotropic spatial resolution and large coverage. The large beam opening of such scanners necessitates the use of adequate algorithms to avoid cone beam artifacts. We have developed a multi-cycle phase selective 3D back projection reconstruction algorithm that provides excellent temporal and spatial resolution for 16-slice CT cardiac images free of cone beam artifacts.
High-quality 3D correction of ring and radiant artifacts in flat panel detector-based cone beam volume CT imaging.
Anas, Emran Mohammad Abu; Kim, Jae Gon; Lee, Soo Yeol; Hasan, Md Kamrul
The use of an x-ray flat panel detector is increasingly becoming popular in 3D cone beam volume CT machines. Due to the deficient semiconductor array manufacturing process, the cone beam projection data are often corrupted by different types of abnormalities, which cause severe ring and radiant artifacts in a cone beam reconstruction image, and as a result, the diagnostic image quality is degraded. In this paper, a novel technique is presented for the correction of error in the 2D cone beam projections due to abnormalities often observed in 2D x-ray flat panel detectors. Template images are derived from the responses of the detector pixels using their statistical properties and then an effective non-causal derivative-based detection algorithm in 2D space is presented for the detection of defective and mis-calibrated detector elements separately. An image inpainting-based 3D correction scheme is proposed for the estimation of responses of defective detector elements, and the responses of the mis-calibrated detector elements are corrected using the normalization technique. For real-time implementation, a simplification of the proposed off-line method is also suggested. Finally, the proposed algorithms are tested using different real cone beam volume CT images and the experimental results demonstrate that the proposed methods can effectively remove ring and radiant artifacts from cone beam volume CT images compared to other reported techniques in the literature.
SU-E-T-296: Dosimetric Analysis of Small Animal Image-Guided Irradiator Using High Resolution Optical CT Imaging of 3D Dosimeters
Na, Y; Qian, X; Wuu, C; Adamovics, J
Purpose: To verify the dosimetric characteristics of a small animal image-guided irradiator using a high-resolution of optical CT imaging of 3D dosimeters. Methods: PRESAEGE 3D dosimeters were used to determine dosimetric characteristics of a small animal image-guided irradiator and compared with EBT2 films. Cylindrical PRESAGE dosimeters with 7cm height and 6cm diameter were placed along the central axis of the beam. The films were positioned between 6×6cm{sup 2} cubed plastic water phantoms perpendicular to the beam direction with multiple depths. PRESAGE dosimeters and EBT2 films were then irradiated with the irradiator beams at 220kVp and 13mA. Each of irradiated PRESAGE dosimeters named PA1, PA2, PB1, and PB2, was independently scanned using a high-resolution single laser beam optical CT scanner. The transverse images were reconstructed with a 0.1mm high-resolution pixel. A commercial Epson Expression 10000XL flatbed scanner was used for readout of irradiated EBT2 films at a 0.4mm pixel resolution. PDD curves and beam profiles were measured for the irradiated PRESAGE dosimeters and EBT2 films. Results: The PDD agreements between the irradiated PRESAGE dosimeter PA1, PA2, PB1, PB2 and the EB2 films were 1.7, 2.3, 1.9, and 1.9% for the multiple depths at 1, 5, 10, 15, 20, 30, 40 and 50mm, respectively. The FWHM measurements for each PRESAEGE dosimeter and film agreed with 0.5, 1.1, 0.4, and 1.7%, respectively, at 30mm depth. Both PDD and FWHM measurements for the PRESAGE dosimeters and the films agreed overall within 2%. The 20%–80% penumbral widths of each PRESAGE dosimeter and the film at a given depth were respectively found to be 0.97, 0.91, 0.79, 0.88, and 0.37mm. Conclusion: Dosimetric characteristics of a small animal image-guided irradiator have been demonstrated with the measurements of PRESAGE dosimeter and EB2 film. With the high resolution and accuracy obtained from this 3D dosimetry system, precise targeting small animal irradiation can be
Imaging the Aqueous Humor Outflow Pathway in Human Eyes by Three-dimensional Micro-computed Tomography (3D micro-CT)
C Hann; M Bentley; A Vercnocke; E Ritman; M Fautsch
The site of outflow resistance leading to elevated intraocular pressure in primary open-angle glaucoma is believed to be located in the region of Schlemm's canal inner wall endothelium, its basement membrane and the adjacent juxtacanalicular tissue. Evidence also suggests collector channels and intrascleral vessels may have a role in intraocular pressure in both normal and glaucoma eyes. Traditional imaging modalities limit the ability to view both proximal and distal portions of the trabecular outflow pathway as a single unit. In this study, we examined the effectiveness of three-dimensional micro-computed tomography (3D micro-CT) as a potential method to view the trabecular outflow pathway. Two normal human eyes were used: one immersion fixed in 4% paraformaldehyde and one with anterior chamber perfusion at 10 mmHg followed by perfusion fixation in 4% paraformaldehyde/2% glutaraldehyde. Both eyes were postfixed in 1% osmium tetroxide and scanned with 3D micro-CT at 2 {mu}m or 5 {mu}m voxel resolution. In the immersion fixed eye, 24 collector channels were identified with an average orifice size of 27.5 {+-} 5 {mu}m. In comparison, the perfusion fixed eye had 29 collector channels with a mean orifice size of 40.5 {+-} 13 {mu}m. Collector channels were not evenly dispersed around the circumference of the eye. There was no significant difference in the length of Schlemm's canal in the immersed versus the perfused eye (33.2 versus 35.1 mm). Structures, locations and size measurements identified by 3D micro-CT were confirmed by correlative light microscopy. These findings confirm 3D micro-CT can be used effectively for the non-invasive examination of the trabecular meshwork, Schlemm's canal, collector channels and intrascleral vasculature that comprise the distal outflow pathway. This imaging modality will be useful for non-invasive study of the role of the trabecular outflow pathway as a whole unit.
Skeletal dosimetry in the MAX06 and the FAX06 phantoms for external exposure to photons based on vertebral 3D-microCT images
NASA Astrophysics Data System (ADS)
Kramer, R.; Khoury, H. J.; Vieira, J. W.; Kawrakow, I.
3D-microCT images of vertebral bodies from three different individuals have been segmented into trabecular bone, bone marrow and bone surface cells (BSC), and then introduced into the spongiosa voxels of the MAX06 and the FAX06 phantoms, in order to calculate the equivalent dose to the red bone marrow (RBM) and the BSC in the marrow cavities of trabecular bone with the EGSnrc Monte Carlo code from whole-body exposure to external photon radiation. The MAX06 and the FAX06 phantoms consist of about 150 million 1.2 mm cubic voxels each, a part of which are spongiosa voxels surrounded by cortical bone. In order to use the segmented 3D-microCT images for skeletal dosimetry, spongiosa voxels in the MAX06 and the FAX06 phantom were replaced at runtime by so-called micro matrices representing segmented trabecular bone, marrow and BSC in 17.65, 30 and 60 µm cubic voxels. The 3D-microCT image-based RBM and BSC equivalent doses for external exposure to photons presented here for the first time for complete human skeletons are in agreement with the results calculated with the three correction factor method and the fluence-to-dose response functions for the same phantoms taking into account the conceptual differences between the different methods. Additionally the microCT image-based results have been compared with corresponding data from earlier studies for other human phantoms. This article is dedicated to Prof. Dr Guenter Drexler from the Laboratório de Ciências Radiológicas, State University of Rio de Janeiro, on the occasion of his 70th birthday.
An Optimized Spline-Based Registration of a 3D CT to a Set of C-Arm Images
Thévenaz, P.; Zheng, G.; Nolte, L. -P.; Unser, M.
We have developed an algorithm for the rigid-body registration of a CT volume to a set of C-arm images. The algorithm uses a gradient-based iterative minimization of a least-squares measure of dissimilarity between the C-arm images and projections of the CT volume. To compute projections, we use a novel method for fast integration of the volume along rays. To improve robustness and speed, we take advantage of a coarse-to-fine processing of the volume/image pyramids. To compute the projections of the volume, the gradient of the dissimilarity measure, and the multiresolution data pyramids, we use a continuous image/volume model based on cubic B-splines, which ensures a high interpolation accuracy and a gradient of the dissimilarity measure that is well defined everywhere. We show the performance of our algorithm on a human spine phantom, where the true alignment is determined using a set of fiducial markers. PMID:23165033
MTF characterization in 2D and 3D for a high resolution, large field of view flat panel imager for cone beam CT
NASA Astrophysics Data System (ADS)
Shah, Jainil; Mann, Steve D.; Tornai, Martin P.; Richmond, Michelle; Zentai, George
The 2D and 3D modulation transfer functions (MTFs) of a custom made, large 40x30cm2 area, 600- micron CsI-TFT based flat panel imager having 127-micron pixellation, along with the micro-fiber scintillator structure, were characterized in detail using various techniques. The larger area detector yields a reconstructed FOV of 25cm diameter with an 80cm SID in CT mode. The MTFs were determined with 1x1 (intrinsic) binning. The 2D MTFs were determined using a 50.8 micron tungsten wire and a solid lead edge, and the 3D MTF was measured using a custom made phantom consisting of three nearly orthogonal 50.8 micron tungsten wires suspended in an acrylic cubic frame. The 2D projection data was reconstructed using an iterative OSC algorithm using 16 subsets and 5 iterations. As additional verification of the resolution, along with scatter, the Catphan® phantom was also imaged and reconstructed with identical parameters. The measured 2D MTF was ~4% using the wire technique and ~1% using the edge technique at the 3.94 lp/mm Nyquist cut-off frequency. The average 3D MTF measured along the wires was ~8% at the Nyquist. At 50% MTF, the resolutions were 1.2 and 2.1 lp/mm in 2D and 3D, respectively. In the Catphan® phantom, the 1.7 lp/mm bars were easily observed. Lastly, the 3D MTF measured on the three wires has an observed 5.9% RMSD, indicating that the resolution of the imaging system is uniform and spatially independent. This high performance detector is integrated into a dedicated breast SPECT-CT imaging system.
Fully Automatic Localization and Segmentation of 3D Vertebral Bodies from CT/MR Images via a Learning-Based Method.
Chu, Chengwen; Belavý, Daniel L; Armbrecht, Gabriele; Bansmann, Martin; Felsenberg, Dieter; Zheng, Guoyan
In this paper, we address the problems of fully automatic localization and segmentation of 3D vertebral bodies from CT/MR images. We propose a learning-based, unified random forest regression and classification framework to tackle these two problems. More specifically, in the first stage, the localization of 3D vertebral bodies is solved with random forest regression where we aggregate the votes from a set of randomly sampled image patches to get a probability map of the center of a target vertebral body in a given image. The resultant probability map is then further regularized by Hidden Markov Model (HMM) to eliminate potential ambiguity caused by the neighboring vertebral bodies. The output from the first stage allows us to define a region of interest (ROI) for the segmentation step, where we use random forest classification to estimate the likelihood of a voxel in the ROI being foreground or background. The estimated likelihood is combined with the prior probability, which is learned from a set of training data, to get the posterior probability of the voxel. The segmentation of the target vertebral body is then done by a binary thresholding of the estimated probability. We evaluated the present approach on two openly available datasets: 1) 3D T2-weighted spine MR images from 23 patients and 2) 3D spine CT images from 10 patients. Taking manual segmentation as the ground truth (each MR image contains at least 7 vertebral bodies from T11 to L5 and each CT image contains 5 vertebral bodies from L1 to L5), we evaluated the present approach with leave-one-out experiments. Specifically, for the T2-weighted MR images, we achieved for localization a mean error of 1.6 mm, and for segmentation a mean Dice metric of 88.7% and a mean surface distance of 1.5 mm, respectively. For the CT images we achieved for localization a mean error of 1.9 mm, and for segmentation a mean Dice metric of 91.0% and a mean surface distance of 0.9 mm, respectively.
Fully Automatic Localization and Segmentation of 3D Vertebral Bodies from CT/MR Images via a Learning-Based Method
Chu, Chengwen; Belavý, Daniel L.; Armbrecht, Gabriele; Bansmann, Martin; Felsenberg, Dieter; Zheng, Guoyan
In this paper, we address the problems of fully automatic localization and segmentation of 3D vertebral bodies from CT/MR images. We propose a learning-based, unified random forest regression and classification framework to tackle these two problems. More specifically, in the first stage, the localization of 3D vertebral bodies is solved with random forest regression where we aggregate the votes from a set of randomly sampled image patches to get a probability map of the center of a target vertebral body in a given image. The resultant probability map is then further regularized by Hidden Markov Model (HMM) to eliminate potential ambiguity caused by the neighboring vertebral bodies. The output from the first stage allows us to define a region of interest (ROI) for the segmentation step, where we use random forest classification to estimate the likelihood of a voxel in the ROI being foreground or background. The estimated likelihood is combined with the prior probability, which is learned from a set of training data, to get the posterior probability of the voxel. The segmentation of the target vertebral body is then done by a binary thresholding of the estimated probability. We evaluated the present approach on two openly available datasets: 1) 3D T2-weighted spine MR images from 23 patients and 2) 3D spine CT images from 10 patients. Taking manual segmentation as the ground truth (each MR image contains at least 7 vertebral bodies from T11 to L5 and each CT image contains 5 vertebral bodies from L1 to L5), we evaluated the present approach with leave-one-out experiments. Specifically, for the T2-weighted MR images, we achieved for localization a mean error of 1.6 mm, and for segmentation a mean Dice metric of 88.7% and a mean surface distance of 1.5 mm, respectively. For the CT images we achieved for localization a mean error of 1.9 mm, and for segmentation a mean Dice metric of 91.0% and a mean surface distance of 0.9 mm, respectively. PMID:26599505
TU-F-12A-05: Sensitivity of Textural Features to 3D Vs. 4D FDG-PET/CT Imaging in NSCLC Patients
Yang, F; Nyflot, M; Bowen, S; Kinahan, P; Sandison, G
Purpose: Neighborhood Gray-level difference matrices (NGLDM) based texture parameters extracted from conventional (3D) 18F-FDG PET scans in patients with NSCLC have been previously shown to associate with response to chemoradiation and poorer patient outcome. However, the change in these parameters when utilizing respiratory-correlated (4D) FDG-PET scans has not yet been characterized for NSCLC. The Objectives: of this study was to assess the extent to which NGLDM-based texture parameters on 4D PET images vary with reference to values derived from 3D scans in NSCLC. Methods: Eight patients with newly diagnosed NSCLC treated with concomitant chemoradiotherapy were included in this study. 4D PET scans were reconstructed with OSEM-IR in 5 respiratory phase-binned images and corresponding CT data of each phase were employed for attenuation correction. NGLDM-based texture features, consisting of coarseness, contrast, busyness, complexity and strength, were evaluated for gross tumor volumes defined on 3D/4D PET scans by radiation oncologists. Variation of the obtained texture parameters over the respiratory cycle were examined with respect to values extracted from 3D scans. Results: Differences between texture parameters derived from 4D scans at different respiratory phases and those extracted from 3D scans ranged from −30% to 13% for coarseness, −12% to 40% for contrast, −5% to 50% for busyness, −7% to 38% for complexity, and −43% to 20% for strength. Furthermore, no evident correlations were observed between respiratory phase and 4D scan texture parameters. Conclusion: Results of the current study showed that NGLDM-based texture parameters varied considerably based on choice of 3D PET and 4D PET reconstruction of NSCLC patient images, indicating that standardized image acquisition and analysis protocols need to be established for clinical studies, especially multicenter clinical trials, intending to validate prognostic values of texture features for NSCLC.
3D dosimetry estimation for selective internal radiation therapy (SIRT) using SPECT/CT images: a phantom study
NASA Astrophysics Data System (ADS)
Debebe, Senait A.; Franquiz, Juan; McGoron, Anthony J.
Selective Internal Radiation Therapy (SIRT) is a common way to treat liver cancer that cannot be treated surgically. SIRT involves administration of Yttrium - 90 (90Y) microspheres via the hepatic artery after a diagnostic procedure using 99mTechnetium (Tc)-macroaggregated albumin (MAA) to detect extrahepatic shunting to the lung or the gastrointestinal tract. Accurate quantification of radionuclide administered to patients and radiation dose absorbed by different organs is of importance in SIRT. Accurate dosimetry for SIRT allows optimization of dose delivery to the target tumor and may allow for the ability to assess the efficacy of the treatment. In this study, we proposed a method that can efficiently estimate radiation absorbed dose from 90Y bremsstrahlung SPECT/CT images of liver and the surrounding organs. Bremsstrahlung radiation from 90Y was simulated using the Compton window of 99mTc (78keV at 57%). 99mTc images acquired at the photopeak energy window were used as a standard to examine the accuracy of dosimetry prediction by the simulated bremsstrahlung images. A Liqui-Phil abdominal phantom with liver, stomach and two tumor inserts was imaged using a Philips SPECT/CT scanner. The Dose Point Kernel convolution method was used to find the radiation absorbed dose at a voxel level for a three dimensional dose distribution. This method will allow for a complete estimate of the distribution of radiation absorbed dose by tumors, liver, stomach and other surrounding organs at the voxel level. The method provides a quantitative predictive method for SIRT treatment outcome and administered dose response for patients who undergo the treatment.
Comparative evaluation of a novel 3D segmentation algorithm on in-treatment radiotherapy cone beam CT images
NASA Astrophysics Data System (ADS)
Price, Gareth; Moore, Chris
Image segmentation and delineation is at the heart of modern radiotherapy, where the aim is to deliver as high a radiation dose as possible to a cancerous target whilst sparing the surrounding healthy tissues. This, of course, requires that a radiation oncologist dictates both where the tumour and any nearby critical organs are located. As well as in treatment planning, delineation is of vital importance in image guided radiotherapy (IGRT): organ motion studies demand that features across image databases are accurately segmented, whilst if on-line adaptive IGRT is to become a reality, speedy and correct target identification is a necessity. Recently, much work has been put into the development of automatic and semi-automatic segmentation tools, often using prior knowledge to constrain some grey level, or derivative thereof, interrogation algorithm. It is hoped that such techniques can be applied to organ at risk and tumour segmentation in radiotherapy. In this work, however, we make the assumption that grey levels do not necessarily determine a tumour's extent, especially in CT where the attenuation coefficient can often vary little between cancerous and normal tissue. In this context we present an algorithm that generates a discontinuity free delineation surface driven by user placed, evidence based support points. In regions of sparse user supplied information, prior knowledge, in the form of a statistical shape model, provides guidance. A small case study is used to illustrate the method. Multiple observers (between 3 and 7) used both the presented tool and a commercial manual contouring package to delineate the bladder on a serially imaged (10 cone beam CT volumes ) prostate patient. A previously presented shape analysis technique is used to quantitatively compare the observer variability.
Computer-aided diagnosis: a 3D segmentation method for lung nodules in CT images by use of a spiral-scanning technique
NASA Astrophysics Data System (ADS)
Wang, Jiahui; Engelmann, Roger; Li, Qiang
Lung nodule segmentation in computed tomography (CT) plays an important role in computer-aided detection, diagnosis, and quantification systems for lung cancer. In this study, we developed a simple but accurate nodule segmentation method in three-dimensional (3D) CT. First, a volume of interest (VOI) was determined at the location of a nodule. We then transformed the VOI into a two-dimensional (2D) image by use of a "spiral-scanning" technique, in which a radial line originating from the center of the VOI spirally scanned the VOI. The voxels scanned by the radial line were arranged sequentially to form a transformed 2D image. Because the surface of a nodule in 3D image became a curve in the transformed 2D image, the spiral-scanning technique considerably simplified our segmentation method and enabled us to obtain accurate segmentation results. We employed a dynamic programming technique to delineate the "optimal" outline of a nodule in the 2D image, which was transformed back into the 3D image space to provide the interior of the nodule. The proposed segmentation method was trained on the first and was tested on the second Lung Image Database Consortium (LIDC) datasets. An overlap between nodule regions provided by computer and by the radiologists was employed as a performance metric. The experimental results on the LIDC database demonstrated that our segmentation method provided relatively robust and accurate segmentation results with mean overlap values of 66% and 64% for the nodules in the first and second LIDC datasets, respectively, and would be useful for the quantification, detection, and diagnosis of lung cancer.
A fast experimental beam hardening correction method for accurate bone mineral measurements in 3D μCT imaging system.
Koubar, Khodor; Bekaert, Virgile; Brasse, David; Laquerriere, Patrice
Bone mineral density plays an important role in the determination of bone strength and fracture risks. Consequently, it is very important to obtain accurate bone mineral density measurements. The microcomputerized tomography system provides 3D information about the architectural properties of bone. Quantitative analysis accuracy is decreased by the presence of artefacts in the reconstructed images, mainly due to beam hardening artefacts (such as cupping artefacts). In this paper, we introduced a new beam hardening correction method based on a postreconstruction technique performed with the use of off-line water and bone linearization curves experimentally calculated aiming to take into account the nonhomogeneity in the scanned animal. In order to evaluate the mass correction rate, calibration line has been carried out to convert the reconstructed linear attenuation coefficient into bone masses. The presented correction method was then applied on a multimaterial cylindrical phantom and on mouse skeleton images. Mass correction rate up to 18% between uncorrected and corrected images were obtained as well as a remarkable improvement of a calculated mouse femur mass has been noticed. Results were also compared to those obtained when using the simple water linearization technique which does not take into account the nonhomogeneity in the object.
Method and phantom to study combined effects of in-plane (x,y) and z-axis resolution for 3D CT imaging.
Goodenough, David; Levy, Josh; Kristinsson, Smari; Fredriksson, Jesper; Olafsdottir, Hildur; Healy, Austin
Increasingly, the advent of multislice CT scanners, volume CT scanners, and total body spiral acquisition modes has led to the use of Multi Planar Reconstruction and 3D datasets. In considering 3D resolution properties of a CT system it is important to note that both the in-plane (x,y) and z-axis (slice thickness) influence the visualization and detection of objects within the scanned volume. This study investigates ways to consider both the in-plane resolution and the z-axis resolution in a single phantom wherein analytic or visualized analysis can yield information on these combined effects. A new phantom called the "Wave Phantom" is developed that can be used to sample the 3D resolution properties of a CT image, including in-plane (x,y) and z-axis information. The key development in this Wave Phantom is the incorporation of a z-axis aspect of a more traditional step (bar) resolution gauge phantom. The phantom can be examined visually wherein a cutoff level may be seen; and/or the analytic analysis of the various characteristics of the waveform profile by including amplitude, frequency, and slope (rate of climb) of the peaks, can be extracted from the Wave Pattern using mathematical analysis such as the Fourier transform. The combined effect of changes in in-plane resolution and z-axis (thickness), are shown, as well as the effect of changes in either in-plane resolution, or z-axis thickness. Examples of visual images of the Wave pattern as well as the analytic characteristics of the various harmonics of a periodic Wave pattern resulting from changes in resolution filter and/or slice thickness, and position in the field of view are shown. The Wave Phantom offers a promising way to investigate 3D resolution results from combined effect of in-plane (x-y) and z-axis resolution as contrasted to the use of simple 2D resolution gauges that need to be used with separate measures of z-axis dependency, such as angled ramps. It offers both a visual pattern as well as a
Method and phantom to study combined effects of in-plane (x,y) and z-axis resolution for 3D CT imaging.
Goodenough, David; Levy, Josh; Kristinsson, Smari; Fredriksson, Jesper; Olafsdottir, Hildur; Healy, Austin
Increasingly, the advent of multislice CT scanners, volume CT scanners, and total body spiral acquisition modes has led to the use of Multi Planar Reconstruction and 3D datasets. In considering 3D resolution properties of a CT system it is important to note that both the in-plane (x,y) and z-axis (slice thickness) influence the visual-ization and detection of objects within the scanned volume. This study investigates ways to consider both the in-plane resolution and the z-axis resolution in a single phantom wherein analytic or visualized analysis can yield information on these combined effects. A new phantom called the "Wave Phantom" is developed that can be used to sample the 3D resolution properties of a CT image, including in-plane (x,y) and z-axis information. The key development in this Wave Phantom is the incorporation of a z-axis aspect of a more traditional step (bar) resolution gauge phantom. The phantom can be examined visually wherein a cutoff level may be seen; and/or the analytic analysis of the various characteristics of the waveform profile by including amplitude, frequency, and slope (rate of climb) of the peaks, can be extracted from the Wave Pattern using mathematical analysis such as the Fourier transform. The combined effect of changes in in-plane resolution and z-axis (thickness), are shown, as well as the effect of changes in either in-plane resolu-tion, or z-axis thickness. Examples of visual images of the Wave pattern as well as the analytic characteristics of the various harmonics of a periodic Wave pattern resulting from changes in resolution filter and/or slice thickness, and position in the field of view are shown. The Wave Phantom offers a promising way to investigate 3D resolution results from combined effect of in-plane (x-y) and z-axis resolution as contrasted to the use of simple 2D resolution gauges that need to be used with separate measures of z-axis dependency, such as angled ramps. It offers both a visual pattern as well as a
Rigid model-based 3D segmentation of the bones of joints in MR and CT images for motion analysis.
Liu, Jiamin; Udupa, Jayaram K; Saha, Punam K; Odhner, Dewey; Hirsch, Bruce E; Siegler, Sorin; Simon, Scott; Winkelstein, Beth A
There are several medical application areas that require the segmentation and separation of the component bones of joints in a sequence of images of the joint acquired under various loading conditions, our own target area being joint motion analysis. This is a challenging problem due to the proximity of bones at the joint, partial volume effects, and other imaging modality-specific factors that confound boundary contrast. In this article, a two-step model-based segmentation strategy is proposed that utilizes the unique context of the current application wherein the shape of each individual bone is preserved in all scans of a particular joint while the spatial arrangement of the bones alters significantly among bones and scans. In the first step, a rigid deterministic model of the bone is generated from a segmentation of the bone in the image corresponding to one position of the joint by using the live wire method. Subsequently, in other images of the same joint, this model is used to search for the same bone by minimizing an energy function that utilizes both boundary- and region-based information. An evaluation of the method by utilizing a total of 60 data sets on MR and CT images of the ankle complex and cervical spine indicates that the segmentations agree very closely with the live wire segmentations, yielding true positive and false positive volume fractions in the range 89%-97% and 0.2%-0.7%. The method requires 1-2 minutes of operator time and 6-7 min of computer time per data set, which makes it significantly more efficient than live wire-the method currently available for the task that can be used routinely.
Issues involved in the quantitative 3D imaging of proton doses using optical CT and chemical dosimeters
NASA Astrophysics Data System (ADS)
Doran, Simon; Gorjiara, Tina; Kacperek, Andrzej; Adamovics, John; Kuncic, Zdenka; Baldock, Clive
Dosimetry of proton beams using 3D imaging of chemical dosimeters is complicated by a variation with proton linear energy transfer (LET) of the dose-response (the so-called 'quenching effect'). Simple theoretical arguments lead to the conclusion that the total absorbed dose from multiple irradiations with different LETs cannot be uniquely determined from post-irradiation imaging measurements on the dosimeter. Thus, a direct inversion of the imaging data is not possible and the proposition is made to use a forward model based on appropriate output from a planning system to predict the 3D response of the dosimeter. In addition to the quenching effect, it is well known that chemical dosimeters have a non-linear response at high doses. To the best of our knowledge it has not yet been determined how this phenomenon is affected by LET. The implications for dosimetry of a number of potential scenarios are examined. Dosimeter response as a function of depth (and hence LET) was measured for four samples of the radiochromic plastic PRESAGE®, using an optical computed tomography readout and entrance doses of 2.0 Gy, 4.0 Gy, 7.8 Gy and 14.7 Gy, respectively. The dosimeter response was separated into two components, a single-exponential low-LET response and a LET-dependent quenching. For the particular formulation of PRESAGE® used, deviations from linearity of the dosimeter response became significant for doses above approximately 16 Gy. In a second experiment, three samples were each irradiated with two separate beams of 4 Gy in various different configurations. On the basis of the previous characterizations, two different models were tested for the calculation of the combined quenching effect from two contributions with different LETs. It was concluded that a linear superposition model with separate calculation of the quenching for each irradiation did not match the measured result where two beams overlapped. A second model, which used the concept of an �
NASA Astrophysics Data System (ADS)
Lee-Elkin, Forest
Three dimensional (3D) autofocus remains a significant challenge for the development of practical 3D multipass radar imaging. The current 2D radar autofocus methods are not readily extendable across sensor passes. We propose a general framework that allows a class of data adaptive solutions for 3D auto-focus across passes with minimal constraints on the scene contents. The key enabling assumption is that portions of the scene are sparse in elevation which reduces the number of free variables and results in a system that is simultaneously solved for scatterer heights and autofocus parameters. The proposed method extends 2-pass interferometric synthetic aperture radar (IFSAR) methods to an arbitrary number of passes allowing the consideration of scattering from multiple height locations. A specific case from the proposed autofocus framework is solved and demonstrates autofocus and coherent multipass 3D estimation across the 8 passes of the "Gotcha Volumetric SAR Data Set" X-Band radar data.
Glasses-free 3D viewing systems for medical imaging
NASA Astrophysics Data System (ADS)
Magalhães, Daniel S. F.; Serra, Rolando L.; Vannucci, André L.; Moreno, Alfredo B.; Li, Li M.
In this work we show two different glasses-free 3D viewing systems for medical imaging: a stereoscopic system that employs a vertically dispersive holographic screen (VDHS) and a multi-autostereoscopic system, both used to produce 3D MRI/CT images. We describe how to obtain a VDHS in holographic plates optimized for this application, with field of view of 7 cm to each eye and focal length of 25 cm, showing images done with the system. We also describe a multi-autostereoscopic system, presenting how it can generate 3D medical imaging from viewpoints of a MRI or CT image, showing results of a 3D angioresonance image.
Effective incorporation of spatial information in a mutual information based 3D-2D registration of a CT volume to X-ray images.
Zheng, Guoyan
This paper addresses the problem of estimating the 3D rigid pose of a CT volume of an object from its 2D X-ray projections. We use maximization of mutual information, an accurate similarity measure for multi-modal and mono-modal image registration tasks. However, it is known that the standard mutual information measure only takes intensity values into account without considering spatial information and its robustness is questionable. In this paper, instead of directly maximizing mutual information, we propose to use a variational approximation derived from the Kullback-Leibler bound. Spatial information is then incorporated into this variational approximation using a Markov random field model. The newly derived similarity measure has a least-squares form and can be effectively minimized by a multi-resolution Levenberg-Marquardt optimizer. Experimental results are presented on X-ray and CT datasets of a plastic phantom and a cadaveric spine segment.
Development of a Hausdorff distance based 3D quantification technique to evaluate the CT imaging system impact on depiction of lesion morphology
NASA Astrophysics Data System (ADS)
Sahbaee, Pooyan; Robins, Marthony; Solomon, Justin; Samei, Ehsan
The purpose of this study was to develop a 3D quantification technique to assess the impact of imaging system on depiction of lesion morphology. Regional Hausdorff Distance (RHD) was computed from two 3D volumes: virtual mesh models of synthetic nodules or "virtual nodules" and CT images of physical nodules or "physical nodules". The method can be described in following steps. First, the synthetic nodule was inserted into anthropomorphic Kyoto thorax phantom and scanned in a Siemens scanner (Flash). Then, nodule was segmented from the image. Second, in order to match the orientation of the nodule, the digital models of the "virtual" and "physical" nodules were both geometrically translated to the origin. Then, the "physical" was gradually rotated at incremental 10 degrees. Third, the Hausdorff Distance was calculated from each pair of "virtual" and "physical" nodules. The minimum HD value represented the most matching pair. Finally, the 3D RHD map and the distribution of RHD were computed for the matched pair. The technique was scalarized using the FWHM of the RHD distribution. The analysis was conducted for various shapes (spherical, lobular, elliptical, and speculated) of nodules. The calculated FWHM values of RHD distribution for the 8-mm spherical, lobular, elliptical, and speculated "virtual" and "physical" nodules were 0.23, 0.42, 0.33, and 0.49, respectively.
Design, fabrication, and implementation of voxel-based 3D printed textured phantoms for task-based image quality assessment in CT
NASA Astrophysics Data System (ADS)
Solomon, Justin; Ba, Alexandre; Diao, Andrew; Lo, Joseph; Bier, Elianna; Bochud, François; Gehm, Michael; Samei, Ehsan
In x-ray computed tomography (CT), task-based image quality studies are typically performed using uniform background phantoms with low-contrast signals. Such studies may have limited clinical relevancy for modern non-linear CT systems due to possible influence of background texture on image quality. The purpose of this study was to design and implement anatomically informed textured phantoms for task-based assessment of low-contrast detection. Liver volumes were segmented from 23 abdominal CT cases. The volumes were characterized in terms of texture features from gray-level co-occurrence and run-length matrices. Using a 3D clustered lumpy background (CLB) model, a fitting technique based on a genetic optimization algorithm was used to find the CLB parameters that were most reflective of the liver textures, accounting for CT system factors of spatial blurring and noise. With the modeled background texture as a guide, a cylinder phantom (165 mm in diameter and 30 mm height) was designed, containing 20 low-contrast spherical signals (6 mm in diameter at targeted contrast levels of ~3.2, 5.2, 7.2, 10, and 14 HU, 4 repeats per signal). The phantom was voxelized and input into a commercial multi-material 3D printer (Object Connex 350), with custom software for voxel-based printing. Using principles of digital half-toning and dithering, the 3D printer was programmed to distribute two base materials (VeroWhite and TangoPlus, nominal voxel size of 42x84x30 microns) to achieve the targeted spatial distribution of x-ray attenuation properties. The phantom was used for task-based image quality assessment of a clinically available iterative reconstruction algorithm (Sinogram Affirmed Iterative Reconstruction, SAFIRE) using a channelized Hotelling observer paradigm. Images of the textured phantom and a corresponding uniform phantom were acquired at six dose levels and observer model performance was estimated for each condition (5 contrasts x 6 doses x 2 reconstructions x 2
Diffusible iodine-based contrast-enhanced computed tomography (diceCT): an emerging tool for rapid, high-resolution, 3-D imaging of metazoan soft tissues.
Gignac, Paul M; Kley, Nathan J; Clarke, Julia A; Colbert, Matthew W; Morhardt, Ashley C; Cerio, Donald; Cost, Ian N; Cox, Philip G; Daza, Juan D; Early, Catherine M; Echols, M Scott; Henkelman, R Mark; Herdina, A Nele; Holliday, Casey M; Li, Zhiheng; Mahlow, Kristin; Merchant, Samer; Müller, Johannes; Orsbon, Courtney P; Paluh, Daniel J; Thies, Monte L; Tsai, Henry P; Witmer, Lawrence M
Morphologists have historically had to rely on destructive procedures to visualize the three-dimensional (3-D) anatomy of animals. More recently, however, non-destructive techniques have come to the forefront. These include X-ray computed tomography (CT), which has been used most commonly to examine the mineralized, hard-tissue anatomy of living and fossil metazoans. One relatively new and potentially transformative aspect of current CT-based research is the use of chemical agents to render visible, and differentiate between, soft-tissue structures in X-ray images. Specifically, iodine has emerged as one of the most widely used of these contrast agents among animal morphologists due to its ease of handling, cost effectiveness, and differential affinities for major types of soft tissues. The rapid adoption of iodine-based contrast agents has resulted in a proliferation of distinct specimen preparations and scanning parameter choices, as well as an increasing variety of imaging hardware and software preferences. Here we provide a critical review of the recent contributions to iodine-based, contrast-enhanced CT research to enable researchers just beginning to employ contrast enhancement to make sense of this complex new landscape of methodologies. We provide a detailed summary of recent case studies, assess factors that govern success at each step of the specimen storage, preparation, and imaging processes, and make recommendations for standardizing both techniques and reporting practices. Finally, we discuss potential cutting-edge applications of diffusible iodine-based contrast-enhanced computed tomography (diceCT) and the issues that must still be overcome to facilitate the broader adoption of diceCT going forward.
Comparison of the effect of simple and complex acquisition trajectories on the 2D SPR and 3D voxelized differences for dedicated breast CT imaging
NASA Astrophysics Data System (ADS)
Shah, Jainil P.; Mann, Steve D.; McKinley, Randolph L.; Tornai, Martin P.
The 2D scatter-to-primary (SPR) ratios and 3D voxelized difference volumes were characterized for a cone beam breast CT scanner capable of arbitrary (non-traditional) 3D trajectories. The CT system uses a 30x30cm2 flat panel imager with 197 micron pixellation and a rotating tungsten anode x-ray source with 0.3mm focal spot, with an SID of 70cm. Data were acquired for two cylindrical phantoms (12.5cm and 15cm diameter) filled with three different combinations of water and methanol yielding a range of uniform densities. Projections were acquired with two acquisition trajectories: 1) simple-circular azimuthal orbit with fixed tilt; and 2) saddle orbit following a +/-15° sinusoidal trajectory around the object. Projection data were acquired in 2x2 binned mode. Projections were scatter corrected using a beam stop array method, and the 2D SPR was measured on the projections. The scatter corrected and uncorrected data were then reconstructed individually using an iterative ordered subsets convex algorithm, and the 3D difference volumes were calculated as the absolute difference between the two. Results indicate that the 2D SPR is ~7-15% higher on projections with greatest tilt for the saddle orbit, due to the longer x-ray path length through the volume, compared to the 0° tilt projections. Additionally, the 2D SPR increases with object diameter as well as density. The 3D voxelized difference volumes are an estimate of the scatter contribution to the reconstructed attenuation coefficients on a voxel level. They help visualize minor deficiencies and artifacts in the volumes due to correction methods.
WE-G-18A-04: 3D Dictionary Learning Based Statistical Iterative Reconstruction for Low-Dose Cone Beam CT Imaging
Bai, T; Yan, H; Shi, F; Jia, X; Jiang, Steve B.; Lou, Y; Xu, Q; Mou, X
Purpose: To develop a 3D dictionary learning based statistical reconstruction algorithm on graphic processing units (GPU), to improve the quality of low-dose cone beam CT (CBCT) imaging with high efficiency. Methods: A 3D dictionary containing 256 small volumes (atoms) of 3x3x3 voxels was trained from a high quality volume image. During reconstruction, we utilized a Cholesky decomposition based orthogonal matching pursuit algorithm to find a sparse representation on this dictionary basis of each patch in the reconstructed image, in order to regularize the image quality. To accelerate the time-consuming sparse coding in the 3D case, we implemented our algorithm in a parallel fashion by taking advantage of the tremendous computational power of GPU. Evaluations are performed based on a head-neck patient case. FDK reconstruction with full dataset of 364 projections is used as the reference. We compared the proposed 3D dictionary learning based method with a tight frame (TF) based one using a subset data of 121 projections. The image qualities under different resolutions in z-direction, with or without statistical weighting are also studied. Results: Compared to the TF-based CBCT reconstruction, our experiments indicated that 3D dictionary learning based CBCT reconstruction is able to recover finer structures, to remove more streaking artifacts, and is less susceptible to blocky artifacts. It is also observed that statistical reconstruction approach is sensitive to inconsistency between the forward and backward projection operations in parallel computing. Using high a spatial resolution along z direction helps improving the algorithm robustness. Conclusion: 3D dictionary learning based CBCT reconstruction algorithm is able to sense the structural information while suppressing noise, and hence to achieve high quality reconstruction. The GPU realization of the whole algorithm offers a significant efficiency enhancement, making this algorithm more feasible for potential
3D mapping of water in oolithic limestone at atmospheric and vacuum saturation using X-ray micro-CT differential imaging
Boone, M.A.; De Kock, T.; Bultreys, T.; De Schutter, G.; Vontobel, P.; Van Hoorebeke, L.; Cnudde, V.
Determining the distribution of fluids in porous sedimentary rocks is of great importance in many geological fields. However, this is not straightforward, especially in the case of complex sedimentary rocks like limestone, where a multidisciplinary approach is often needed to capture its broad, multimodal pore size distribution and complex pore geometries. This paper focuses on the porosity and fluid distribution in two varieties of Massangis limestone, a widely used natural building stone from the southeast part of the Paris basin (France). The Massangis limestone shows locally varying post-depositional alterations, resulting in different types of pore networks and very different water distributions within the limestone. Traditional techniques for characterizing the porosity and pore size distribution are compared with state-of-the-art neutron radiography and X-ray computed microtomography to visualize the distribution of water inside the limestone at different imbibition conditions. X-ray computed microtomography images have the great advantage to non-destructively visualize and analyze the pore space inside of a rock, but are often limited to the larger macropores in the rock due to resolution limitations. In this paper, differential imaging is successfully applied to the X-ray computed microtomography images to obtain sub-resolution information about fluid occupancy and to map the fluid distribution in three dimensions inside the scanned limestone samples. The detailed study of the pore space with differential imaging allows understanding the difference in the water uptake behavior of the limestone, a primary factor that affects the weathering of the rock. - Highlights: • The water distribution in a limestone was visualized in 3D with micro-CT. • Differential imaging allowed to map both macro and microporous zones in the rock. • The 3D study of the pore space clarified the difference in water uptake behavior. • Trapped air is visualized in the moldic
ACM-based automatic liver segmentation from 3-D CT images by combining multiple atlases and improved mean-shift techniques.
Ji, Hongwei; He, Jiangping; Yang, Xin; Deklerck, Rudi; Cornelis, Jan
In this paper, we present an autocontext model(ACM)-based automatic liver segmentation algorithm, which combines ACM, multiatlases, and mean-shift techniques to segment liver from 3-D CT images. Our algorithm is a learning-based method and can be divided into two stages. At the first stage, i.e., the training stage, ACM is performed to learn a sequence of classifiers in each atlas space (based on each atlas and other aligned atlases). With the use of multiple atlases, multiple sequences of ACM-based classifiers are obtained. At the second stage, i.e., the segmentation stage, the test image will be segmented in each atlas space by applying each sequence of ACM-based classifiers. The final segmentation result will be obtained by fusing segmentation results from all atlas spaces via a multiclassifier fusion technique. Specially, in order to speed up segmentation, given a test image, we first use an improved mean-shift algorithm to perform over-segmentation and then implement the region-based image labeling instead of the original inefficient pixel-based image labeling. The proposed method is evaluated on the datasets of MICCAI 2007 liver segmentation challenge. The experimental results show that the average volume overlap error and the average surface distance achieved by our method are 8.3% and 1.5 m, respectively, which are comparable to the results reported in the existing state-of-the-art work on liver segmentation.
3D inpatient dose reconstruction from the PET-CT imaging of {sup 90}Y microspheres for metastatic cancer to the liver: Feasibility study
Fourkal, E.; Veltchev, I.; Lin, M.; Meyer, J.; Koren, S.; Doss, M.; Yu, J. Q.
Purpose: The introduction of radioembolization with microspheres represents a significant step forward in the treatment of patients with metastatic disease to the liver. This technique uses semiempirical formulae based on body surface area or liver and target volumes to calculate the required total activity for a given patient. However, this treatment modality lacks extremely important information, which is the three-dimensional (3D) dose delivered by microspheres to different organs after their administration. The absence of this information dramatically limits the clinical efficacy of this modality, specifically the predictive power of the treatment. Therefore, the aim of this study is to develop a 3D dose calculation technique that is based on the PET imaging of the infused microspheres.Methods: The Fluka Monte Carlo code was used to calculate the voxel dose kernel for {sup 90}Y source with voxel size equal to that of the PET scan. The measured PET activity distribution was converted to total activity distribution for the subsequent convolution with the voxel dose kernel to obtain the 3D dose distribution. In addition, dose-volume histograms were generated to analyze the dose to the tumor and critical structures.Results: The 3D inpatient dose distribution can be reconstructed from the PET data of a patient scanned after the infusion of microspheres. A total of seven patients have been analyzed so far using the proposed reconstruction method. Four patients underwent treatment with SIR-Spheres for liver metastases from colorectal cancer and three patients were treated with Therasphere for hepatocellular cancer. A total of 14 target tumors were contoured on post-treatment PET-CT scans for dosimetric evaluation. Mean prescription activity was 1.7 GBq (range: 0.58–3.8 GBq). The resulting mean maximum measured dose to targets was 167 Gy (range: 71–311 Gy). Mean minimum dose to 70% of target (D70) was 68 Gy (range: 25–155 Gy). Mean minimum dose to 90% of target
A Semi-Automatic Method to Extract Canal Pathways in 3D Micro-CT Images of Octocorals
Morales Pinzón, Alfredo; Orkisz, Maciej; Rodríguez Useche, Catalina María; Torres González, Juan Sebastián; Teillaud, Stanislas; Sánchez, Juan Armando; Hernández Hoyos, Marcela
The long-term goal of our study is to understand the internal organization of the octocoral stem canals, as well as their physiological and functional role in the growth of the colonies, and finally to assess the influence of climatic changes on this species. Here we focus on imaging tools, namely acquisition and processing of three-dimensional high-resolution images, with emphasis on automated extraction of canal pathways. Our aim was to evaluate the feasibility of the whole process, to point out and solve – if possible – technical problems related to the specimen conditioning, to determine the best acquisition parameters and to develop necessary image-processing algorithms. The pathways extracted are expected to facilitate the structural analysis of the colonies, namely to help observing the distribution, formation and number of canals along the colony. Five volumetric images of Muricea muricata specimens were successfully acquired by X-ray computed tomography with spatial resolution ranging from 4.5 to 25 micrometers. The success mainly depended on specimen immobilization. More than of the canals were successfully detected and tracked by the image-processing method developed. Thus obtained three-dimensional representation of the canal network was generated for the first time without the need of histological or other destructive methods. Several canal patterns were observed. Although most of them were simple, i.e. only followed the main branch or "turned" into a secondary branch, many others bifurcated or fused. A majority of bifurcations were observed at branching points. However, some canals appeared and/or ended anywhere along a branch. At the tip of a branch, all canals fused into a unique chamber. Three-dimensional high-resolution tomographic imaging gives a non-destructive insight to the coral ultrastructure and helps understanding the organization of the canal network. Advanced image-processing techniques greatly reduce human observer's effort and
Comprehensive Non-Destructive Conservation Documentation of Lunar Samples Using High-Resolution Image-Based 3D Reconstructions and X-Ray CT Data
NASA Technical Reports Server (NTRS)
Blumenfeld, E. H.; Evans, C. A.; Oshel, E. R.; Liddle, D. A.; Beaulieu, K.; Zeigler, R. A.; Hanna, R. D.; Ketcham, R. A.
Established contemporary conservation methods within the fields of Natural and Cultural Heritage encourage an interdisciplinary approach to preservation of heritage material (both tangible and intangible) that holds "Outstanding Universal Value" for our global community. NASA's lunar samples were acquired from the moon for the primary purpose of intensive scientific investigation. These samples, however, also invoke cultural significance, as evidenced by the millions of people per year that visit lunar displays in museums and heritage centers around the world. Being both scientifically and culturally significant, the lunar samples require a unique conservation approach. Government mandate dictates that NASA's Astromaterials Acquisition and Curation Office develop and maintain protocols for "documentation, preservation, preparation and distribution of samples for research, education and public outreach" for both current and future collections of astromaterials. Documentation, considered the first stage within the conservation methodology, has evolved many new techniques since curation protocols for the lunar samples were first implemented, and the development of new documentation strategies for current and future astromaterials is beneficial to keeping curation protocols up to date. We have developed and tested a comprehensive non-destructive documentation technique using high-resolution image-based 3D reconstruction and X-ray CT (XCT) data in order to create interactive 3D models of lunar samples that would ultimately be served to both researchers and the public. These data enhance preliminary scientific investigations including targeted sample requests, and also provide a new visual platform for the public to experience and interact with the lunar samples. We intend to serve these data as they are acquired on NASA's Astromaterials Acquisistion and Curation website at http://curator.jsc.nasa.gov/. Providing 3D interior and exterior documentation of astromaterial
True 3d Images and Their Applications
NASA Astrophysics Data System (ADS)
Wang, Z.; wang@hzgeospace., zheng.
A true 3D image is a geo-referenced image. Besides having its radiometric information, it also has true 3Dground coordinates XYZ for every pixels of it. For a true 3D image, especially a true 3D oblique image, it has true 3D coordinates not only for building roofs and/or open grounds, but also for all other visible objects on the ground, such as visible building walls/windows and even trees. The true 3D image breaks the 2D barrier of the traditional orthophotos by introducing the third dimension (elevation) into the image. From a true 3D image, for example, people will not only be able to read a building's location (XY), but also its height (Z). true 3D images will fundamentally change, if not revolutionize, the way people display, look, extract, use, and represent the geospatial information from imagery. In many areas, true 3D images can make profound impacts on the ways of how geospatial information is represented, how true 3D ground modeling is performed, and how the real world scenes are presented. This paper first gives a definition and description of a true 3D image and followed by a brief review of what key advancements of geospatial technologies have made the creation of true 3D images possible. Next, the paper introduces what a true 3D image is made of. Then, the paper discusses some possible contributions and impacts the true 3D images can make to geospatial information fields. At the end, the paper presents a list of the benefits of having and using true 3D images and the applications of true 3D images in a couple of 3D city modeling projects.
WE-AB-204-03: A Novel 3D Printed Phantom for 4D PET/CT Imaging and SIB Radiotherapy Verification
Soultan, D; Murphy, J; Moiseenko, V; Cervino, L; Gill, B
Purpose: To construct and test a 3D printed phantom designed to mimic variable PET tracer uptake seen in lung tumor volumes. To assess segmentation accuracy of sub-volumes of the phantom following 4D PET/CT scanning with ideal and patient-specific respiratory motion. To plan, deliver and verify delivery of PET-driven, gated, simultaneous integrated boost (SIB) radiotherapy plans. Methods: A set of phantoms and inserts were designed and manufactured for a realistic representation of lung cancer gated radiotherapy steps from 4D PET/CT scanning to dose delivery. A cylindrical phantom (40x 120 mm) holds inserts for PET/CT scanning. The novel 3D printed insert dedicated to 4D PET/CT mimics high PET tracer uptake in the core and lower uptake in the periphery. This insert is a variable density porous cylinder (22.12×70 mm), ABS-P430 thermoplastic, 3D printed by uPrint SE Plus with inner void volume (5.5×42 mm). The square pores (1.8×1.8 mm2 each) fill 50% of outer volume, resulting in a 2:1 SUV ratio of PET-tracer in the void volume with respect to porous volume. A matching in size cylindrical phantom is dedicated to validate gated radiotherapy. It contains eight peripheral holes matching the location of the porous part of the 3D printed insert, and one central hole. These holes accommodate adaptors for Farmer-type ion chamber and cells vials. Results: End-to-end test were performed from 4D PET/CT scanning to transferring data to the planning system and target volume delineation. 4D PET/CT scans were acquired of the phantom with different respiratory motion patterns and gating windows. A measured 2:1 18F-FDG SUV ratio between inner void and outer volume matched the 3D printed design. Conclusion: The novel 3D printed phantom mimics variable PET tracer uptake typical of tumors. Obtained 4D PET/CT scans are suitable for segmentation, treatment planning and delivery in SIB gated treatments of NSCLC.
Effective incorporating spatial information in a mutual information based 3D-2D registration of a CT volume to X-ray images.
Zheng, Guoyan
This paper addresses the problem of estimating the 3D rigid poses of a CT volume of an object from its 2D X-ray projection(s). We use maximization of mutual information, an accurate similarity measure for multi-modal and mono-modal image registration tasks. However, it is known that the standard mutual information measures only take intensity values into account without considering spatial information and their robustness is questionable. In this paper, instead of directly maximizing mutual information, we propose to use a variational approximation derived from the Kullback-Leibler bound. Spatial information is then incorporated into this variational approximation using a Markov random field model. The newly derived similarity measure has a least-squares form and can be effectively minimized by a multi-resolution Levenberg-Marquardt optimizer. Experiments were conducted on datasets from two applications: (a) intra-operative patient pose estimation from a limited number (e.g. 2) of calibrated fluoroscopic images, and (b) post-operative cup orientation estimation from a single standard X-ray radiograph with/without gonadal shielding. The experiment on intra-operative patient pose estimation showed a mean target registration accuracy of 0.8mm and a capture range of 11.5mm, while the experiment on estimating the post-operative cup orientation from a single X-ray radiograph showed a mean accuracy below 2 degrees for both anteversion and inclination. More importantly, results from both experiments demonstrated that the newly derived similarity measures were robust to occlusions in the X-ray image(s).
A new 3-D diagnosis strategy for duodenal malignant lesions using multidetector row CT, CT virtual duodenoscopy, duodenography, and 3-D multicholangiography.
Sata, N; Endo, K; Shimura, K; Koizumi, M; Nagai, H
Recent advances in multidetector row computed tomography (MD-CT) technology provide new opportunities for clinical diagnoses of various diseases. Here we assessed CT virtual duodenoscopy, duodenography, and three-dimensional (3D) multicholangiography created by MD-CT for clinical diagnosis of duodenal malignant lesions. The study involved seven cases of periduodenal carcinoma (four ampullary carcinomas, two duodenal carcinomas, one pancreatic carcinoma). Biliary contrast medium was administered intravenously, followed by intravenous administration of an anticholinergic agent and oral administration of effervescent granules for expanding the upper gastrointestinal tract. Following intravenous administration of a nonionic contrast medium, an upper abdominal MD-CT scan was performed in the left lateral position. Scan data were processed on a workstation to create CT virtual duodenoscopy, duodenography, 3D multicholangiography, and various postprocessing images, which were then evaluated for their effectiveness as preoperative diagnostic tools. Carcinoma location and extent were clearly demonstrated as defects or colored low-density areas in 3-D multicholangiography images and as protruding lesions in virtual duodenography and duodenoscopy images. These findings were confirmed using multiplanar or curved planar reformation images. In conclusion, CT virtual duodenoscopy, doudenography, 3-D multicholangiography, and various images created by MD-CT alone provided necessary and adequate preoperative diagnostic information.
Self-Calibration of Cone-Beam CT Geometry Using 3D-2D Image Registration: Development and Application to Task-Based Imaging with a Robotic C-Arm
Ouadah, S.; Stayman, J. W.; Gang, G.; Uneri, A.; Ehtiati, T.; Siewerdsen, J. H.
Purpose Robotic C-arm systems are capable of general noncircular orbits whose trajectories can be driven by the particular imaging task. However obtaining accurate calibrations for reconstruction in such geometries can be a challenging problem. This work proposes a method to perform a unique geometric calibration of an arbitrary C-arm orbit by registering 2D projections to a previously acquired 3D image to determine the transformation parameters representing the system geometry. Methods Experiments involved a cone-beam CT (CBCT) bench system, a robotic C-arm, and three phantoms. A robust 3D-2D registration process was used to compute the 9 degree of freedom (DOF) transformation between each projection and an existing 3D image by maximizing normalized gradient information with a digitally reconstructed radiograph (DRR) of the 3D volume. The quality of the resulting "self-calibration" was evaluated in terms of the agreement with an established calibration method using a BB phantom as well as image quality in the resulting CBCT reconstruction. Results The self-calibration yielded CBCT images without significant difference in spatial resolution from the standard ("true") calibration methods (p-value >0.05 for all three phantoms), and the differences between CBCT images reconstructed using the "self" and "true" calibration methods were on the order of 10−3 mm−1. Maximum error in magnification was 3.2%, and back-projection ray placement was within 0.5 mm. Conclusion The proposed geometric "self" calibration provides a means for 3D imaging on general non-circular orbits in CBCT systems for which a geometric calibration is either not available or not reproducible. The method forms the basis of advanced "task-based" 3D imaging methods now in development for robotic C-arms. PMID:26388661
Self-calibration of cone-beam CT geometry using 3D-2D image registration: development and application to tasked-based imaging with a robotic C-arm
NASA Astrophysics Data System (ADS)
Ouadah, S.; Stayman, J. W.; Gang, G.; Uneri, A.; Ehtiati, T.; Siewerdsen, J. H.
Purpose: Robotic C-arm systems are capable of general noncircular orbits whose trajectories can be driven by the particular imaging task. However obtaining accurate calibrations for reconstruction in such geometries can be a challenging problem. This work proposes a method to perform a unique geometric calibration of an arbitrary C-arm orbit by registering 2D projections to a previously acquired 3D image to determine the transformation parameters representing the system geometry. Methods: Experiments involved a cone-beam CT (CBCT) bench system, a robotic C-arm, and three phantoms. A robust 3D-2D registration process was used to compute the 9 degree of freedom (DOF) transformation between each projection and an existing 3D image by maximizing normalized gradient information with a digitally reconstructed radiograph (DRR) of the 3D volume. The quality of the resulting "self-calibration" was evaluated in terms of the agreement with an established calibration method using a BB phantom as well as image quality in the resulting CBCT reconstruction. Results: The self-calibration yielded CBCT images without significant difference in spatial resolution from the standard ("true") calibration methods (p-value >0.05 for all three phantoms), and the differences between CBCT images reconstructed using the "self" and "true" calibration methods were on the order of 10-3 mm-1. Maximum error in magnification was 3.2%, and back-projection ray placement was within 0.5 mm. Conclusion: The proposed geometric "self" calibration provides a means for 3D imaging on general noncircular orbits in CBCT systems for which a geometric calibration is either not available or not reproducible. The method forms the basis of advanced "task-based" 3D imaging methods now in development for robotic C-arms.
Reconstruction-based 3D/2D image registration.
Tomazevic, Dejan; Likar, Bostjan; Pernus, Franjo
In this paper we present a novel 3D/2D registration method, where first, a 3D image is reconstructed from a few 2D X-ray images and next, the preoperative 3D image is brought into the best possible spatial correspondence with the reconstructed image by optimizing a similarity measure. Because the quality of the reconstructed image is generally low, we introduce a novel asymmetric mutual information similarity measure, which is able to cope with low image quality as well as with different imaging modalities. The novel 3D/2D registration method has been evaluated using standardized evaluation methodology and publicly available 3D CT, 3DRX, and MR and 2D X-ray images of two spine phantoms, for which gold standard registrations were known. In terms of robustness, reliability and capture range the proposed method outperformed the gradient-based method and the method based on digitally reconstructed radiographs (DRRs).
Parker, Dennis L.
SYNOPSIS There has been significant progress made in 3D carotid plaque magnetic resonance imaging techniques in recent years. 3D plaque imaging clearly represents the future in clinical use. With effective flow suppression techniques, choices of different contrast weighting acquisitions, and time-efficient imaging approaches, 3D plaque imaging offers flexible imaging plane and view angle analysis, large coverage, multi-vascular beds capability, and even can be used in fast screening. PMID:26610656
Evaluation of 1D, 2D and 3D nodule size estimation by radiologists for spherical and non-spherical nodules through CT thoracic phantom imaging
NASA Astrophysics Data System (ADS)
Petrick, Nicholas; Kim, Hyun J. Grace; Clunie, David; Borradaile, Kristin; Ford, Robert; Zeng, Rongping; Gavrielides, Marios A.; McNitt-Gray, Michael F.; Fenimore, Charles; Lu, Z. Q. John; Zhao, Binsheng; Buckler, Andrew J.
The purpose of this work was to estimate bias in measuring the size of spherical and non-spherical lesions by radiologists using three sizing techniques under a variety of simulated lesion and reconstruction slice thickness conditions. We designed a reader study in which six radiologists estimated the size of 10 synthetic nodules of various sizes, shapes and densities embedded within a realistic anthropomorphic thorax phantom from CT scan data. In this manuscript we report preliminary results for the first four readers (Reader 1-4). Two repeat CT scans of the phantom containing each nodule were acquired using a Philips 16-slice scanner at a 0.8 and 5 mm slice thickness. The readers measured the sizes of all nodules for each of the 40 resulting scans (10 nodules x 2 slice thickness x 2 repeat scans) using three sizing techniques (1D longest in-slice dimension; 2D area from longest in-slice dimension and corresponding longest perpendicular dimension; 3D semi-automated volume) in each of 2 reading sessions. The normalized size was estimated for each sizing method and an inter-comparison of bias among methods was performed. The overall relative biases (standard deviation) of the 1D, 2D and 3D methods for the four readers subset (Readers 1-4) were -13.4 (20.3), -15.3 (28.4) and 4.8 (21.2) percentage points, respectively. The relative biases for the 3D volume sizing method was statistically lower than either the 1D or 2D method (p<0.001 for 1D vs. 3D and 2D vs. 3D).
3D Ultrasound Can Contribute to Planning CT to Define the Target for Partial Breast Radiotherapy
Berrang, Tanya S.; Truong, Pauline T. Popescu, Carmen; Drever, Laura; Kader, Hosam A.; Hilts, Michelle L.; Mitchell, Tracy; Soh, S.Y.; Sands, Letricia; Silver, Stuart; Olivotto, Ivo A.
Purpose: The role of three-dimensional breast ultrasound (3D US) in planning partial breast radiotherapy (PBRT) is unknown. This study evaluated the accuracy of coregistration of 3D US to planning computerized tomography (CT) images, the seroma contouring consistency of radiation oncologists using the two imaging modalities and the clinical situations in which US was associated with improved contouring consistency compared to CT. Materials and Methods: Twenty consecutive women with early-stage breast cancer were enrolled prospectively after breast-conserving surgery. Subjects underwent 3D US at CT simulation for adjuvant RT. Three radiation oncologists independently contoured the seroma on separate CT and 3D US image sets. Seroma clarity, seroma volumes, and interobserver contouring consistency were compared between the imaging modalities. Associations between clinical characteristics and seroma clarity were examined using Pearson correlation statistics. Results: 3D US and CT coregistration was accurate to within 2 mm or less in 19/20 (95%) cases. CT seroma clarity was reduced with dense breast parenchyma (p = 0.035), small seroma volume (p < 0.001), and small volume of excised breast tissue (p = 0.01). US seroma clarity was not affected by these factors (p = NS). US was associated with improved interobserver consistency compared with CT in 8/20 (40%) cases. Of these 8 cases, 7 had low CT seroma clarity scores and 4 had heterogeneously to extremely dense breast parenchyma. Conclusion: 3D US can be a useful adjunct to CT in planning PBRT. Radiation oncologists were able to use US images to contour the seroma target, with improved interobserver consistency compared with CT in cases with dense breast parenchyma and poor CT seroma clarity.
The effect of activity outside the field of view on image quality for a 3D LSO-based whole body PET/CT scanner.
Matheoud, R; Secco, C; Della Monica, P; Leva, L; Sacchetti, G; Inglese, E; Brambilla, M
The purpose of this study was to quantify the influence of outside field of view (FOV) activity concentration (A(c)(,out)) on the noise equivalent count rate (NECR), scatter fraction (SF) and image quality of a 3D LSO whole-body PET/CT scanner. The contrast-to-noise ratio (CNR) was the figure of merit used to characterize the image quality of PET scans. A modified International Electrotechnical Commission (IEC) phantom was used to obtain SF and counting rates similar to those found in average patients. A scatter phantom was positioned at the end of the modified IEC phantom to simulate an activity that extends beyond the scanner. The modified IEC phantom was filled with (18)F (11 kBq mL(-1)) and the spherical targets, with internal diameter (ID) ranging from 10 to 37 mm, had a target-to-background ratio of 10. PET images were acquired with background activity concentrations into the FOV (A(c)(,bkg)) about 11, 9.2, 6.6, 5.2 and 3.5 kBq mL(-1). The emission scan duration (ESD) was set to 1, 2, 3 and 4 min. The tube inside the scatter phantom was filled with activities to provide A(c)(,out) in the whole scatter phantom of zero, half, unity, twofold and fourfold the one of the modified IEC phantom. Plots of CNR versus the various parameters are provided. Multiple linear regression was employed to study the effects of A(c)(,out) on CNR, adjusted for the presence of variables (sphere ID, A(c)(,bkg) and ESD) related to CNR. The presence of outside FOV activity at the same concentration as the one inside the FOV reduces peak NECR of 30%. The increase in SF is marginal (1.2%). CNR diminishes significantly with increasing outside FOV activity, in the range explored. ESD and A(c)(,out) have a similar weight in accounting for CNR variance. Thus, an experimental law that adjusts the scan duration to the outside FOV activity can be devised. Recovery of CNR loss due to an elevated A(c)(,out) activity seems feasible by modulating the ESD in individual bed positions according to A(c)(,out).
Test of 3D CT reconstructions by EM + TV algorithm from undersampled data
Evseev, Ivan; Ahmann, Francielle; Silva, Hamilton P. da
Computerized tomography (CT) plays an important role in medical imaging for diagnosis and therapy. However, CT imaging is connected with ionization radiation exposure of patients. Therefore, the dose reduction is an essential issue in CT. In 2011, the Expectation Maximization and Total Variation Based Model for CT Reconstruction (EM+TV) was proposed. This method can reconstruct a better image using less CT projections in comparison with the usual filtered back projection (FBP) technique. Thus, it could significantly reduce the overall dose of radiation in CT. This work reports the results of an independent numerical simulation for cone beam CT geometry with alternative virtual phantoms. As in the original report, the 3D CT images of 128 Multiplication-Sign 128 Multiplication-Sign 128 virtual phantoms were reconstructed. It was not possible to implement phantoms with lager dimensions because of the slowness of code execution even by the CORE i7 CPU.
Digital holography and 3-D imaging.
Banerjee, Partha; Barbastathis, George; Kim, Myung; Kukhtarev, Nickolai
This feature issue on Digital Holography and 3-D Imaging comprises 15 papers on digital holographic techniques and applications, computer-generated holography and encryption techniques, and 3-D display. It is hoped that future work in the area leads to innovative applications of digital holography and 3-D imaging to biology and sensing, and to the development of novel nonlinear dynamic digital holographic techniques.
Volumetric image display for complex 3D data visualization
NASA Astrophysics Data System (ADS)
Tsao, Che-Chih; Chen, Jyh Shing
A volumetric image display is a new display technology capable of displaying computer generated 3D images in a volumetric space. Many viewers can walk around the display and see the image from omni-directions simultaneously without wearing any glasses. The image is real and possesses all major elements in both physiological and psychological depth cues. Due to the volumetric nature of its image, the VID can provide the most natural human-machine interface in operations involving 3D data manipulation and 3D targets monitoring. The technology creates volumetric 3D images by projecting a series of profiling images distributed in the space form a volumetric image because of the after-image effect of human eyes. Exemplary applications in biomedical image visualization were tested on a prototype display, using different methods to display a data set from Ct-scans. The features of this display technology make it most suitable for applications that require quick understanding of the 3D relations, need frequent spatial interactions with the 3D images, or involve time-varying 3D data. It can also be useful for group discussion and decision making.
SU-C-BRB-06: Utilizing 3D Scanner and Printer for Dummy Eye-Shield: Artifact-Free CT Images of Tungsten Eye-Shield for Accurate Dose Calculation
Park, J; Lee, J; Kim, H; Kim, I; Ye, S
Purpose: To evaluate the effect of a tungsten eye-shield on the dose distribution of a patient. Methods: A 3D scanner was used to extract the dimension and shape of a tungsten eye-shield in the STL format. Scanned data was transferred into a 3D printer. A dummy eye shield was then produced using bio-resin (3D systems, VisiJet M3 Proplast). For a patient with mucinous carcinoma, the planning CT was obtained with the dummy eye-shield placed on the patient's right eye. Field shaping of 6 MeV was performed using a patient-specific cerrobend block on the 15 x 15 cm{sup 2} applicator. The gantry angle was 330° to cover the planning target volume near by the lens. EGS4/BEAMnrc was commissioned from our measurement data from a Varian 21EX. For the CT-based dose calculation using EGS4/DOSXYZnrc, the CT images were converted to a phantom file through the ctcreate program. The phantom file had the same resolution as the planning CT images. By assigning the CT numbers of the dummy eye-shield region to 17000, the real dose distributions below the tungsten eye-shield were calculated in EGS4/DOSXYZnrc. In the TPS, the CT number of the dummy eye-shield region was assigned to the maximum allowable CT number (3000). Results: As compared to the maximum dose, the MC dose on the right lens or below the eye shield area was less than 2%, while the corresponding RTP calculated dose was an unrealistic value of approximately 50%. Conclusion: Utilizing a 3D scanner and a 3D printer, a dummy eye-shield for electron treatment can be easily produced. The artifact-free CT images were successfully incorporated into the CT-based Monte Carlo simulations. The developed method was useful in predicting the realistic dose distributions around the lens blocked with the tungsten shield.
3D ultrafast ultrasound imaging in vivo.
Provost, Jean; Papadacci, Clement; Arango, Juan Esteban; Imbault, Marion; Fink, Mathias; Gennisson, Jean-Luc; Tanter, Mickael; Pernot, Mathieu
Very high frame rate ultrasound imaging has recently allowed for the extension of the applications of echography to new fields of study such as the functional imaging of the brain, cardiac electrophysiology, and the quantitative imaging of the intrinsic mechanical properties of tumors, to name a few, non-invasively and in real time. In this study, we present the first implementation of Ultrafast Ultrasound Imaging in 3D based on the use of either diverging or plane waves emanating from a sparse virtual array located behind the probe. It achieves high contrast and resolution while maintaining imaging rates of thousands of volumes per second. A customized portable ultrasound system was developed to sample 1024 independent channels and to drive a 32 × 32 matrix-array probe. Its ability to track in 3D transient phenomena occurring in the millisecond range within a single ultrafast acquisition was demonstrated for 3D Shear-Wave Imaging, 3D Ultrafast Doppler Imaging, and, finally, 3D Ultrafast combined Tissue and Flow Doppler Imaging. The propagation of shear waves was tracked in a phantom and used to characterize its stiffness. 3D Ultrafast Doppler was used to obtain 3D maps of Pulsed Doppler, Color Doppler, and Power Doppler quantities in a single acquisition and revealed, at thousands of volumes per second, the complex 3D flow patterns occurring in the ventricles of the human heart during an entire cardiac cycle, as well as the 3D in vivo interaction of blood flow and wall motion during the pulse wave in the carotid at the bifurcation. This study demonstrates the potential of 3D Ultrafast Ultrasound Imaging for the 3D mapping of stiffness, tissue motion, and flow in humans in vivo and promises new clinical applications of ultrasound with reduced intra--and inter-observer variability.
3D ultrafast ultrasound imaging in vivo
NASA Astrophysics Data System (ADS)
Provost, Jean; Papadacci, Clement; Esteban Arango, Juan; Imbault, Marion; Fink, Mathias; Gennisson, Jean-Luc; Tanter, Mickael; Pernot, Mathieu
Very high frame rate ultrasound imaging has recently allowed for the extension of the applications of echography to new fields of study such as the functional imaging of the brain, cardiac electrophysiology, and the quantitative imaging of the intrinsic mechanical properties of tumors, to name a few, non-invasively and in real time. In this study, we present the first implementation of Ultrafast Ultrasound Imaging in 3D based on the use of either diverging or plane waves emanating from a sparse virtual array located behind the probe. It achieves high contrast and resolution while maintaining imaging rates of thousands of volumes per second. A customized portable ultrasound system was developed to sample 1024 independent channels and to drive a 32 × 32 matrix-array probe. Its ability to track in 3D transient phenomena occurring in the millisecond range within a single ultrafast acquisition was demonstrated for 3D Shear-Wave Imaging, 3D Ultrafast Doppler Imaging, and, finally, 3D Ultrafast combined Tissue and Flow Doppler Imaging. The propagation of shear waves was tracked in a phantom and used to characterize its stiffness. 3D Ultrafast Doppler was used to obtain 3D maps of Pulsed Doppler, Color Doppler, and Power Doppler quantities in a single acquisition and revealed, at thousands of volumes per second, the complex 3D flow patterns occurring in the ventricles of the human heart during an entire cardiac cycle, as well as the 3D in vivo interaction of blood flow and wall motion during the pulse wave in the carotid at the bifurcation. This study demonstrates the potential of 3D Ultrafast Ultrasound Imaging for the 3D mapping of stiffness, tissue motion, and flow in humans in vivo and promises new clinical applications of ultrasound with reduced intra—and inter-observer variability.
Fast 3D multiple fan-beam CT systems
NASA Astrophysics Data System (ADS)
Kohlbrenner, Adrian; Haemmerle, Stefan; Laib, Andres; Koller, Bruno; Ruegsegger, Peter
Two fast, CCD-based three-dimensional CT scanners for in vivo applications have been developed. One is designed for small laboratory animals and has a voxel size of 20 micrometer, while the other, having a voxel size of 80 micrometer, is used for human examinations. Both instruments make use of a novel multiple fan-beam technique: radiation from a line-focus X-ray tube is divided into a stack of fan-beams by a 28 micrometer pitch foil collimator. The resulting wedge-shaped X-ray field is the key to the instrument's high scanning speed and allows to position the sample close to the X-ray source, which makes it possible to build compact CT systems. In contrast to cone- beam scanners, the multiple fan-beam scanner relies on standard fan-beam algorithms, thereby eliminating inaccuracies in the reconstruction process. The projections from one single rotation are acquired within 2 min and are subsequently reconstructed into a 1024 X 1024 X 255 voxel array. Hence a single rotation about the sample delivers a 3D image containing a quarter of a billion voxels. Such volumetric images are 6.6 mm in height and can be stacked on top of each other. An area CCD sensor bonded to a fiber-optic light guide acts as a detector. Since no image intensifier, conventional optics or tapers are used throughout the system, the image is virtually distortion free. The scanner's high scanning speed and high resolution at moderately low radiation dose are the basis for reliable time serial measurements and analyses.
NASA Technical Reports Server (NTRS)
Turner, D. Clark (Inventor); Whitaker, Ross (Inventor)
Systems and methods for imaging an object using backscattered radiation are described. The imaging system comprises both a radiation source for irradiating an object that is rotationally movable about the object, and a detector for detecting backscattered radiation from the object that can be disposed on substantially the same side of the object as the source and which can be rotationally movable about the object. The detector can be separated into multiple detector segments with each segment having a single line of sight projection through the object and so detects radiation along that line of sight. Thus, each detector segment can isolate the desired component of the backscattered radiation. By moving independently of each other about the object, the source and detector can collect multiple images of the object at different angles of rotation and generate a three dimensional reconstruction of the object. Other embodiments are described.
3D Ultrafast Ultrasound Imaging In Vivo
Provost, Jean; Papadacci, Clement; Arango, Juan Esteban; Imbault, Marion; Gennisson, Jean-Luc; Tanter, Mickael; Pernot, Mathieu
Very high frame rate ultrasound imaging has recently allowed for the extension of the applications of echography to new fields of study such as the functional imaging of the brain, cardiac electrophysiology, and the quantitative real-time imaging of the intrinsic mechanical properties of tumors, to name a few, non-invasively and in real time. In this study, we present the first implementation of Ultrafast Ultrasound Imaging in three dimensions based on the use of either diverging or plane waves emanating from a sparse virtual array located behind the probe. It achieves high contrast and resolution while maintaining imaging rates of thousands of volumes per second. A customized portable ultrasound system was developed to sample 1024 independent channels and to drive a 32×32 matrix-array probe. Its capability to track in 3D transient phenomena occurring in the millisecond range within a single ultrafast acquisition was demonstrated for 3-D Shear-Wave Imaging, 3-D Ultrafast Doppler Imaging and finally 3D Ultrafast combined Tissue and Flow Doppler. The propagation of shear waves was tracked in a phantom and used to characterize its stiffness. 3-D Ultrafast Doppler was used to obtain 3-D maps of Pulsed Doppler, Color Doppler, and Power Doppler quantities in a single acquisition and revealed, for the first time, the complex 3-D flow patterns occurring in the ventricles of the human heart during an entire cardiac cycle, and the 3-D in vivo interaction of blood flow and wall motion during the pulse wave in the carotid at the bifurcation. This study demonstrates the potential of 3-D Ultrafast Ultrasound Imaging for the 3-D real-time mapping of stiffness, tissue motion, and flow in humans in vivo and promises new clinical applications of ultrasound with reduced intra- and inter-observer variability. PMID:25207828
Three-Dimensional Mapping of Soil Chemical Characteristics at Micrometric Scale by Combining 2D SEM-EDX Data and 3D X-Ray CT Images
Hapca, Simona; Baveye, Philippe C.; Wilson, Clare; Lark, Richard Murray; Otten, Wilfred
There is currently a significant need to improve our understanding of the factors that control a number of critical soil processes by integrating physical, chemical and biological measurements on soils at microscopic scales to help produce 3D maps of the related properties. Because of technological limitations, most chemical and biological measurements can be carried out only on exposed soil surfaces or 2-dimensional cuts through soil samples. Methods need to be developed to produce 3D maps of soil properties based on spatial sequences of 2D maps. In this general context, the objective of the research described here was to develop a method to generate 3D maps of soil chemical properties at the microscale by combining 2D SEM-EDX data with 3D X-ray computed tomography images. A statistical approach using the regression tree method and ordinary kriging applied to the residuals was developed and applied to predict the 3D spatial distribution of carbon, silicon, iron, and oxygen at the microscale. The spatial correlation between the X-ray grayscale intensities and the chemical maps made it possible to use a regression-tree model as an initial step to predict the 3D chemical composition. For chemical elements, e.g., iron, that are sparsely distributed in a soil sample, the regression-tree model provides a good prediction, explaining as much as 90% of the variability in some of the data. However, for chemical elements that are more homogenously distributed, such as carbon, silicon, or oxygen, the additional kriging of the regression tree residuals improved significantly the prediction with an increase in the R2 value from 0.221 to 0.324 for carbon, 0.312 to 0.423 for silicon, and 0.218 to 0.374 for oxygen, respectively. The present research develops for the first time an integrated experimental and theoretical framework, which combines geostatistical methods with imaging techniques to unveil the 3-D chemical structure of soil at very fine scales. The methodology presented
Three-Dimensional Mapping of Soil Chemical Characteristics at Micrometric Scale by Combining 2D SEM-EDX Data and 3D X-Ray CT Images.
Hapca, Simona; Baveye, Philippe C; Wilson, Clare; Lark, Richard Murray; Otten, Wilfred
There is currently a significant need to improve our understanding of the factors that control a number of critical soil processes by integrating physical, chemical and biological measurements on soils at microscopic scales to help produce 3D maps of the related properties. Because of technological limitations, most chemical and biological measurements can be carried out only on exposed soil surfaces or 2-dimensional cuts through soil samples. Methods need to be developed to produce 3D maps of soil properties based on spatial sequences of 2D maps. In this general context, the objective of the research described here was to develop a method to generate 3D maps of soil chemical properties at the microscale by combining 2D SEM-EDX data with 3D X-ray computed tomography images. A statistical approach using the regression tree method and ordinary kriging applied to the residuals was developed and applied to predict the 3D spatial distribution of carbon, silicon, iron, and oxygen at the microscale. The spatial correlation between the X-ray grayscale intensities and the chemical maps made it possible to use a regression-tree model as an initial step to predict the 3D chemical composition. For chemical elements, e.g., iron, that are sparsely distributed in a soil sample, the regression-tree model provides a good prediction, explaining as much as 90% of the variability in some of the data. However, for chemical elements that are more homogenously distributed, such as carbon, silicon, or oxygen, the additional kriging of the regression tree residuals improved significantly the prediction with an increase in the R2 value from 0.221 to 0.324 for carbon, 0.312 to 0.423 for silicon, and 0.218 to 0.374 for oxygen, respectively. The present research develops for the first time an integrated experimental and theoretical framework, which combines geostatistical methods with imaging techniques to unveil the 3-D chemical structure of soil at very fine scales. The methodology presented
Comparison of physical quality assurance between Scanora 3D and 3D Accuitomo 80 dental CT scanners
Ali, Ahmed S.; Fteita, Dareen; Kulmala, Jarmo
Background The use of cone beam computed tomography (CBCT) in dentistry has proven to be useful in the diagnosis and treatment planning of several oral and maxillofacial diseases. The quality of the resulting image is dictated by many factors related to the patient, unit, and operator. Materials and methods In this work, two dental CBCT units, namely Scanora 3D and 3D Accuitomo 80, were assessed and compared in terms of quantitative effective dose delivered to specific locations in a dosimetry phantom. Resolution and contrast were evaluated in only 3D Accuitomo 80 using special quality assurance phantoms. Results Scanora 3D, with less radiation time, showed less dosing values compared to 3D Accuitomo 80 (mean 0.33 mSv, SD±0.16 vs. 0.18 mSv, SD±0.1). Using paired t-test, no significant difference was found in Accuitomo two scan sessions (p>0.05), while it was highly significant in Scanora (p>0.05). The modulation transfer function value (at 2 lp/mm), in both measurements, was found to be 4.4%. The contrast assessment of 3D Accuitomo 80 in the two measurements showed few differences, for example, the grayscale values were the same (SD=0) while the noise level was slightly different (SD=0 and 0.67, respectively). Conclusions The radiation dose values in these two CBCT units are significantly less than those encountered in systemic CT scans. However, the dose seems to be affected more by changing the field of view rather than the voltage or amperage. The low doses were at the expense of the image quality produced, which was still acceptable. Although the spatial resolution and contrast were inferior to the medical images produced in systemic CT units, the present results recommend adopting CBCTs in maxillofacial imaging because of low radiation dose and adequate image quality. PMID:26091832
3-D printouts of the tracheobronchial tree generated from CT images as an aid to management in a case of tracheobronchial chondromalacia caused by relapsing polychondritis.
Tam, Matthew David; Laycock, Stephen David; Jayne, David; Babar, Judith; Noble, Brendon
This report concerns a 67 year old male patient with known advanced relapsing polychondritis complicated by tracheobronchial chondromalacia who is increasingly symptomatic and therapeutic options such as tracheostomy and stenting procedures are being considered. The DICOM files from the patient's dynamic chest CT in its inspiratory and expiratory phases were used to generate stereolithography (STL) files and hence print out 3-D models of the patient's trachea and central airways. The 4 full-sized models allowed better understanding of the extent and location of any stenosis or malacic change and should aid any planned future stenting procedures. The future possibility of using the models as scaffolding to generate a new cartilaginous upper airway using regenerative medical techniques is also discussed.
3D ultrasound imaging for prosthesis fabrication and diagnostic imaging
Morimoto, A.K.; Bow, W.J.; Strong, D.S.
The fabrication of a prosthetic socket for a below-the-knee amputee requires knowledge of the underlying bone structure in order to provide pressure relief for sensitive areas and support for load bearing areas. The goal is to enable the residual limb to bear pressure with greater ease and utility. Conventional methods of prosthesis fabrication are based on limited knowledge about the patient`s underlying bone structure. A 3D ultrasound imaging system was developed at Sandia National Laboratories. The imaging system provides information about the location of the bones in the residual limb along with the shape of the skin surface. Computer assisted design (CAD) software can use this data to design prosthetic sockets for amputees. Ultrasound was selected as the imaging modality. A computer model was developed to analyze the effect of the various scanning parameters and to assist in the design of the overall system. The 3D ultrasound imaging system combines off-the-shelf technology for image capturing, custom hardware, and control and image processing software to generate two types of image data -- volumetric and planar. Both volumetric and planar images reveal definition of skin and bone geometry with planar images providing details on muscle fascial planes, muscle/fat interfaces, and blood vessel definition. The 3D ultrasound imaging system was tested on 9 unilateral below-the- knee amputees. Image data was acquired from both the sound limb and the residual limb. The imaging system was operated in both volumetric and planar formats. An x-ray CT (Computed Tomography) scan was performed on each amputee for comparison. Results of the test indicate beneficial use of ultrasound to generate databases for fabrication of prostheses at a lower cost and with better initial fit as compared to manually fabricated prostheses.
3D statistical shape models incorporating 3D random forest regression voting for robust CT liver segmentation
NASA Astrophysics Data System (ADS)
Norajitra, Tobias; Meinzer, Hans-Peter; Maier-Hein, Klaus H.
During image segmentation, 3D Statistical Shape Models (SSM) usually conduct a limited search for target landmarks within one-dimensional search profiles perpendicular to the model surface. In addition, landmark appearance is modeled only locally based on linear profiles and weak learners, altogether leading to segmentation errors from landmark ambiguities and limited search coverage. We present a new method for 3D SSM segmentation based on 3D Random Forest Regression Voting. For each surface landmark, a Random Regression Forest is trained that learns a 3D spatial displacement function between the according reference landmark and a set of surrounding sample points, based on an infinite set of non-local randomized 3D Haar-like features. Landmark search is then conducted omni-directionally within 3D search spaces, where voxelwise forest predictions on landmark position contribute to a common voting map which reflects the overall position estimate. Segmentation experiments were conducted on a set of 45 CT volumes of the human liver, of which 40 images were randomly chosen for training and 5 for testing. Without parameter optimization, using a simple candidate selection and a single resolution approach, excellent results were achieved, while faster convergence and better concavity segmentation were observed, altogether underlining the potential of our approach in terms of increased robustness from distinct landmark detection and from better search coverage.
A dataset of fishes in and around Inle Lake, an ancient lake of Myanmar, with DNA barcoding, photo images and CT/3D models
Kano, Yuichi; Musikasinthorn, Prachya; Iwata, Akihisa; Tun, Sein; Yun, LKC; Win, Seint Seint; Matsui, Shoko; Tabata, Ryoichi; Yamasaki, Takeshi
Abstract Background Inle (Inlay) Lake, an ancient lake of Southeast Asia, is located at the eastern part of Myanmar, surrounded by the Shan Mountains. Detailed information on fish fauna in and around the lake has long been unknown, although its outstanding endemism was reported a century ago. New information Based on the fish specimens collected from markets, rivers, swamps, ponds and ditches around Inle Lake as well as from the lake itself from 2014 to 2016, we recorded a total of 948 occurrence data (2120 individuals), belonging to 10 orders, 19 families, 39 genera and 49 species. Amongst them, 13 species of 12 genera are endemic or nearly endemic to the lake system and 17 species of 16 genera are suggested as non-native. The data are all accessible from the document "A dataset of Inle Lake fish fauna and its distribution (http://ipt.pensoft.net/resource.do?r=inle_fish_2014-16)", as well as DNA barcoding data (mitochondrial COI) for all species being available from the DDBJ/EMBL/GenBank (Accession numbers: LC189568–LC190411). Live photographs of almost all the individuals and CT/3D model data of several specimens are also available at the graphical fish biodiversity database (http://ffish.asia/INLE2016; http://ffish.asia/INLE2016-3D). The information can benefit the clarification, public concern and conservation of the fish biodiversity in the region. PMID:27932926
3D imaging in forensic odontology.
Evans, Sam; Jones, Carl; Plassmann, Peter
This paper describes the investigation of a new 3D capture method for acquiring and subsequent forensic analysis of bite mark injuries on human skin. When documenting bite marks with standard 2D cameras errors in photographic technique can occur if best practice is not followed. Subsequent forensic analysis of the mark is problematic when a 3D structure is recorded into a 2D space. Although strict guidelines (BAFO) exist, these are time-consuming to follow and, due to their complexity, may produce errors. A 3D image capture and processing system might avoid the problems resulting from the 2D reduction process, simplifying the guidelines and reducing errors. Proposed Solution: a series of experiments are described in this paper to demonstrate that the potential of a 3D system might produce suitable results. The experiments tested precision and accuracy of the traditional 2D and 3D methods. A 3D image capture device minimises the amount of angular distortion, therefore such a system has the potential to create more robust forensic evidence for use in courts. A first set of experiments tested and demonstrated which method of forensic analysis creates the least amount of intra-operator error. A second set tested and demonstrated which method of image capture creates the least amount of inter-operator error and visual distortion. In a third set the effects of angular distortion on 2D and 3D methods of image capture were evaluated.
Automated 3D vascular segmentation in CT hepatic venography
NASA Astrophysics Data System (ADS)
Fetita, Catalin; Lucidarme, Olivier; Preteux, Francoise
In the framework of preoperative evaluation of the hepatic venous anatomy in living-donor liver transplantation or oncologic rejections, this paper proposes an automated approach for the 3D segmentation of the liver vascular structure from 3D CT hepatic venography data. The developed segmentation approach takes into account the specificities of anatomical structures in terms of spatial location, connectivity and morphometric properties. It implements basic and advanced morphological operators (closing, geodesic dilation, gray-level reconstruction, sup-constrained connection cost) in mono- and multi-resolution filtering schemes in order to achieve an automated 3D reconstruction of the opacified hepatic vessels. A thorough investigation of the venous anatomy including morphometric parameter estimation is then possible via computer-vision 3D rendering, interaction and navigation capabilities.
Nonlaser-based 3D surface imaging
Lu, Shin-yee; Johnson, R.K.; Sherwood, R.J.
3D surface imaging refers to methods that generate a 3D surface representation of objects of a scene under viewing. Laser-based 3D surface imaging systems are commonly used in manufacturing, robotics and biomedical research. Although laser-based systems provide satisfactory solutions for most applications, there are situations where non laser-based approaches are preferred. The issues that make alternative methods sometimes more attractive are: (1) real-time data capturing, (2) eye-safety, (3) portability, and (4) work distance. The focus of this presentation is on generating a 3D surface from multiple 2D projected images using CCD cameras, without a laser light source. Two methods are presented: stereo vision and depth-from-focus. Their applications are described.
Imaging detection of new HCCs in cirrhotic patients treated with different techniques: Comparison of conventional US, spiral CT, and 3-dimensional contrast-enhanced US with the Navigator technique (Nav 3D CEUS)☆
Giangregorio, F.; Comparato, G.; Marinone, M.G.; Di Stasi, M.; Sbolli, G.; Aragona, G.; Tansini, P.; Fornari, F.
Introduction The commercially available Navigator system© (Esaote, Italy) allows easy 3D reconstruction of a single 2D acquisition of contrast-enhanced US (CEUS) imaging of the whole liver (with volumetric correction provided by the electromagnetic device of the Navigator©). The aim of our study was to compare the efficacy of this panoramic technique (Nav 3D CEUS) with that of conventional US and spiral CT in the detection of new hepatic lesions in patients treated for hepatocellular carcinoma (HCC). Materials and methods From November 2006 to May 2007, we performed conventional US, Nav 3D CEUS, and spiral CT on 72 cirrhotic patients previously treated for 1 or more HCCs (M/F: 38/34; all HCV-positive; Child: A/B 58/14) (1 examination: 48 patients; 2 examinations: 20 patients; 3 examinations: 4 patients). Nav 3D CEUS was performed with SonoVue© (Bracco, Milan, Italy) as a contrast agent and Technos MPX© scanner (Esaote, Genoa, Italy). Sensitivity, specificity, diagnostic accuracy, and positive and negative predictive values (PPV and NPV, respectively) were evaluated. Differences between the techniques were assessed with the chi-square test (SPSS release-15). Results Definitive diagnoses (based on spiral CT and additional follow-up) were: 6 cases of local recurrence (LocRecs) in 4 patients, 49 new nodules >2 cm from a treated nodule (NewNods) in 34 patients, and 10 cases of multinodular recurrence consisting of 4 or more nodules (NewMulti). The remaining 24 patients (22 treated for 1–3 nodules, 2 treated for >3 nodules) remained recurrence-free. Conventional US correctly detected 29/49 NewNods, 9/10 NewMultis, and 3/6 LocRecs (sensitivity: 59.2%; specificity: 100%; diagnostic accuracy: 73.6%; PPV: 100%; NPV: 70.1%). Spiral CT detected 42/49 NewNods plus 1 that was a false positive, 9/10 NewMultis, and all 6 LocRecs (sensitivity: 85.7%; specificity: 95.7%; diagnostic accuracy: 90.9%; PPV: 97.7%; NPV: 75.9%). 3D NAV results were: 46N (+9 multinodularN and 6 LR
3D integral imaging with optical processing
NASA Astrophysics Data System (ADS)
Martínez-Corral, Manuel; Martínez-Cuenca, Raúl; Saavedra, Genaro; Javidi, Bahram
Integral imaging (InI) systems are imaging devices that provide auto-stereoscopic images of 3D intensity objects. Since the birth of this new technology, InI systems have faced satisfactorily many of their initial drawbacks. Basically, two kind of procedures have been used: digital and optical procedures. The "3D Imaging and Display Group" at the University of Valencia, with the essential collaboration of Prof. Javidi, has centered its efforts in the 3D InI with optical processing. Among other achievements, our Group has proposed the annular amplitude modulation for enlargement of the depth of field, dynamic focusing for reduction of the facet-braiding effect, or the TRES and MATRES devices to enlarge the viewing angle.
Simulation and experimental studies of three-dimensional (3D) image reconstruction from insufficient sampling data based on compressed-sensing theory for potential applications to dental cone-beam CT
NASA Astrophysics Data System (ADS)
Je, U. K.; Lee, M. S.; Cho, H. S.; Hong, D. K.; Park, Y. O.; Park, C. K.; Cho, H. M.; Choi, S. I.; Woo, T. H.
In practical applications of three-dimensional (3D) tomographic imaging, there are often challenges for image reconstruction from insufficient sampling data. In computed tomography (CT), for example, image reconstruction from sparse views and/or limited-angle (<360°) views would enable fast scanning with reduced imaging doses to the patient. In this study, we investigated and implemented a reconstruction algorithm based on the compressed-sensing (CS) theory, which exploits the sparseness of the gradient image with substantially high accuracy, for potential applications to low-dose, high-accurate dental cone-beam CT (CBCT). We performed systematic simulation works to investigate the image characteristics and also performed experimental works by applying the algorithm to a commercially-available dental CBCT system to demonstrate its effectiveness for image reconstruction in insufficient sampling problems. We successfully reconstructed CBCT images of superior accuracy from insufficient sampling data and evaluated the reconstruction quality quantitatively. Both simulation and experimental demonstrations of the CS-based reconstruction from insufficient data indicate that the CS-based algorithm can be applied directly to current dental CBCT systems for reducing the imaging doses and further improving the image quality.
ICER-3D Hyperspectral Image Compression Software
NASA Technical Reports Server (NTRS)
Xie, Hua; Kiely, Aaron; Klimesh, matthew; Aranki, Nazeeh
Software has been developed to implement the ICER-3D algorithm. ICER-3D effects progressive, three-dimensional (3D), wavelet-based compression of hyperspectral images. If a compressed data stream is truncated, the progressive nature of the algorithm enables reconstruction of hyperspectral data at fidelity commensurate with the given data volume. The ICER-3D software is capable of providing either lossless or lossy compression, and incorporates an error-containment scheme to limit the effects of data loss during transmission. The compression algorithm, which was derived from the ICER image compression algorithm, includes wavelet-transform, context-modeling, and entropy coding subalgorithms. The 3D wavelet decomposition structure used by ICER-3D exploits correlations in all three dimensions of sets of hyperspectral image data, while facilitating elimination of spectral ringing artifacts, using a technique summarized in "Improving 3D Wavelet-Based Compression of Spectral Images" (NPO-41381), NASA Tech Briefs, Vol. 33, No. 3 (March 2009), page 7a. Correlation is further exploited by a context-modeling subalgorithm, which exploits spectral dependencies in the wavelet-transformed hyperspectral data, using an algorithm that is summarized in "Context Modeler for Wavelet Compression of Hyperspectral Images" (NPO-43239), which follows this article. An important feature of ICER-3D is a scheme for limiting the adverse effects of loss of data during transmission. In this scheme, as in the similar scheme used by ICER, the spatial-frequency domain is partitioned into rectangular error-containment regions. In ICER-3D, the partitions extend through all the wavelength bands. The data in each partition are compressed independently of those in the other partitions, so that loss or corruption of data from any partition does not affect the other partitions. Furthermore, because compression is progressive within each partition, when data are lost, any data from that partition received
Acquisition and applications of 3D images
NASA Astrophysics Data System (ADS)
Sterian, Paul; Mocanu, Elena
The moiré fringes method and their analysis up to medical and entertainment applications are discussed in this paper. We describe the procedure of capturing 3D images with an Inspeck Camera that is a real-time 3D shape acquisition system based on structured light techniques. The method is a high-resolution one. After processing the images, using computer, we can use the data for creating laser fashionable objects by engraving them with a Q-switched Nd:YAG. In medical field we mention the plastic surgery and the replacement of X-Ray especially in pediatric use.
Development of CT and 3D-CT Using Flat Panel Detector Based Real-Time Digital Radiography System
Ravindran, V. R.; Sreelakshmi, C.; Vibin
The application of Digital Radiography in the Nondestructive Evaluation (NDE) of space vehicle components is a recent development in India. A Real-time DR system based on amorphous silicon Flat Panel Detector has been developed for the NDE of solid rocket motors at Rocket Propellant Plant of VSSC in a few years back. The technique has been successfully established for the nondestructive evaluation of solid rocket motors. The DR images recorded for a few solid rocket specimens are presented in the paper. The Real-time DR system is capable of generating sufficient digital X-ray image data with object rotation for the CT image reconstruction. In this paper the indigenous development of CT imaging based on the Realtime DR system for solid rocket motor is presented. Studies are also carried out to generate 3D-CT image from a set of adjacent CT images of the rocket motor. The capability of revealing the spatial location and characterisation of defect is demonstrated by the CT and 3D-CT images generated.
Development of CT and 3D-CT Using Flat Panel Detector Based Real-Time Digital Radiography System
NASA Astrophysics Data System (ADS)
Ravindran, V. R.; Sreelakshmi, C.; Vibin, Vibin
The application of Digital Radiography in the Nondestructive Evaluation (NDE) of space vehicle components is a recent development in India. A Real-time DR system based on amorphous silicon Flat Panel Detector has been developed for the NDE of solid rocket motors at Rocket Propellant Plant of VSSC in a few years back. The technique has been successfully established for the nondestructive evaluation of solid rocket motors. The DR images recorded for a few solid rocket specimens are presented in the paper. The Real-time DR system is capable of generating sufficient digital X-ray image data with object rotation for the CT image reconstruction. In this paper the indigenous development of CT imaging based on the Realtime DR system for solid rocket motor is presented. Studies are also carried out to generate 3D-CT image from a set of adjacent CT images of the rocket motor. The capability of revealing the spatial location and characterisation of defect is demonstrated by the CT and 3D-CT images generated.
Active segmentation of 3D axonal images.
Muralidhar, Gautam S; Gopinath, Ajay; Bovik, Alan C; Ben-Yakar, Adela
We present an active contour framework for segmenting neuronal axons on 3D confocal microscopy data. Our work is motivated by the need to conduct high throughput experiments involving microfluidic devices and femtosecond lasers to study the genetic mechanisms behind nerve regeneration and repair. While most of the applications for active contours have focused on segmenting closed regions in 2D medical and natural images, there haven't been many applications that have focused on segmenting open-ended curvilinear structures in 2D or higher dimensions. The active contour framework we present here ties together a well known 2D active contour model [5] along with the physics of projection imaging geometry to yield a segmented axon in 3D. Qualitative results illustrate the promise of our approach for segmenting neruonal axons on 3D confocal microscopy data.
Runge, V M; Gelblum, D Y; Wood, M L
3-D gradient echo techniques, and in particular FLASH, represent a significant advance in MR imaging strategy allowing thin section, high resolution imaging through a large region of interest. Anatomical areas of application include the brain, spine, and extremities, although the majority of work to date has been performed in the brain. Superior T1 contrast and thus sensitivity to the presence of GdDTPA is achieved with 3-D FLASH when compared to 2-D spin echo technique. There is marked arterial and venous enhancement following Gd DTPA administration on 3-D FLASH, a less common finding with 2-D spin echo. Enhancement of the falx and tentorium is also more prominent. From a single data acquisition, requiring less than 11 min of scan time, high resolution reformatted sagittal, coronal, and axial images can obtained in addition to sections in any arbitrary plane. Tissue segmentation techniques can be applied and lesions displayed in three dimensions. These results may lead to the replacement of 2-D spin echo with 3-D FLASH for high resolution T1-weighted MR imaging of the CNS, particularly in the study of mass lesions and structural anomalies. The application of similar T2-weighted gradient echo techniques may follow, however the signal-to-noise ratio which can be achieved remains a potential limitation.
Multimodal 3D PET/CT system for bronchoscopic procedure planning
NASA Astrophysics Data System (ADS)
Cheirsilp, Ronnarit; Higgins, William E.
Integrated positron emission tomography (PET) / computed-tomography (CT) scanners give 3D multimodal data sets of the chest. Such data sets offer the potential for more complete and specific identification of suspect lesions and lymph nodes for lung-cancer assessment. This in turn enables better planning of staging bronchoscopies. The richness of the data, however, makes the visualization and planning process difficult. We present an integrated multimodal 3D PET/CT system that enables efficient region identification and bronchoscopic procedure planning. The system first invokes a series of automated 3D image-processing methods that construct a 3D chest model. Next, the user interacts with a set of interactive multimodal graphical tools that facilitate procedure planning for specific regions of interest (ROIs): 1) an interactive region candidate list that enables efficient ROI viewing in all tools; 2) a virtual PET-CT bronchoscopy rendering with SUV quantitative visualization to give a "fly through" endoluminal view of prospective ROIs; 3) transverse, sagittal, coronal multi-planar reformatted (MPR) views of the raw CT, PET, and fused CT-PET data; and 4) interactive multimodal volume/surface rendering to give a 3D perspective of the anatomy and candidate ROIs. In addition the ROI selection process is driven by a semi-automatic multimodal method for region identification. In this way, the system provides both global and local information to facilitate more specific ROI identification and procedure planning. We present results to illustrate the system's function and performance.
Reliability of the Planned Pedicle Screw Trajectory versus the Actual Pedicle Screw Trajectory using Intra-operative 3D CT and Image Guidance
Ledonio, Charles G.; Hunt, Matthew A.; Siddiq, Farhan; Polly, David W.
Background Technological advances, including navigation, have been made to improve safety and accuracy of pedicle screw fixation. We evaluated the accuracy of the virtual screw placement (Stealth projection) compared to actual screw placement (intra-operative O-Arm) and examined for differences based on the distance from the reference frame. Methods A retrospective evaluation of prospectively collected data was conducted from January 2013 to September 2013. We evaluated thoracic and lumbosacral pedicle screws placed using intraoperative O-arm and Stealth navigation by obtaining virtual screw projections and intraoperative O-arm images after screw placement. The screw trajectory angle to the midsagittal line and superior endplate was compared in the axial and sagittal views, respectively. Percent error and paired t-test statistics were then performed. Results Thirty-one patients with 240 pedicle screws were analyzed. The mean angular difference between the virtual and actual image in all screws was 2.17° ± 2.20° on axial images and 2.16° ± 2.24° on sagittal images. There was excellent agreement between actual and virtual pedicle screw trajectories in the axial and sagittal plane with ICC = 0.99 (95%CI: 0.992-0.995) (p<0.001) and ICC= 0.81 (95%CI: 0.759-0.855) (p<0.001) respectively. When comparing thoracic and lumbar screws, there was a significant difference in the sagittal angulation between the two distributions. No statistical differences were found distance from the reference frame. Conclusion The virtual projection view is clinically accurate compared to the actual placement on intra-operative CT in both the axial and sagittal views. There is slight imprecision (~2°) in the axial and sagittal planes and a minor difference in the sagittal thoracic and lumbar angulation, although these did not affect clinical outcomes. In general, we find that pedicle screw placement using intraoperative cone beam CT and navigation to be accurate and reliable, and as such
Getting in touch--3D printing in forensic imaging.
Ebert, Lars Chr; Thali, Michael J; Ross, Steffen
With the increasing use of medical imaging in forensics, as well as the technological advances in rapid prototyping, we suggest combining these techniques to generate displays of forensic findings. We used computed tomography (CT), CT angiography, magnetic resonance imaging (MRI) and surface scanning with photogrammetry in conjunction with segmentation techniques to generate 3D polygon meshes. Based on these data sets, a 3D printer created colored models of the anatomical structures. Using this technique, we could create models of bone fractures, vessels, cardiac infarctions, ruptured organs as well as bitemark wounds. The final models are anatomically accurate, fully colored representations of bones, vessels and soft tissue, and they demonstrate radiologically visible pathologies. The models are more easily understood by laypersons than volume rendering or 2D reconstructions. Therefore, they are suitable for presentations in courtrooms and for educational purposes.
Walker Ranch 3D seismic images
Robert J. Mellors
Amplitude images (both vertical and depth slices) extracted from 3D seismic reflection survey over area of Walker Ranch area (adjacent to Raft River). Crossline spacing of 660 feet and inline of 165 feet using a Vibroseis source. Processing included depth migration. Micro-earthquake hypocenters on images. Stratigraphic information and nearby well tracks added to images. Images are embedded in a Microsoft Word document with additional information. Exact location and depth restricted for proprietary reasons. Data collection and processing funded by Agua Caliente. Original data remains property of Agua Caliente.
A statistical description of 3D lung texture from CT data
NASA Astrophysics Data System (ADS)
Chaisaowong, Kraisorn; Paul, Andreas
A method was described to create a statistical description of 3D lung texture from CT data. The second order statistics, i.e. the gray level co-occurrence matrix (GLCM), has been applied to characterize texture of lung by defining the joint probability distribution of pixel pairs. The required GLCM was extended to three-dimensional image regions to deal with CT volume data. For a fine-scale lung segmentation, both the 3D GLCM of lung and thorax without lung are required. Once the co-occurrence densities are measured, the 3D models of the joint probability density function for each describing direction of involving voxel pairs and for each class (lung or thorax) are estimated using mixture of Gaussians through the expectation-maximization algorithm. This leads to a feature space that describes the 3D lung texture.
Feasibility of CT-based intraoperative 3D stereotactic image-guided navigation in the upper cervical spine of children 10 years of age or younger: initial experience.
Kovanda, Timothy J; Ansari, Shaheryar F; Qaiser, Rabia; Fulkerson, Daniel H
OBJECT Rigid screw fixation may be technically difficult in the upper cervical spine of young children. Intraoperative stereotactic navigation may potentially assist a surgeon in precise placement of screws in anatomically challenging locations. Navigation may also assist in defining abnormal anatomy. The object of this study was to evaluate the authors' initial experience with the feasibility and accuracy of this technique, both for resection and for screw placement in the upper cervical spine in younger children. METHODS Eight consecutive pediatric patients 10 years of age or younger underwent upper cervical spine surgery aided by image-guided navigation. The demographic, surgical, and clinical data were recorded. Screw position was evaluated with either an intraoperative or immediately postoperative CT scan. RESULTS One patient underwent navigation purely for guidance of bony resection. A total of 14 navigated screws were placed in the other 7 patients, including 5 C-2 pedicle screws. All 14 screws were properly positioned, defined as the screw completely contained within the cortical bone in the expected trajectory. There were no immediate complications associated with navigation. CONCLUSIONS Image-guided navigation is feasible within the pediatric cervical spine and may be a useful surgical tool for placing screws in a patient with small, often difficult bony anatomy. The authors describe their experience with their first 8 pediatric patients who underwent navigation in cervical spine surgery. The authors highlight differences in technique compared with similar navigation in adults.
Backhoe 3D "gold standard" image
NASA Astrophysics Data System (ADS)
Gorham, LeRoy; Naidu, Kiranmai D.; Majumder, Uttam; Minardi, Michael A.
ViSUAl-D (VIsual Sar Using ALl Dimensions), a 2004 DARPA/IXO seedling effort, is developing a capability for reliable high confidence ID from standoff ranges. Recent conflicts have demonstrated that the warfighter would greatly benefit from the ability to ID targets beyond visual and electro-optical ranges[1]. Forming optical-quality SAR images while exploiting full polarization, wide angles, and large bandwidth would be key evidence such a capability is achievable. Using data generated by the Xpatch EM scattering code, ViSUAl-D investigates all degrees of freedom available to the radar designer, including 6 GHz bandwidth, full polarization and angle sampling over 2π steradians (upper hemisphere), in order to produce a "literal" image or representation of the target. This effort includes the generation of a "Gold Standard" image that can be produced at X-band utilizing all available target data. This "Gold Standard" image of the backhoe will serve as a test bed for future more relevant military targets and their image development. The seedling team produced a public release data which was released at the 2004 SPIE conference, as well as a 3D "Gold Standard" backhoe image using a 3D image formation algorithm. This paper describes the full backhoe data set, the image formation algorithm, the visualization process and the resulting image.
Tilted planes in 3D image analysis
NASA Astrophysics Data System (ADS)
Pargas, Roy P.; Staples, Nancy J.; Malloy, Brian F.; Cantrell, Ken; Chhatriwala, Murtuza
Reliable 3D wholebody scanners which output digitized 3D images of a complete human body are now commercially available. This paper describes a software package, called 3DM, being developed by researchers at Clemson University and which manipulates and extracts measurements from such images. The focus of this paper is on tilted planes, a 3DM tool which allows a user to define a plane through a scanned image, tilt it in any direction, and effectively define three disjoint regions on the image: the points on the plane and the points on either side of the plane. With tilted planes, the user can accurately take measurements required in applications such as apparel manufacturing. The user can manually segment the body rather precisely. Tilted planes assist the user in analyzing the form of the body and classifying the body in terms of body shape. Finally, titled planes allow the user to eliminate extraneous and unwanted points often generated by a 3D scanner. This paper describes the user interface for tilted planes, the equations defining the plane as the user moves it through the scanned image, an overview of the algorithms, and the interaction of the tilted plane feature with other tools in 3DM.
Recent progress in 3-D imaging of sea freight containers
Fuchs, Theobald Schön, Tobias Sukowski, Frank; Dittmann, Jonas; Hanke, Randolf
The inspection of very large objects like sea freight containers with X-ray Computed Tomography (CT) is an emerging technology. A complete 3-D CT scan of a see-freight container takes several hours. Of course, this is too slow to apply it to a large number of containers. However, the benefits of a 3-D CT for sealed freight are obvious: detection of potential threats or illicit cargo without being confronted with legal complications or high time consumption and risks for the security personnel during a manual inspection. Recently distinct progress was made in the field of reconstruction of projections with only a relatively low number of angular positions. Instead of today's 500 to 1000 rotational steps, as needed for conventional CT reconstruction techniques, this new class of algorithms provides the potential to reduce the number of projection angles approximately by a factor of 10. The main drawback of these advanced iterative methods is the high consumption for numerical processing. But as computational power is getting steadily cheaper, there will be practical applications of these complex algorithms in a foreseeable future. In this paper, we discuss the properties of iterative image reconstruction algorithms and show results of their application to CT of extremely large objects scanning a sea-freight container. A specific test specimen is used to quantitatively evaluate the image quality in terms of spatial and contrast resolution and depending on different number of projections.
Computerized analysis of pelvic incidence from 3D images
NASA Astrophysics Data System (ADS)
Vrtovec, Tomaž; Janssen, Michiel M. A.; Pernuš, Franjo; Castelein, René M.; Viergever, Max A.
The sagittal alignment of the pelvis can be evaluated by the angle of pelvic incidence (PI), which is constant for an arbitrary subject position and orientation and can be therefore compared among subjects in standing, sitting or supine position. In this study, PI was measured from three-dimensional (3D) computed tomography (CT) images of normal subjects that were acquired in supine position. A novel computerized method, based on image processing techniques, was developed to automatically determine the anatomical references required to measure PI, i.e. the centers of the femoral heads in 3D, and the center and inclination of the sacral endplate in 3D. Multiplanar image reformation was applied to obtain perfect sagittal views with all anatomical structures completely in line with the hip axis, from which PI was calculated. The resulting PI (mean+/-standard deviation) was equal to 46.6°+/-9.2° for male subjects (N = 189), 47.6°+/-10.7° for female subjects (N = 181), and 47.1°+/-10.0° for all subjects (N = 370). The obtained measurements of PI from 3D images were not biased by acquisition projection or structure orientation, because all anatomical structures were completely in line with the hip axis. The performed measurements in 3D therefore represent PI according to the actual geometrical relationships among anatomical structures of the sacrum, pelvis and hips, as observed from the perfect sagittal views.
Automated curved planar reformation of 3D spine images
NASA Astrophysics Data System (ADS)
Vrtovec, Tomaz; Likar, Bostjan; Pernus, Franjo
Traditional techniques for visualizing anatomical structures are based on planar cross-sections from volume images, such as images obtained by computed tomography (CT) or magnetic resonance imaging (MRI). However, planar cross-sections taken in the coordinate system of the 3D image often do not provide sufficient or qualitative enough diagnostic information, because planar cross-sections cannot follow curved anatomical structures (e.g. arteries, colon, spine, etc). Therefore, not all of the important details can be shown simultaneously in any planar cross-section. To overcome this problem, reformatted images in the coordinate system of the inspected structure must be created. This operation is usually referred to as curved planar reformation (CPR). In this paper we propose an automated method for CPR of 3D spine images, which is based on the image transformation from the standard image-based to a novel spine-based coordinate system. The axes of the proposed spine-based coordinate system are determined on the curve that represents the vertebral column, and the rotation of the vertebrae around the spine curve, both of which are described by polynomial models. The optimal polynomial parameters are obtained in an image analysis based optimization framework. The proposed method was qualitatively and quantitatively evaluated on five CT spine images. The method performed well on both normal and pathological cases and was consistent with manually obtained ground truth data. The proposed spine-based CPR benefits from reduced structural complexity in favour of improved feature perception of the spine. The reformatted images are diagnostically valuable and enable easier navigation, manipulation and orientation in 3D space. Moreover, reformatted images may prove useful for segmentation and other image analysis tasks.
Two-alternative forced-choice evaluation of 3D CT angiograms
NASA Astrophysics Data System (ADS)
Habets, Damiaan F.; Chapman, Brian E.; Fox, Allan J.; Hyde, Derek E.; Holdsworth, David W.
This study describes the development and evaluation of an appropriate methodology to study observer performance when comparing 2D and 3D angiographic techniques. 3D-CT angiograms were obtained from patients with cerebral aneurysms or occlusive carotid artery disease and perspective rendering of this 3D data was performed to produce maximum intensity projections (MIP) at view angles identical to digital subtraction angiography (DSA) images. Two-alternative-forced-choice methodology (2AFC) was then used to determine the percent correct (Pc), which is equivalent to the area Az under the receiver-operating characteristic (RTOC) curve. In a comparison of CRA MIP images and DSA images of the intracranial vasculature, the average value of Pc was 0.90+/- 0.03. Perspective reprojection produces digitally reconstructed radiographs (DRRs) with image quality that is nearly equivalent to conventional DSA, with the additional clinical advantage of providing digitally reconstructed images at an unlimited number of viewing angles.
Practical pseudo-3D registration for large tomographic images
NASA Astrophysics Data System (ADS)
Liu, Xuan; Laperre, Kjell; Sasov, Alexander
Image registration is a powerful tool in various tomographic applications. Our main focus is on microCT applications in which samples/animals can be scanned multiple times under different conditions or at different time points. For this purpose, a registration tool capable of handling fairly large volumes has been developed, using a novel pseudo-3D method to achieve fast and interactive registration with simultaneous 3D visualization. To reduce computation complexity in 3D registration, we decompose it into several 2D registrations, which are applied to the orthogonal views (transaxial, sagittal and coronal) sequentially and iteratively. After registration in each view, the next view is retrieved with the new transformation matrix for registration. This reduces the computation complexity significantly. For rigid transform, we only need to search for 3 parameters (2 shifts, 1 rotation) in each of the 3 orthogonal views instead of 6 (3 shifts, 3 rotations) for full 3D volume. In addition, the amount of voxels involved is also significantly reduced. For the proposed pseudo-3D method, image-based registration is employed, with Sum of Square Difference (SSD) as the similarity measure. The searching engine is Powell's conjugate direction method. In this paper, only rigid transform is used. However, it can be extended to affine transform by adding scaling and possibly shearing to the transform model. We have noticed that more information can be used in the 2D registration if Maximum Intensity Projections (MIP) or Parallel Projections (PP) is used instead of the orthogonal views. Also, other similarity measures, such as covariance or mutual information, can be easily incorporated. The initial evaluation on microCT data shows very promising results. Two application examples are shown: dental samples before and after treatment and structural changes in materials before and after compression. Evaluation on registration accuracy between pseudo-3D method and true 3D method has
3D Imaging with Holographic Tomography
NASA Astrophysics Data System (ADS)
Sheppard, Colin J. R.; Kou, Shan Shan
There are two main types of tomography that enable the 3D internal structures of objects to be reconstructed from scattered data. The commonly known computerized tomography (CT) give good results in the x-ray wavelength range where the filtered back-projection theorem and Radon transform can be used. These techniques rely on the Fourier projection-slice theorem where rays are considered to propagate straight through the object. Another type of tomography called `diffraction tomography' applies in applications in optics and acoustics where diffraction and scattering effects must be taken into account. The latter proves to be a more difficult problem, as light no longer travels straight through the sample. Holographic tomography is a popular way of performing diffraction tomography and there has been active experimental research on reconstructing complex refractive index data using this approach recently. However, there are two distinct ways of doing tomography: either by rotation of the object or by rotation of the illumination while fixing the detector. The difference between these two setups is intuitive but needs to be quantified. From Fourier optics and information transformation point of view, we use 3D transfer function analysis to quantitatively describe how spatial frequencies of the object are mapped to the Fourier domain. We first employ a paraxial treatment by calculating the Fourier transform of the defocused OTF. The shape of the calculated 3D CTF for tomography, by scanning the illumination in one direction only, takes on a form that we might call a 'peanut,' compared to the case of object rotation, where a diablo is formed, the peanut exhibiting significant differences and non-isotropy. In particular, there is a line singularity along one transverse direction. Under high numerical aperture conditions, the paraxial treatment is not accurate, and so we make use of 3D analytical geometry to calculate the behaviour in the non-paraxial case. This time, we
Feasibility of 3D harmonic contrast imaging.
Voormolen, M M; Bouakaz, A; Krenning, B J; Lancée, C T; ten Cate, F J; de Jong, N
Improved endocardial border delineation with the application of contrast agents should allow for less complex and faster tracing algorithms for left ventricular volume analysis. We developed a fast rotating phased array transducer for 3D imaging of the heart with harmonic capabilities making it suitable for contrast imaging. In this study the feasibility of 3D harmonic contrast imaging is evaluated in vitro. A commercially available tissue mimicking flow phantom was used in combination with Sonovue. Backscatter power spectra from a tissue and contrast region of interest were calculated from recorded radio frequency data. The spectra and the extracted contrast to tissue ratio from these spectra were used to optimize the excitation frequency, the pulse length and the receive filter settings of the transducer. Frequencies ranging from 1.66 to 2.35 MHz and pulse lengths of 1.5, 2 and 2.5 cycles were explored. An increase of more than 15 dB in the contrast to tissue ratio was found around the second harmonic compared with the fundamental level at an optimal excitation frequency of 1.74 MHz and a pulse length of 2.5 cycles. Using the optimal settings for 3D harmonic contrast recordings volume measurements of a left ventricular shaped agar phantom were performed. Without contrast the extracted volume data resulted in a volume error of 1.5%, with contrast an accuracy of 3.8% was achieved. The results show the feasibility of accurate volume measurements from 3D harmonic contrast images. Further investigations will include the clinical evaluation of the presented technique for improved assessment of the heart.
A comparison of 3D poly(ε-caprolactone) tissue engineering scaffolds produced with conventional and additive manufacturing techniques by means of quantitative analysis of SR μ-CT images
NASA Astrophysics Data System (ADS)
Brun, F.; Intranuovo, F.; Mohammadi, S.; Domingos, M.; Favia, P.; Tromba, G.
The technique used to produce a 3D tissue engineering (TE) scaffold is of fundamental importance in order to guarantee its proper morphological characteristics. An accurate assessment of the resulting structural properties is therefore crucial in order to evaluate the effectiveness of the produced scaffold. Synchrotron radiation (SR) computed microtomography (μ-CT) combined with further image analysis seems to be one of the most effective techniques to this aim. However, a quantitative assessment of the morphological parameters directly from the reconstructed images is a non trivial task. This study considers two different poly(ε-caprolactone) (PCL) scaffolds fabricated with a conventional technique (Solvent Casting Particulate Leaching, SCPL) and an additive manufacturing (AM) technique (BioCell Printing), respectively. With the first technique it is possible to produce scaffolds with random, non-regular, rounded pore geometry. The AM technique instead is able to produce scaffolds with square-shaped interconnected pores of regular dimension. Therefore, the final morphology of the AM scaffolds can be predicted and the resulting model can be used for the validation of the applied imaging and image analysis protocols. It is here reported a SR μ-CT image analysis approach that is able to effectively and accurately reveal the differences in the pore- and throat-size distributions as well as connectivity of both AM and SCPL scaffolds.
3-D Reconstruction From 2-D Radiographic Images and Its Application to Clinical Veterinary Medicine
NASA Astrophysics Data System (ADS)
Hamamoto, Kazuhiko; Sato, Motoyoshi
3D imaging technique is very important and indispensable in diagnosis. The main stream of the technique is one in which 3D image is reconstructed from a set of slice images, such as X-ray CT and MRI. However, these systems require large space and high costs. On the other hand, a low cost and small size 3D imaging system is needed in clinical veterinary medicine, for example, in the case of diagnosis in X-ray car or pasture area. We propose a novel 3D imaging technique using 2-D X-ray radiographic images. This system can be realized by cheaper system than X-ray CT and enables to get 3D image in X-ray car or portable X-ray equipment. In this paper, a 3D visualization technique from 2-D radiographic images is proposed and several reconstructions are shown. These reconstructions are evaluated by veterinarians.
3D imaging system for biometric applications
NASA Astrophysics Data System (ADS)
Harding, Kevin; Abramovich, Gil; Paruchura, Vijay; Manickam, Swaminathan; Vemury, Arun
There is a growing interest in the use of 3D data for many new applications beyond traditional metrology areas. In particular, using 3D data to obtain shape information of both people and objects for applications ranging from identification to game inputs does not require high degrees of calibration or resolutions in the tens of micron range, but does require a means to quickly and robustly collect data in the millimeter range. Systems using methods such as structured light or stereo have seen wide use in measurements, but due to the use of a triangulation angle, and thus the need for a separated second viewpoint, may not be practical for looking at a subject 10 meters away. Even when working close to a subject, such as capturing hands or fingers, the triangulation angle causes occlusions, shadows, and a physically large system that may get in the way. This paper will describe methods to collect medium resolution 3D data, plus highresolution 2D images, using a line of sight approach. The methods use no moving parts and as such are robust to movement (for portability), reliable, and potentially very fast at capturing 3D data. This paper will describe the optical methods considered, variations on these methods, and present experimental data obtained with the approach.
3-D Imaging Based, Radiobiological Dosimetry
Sgouros, George; Frey, Eric; Wahl, Richard; He, Bin; Prideaux, Andrew; Hobbs, Robert
Targeted radionuclide therapy holds promise as a new treatment against cancer. Advances in imaging are making it possible to evaluate the spatial distribution of radioactivity in tumors and normal organs over time. Matched anatomical imaging such as combined SPECT/CT and PET/CT have also made it possible to obtain tissue density information in conjunction with the radioactivity distribution. Coupled with sophisticated iterative reconstruction algorithims, these advances have made it possible to perform highly patient-specific dosimetry that also incorporates radiobiological modeling. Such sophisticated dosimetry techniques are still in the research investigation phase. Given the attendant logistical and financial costs, a demonstrated improvement in patient care will be a prerequisite for the adoption of such highly-patient specific internal dosimetry methods. PMID:18662554
3D strain measurement in soft tissue: demonstration of a novel inverse finite element model algorithm on MicroCT images of a tissue phantom exposed to negative pressure wound therapy.
Wilkes, R; Zhao, Y; Cunningham, K; Kieswetter, K; Haridas, B
This study describes a novel system for acquiring the 3D strain field in soft tissue at sub-millimeter spatial resolution during negative pressure wound therapy (NPWT). Recent research in advanced wound treatment modalities theorizes that microdeformations induced by the application of sub-atmospheric (negative) pressure through V.A.C. GranuFoam Dressing, a reticulated open-cell polyurethane foam (ROCF), is instrumental in regulating the mechanobiology of granulation tissue formation [Saxena, V., Hwang, C.W., Huang, S., Eichbaum, Q., Ingber, D., Orgill, D.P., 2004. Vacuum-assisted closure: Microdeformations of wounds and cell proliferation. Plast. Reconstr. Surg. 114, 1086-1096]. While the clinical response is unequivocal, measurement of deformations at the wound-dressing interface has not been possible due to the inaccessibility of the wound tissue beneath the sealed dressing. Here we describe the development of a bench-test wound model for microcomputed tomography (microCT) imaging of deformation induced by NPWT and an algorithm set for quantifying the 3D strain field at sub-millimeter resolution. Microdeformations induced in the tissue phantom revealed average tensile strains of 18%-23% at sub-atmospheric pressures of -50 to -200 mmHg (-6.7 to -26.7 kPa). The compressive strains (22%-24%) and shear strains (20%-23%) correlate with 2D FEM studies of microdeformational wound therapy in the reference cited above. We anticipate that strain signals quantified using this system can then be used in future research aimed at correlating the effects of mechanical loading on the phenotypic expression of dermal fibroblasts in acute and chronic ulcer models. Furthermore, the method developed here can be applied to continuum deformation analysis in other contexts, such as 3D cell culture via confocal microscopy, full scale CT and MRI imaging, and in machine vision.
Repositioning accuracy of two different mask systems-3D revisited: Comparison using true 3D/3D matching with cone-beam CT
Boda-Heggemann, Judit . E-mail: email@example.com; Walter, Cornelia; Rahn, Angelika; Wertz, Hansjoerg; Loeb, Iris; Lohr, Frank; Wenz, Frederik
Purpose: The repositioning accuracy of mask-based fixation systems has been assessed with two-dimensional/two-dimensional or two-dimensional/three-dimensional (3D) matching. We analyzed the accuracy of commercially available head mask systems, using true 3D/3D matching, with X-ray volume imaging and cone-beam CT. Methods and Materials: Twenty-one patients receiving radiotherapy (intracranial/head-and-neck tumors) were evaluated (14 patients with rigid and 7 with thermoplastic masks). X-ray volume imaging was analyzed online and offline separately for the skull and neck regions. Translation/rotation errors of the target isocenter were analyzed. Four patients were treated to neck sites. For these patients, repositioning was aided by additional body tattoos. A separate analysis of the setup error on the basis of the registration of the cervical vertebra was performed. The residual error after correction and intrafractional motility were calculated. Results: The mean length of the displacement vector for rigid masks was 0.312 {+-} 0.152 cm (intracranial) and 0.586 {+-} 0.294 cm (neck). For the thermoplastic masks, the value was 0.472 {+-} 0.174 cm (intracranial) and 0.726 {+-} 0.445 cm (neck). Rigid masks with body tattoos had a displacement vector length in the neck region of 0.35 {+-} 0.197 cm. The intracranial residual error and intrafractional motility after X-ray volume imaging correction for rigid masks was 0.188 {+-} 0.074 cm, and was 0.134 {+-} 0.14 cm for thermoplastic masks. Conclusions: The results of our study have demonstrated that rigid masks have a high intracranial repositioning accuracy per se. Given the small residual error and intrafractional movement, thermoplastic masks may also be used for high-precision treatments when combined with cone-beam CT. The neck region repositioning accuracy was worse than the intracranial accuracy in both cases. However, body tattoos and image guidance improved the accuracy. Finally, the combination of both mask
Pattern based 3D image Steganography
NASA Astrophysics Data System (ADS)
Thiyagarajan, P.; Natarajan, V.; Aghila, G.; Prasanna Venkatesan, V.; Anitha, R.
This paper proposes a new high capacity Steganographic scheme using 3D geometric models. The novel algorithm re-triangulates a part of a triangle mesh and embeds the secret information into newly added position of triangle meshes. Up to nine bits of secret data can be embedded into vertices of a triangle without causing any changes in the visual quality and the geometric properties of the cover image. Experimental results show that the proposed algorithm is secure, with high capacity and low distortion rate. Our algorithm also resists against uniform affine transformations such as cropping, rotation and scaling. Also, the performance of the method is compared with other existing 3D Steganography algorithms. [Figure not available: see fulltext.
The Diagnostic Radiological Utilization Of 3-D Display Images
NASA Astrophysics Data System (ADS)
Cook, Larry T.; Dwyer, Samuel J.; Preston, David F.; Batnitzky, Solomon; Lee, Kyo R.
In the practice of radiology, computer graphics systems have become an integral part of the use of computed tomography (CT), nuclear medicine (NM), magnetic resonance imaging (MRI), digital subtraction angiography (DSA) and ultrasound. Gray scale computerized display systems are used to display, manipulate, and record scans in all of these modalities. As the use of these imaging systems has spread, various applications involving digital image manipulation have also been widely accepted in the radiological community. We discuss one of the more esoteric of such applications, namely, the reconstruction of 3-D structures from plane section data, such as CT scans. Our technique is based on the acquisition of contour data from successive sections, the definition of the implicit surface defined by such contours, and the application of the appropriate computer graphics hardware and software to present reasonably pleasing pictures.
Crouzon syndrome associated with acanthosis nigricans: prenatal 2D and 3D ultrasound findings and postnatal 3D CT findings
Nørgaard, Pernille; Hagen, Casper Petri; Hove, Hanne; Dunø, Morten; Nissen, Kamilla Rothe; Kreiborg, Sven; Jørgensen, Finn Stener
Crouzon syndrome with acanthosis nigricans (CAN) is a very rare condition with an approximate prevalence of 1 per 1 million newborns. We add the first report on prenatal 2D and 3D ultrasound findings in CAN. In addition we present the postnatal 3D CT findings. The diagnosis was confirmed by molecular testing. PMID:23986840
3D goes digital: from stereoscopy to modern 3D imaging techniques
NASA Astrophysics Data System (ADS)
Kerwien, N.
In the 19th century, English physicist Charles Wheatstone discovered stereopsis, the basis for 3D perception. His construction of the first stereoscope established the foundation for stereoscopic 3D imaging. Since then, many optical instruments were influenced by these basic ideas. In recent decades, the advent of digital technologies revolutionized 3D imaging. Powerful readily available sensors and displays combined with efficient pre- or post-processing enable new methods for 3D imaging and applications. This paper draws an arc from basic concepts of 3D imaging to modern digital implementations, highlighting instructive examples from its 175 years of history.
3D seismic image processing for interpretation
NASA Astrophysics Data System (ADS)
Wu, Xinming
Extracting fault, unconformity, and horizon surfaces from a seismic image is useful for interpretation of geologic structures and stratigraphic features. Although interpretation of these surfaces has been automated to some extent by others, significant manual effort is still required for extracting each type of these geologic surfaces. I propose methods to automatically extract all the fault, unconformity, and horizon surfaces from a 3D seismic image. To a large degree, these methods just involve image processing or array processing which is achieved by efficiently solving partial differential equations. For fault interpretation, I propose a linked data structure, which is simpler than triangle or quad meshes, to represent a fault surface. In this simple data structure, each sample of a fault corresponds to exactly one image sample. Using this linked data structure, I extract complete and intersecting fault surfaces without holes from 3D seismic images. I use the same structure in subsequent processing to estimate fault slip vectors. I further propose two methods, using precomputed fault surfaces and slips, to undo faulting in seismic images by simultaneously moving fault blocks and faults themselves. For unconformity interpretation, I first propose a new method to compute a unconformity likelihood image that highlights both the termination areas and the corresponding parallel unconformities and correlative conformities. I then extract unconformity surfaces from the likelihood image and use these surfaces as constraints to more accurately estimate seismic normal vectors that are discontinuous near the unconformities. Finally, I use the estimated normal vectors and use the unconformities as constraints to compute a flattened image, in which seismic reflectors are all flat and vertical gaps correspond to the unconformities. Horizon extraction is straightforward after computing a map of image flattening; we can first extract horizontal slices in the flattened space
Thoracic cavity definition for 3D PET/CT analysis and visualization.
Cheirsilp, Ronnarit; Bascom, Rebecca; Allen, Thomas W; Higgins, William E
X-ray computed tomography (CT) and positron emission tomography (PET) serve as the standard imaging modalities for lung-cancer management. CT gives anatomical details on diagnostic regions of interest (ROIs), while PET gives highly specific functional information. During the lung-cancer management process, a patient receives a co-registered whole-body PET/CT scan pair and a dedicated high-resolution chest CT scan. With these data, multimodal PET/CT ROI information can be gleaned to facilitate disease management. Effective image segmentation of the thoracic cavity, however, is needed to focus attention on the central chest. We present an automatic method for thoracic cavity segmentation from 3D CT scans. We then demonstrate how the method facilitates 3D ROI localization and visualization in patient multimodal imaging studies. Our segmentation method draws upon digital topological and morphological operations, active-contour analysis, and key organ landmarks. Using a large patient database, the method showed high agreement to ground-truth regions, with a mean coverage=99.2% and leakage=0.52%. Furthermore, it enabled extremely fast computation. For PET/CT lesion analysis, the segmentation method reduced ROI search space by 97.7% for a whole-body scan, or nearly 3 times greater than that achieved by a lung mask. Despite this reduction, we achieved 100% true-positive ROI detection, while also reducing the false-positive (FP) detection rate by >5 times over that achieved with a lung mask. Finally, the method greatly improved PET/CT visualization by eliminating false PET-avid obscurations arising from the heart, bones, and liver. In particular, PET MIP views and fused PET/CT renderings depicted unprecedented clarity of the lesions and neighboring anatomical structures truly relevant to lung-cancer assessment.
Thoracic Cavity Definition for 3D PET/CT Analysis and Visualization
Cheirsilp, Ronnarit; Bascom, Rebecca; Allen, Thomas W.; Higgins, William E.
X-ray computed tomography (CT) and positron emission tomography (PET) serve as the standard imaging modalities for lung-cancer management. CT gives anatomical detail on diagnostic regions of interest (ROIs), while PET gives highly specific functional information. During the lung-cancer management process, a patient receives a co-registered whole-body PET/CT scan pair and a dedicated high-resolution chest CT scan. With these data, multimodal PET/CT ROI information can be gleaned to facilitate disease management. Effective image segmentation of the thoracic cavity, however, is needed to focus attention on the central chest. We present an automatic method for thoracic cavity segmentation from 3D CT scans. We then demonstrate how the method facilitates 3D ROI localization and visualization in patient multimodal imaging studies. Our segmentation method draws upon digital topological and morphological operations, active-contour analysis, and key organ landmarks. Using a large patient database, the method showed high agreement to ground-truth regions, with a mean coverage = 99.2% and leakage = 0.52%. Furthermore, it enabled extremely fast computation. For PET/CT lesion analysis, the segmentation method reduced ROI search space by 97.7% for a whole-body scan, or nearly 3 times greater than that achieved by a lung mask. Despite this reduction, we achieved 100% true-positive ROI detection, while also reducing the false-positive (FP) detection rate by >5 times over that achieved with a lung mask. Finally, the method greatly improved PET/CT visualization by eliminating false PET-avid obscurations arising from the heart, bones, and liver. In particular, PET MIP views and fused PET/CT renderings depicted unprecedented clarity of the lesions and neighboring anatomical structures truly relevant to lung-cancer assessment. PMID:25957746
Digimouse: a 3D whole body mouse atlas from CT and cryosection data
NASA Astrophysics Data System (ADS)
Dogdas, Belma; Stout, David; Chatziioannou, Arion F.; Leahy, Richard M.
We have constructed a three-dimensional (3D) whole body mouse atlas from coregistered x-ray CT and cryosection data of a normal nude male mouse. High quality PET, x-ray CT and cryosection images were acquired post mortem from a single mouse placed in a stereotactic frame with fiducial markers visible in all three modalities. The image data were coregistered to a common coordinate system using the fiducials and resampled to an isotropic 0.1 mm voxel size. Using interactive editing tools we segmented and labelled whole brain, cerebrum, cerebellum, olfactory bulbs, striatum, medulla, masseter muscles, eyes, lachrymal glands, heart, lungs, liver, stomach, spleen, pancreas, adrenal glands, kidneys, testes, bladder, skeleton and skin surface. The final atlas consists of the 3D volume, in which the voxels are labelled to define the anatomical structures listed above, with coregistered PET, x-ray CT and cryosection images. To illustrate use of the atlas we include simulations of 3D bioluminescence and PET image reconstruction. Optical scatter and absorption values are assigned to each organ to simulate realistic photon transport within the animal for bioluminescence imaging. Similarly, 511 keV photon attenuation values are assigned to each structure in the atlas to simulate realistic photon attenuation in PET. The Digimouse atlas and data are available at http://neuroimage.usc.edu/Digimouse.html.
Method of Individual Adjustment for 3D CT Analysis: Linear Measurement.
Kim, Dong Kyu; Choi, Dong Hun; Lee, Jeong Woo; Yang, Jung Dug; Chung, Ho Yun; Cho, Byung Chae; Choi, Kang Young
Introduction. We aim to regularize measurement values in three-dimensional (3D) computed tomography (CT) reconstructed images for higher-precision 3D analysis, focusing on length-based 3D cephalometric examinations. Methods. We measure the linear distances between points on different skull models using Vernier calipers (real values). We use 10 differently tilted CT scans for 3D CT reconstruction of the models and measure the same linear distances from the picture archiving and communication system (PACS). In both cases, each measurement is performed three times by three doctors, yielding nine measurements. The real values are compared with the PACS values. Each PACS measurement is revised based on the display field of view (DFOV) values and compared with the real values. Results. The real values and the PACS measurement changes according to tilt value have no significant correlations (p > 0.05). However, significant correlations appear between the real values and DFOV-adjusted PACS measurements (p < 0.001). Hence, we obtain a correlation expression that can yield real physical values from PACS measurements. The DFOV value intervals for various age groups are also verified. Conclusion. Precise confirmation of individual preoperative length and precise analysis of postoperative improvements through 3D analysis is possible, which is helpful for facial-bone-surgery symmetry correction.
Method of Individual Adjustment for 3D CT Analysis: Linear Measurement
Choi, Dong Hun; Lee, Jeong Woo; Yang, Jung Dug; Chung, Ho Yun; Cho, Byung Chae
Introduction. We aim to regularize measurement values in three-dimensional (3D) computed tomography (CT) reconstructed images for higher-precision 3D analysis, focusing on length-based 3D cephalometric examinations. Methods. We measure the linear distances between points on different skull models using Vernier calipers (real values). We use 10 differently tilted CT scans for 3D CT reconstruction of the models and measure the same linear distances from the picture archiving and communication system (PACS). In both cases, each measurement is performed three times by three doctors, yielding nine measurements. The real values are compared with the PACS values. Each PACS measurement is revised based on the display field of view (DFOV) values and compared with the real values. Results. The real values and the PACS measurement changes according to tilt value have no significant correlations (p > 0.05). However, significant correlations appear between the real values and DFOV-adjusted PACS measurements (p < 0.001). Hence, we obtain a correlation expression that can yield real physical values from PACS measurements. The DFOV value intervals for various age groups are also verified. Conclusion. Precise confirmation of individual preoperative length and precise analysis of postoperative improvements through 3D analysis is possible, which is helpful for facial-bone-surgery symmetry correction. PMID:28070517
Microstructure analysis of the secondary pulmonary lobules by 3D synchrotron radiation CT
NASA Astrophysics Data System (ADS)
Fukuoka, Y.; Kawata, Y.; Niki, N.; Umetani, K.; Nakano, Y.; Ohmatsu, H.; Moriyama, N.; Itoh, H.
Recognition of abnormalities related to the lobular anatomy has become increasingly important in the diagnosis and differential diagnosis of lung abnormalities at clinical routines of CT examinations. This paper aims a 3-D microstructural analysis of the pulmonary acinus with isotropic spatial resolution in the range of several micrometers by using micro CT. Previously, we demonstrated the ability of synchrotron radiation micro CT (SRμCT) using offset scan mode in microstructural analysis of the whole part of the secondary pulmonary lobule. In this paper, we present a semiautomatic method to segment the acinar and subacinar airspaces from the secondary pulmonary lobule and to track small vessels running inside alveolar walls in human acinus imaged by the SRμCT. The method beains with and segmentation of the tissues such as pleural surface, interlobular septa, alveola wall, or vessel using a threshold technique and 3-D connected component analysis. 3-D air space are then conustructed separated by tissues and represented branching patterns of airways and airspaces distal to the terminal bronchiole. A graph-partitioning approach isolated acini whose stems are interactively defined as the terminal bronchiole in the secondary pulmonary lobule. Finally, we performed vessel tracking using a non-linear sate space which captures both smoothness of the trajectories and intensity coherence along vessel orientations. Results demonstrate that the proposed method can extract several acinar airspaces from the 3-D SRμCT image of secondary pulmonary lobule and that the extracted acinar airspace enable an accurate quantitative description of the anatomy of the human acinus for interpretation of the basic unit of pulmonary structure and function.
A fast 3D region growing approach for CT angiography applications
NASA Astrophysics Data System (ADS)
Ye, Zhen; Lin, Zhongmin; Lu, Cheng-chang
Region growing is one of the most popular methods for low-level image segmentation. Many researches on region growing have focused on the definition of the homogeneity criterion or growing and merging criterion. However, one disadvantage of conventional region growing is redundancy. It requires a large memory usage, and the computation-efficiency is very low especially for 3D images. To overcome this problem, a non-recursive single-pass 3D region growing algorithm named SymRG is implemented and successfully applied to 3D CT angiography (CTA) applications for vessel segmentation and bone removal. The method consists of three steps: segmenting one-dimensional regions of each row; doing region merging to adjacent rows to obtain the region segmentation of each slice; and doing region merging to adjacent slices to obtain the final region segmentation of 3D images. To improve the segmentation speed for very large volume 3D CTA images, this algorithm is applied repeatedly to newly updated local cubes. The next new cube can be estimated by checking isolated segmented regions on all 6 faces of the current local cube. This local non-recursive 3D region-growing algorithm is memory-efficient and computation-efficient. Clinical testings of this algorithm on Brain CTA show this technique could effectively remove whole skull, most of the bones on the skull base, and reveal the cerebral vascular structures clearly.
NASA Astrophysics Data System (ADS)
Halabe, Udaya B.; Pyakurel, Sandeep
There has been a lack of an effective NDE technique to locate internal defects within wooden logs. The few available elastic wave propagation based techniques are limited to predicting E values. Other techniques such as X-rays have not been very successful in detecting internal defects in logs. If defects such as embedded metals could be identified before the sawing process, the saw mills could significantly increase their production by reducing the probability of damage to the saw blade and the associated downtime and the repair cost. Also, if the internal defects such as knots and decayed areas could be identified in logs, the sawing blade can be oriented to exclude the defective portion and optimize the volume of high valued lumber that can be obtained from the logs. In this research, GPR has been successfully used to locate internal defects (knots, decays and embedded metals) within the logs. This paper discusses GPR imaging and mapping of the internal defects using both 2D and 3D interpretation methodology. Metal pieces were inserted in a log and the reflection patterns from these metals were interpreted from the radargrams acquired using 900 MHz antenna. Also, GPR was able to accurately identify the location of knots and decays. Scans from several orientations of the log were collected to generate 3D cylindrical volume. The actual location of the defects showed good correlation with the interpreted defects in the 3D volume. The time/depth slices from 3D cylindrical volume data were useful in understanding the extent of defects inside the log.
"High-precision, reconstructed 3D model" of skull scanned by conebeam CT: Reproducibility verified using CAD/CAM data.
Katsumura, Seiko; Sato, Keita; Ikawa, Tomoko; Yamamura, Keiko; Ando, Eriko; Shigeta, Yuko; Ogawa, Takumi
Computed tomography (CT) scanning has recently been introduced into forensic medicine and dentistry. However, the presence of metal restorations in the dentition can adversely affect the quality of three-dimensional reconstruction from CT scans. In this study, we aimed to evaluate the reproducibility of a "high-precision, reconstructed 3D model" obtained from a conebeam CT scan of dentition, a method that might be particularly helpful in forensic medicine. We took conebeam CT and helical CT images of three dry skulls marked with 47 measuring points; reconstructed three-dimensional images; and measured the distances between the points in the 3D images with a computer-aided design/computer-aided manufacturing (CAD/CAM) marker. We found that in comparison with the helical CT, conebeam CT is capable of reproducing measurements closer to those obtained from the actual samples. In conclusion, our study indicated that the image-reproduction from a conebeam CT scan was more accurate than that from a helical CT scan. Furthermore, the "high-precision reconstructed 3D model" facilitates reliable visualization of full-sized oral and maxillofacial regions in both helical and conebeam CT scans.
High-Resolution Imaged-Based 3D Reconstruction Combined with X-Ray CT Data Enables Comprehensive Non-Destructive Documentation and Targeted Research of Astromaterials
NASA Technical Reports Server (NTRS)
Blumenfeld, E. H.; Evans, C. A.; Oshel, E. R.; Liddle, D. A.; Beaulieu, K.; Zeigler, R. A.; Righter, K.; Hanna, R. D.; Ketcham, R. A.
Providing web-based data of complex and sensitive astromaterials (including meteorites and lunar samples) in novel formats enhances existing preliminary examination data on these samples and supports targeted sample requests and analyses. We have developed and tested a rigorous protocol for collecting highly detailed imagery of meteorites and complex lunar samples in non-contaminating environments. These data are reduced to create interactive 3D models of the samples. We intend to provide these data as they are acquired on NASA's Astromaterials Acquisition and Curation website at http://curator.jsc.nasa.gov/.
3D documentation and visualization of external injury findings by integration of simple photography in CT/MRI data sets (IprojeCT).
Campana, Lorenzo; Breitbeck, Robert; Bauer-Kreuz, Regula; Buck, Ursula
This study evaluated the feasibility of documenting patterned injury using three dimensions and true colour photography without complex 3D surface documentation methods. This method is based on a generated 3D surface model using radiologic slice images (CT) while the colour information is derived from photographs taken with commercially available cameras. The external patterned injuries were documented in 16 cases using digital photography as well as highly precise photogrammetry-supported 3D structured light scanning. The internal findings of these deceased were recorded using CT and MRI. For registration of the internal with the external data, two different types of radiographic markers were used and compared. The 3D surface model generated from CT slice images was linked with the photographs, and thereby digital true-colour 3D models of the patterned injuries could be created (Image projection onto CT/IprojeCT). In addition, these external models were merged with the models of the somatic interior. We demonstrated that 3D documentation and visualization of external injury findings by integration of digital photography in CT/MRI data sets is suitable for the 3D documentation of individual patterned injuries to a body. Nevertheless, this documentation method is not a substitution for photogrammetry and surface scanning, especially when the entire bodily surface is to be recorded in three dimensions including all external findings, and when precise data is required for comparing highly detailed injury features with the injury-inflicting tool.
Imaging hypoxia using 3D photoacoustic spectroscopy
NASA Astrophysics Data System (ADS)
Stantz, Keith M.
Purpose: The objective is to develop a multivariate in vivo hemodynamic model of tissue oxygenation (MiHMO2) based on 3D photoacoustic spectroscopy. Introduction: Low oxygen levels, or hypoxia, deprives cancer cells of oxygen and confers resistance to irradiation, some chemotherapeutic drugs, and oxygen-dependent therapies (phototherapy) leading to treatment failure and poor disease-free and overall survival. For example, clinical studies of patients with breast carcinomas, cervical cancer, and head and neck carcinomas (HNC) are more likely to suffer local reoccurrence and metastasis if their tumors are hypoxic. A novel method to non invasively measure tumor hypoxia, identify its type, and monitor its heterogeneity is devised by measuring tumor hemodynamics, MiHMO2. Material and Methods: Simulations are performed to compare tumor pO2 levels and hypoxia based on physiology - perfusion, fractional plasma volume, fractional cellular volume - and its hemoglobin status - oxygen saturation and hemoglobin concentration - based on in vivo measurements of breast, prostate, and ovarian tumors. Simulations of MiHMO2 are performed to assess the influence of scanner resolutions and different mathematic models of oxygen delivery. Results: Sensitivity of pO2 and hypoxic fraction to photoacoustic scanner resolution and dependencies on model complexity will be presented using hemodynamic parameters for different tumors. Conclusions: Photoacoustic CT spectroscopy provides a unique ability to monitor hemodynamic and cellular physiology in tissue, which can be used to longitudinally monitor tumor oxygenation and its response to anti-angiogenic therapies.
Photogrammetric 3D reconstruction using mobile imaging
NASA Astrophysics Data System (ADS)
Fritsch, Dieter; Syll, Miguel
In our paper we demonstrate the development of an Android Application (AndroidSfM) for photogrammetric 3D reconstruction that works on smartphones and tablets likewise. The photos are taken with mobile devices, and can thereafter directly be calibrated using standard calibration algorithms of photogrammetry and computer vision, on that device. Due to still limited computing resources on mobile devices, a client-server handshake using Dropbox transfers the photos to the sever to run AndroidSfM for the pose estimation of all photos by Structure-from-Motion and, thereafter, uses the oriented bunch of photos for dense point cloud estimation by dense image matching algorithms. The result is transferred back to the mobile device for visualization and ad-hoc on-screen measurements.
3D imaging reconstruction and impacted third molars: case reports
Tuzi, Andrea; Di Bari, Roberto; Cicconetti, Andrea
Summary There is a debate in the literature about the need for Computed Tomagraphy (CT) before removing third molars, even if positive radiographic signs are present. In few cases, the third molar is so close to the inferior alveolar nerve that its extraction might expose patients to the risk of post-operative neuro-sensitive alterations of the skin and the mucosa of the homolateral lower lip and chin. Thus, the injury of the inferior alveolar nerve may represent a serious, though infrequent, neurologic complication in the surgery of the third molars rendering necessary a careful pre-operative evaluation of their anatomical relationship with the inferior alveolar nerve by means of radiographic imaging techniques. This contribution presents two case reports showing positive radiographic signs, which are the hallmarks of a possible close relationship between the inferior alveolar nerve and the third molars. We aim at better defining the relationship between third molars and the mandibular canal using Dental CT Scan, DICOM image acquisition and 3D reconstruction with a dedicated software. By our study we deduce that 3D images are not indispensable, but they can provide a very agreeable assistance in the most complicated cases. PMID:23386934
Ames Lab 101: Real-Time 3D Imaging
Zhang, Song
Ames Laboratory scientist Song Zhang explains his real-time 3-D imaging technology. The technique can be used to create high-resolution, real-time, precise, 3-D images for use in healthcare, security, and entertainment applications.
Ames Lab 101: Real-Time 3D Imaging
Zhang, Song
Ames Laboratory scientist Song Zhang explains his real-time 3-D imaging technology. The technique can be used to create high-resolution, real-time, precise, 3-D images for use in healthcare, security, and entertainment applications.
Needle placement for piriformis injection using 3-D imaging.
Clendenen, Steven R; Candler, Shawn A; Osborne, Michael D; Palmer, Scott C; Duench, Stephanie; Glynn, Laura; Ghazi, Salim M
Piriformis syndrome is a pain syndrome originating in the buttock and is attributed to 6% - 8% of patients referred for the treatment of back and leg pain. The treatment for piriformis syndrome using fluoroscopy, computed tomography (CT), electromyography (EMG), and ultrasound (US) has become standard practice. The treatment of Piriformis Syndrome has evolved to include fluoroscopy and EMG with CT guidance. We present a case study of 5 successful piriformis injections using 3-D computer-assisted electromagnet needle tracking coupled with ultrasound. A 6-degree of freedom electromagnetic position tracker was attached to the ultrasound probe that allowed the system to detect the position and orientation of the probe in the magnetic field. The tracked ultrasound probe was used to find the posterior superior iliac spine. Subsequently, 3 points were captured to register the ultrasound image with the CT or magnetic resonance image scan. Moreover, after the registration was obtained, the navigation system visualized the tracked needle relative to the CT scan in real-time using 2 orthogonal multi-planar reconstructions centered at the tracked needle tip. Conversely, a recent study revealed that fluoroscopically guided injections had 30% accuracy compared to ultrasound guided injections, which tripled the accuracy percentage. This novel technique exhibited an accurate needle guidance injection precision of 98% while advancing to the piriformis muscle and avoiding the sciatic nerve. The mean (± SD) procedure time was 19.08 (± 4.9) minutes. This technique allows for electromagnetic instrument tip tracking with real-time 3-D guidance to the selected target. As with any new technique, a learning curve is expected; however, this technique could offer an alternative, minimizing radiation exposure.
[3D display of sequential 2D medical images].
Lu, Yisong; Chen, Yazhu
A detailed review is given in this paper on various current 3D display methods for sequential 2D medical images and the new development in 3D medical image display. True 3D display, surface rendering, volume rendering, 3D texture mapping and distributed collaborative rendering are discussed in depth. For two kinds of medical applications: Real-time navigation system and high-fidelity diagnosis in computer aided surgery, different 3D display methods are presented.
Performance of a commercial optical CT scanner and polymer gel dosimeters for 3-D dose verification.
Xu, Y; Wuu, Cheng-Shie; Maryanski, Marek J
Performance analysis of a commercial three-dimensional (3-D) dose mapping system based on optical CT scanning of polymer gels is presented. The system consists of BANG 3 polymer gels (MGS Research, Inc., Madison, CT), OCTOPUS laser CT scanner (MGS Research, Inc., Madison, CT), and an in-house developed software for optical CT image reconstruction and 3-D dose distribution comparison between the gel, film measurements and the radiation therapy treatment plans. Various sources of image noise (digitization, electronic, optical, and mechanical) generated by the scanner as well as optical uniformity of the polymer gel are analyzed. The performance of the scanner is further evaluated in terms of the reproducibility of the data acquisition process, the uncertainties at different levels of reconstructed optical density per unit length and the effects of scanning parameters. It is demonstrated that for BANG 3 gel phantoms held in cylindrical plastic containers, the relative dose distribution can be reproduced by the scanner with an overall uncertainty of about 3% within approximately 75% of the radius of the container. In regions located closer to the container wall, however, the scanner generates erroneous optical density values that arise from the reflection and refraction of the laser rays at the interface between the gel and the container. The analysis of the accuracy of the polymer gel dosimeter is exemplified by the comparison of the gel/OCT-derived dose distributions with those from film measurements and a commercial treatment planning system (Cadplan, Varian Corporation, Palo Alto, CA) for a 6 cm x 6 cm single field of 6 MV x rays and a 3-D conformal radiotherapy (3DCRT) plan. The gel measurements agree with the treatment plans and the film measurements within the "3%-or-2 mm" criterion throughout the usable, artifact-free central region of the gel volume. Discrepancies among the three data sets are analyzed.
Progress in 3D imaging and display by integral imaging
NASA Astrophysics Data System (ADS)
Martinez-Cuenca, R.; Saavedra, G.; Martinez-Corral, M.; Pons, A.; Javidi, B.
Three-dimensionality is currently considered an important added value in imaging devices, and therefore the search for an optimum 3D imaging and display technique is a hot topic that is attracting important research efforts. As main value, 3D monitors should provide the observers with different perspectives of a 3D scene by simply varying the head position. Three-dimensional imaging techniques have the potential to establish a future mass-market in the fields of entertainment and communications. Integral imaging (InI), which can capture true 3D color images, has been seen as the right technology to 3D viewing to audiences of more than one person. Due to the advanced degree of development, InI technology could be ready for commercialization in the coming years. This development is the result of a strong research effort performed along the past few years by many groups. Since Integral Imaging is still an emerging technology, the first aim of the "3D Imaging and Display Laboratory" at the University of Valencia, has been the realization of a thorough study of the principles that govern its operation. Is remarkable that some of these principles have been recognized and characterized by our group. Other contributions of our research have been addressed to overcome some of the classical limitations of InI systems, like the limited depth of field (in pickup and in display), the poor axial and lateral resolution, the pseudoscopic-to-orthoscopic conversion, the production of 3D images with continuous relief, or the limited range of viewing angles of InI monitors.
3D segmentation of lung CT data with graph-cuts: analysis of parameter sensitivities
NASA Astrophysics Data System (ADS)
Cha, Jung won; Dunlap, Neal; Wang, Brian; Amini, Amir
Lung boundary image segmentation is important for many tasks including for example in development of radiation treatment plans for subjects with thoracic malignancies. In this paper, we describe a method and parameter settings for accurate 3D lung boundary segmentation based on graph-cuts from X-ray CT data1. Even though previously several researchers have used graph-cuts for image segmentation, to date, no systematic studies have been performed regarding the range of parameter that give accurate results. The energy function in the graph-cuts algorithm requires 3 suitable parameter settings: K, a large constant for assigning seed points, c, the similarity coefficient for n-links, and λ, the terminal coefficient for t-links. We analyzed the parameter sensitivity with four lung data sets from subjects with lung cancer using error metrics. Large values of K created artifacts on segmented images, and relatively much larger value of c than the value of λ influenced the balance between the boundary term and the data term in the energy function, leading to unacceptable segmentation results. For a range of parameter settings, we performed 3D image segmentation, and in each case compared the results with the expert-delineated lung boundaries. We used simple 6-neighborhood systems for n-link in 3D. The 3D image segmentation took 10 minutes for a 512x512x118 ~ 512x512x190 lung CT image volume. Our results indicate that the graph-cuts algorithm was more sensitive to the K and λ parameter settings than to the C parameter and furthermore that amongst the range of parameters tested, K=5 and λ=0.5 yielded good results.
Description of patellar movement by 3D parameters obtained from dynamic CT acquisition
NASA Astrophysics Data System (ADS)
de Sá Rebelo, Marina; Moreno, Ramon Alfredo; Gobbi, Riccardo Gomes; Camanho, Gilberto Luis; de Ávila, Luiz Francisco Rodrigues; Demange, Marco Kawamura; Pecora, Jose Ricardo; Gutierrez, Marco Antonio
The patellofemoral joint is critical in the biomechanics of the knee. The patellofemoral instability is one condition that generates pain, functional impairment and often requires surgery as part of orthopedic treatment. The analysis of the patellofemoral dynamics has been performed by several medical image modalities. The clinical parameters assessed are mainly based on 2D measurements, such as the patellar tilt angle and the lateral shift among others. Besides, the acquisition protocols are mostly performed with the leg laid static at fixed angles. The use of helical multi slice CT scanner can allow the capture and display of the joint's movement performed actively by the patient. However, the orthopedic applications of this scanner have not yet been standardized or widespread. In this work we present a method to evaluate the biomechanics of the patellofemoral joint during active contraction using multi slice CT images. This approach can greatly improve the analysis of patellar instability by displaying the physiology during muscle contraction. The movement was evaluated by computing its 3D displacements and rotations from different knee angles. The first processing step registered the images in both angles based on the femuŕs position. The transformation matrix of the patella from the images was then calculated, which provided the rotations and translations performed by the patella from its position in the first image to its position in the second image. Analysis of these parameters for all frames provided real 3D information about the patellar displacement.
Infrastructure for 3D Imaging Test Bed
analysis. (c.) Real time detection & analysis of human gait: using a video camera we capture walking human silhouette for pattern modeling and gait ... analysis . Fig. 5 shows the scanning result result that is fed into a Geo-magic software tool for 3D meshing. Fig. 5: 3D scanning result In
[3D virtual imaging of the upper airways].
Ferretti, G; Coulomb, M
The different three dimensional reconstructions of the upper airways that can be obtained with spiral computed tomograpy (CT) are presented here. The parameters indispensable to achieve as real as possible spiral CT images are recalled together with the advantages and disadvantages of the different techniues. Multislice reconstruction (MSR) produces slices in different planes of space with the high contrast of CT slices. They provide information similar to that obtained for the rare indications for thoracic MRI. Thick slice reconstructions with maximum intensity projection (MIP) or minimum intensity projection (minIP) give projection views where the contrast can be modified by selecting the more dense (MIP) or less dense (minIP) voxels. They find their application in the exploration of the upper airways. Surface and volume external 3D reconstructions can be obtained. They give an overall view of the upper airways, similar to a bronchogram. Virtual endoscopy reproduces real endoscopic images but cannot provide information on the aspect of the mucosa or biopsy specimens. It offers possible applications for preparing, guiding and controlling interventional fibroscopy procedures.
Quantitative 3D Optical Imaging: Applications in Dosimetry and Biophysics
NASA Astrophysics Data System (ADS)
Thomas, Andrew Stephen
Optical-CT has been shown to be a potentially useful imaging tool for the two very different spheres of biologists and radiation therapy physicists, but it has yet to live up to that potential. In radiation therapy, researchers have used optical-CT for the readout of 3D dosimeters, but it is yet to be a clinically relevant tool as the technology is too slow to be considered practical. Biologists have used the technique for structural imaging, but have struggled with emission tomography as the reality of photon attenuation for both excitation and emission have made the images quantitatively irrelevant. Dosimetry. The DLOS (Duke Large field of view Optical-CT Scanner) was designed and constructed to make 3D dosimetry utilizing optical-CT a fast and practical tool while maintaining the accuracy of readout of the previous, slower readout technologies. Upon construction/optimization/implementation of several components including a diffuser, band pass filter, registration mount & fluid filtration system the dosimetry system provides high quality data comparable to or exceeding that of commercial products. In addition, a stray light correction algorithm was tested and implemented. The DLOS in combination with the 3D dosimeter it was designed for, PREAGETM, then underwent rigorous commissioning and benchmarking tests validating its performance against gold standard data including a set of 6 irradiations. DLOS commissioning tests resulted in sub-mm isotropic spatial resolution (MTF >0.5 for frequencies of 1.5lp/mm) and a dynamic range of ˜60dB. Flood field uniformity was 10% and stable after 45minutes. Stray light proved to be small, due to telecentricity, but even the residual can be removed through deconvolution. Benchmarking tests showed the mean 3D passing gamma rate (3%, 3mm, 5% dose threshold) over the 6 benchmark data sets was 97.3% +/- 0.6% (range 96%-98%) scans totaling ˜10 minutes, indicating excellent ability to perform 3D dosimetry while improving the speed of
Radon transform based automatic metal artefacts generation for 3D threat image projection
NASA Astrophysics Data System (ADS)
Megherbi, Najla; Breckon, Toby P.; Flitton, Greg T.; Mouton, Andre
Threat Image Projection (TIP) plays an important role in aviation security. In order to evaluate human security screeners in determining threats, TIP systems project images of realistic threat items into the images of the passenger baggage being scanned. In this proof of concept paper, we propose a 3D TIP method which can be integrated within new 3D Computed Tomography (CT) screening systems. In order to make the threat items appear as if they were genuinely located in the scanned bag, appropriate CT metal artefacts are generated in the resulting TIP images according to the scan orientation, the passenger bag content and the material of the inserted threat items. This process is performed in the projection domain using a novel methodology based on the Radon Transform. The obtained results using challenging 3D CT baggage images are very promising in terms of plausibility and realism.
Assessing 3D tunnel position in ACL reconstruction using a novel single image 3D-2D registration
NASA Astrophysics Data System (ADS)
Kang, X.; Yau, W. P.; Otake, Y.; Cheung, P. Y. S.; Hu, Y.; Taylor, R. H.
The routinely used procedure for evaluating tunnel positions following anterior cruciate ligament (ACL) reconstructions based on standard X-ray images is known to pose difficulties in terms of obtaining accurate measures, especially in providing three-dimensional tunnel positions. This is largely due to the variability in individual knee joint pose relative to X-ray plates. Accurate results were reported using postoperative CT. However, its extensive usage in clinical routine is hampered by its major requirement of having CT scans of individual patients, which is not available for most ACL reconstructions. These difficulties are addressed through the proposed method, which aligns a knee model to X-ray images using our novel single-image 3D-2D registration method and then estimates the 3D tunnel position. In the proposed method, the alignment is achieved by using a novel contour-based 3D-2D registration method wherein image contours are treated as a set of oriented points. However, instead of using some form of orientation weighting function and multiplying it with a distance function, we formulate the 3D-2D registration as a probability density estimation using a mixture of von Mises-Fisher-Gaussian (vMFG) distributions and solve it through an expectation maximization (EM) algorithm. Compared with the ground-truth established from postoperative CT, our registration method in an experiment using a plastic phantom showed accurate results with errors of (-0.43°+/-1.19°, 0.45°+/-2.17°, 0.23°+/-1.05°) and (0.03+/-0.55, -0.03+/-0.54, -2.73+/-1.64) mm. As for the entry point of the ACL tunnel, one of the key measurements, it was obtained with high accuracy of 0.53+/-0.30 mm distance errors.
3D Soil Images Structure Quantification using Relative Entropy
NASA Astrophysics Data System (ADS)
Tarquis, A. M.; Gonzalez-Nieto, P. L.; Bird, N. R. A.
Soil voids manifest the cumulative effect of local pedogenic processes and ultimately influence soil behavior - especially as it pertains to aeration and hydrophysical properties. Because of the relatively weak attenuation of X-rays by air, compared with liquids or solids, non-disruptive CT scanning has become a very attractive tool for generating three-dimensional imagery of soil voids. One of the main steps involved in this analysis is the thresholding required to transform the original (greyscale) images into the type of binary representation (e.g., pores in white, solids in black) needed for fractal analysis or simulation with Lattice-Boltzmann models (Baveye et al., 2010). The objective of the current work is to apply an innovative approach to quantifying soil voids and pore networks in original X-ray CT imagery using Relative Entropy (Bird et al., 2006; Tarquis et al., 2008). These will be illustrated using typical imagery representing contrasting soil structures. Particular attention will be given to the need to consider the full 3D context of the CT imagery, as well as scaling issues, in the application and interpretation of this index.
Deformable 3D-2D registration for CT and its application to low dose tomographic fluoroscopy
NASA Astrophysics Data System (ADS)
Flach, Barbara; Brehm, Marcus; Sawall, Stefan; Kachelrieß, Marc
Many applications in medical imaging include image registration for matching of images from the same or different modalities. In the case of full data sampling, the respective reconstructed images are usually of such a good image quality that standard deformable volume-to-volume (3D-3D) registration approaches can be applied. But research in temporal-correlated image reconstruction and dose reductions increases the number of cases where rawdata are available from only few projection angles. Here, deteriorated image quality leads to non-acceptable deformable volume-to-volume registration results. Therefore a registration approach is required that is robust against a decreasing number of projections defining the target position. We propose a deformable volume-to-rawdata (3D-2D) registration method that aims at finding a displacement vector field maximizing the alignment of a CT volume and the acquired rawdata based on the sum of squared differences in rawdata domain. The registration is constrained by a regularization term in accordance with a fluid-based diffusion. Both cost function components, the rawdata fidelity and the regularization term, are optimized in an alternating manner. The matching criterion is optimized by a conjugate gradient descent for nonlinear functions, while the regularization is realized by convolution of the vector fields with Gaussian kernels. We validate the proposed method and compare it to the demons algorithm, a well-known 3D-3D registration method. The comparison is done for a range of 4-60 target projections using datasets from low dose tomographic fluoroscopy as an application example. The results show a high correlation to the ground truth target position without introducing artifacts even in the case of very few projections. In particular the matching in the rawdata domain is improved compared to the 3D-3D registration for the investigated range. The proposed volume-to-rawdata registration increases the robustness regarding sparse
Deformable 3D-2D registration for CT and its application to low dose tomographic fluoroscopy.
Flach, Barbara; Brehm, Marcus; Sawall, Stefan; Kachelrieß, Marc
Many applications in medical imaging include image registration for matching of images from the same or different modalities. In the case of full data sampling, the respective reconstructed images are usually of such a good image quality that standard deformable volume-to-volume (3D-3D) registration approaches can be applied. But research in temporal-correlated image reconstruction and dose reductions increases the number of cases where rawdata are available from only few projection angles. Here, deteriorated image quality leads to non-acceptable deformable volume-to-volume registration results. Therefore a registration approach is required that is robust against a decreasing number of projections defining the target position. We propose a deformable volume-to-rawdata (3D-2D) registration method that aims at finding a displacement vector field maximizing the alignment of a CT volume and the acquired rawdata based on the sum of squared differences in rawdata domain. The registration is constrained by a regularization term in accordance with a fluid-based diffusion. Both cost function components, the rawdata fidelity and the regularization term, are optimized in an alternating manner. The matching criterion is optimized by a conjugate gradient descent for nonlinear functions, while the regularization is realized by convolution of the vector fields with Gaussian kernels. We validate the proposed method and compare it to the demons algorithm, a well-known 3D-3D registration method. The comparison is done for a range of 4-60 target projections using datasets from low dose tomographic fluoroscopy as an application example. The results show a high correlation to the ground truth target position without introducing artifacts even in the case of very few projections. In particular the matching in the rawdata domain is improved compared to the 3D-3D registration for the investigated range. The proposed volume-to-rawdata registration increases the robustness regarding sparse
3D patient-specific model of the tibia from CT for orthopedic use
González-Carbonell, Raide A.; Ortiz-Prado, Armando; Jacobo-Armendáriz, Victor H.; Cisneros-Hidalgo, Yosbel A.; Alpízar-Aguirre, Armando
Objectives 3D patient-specific model of the tibia is used to determine the torque needed to initialize the tibial torsion correction. Methods The finite elements method is used in the biomechanical modeling of tibia. The geometric model of the tibia is obtained from CT images. The tibia is modeled as an anisotropic material with non-homogeneous mechanical properties. Conclusions The maximum stress is located in the shaft of tibia diaphysis. With both meshes are obtained similar results of stresses and displacements. For this patient-specific model, the torque must be greater than 30 Nm to initialize the correction of tibial torsion deformity. PMID:25829755
Development of 3D-CT System Using MIRRORCLE-6X
NASA Astrophysics Data System (ADS)
Sasaki, M.; Takaku, J.; Hirai, T.; Yamada, H.
The technique of computed tomography (CT) has been used in various fields, such as medical, non-destructive testing (NDT), baggage checking, etc. A 3D-CT system based on the portable synchrotron "MIRRORCLE"-series will be a novel instrument for these fields. The hard x-rays generated from the "MIRRORCLE" have a wide energy spectrum. Light and thin materials create absorption and refraction contrast in x-ray images by the lower energy component (< 60 keV), and heavy and thick materials create absorption contrast by the higher energy component. In addition, images with higher resolutions can be obtained using "MIRRORCLE" with a small source size of micron order. Thus, high resolution 3D-CT images of specimens containing both light and heavy materials can be obtained using "MIRRORCLE" and a 2D-detector with a wide dynamic range. In this paper, the development and output of a 3D-CT system using the "MIRRORCLE-6X" and a flat panel detector are reported. A 3D image of a piece of concrete was obtained. The detector was a flat panel detector (VARIAN, PAXSCAN2520) with 254 μm pixel size. The object and the detector were set at 50 cm and 250 cm respectively from the x-ray source, so that the magnification was 5x. The x-ray source was a 50 μm Pt rod. The rotation stage and the detector were remote-controlled using a computer, which was originally created using LabView and Visual Basic software. The exposure time was about 20 minutes. The reconstruction calculation was based on the Feldkamp algorithm, and the pixel size was 50 μm. We could observe sub-mm holes and density differences in the object. Thus, the "MIRRORCLE-CV" with 1MeV electron energy, which has same x-ray generation principles, will be an excellent x-ray source for medical diagnostics and NDT.
3D x-ray reconstruction using lightfield imaging
NASA Astrophysics Data System (ADS)
Saha, Sajib; Tahtali, Murat; Lambert, Andrew; Pickering, Mark R.
Existing Computed Tomography (CT) systems require full 360° rotation projections. Using the principles of lightfield imaging, only 4 projections under ideal conditions can be sufficient when the object is illuminated with multiple-point Xray sources. The concept was presented in a previous work with synthetically sampled data from a synthetic phantom. Application to real data requires precise calibration of the physical set up. This current work presents the calibration procedures along with experimental findings for the reconstruction of a physical 3D phantom consisting of simple geometric shapes. The crucial part of this process is to determine the effective distances of the X-ray paths, which are not possible or very difficult by direct measurements. Instead, they are calculated by tracking the positions of fiducial markers under prescribed source and object movements. Iterative algorithms are used for the reconstruction. Customized backprojection is used to ensure better initial guess for the iterative algorithms to start with.
Research of range-gated 3D imaging technology
NASA Astrophysics Data System (ADS)
Yang, Haitao; Zhao, Hongli; Youchen, Fan
Laser image data-based target recognition technology is one of the key technologies of laser active imaging systems. This paper discussed the status quo of 3-D imaging development at home and abroad, analyzed the current technological bottlenecks, and built a prototype of range-gated systems to obtain a set of range-gated slice images, and then constructed the 3-D images of the target by binary method and centroid method, respectively, and by constructing different numbers of slice images explored the relationship between the number of images and the reconstruction accuracy in the 3-D image reconstruction process. The experiment analyzed the impact of two algorithms, binary method and centroid method, on the results of 3-D image reconstruction. In the binary method, a comparative analysis was made on the impact of different threshold values on the results of reconstruction, where 0.1, 0.2, 0.3 and adaptive threshold values were selected for 3-D reconstruction of the slice images. In the centroid method, 15, 10, 6, 3, and 2 images were respectively used to realize 3-D reconstruction. Experimental results showed that with the same number of slice images, the accuracy of centroid method was higher than the binary algorithm, and the binary algorithm had a large dependence on the selection of threshold; with the number of slice images dwindling, the accuracy of images reconstructed by centroid method continued to reduce, and at least three slice images were required in order to obtain one 3-D image.
3D cardiac motion reconstruction from CT data and tagged MRI.
Wang, Xiaoxu; Mihalef, Viorel; Qian, Zhen; Voros, Szilard; Metaxas, Dimitris
In this paper we present a novel method for left ventricle (LV) endocardium motion reconstruction using high resolution CT data and tagged MRI. High resolution CT data provide anatomic details on the LV endocardial surface, such as the papillary muscle and trabeculae carneae. Tagged MRI provides better time resolution. The combination of these two imaging techniques can give us better understanding on left ventricle motion. The high resolution CT images are segmented with mean shift method and generate the LV endocardium mesh. The meshless deformable model built with high resolution endocardium surface from CT data fit to the tagged MRI of the same phase. 3D deformation of the myocardium is computed with the Lagrangian dynamics and local Laplacian deformation. The segmented inner surface of left ventricle is compared with the heart inner surface picture and show high agreement. The papillary muscles are attached to the inner surface with roots. The free wall of the left ventricle inner surface is covered with trabeculae carneae. The deformation of the heart wall and the papillary muscle in the first half of the cardiac cycle is presented. The motion reconstruction results are very close to the live heart video.
3D Imaging by Mass Spectrometry: A New Frontier
Seeley, Erin H.; Caprioli, Richard M.
Summary Imaging mass spectrometry can generate three-dimensional volumes showing molecular distributions in an entire organ or animal through registration and stacking of serial tissue sections. Here we review the current state of 3D imaging mass spectrometry as well as provide insights and perspectives on the process of generating 3D mass spectral data along with a discussion of the process necessary to generate a 3D image volume. PMID:22276611
3D Dose Verification Using Tomotherapy CT Detector Array
Sheng Ke; Jones, Ryan; Yang Wensha; Saraiya, Siddharth; Schneider, Bernard; Chen Quan; Sobering, Geoff; Olivera, Gustavo; Read, Paul
Purpose: To evaluate a three-dimensional dose verification method based on the exit dose using the onboard detector of tomotherapy. Methods and Materials: The study included 347 treatment fractions from 24 patients, including 10 prostate, 5 head and neck (HN), and 9 spinal stereotactic body radiation therapy (SBRT) cases. Detector sonograms were retrieved and back-projected to calculate entrance fluence, which was then forward-projected on the CT images to calculate the verification dose, which was compared with ion chamber and film measurement in the QA plans and with the planning dose in patient plans. Results: Root mean square (RMS) errors of 2.0%, 2.2%, and 2.0% were observed comparing the dose verification (DV) and the ion chamber measured point dose in the phantom plans for HN, prostate, and spinal SBRT patients, respectively. When cumulative dose in the entire treatment is considered, for HN patients, the error of the mean dose to the planning target volume (PTV) varied from 1.47% to 5.62% with a RMS error of 3.55%. For prostate patients, the error of the mean dose to the prostate target volume varied from -5.11% to 3.29%, with a RMS error of 2.49%. The RMS error of maximum doses to the bladder and the rectum were 2.34% (-4.17% to 2.61%) and 2.64% (-4.54% to 3.94%), respectively. For the nine spinal SBRT patients, the RMS error of the minimum dose to the PTV was 2.43% (-5.39% to 2.48%). The RMS error of maximum dose to the spinal cord was 1.05% (-2.86% to 0.89%). Conclusions: An excellent agreement was observed between the measurement and the verification dose. In the patient treatments, the agreement in doses to the majority of PTVs and organs at risk is within 5% for the cumulative treatment course doses. The dosimetric error strongly depends on the error in multileaf collimator leaf opening time with a sensitivity correlating to the gantry rotation period.
Development of a 3D CT-scanner using a cone beam and video-fluoroscopic system.
Endo, M; Yoshida, K; Kamagata, N; Satoh, K; Okazaki, T; Hattori, Y; Kobayashi, S; Jimbo, M; Kusakabe, M; Tateno, Y
We describe the design and implementation of a system that acquires three-dimensional (3D) data of high-contrast objects such as bone, lung, and blood vessels (enhanced by contrast agent). This 3D computed tomography (CT) system is based on a cone beam and video-fluoroscopic system and yields data that is amenable to 3D image processing. An X-ray tube and a large area two-dimensional detector were mounted on a single frame and rotated around objects in 12 seconds. The large area detector consisted of a fluorescent plate and a charge coupled device (CCD) video camera. While the X-ray tube was rotated around the object, a pulsed X-ray was generated (30 pulses per second) and 360 projected images were collected in a 12-second scan. A 256 x 256 x 256 matrix image was reconstructed using a high-speed parallel processor. Reconstruction required approximately 6 minutes. Two volunteers underwent scans of the head or chest. High-contrast objects such as bronchial, vascular, and mediastinal structures in the thorax, or bones and air cavities in the head were delineated in a "real" 3D format. Our 3D CT-scanner appears to produce data useful for clinical imaging and 3D image processing.
Value of 3-D CT in classifying acetabular fractures during orthopedic residency training.
Garrett, Jeffrey; Halvorson, Jason; Carroll, Eben; Webb, Lawrence X
The complex anatomy of the pelvis and acetabulum have historically made classification and interpretation of acetabular fractures difficult for orthopedic trainees. The addition of 3-dimensional (3-D) computed tomography (CT) scan has gained popularity in preoperative planning, identification, and education of acetabular fractures given their complexity. Therefore, the authors examined the value of 3-D CT compared with conventional radiography in classifying acetabular fractures at different levels of orthopedic training. Their hypothesis was that 3-D CT would improve correct identification of acetabular fractures compared with conventional radiography.The classic Letournel fracture pattern classification system was presented in quiz format to 57 orthopedic residents and 20 fellowship-trained orthopedic traumatologists. A case consisted of (1) plain radiographs and 2-dimensional axial CT scans or (2) 3-D CT scans. All levels of training showed significant improvement in classifying acetabular fractures with 3-D vs 2-D CT, with the greatest benefit from 3-D CT found in junior residents (postgraduate years 1-3).Three-dimensional CT scans can be an effective educational tool for understanding the complex spatial anatomy of the pelvis, learning acetabular fracture patterns, and correctly applying a widely accepted fracture classification system.
Optical 3D imaging and visualization of concealed objects
NASA Astrophysics Data System (ADS)
Berginc, G.; Bellet, J.-B.; Berechet, I.; Berechet, S.
This paper gives new insights on optical 3D imagery. In this paper we explore the advantages of laser imagery to form a three-dimensional image of the scene. 3D laser imaging can be used for three-dimensional medical imaging and surveillance because of ability to identify tumors or concealed objects. We consider the problem of 3D reconstruction based upon 2D angle-dependent laser images. The objective of this new 3D laser imaging is to provide users a complete 3D reconstruction of objects from available 2D data limited in number. The 2D laser data used in this paper come from simulations that are based on the calculation of the laser interactions with the different meshed objects of the scene of interest or from experimental 2D laser images. We show that combining the Radom transform on 2D laser images with the Maximum Intensity Projection can generate 3D views of the considered scene from which we can extract the 3D concealed object in real time. With different original numerical or experimental examples, we investigate the effects of the input contrasts. We show the robustness and the stability of the method. We have developed a new patented method of 3D laser imaging based on three-dimensional reflective tomographic reconstruction algorithms and an associated visualization method. In this paper we present the global 3D reconstruction and visualization procedures.
Augmented Reality Imaging System: 3D Viewing of a Breast Cancer
Douglas, David B.; Boone, John M.; Petricoin, Emanuel; Liotta, Lance; Wilson, Eugene
Objective To display images of breast cancer from a dedicated breast CT using Depth 3-Dimensional (D3D) augmented reality. Methods A case of breast cancer imaged using contrast-enhanced breast CT (Computed Tomography) was viewed with the augmented reality imaging, which uses a head display unit (HDU) and joystick control interface. Results The augmented reality system demonstrated 3D viewing of the breast mass with head position tracking, stereoscopic depth perception, focal point convergence and the use of a 3D cursor and joy-stick enabled fly through with visualization of the spiculations extending from the breast cancer. Conclusion The augmented reality system provided 3D visualization of the breast cancer with depth perception and visualization of the mass's spiculations. The augmented reality system should be further researched to determine the utility in clinical practice. PMID:27774517
Light field display and 3D image reconstruction
NASA Astrophysics Data System (ADS)
Iwane, Toru
Light field optics and its applications become rather popular in these days. With light field optics or light field thesis, real 3D space can be described in 2D plane as 4D data, which we call as light field data. This process can be divided in two procedures. First, real3D scene is optically reduced with imaging lens. Second, this optically reduced 3D image is encoded into light field data. In later procedure we can say that 3D information is encoded onto a plane as 2D data by lens array plate. This transformation is reversible and acquired light field data can be decoded again into 3D image with the arrayed lens plate. "Refocusing" (focusing image on your favorite point after taking a picture), light-field camera's most popular function, is some kind of sectioning process from encoded 3D data (light field data) to 2D image. In this paper at first I show our actual light field camera and our 3D display using acquired and computer-simulated light field data, on which real 3D image is reconstructed. In second I explain our data processing method whose arithmetic operation is performed not in Fourier domain but in real domain. Then our 3D display system is characterized by a few features; reconstructed image is of finer resolutions than density of arrayed lenses and it is not necessary to adjust lens array plate to flat display on which light field data is displayed.
3D Imaging with Structured Illumination for Advanced Security Applications
Birch, Gabriel Carisle; Dagel, Amber Lynn; Kast, Brian A.; Smith, Collin S.
Three-dimensional (3D) information in a physical security system is a highly useful dis- criminator. The two-dimensional data from an imaging systems fails to provide target dis- tance and three-dimensional motion vector, which can be used to reduce nuisance alarm rates and increase system effectiveness. However, 3D imaging devices designed primarily for use in physical security systems are uncommon. This report discusses an architecture favorable to physical security systems; an inexpensive snapshot 3D imaging system utilizing a simple illumination system. The method of acquiring 3D data, tests to understand illumination de- sign, and software modifications possible to maximize information gathering capability are discussed.
Semi-automatic 3D segmentation of costal cartilage in CT data from Pectus Excavatum patients
NASA Astrophysics Data System (ADS)
Barbosa, Daniel; Queirós, Sandro; Rodrigues, Nuno; Correia-Pinto, Jorge; Vilaça, J.
One of the current frontiers in the clinical management of Pectus Excavatum (PE) patients is the prediction of the surgical outcome prior to the intervention. This can be done through computerized simulation of the Nuss procedure, which requires an anatomically correct representation of the costal cartilage. To this end, we take advantage of the costal cartilage tubular structure to detect it through multi-scale vesselness filtering. This information is then used in an interactive 2D initialization procedure which uses anatomical maximum intensity projections of 3D vesselness feature images to efficiently initialize the 3D segmentation process. We identify the cartilage tissue centerlines in these projected 2D images using a livewire approach. We finally refine the 3D cartilage surface through region-based sparse field level-sets. We have tested the proposed algorithm in 6 noncontrast CT datasets from PE patients. A good segmentation performance was found against reference manual contouring, with an average Dice coefficient of 0.75±0.04 and an average mean surface distance of 1.69+/-0.30mm. The proposed method requires roughly 1 minute for the interactive initialization step, which can positively contribute to an extended use of this tool in clinical practice, since current manual delineation of the costal cartilage can take up to an hour.
3D augmented reality with integral imaging display
NASA Astrophysics Data System (ADS)
Shen, Xin; Hua, Hong; Javidi, Bahram
In this paper, a three-dimensional (3D) integral imaging display for augmented reality is presented. By implementing the pseudoscopic-to-orthoscopic conversion method, elemental image arrays with different capturing parameters can be transferred into the identical format for 3D display. With the proposed merging algorithm, a new set of elemental images for augmented reality display is generated. The newly generated elemental images contain both the virtual objects and real world scene with desired depth information and transparency parameters. The experimental results indicate the feasibility of the proposed 3D augmented reality with integral imaging.
On Alternative Approaches to 3D Image Perception: Monoscopic 3D Techniques
NASA Astrophysics Data System (ADS)
Blundell, Barry G.
In the eighteenth century, techniques that enabled a strong sense of 3D perception to be experienced without recourse to binocular disparities (arising from the spatial separation of the eyes) underpinned the first significant commercial sales of 3D viewing devices and associated content. However following the advent of stereoscopic techniques in the nineteenth century, 3D image depiction has become inextricably linked to binocular parallax and outside the vision science and arts communities relatively little attention has been directed towards earlier approaches. Here we introduce relevant concepts and terminology and consider a number of techniques and optical devices that enable 3D perception to be experienced on the basis of planar images rendered from a single vantage point. Subsequently we allude to possible mechanisms for non-binocular parallax based 3D perception. Particular attention is given to reviewing areas likely to be thought-provoking to those involved in 3D display development, spatial visualization, HCI, and other related areas of interdisciplinary research.
Knowledge-Based Analysis And Understanding Of 3D Medical Images
NASA Astrophysics Data System (ADS)
Dhawan, Atam P.; Juvvadi, Sridhar
The anatomical three-dimensional (3D) medical imaging modalities, such as X-ray CT and MRI, have been well recognized in the diagnostic radiology for several years while the nuclear medicine modalities, such as PET, have just started making a strong impact through functional imaging. Though PET images provide the functional information about the human organs, they are hard to interpret because of the lack of anatomical information. Our objective is to develop a knowledge-based biomedical image analysis system which can interpret the anatomical images (such as CT). The anatomical information thus obtained can then be used in analyzing PET images of the same patient. This will not only help in interpreting PET images but it will also provide a means of studying the correlation between the anatomical and functional imaging. This paper presents the preliminary results of the knowledge based biomedical image analysis system for interpreting CT images of the chest.
Cascaded systems analysis of the 3D noise transfer characteristics of flat-panel cone-beam CT.
Tward, Daniel J; Siewerdsen, Jeffrey H
The physical factors that govern 2D and 3D imaging performance may be understood from quantitative analysis of the spatial-frequency-dependent signal and noise transfer characteristics [e.g., modulation transfer function (MTF), noise-power spectrum (NPS), detective quantum efficiency (DQE), and noise-equivalent quanta (NEQ)] along with a task-based assessment of performance (e.g., detectability index). This paper advances a theoretical framework based on cascaded systems analysis for calculation of such metrics in cone-beam CT (CBCT). The model considers the 2D projection NPS propagated through a series of reconstruction stages to yield the 3D NPS and allows quantitative investigation of tradeoffs in image quality associated with acquisition and reconstruction techniques. While the mathematical process of 3D image reconstruction is deterministic, it is shown that the process is irreversible, the associated reconstruction parameters significantly affect the 3D DQE and NEQ, and system optimization should consider the full 3D imaging chain. Factors considered in the cascade include: system geometry; number of projection views; logarithmic scaling; ramp, apodization, and interpolation filters; 3D back-projection; and 3D sampling (noise aliasing). The model is validated in comparison to experiment across a broad range of dose, reconstruction filters, and voxel sizes, and the effects of 3D noise correlation on detectability are explored. The work presents a model for the 3D NPS, DQE, and NEQ of CBCT that reduces to conventional descriptions of axial CT as a special case and provides a fairly general framework that can be applied to the design and optimization of CBCT systems for various applications.
Optical-CT 3D Dosimetry Using Fresnel Lenses with Minimal Refractive-Index Matching Fluid
Bache, Steven; Malcolm, Javian; Adamovics, John; Oldham, Mark
Telecentric optical computed tomography (optical-CT) is a state-of-the-art method for visualizing and quantifying 3-dimensional dose distributions in radiochromic dosimeters. In this work a prototype telecentric system (DFOS—Duke Fresnel Optical-CT Scanner) is evaluated which incorporates two substantial design changes: the use of Fresnel lenses (reducing lens costs from $10-30K t0 $1-3K) and the use of a 'solid tank' (which reduces noise, and the volume of refractively matched fluid from 1ltr to 10cc). The efficacy of DFOS was evaluated by direct comparison against commissioned scanners in our lab. Measured dose distributions from all systems were compared against the predicted dose distributions from a commissioned treatment planning system (TPS). Three treatment plans were investigated including a simple four-field box treatment, a multiple small field delivery, and a complex IMRT treatment. Dosimeters were imaged within 2h post irradiation, using consistent scanning techniques (360 projections acquired at 1 degree intervals, reconstruction at 2mm). DFOS efficacy was evaluated through inspection of dose line-profiles, and 2D and 3D dose and gamma maps. DFOS/TPS gamma pass rates with 3%/3mm dose difference/distance-to-agreement criteria ranged from 89.3% to 92.2%, compared to from 95.6% to 99.0% obtained with the commissioned system. The 3D gamma pass rate between the commissioned system and DFOS was 98.2%. The typical noise rates in DFOS reconstructions were up to 3%, compared to under 2% for the commissioned system. In conclusion, while the introduction of a solid tank proved advantageous with regards to cost and convenience, further work is required to improve the image quality and dose reconstruction accuracy of the new DFOS optical-CT system. PMID:27019460
Optical-CT 3D Dosimetry Using Fresnel Lenses with Minimal Refractive-Index Matching Fluid.
Bache, Steven; Malcolm, Javian; Adamovics, John; Oldham, Mark
Telecentric optical computed tomography (optical-CT) is a state-of-the-art method for visualizing and quantifying 3-dimensional dose distributions in radiochromic dosimeters. In this work a prototype telecentric system (DFOS-Duke Fresnel Optical-CT Scanner) is evaluated which incorporates two substantial design changes: the use of Fresnel lenses (reducing lens costs from $10-30K t0 $1-3K) and the use of a 'solid tank' (which reduces noise, and the volume of refractively matched fluid from 1 ltr to 10 cc). The efficacy of DFOS was evaluated by direct comparison against commissioned scanners in our lab. Measured dose distributions from all systems were compared against the predicted dose distributions from a commissioned treatment planning system (TPS). Three treatment plans were investigated including a simple four-field box treatment, a multiple small field delivery, and a complex IMRT treatment. Dosimeters were imaged within 2 h post irradiation, using consistent scanning techniques (360 projections acquired at 1 degree intervals, reconstruction at 2mm). DFOS efficacy was evaluated through inspection of dose line-profiles, and 2D and 3D dose and gamma maps. DFOS/TPS gamma pass rates with 3%/3mm dose difference/distance-to-agreement criteria ranged from 89.3% to 92.2%, compared to from 95.6% to 99.0% obtained with the commissioned system. The 3D gamma pass rate between the commissioned system and DFOS was 98.2%. The typical noise rates in DFOS reconstructions were up to 3%, compared to under 2% for the commissioned system. In conclusion, while the introduction of a solid tank proved advantageous with regards to cost and convenience, further work is required to improve the image quality and dose reconstruction accuracy of the new DFOS optical-CT system.
3D nonrigid medical image registration using a new information theoretic measure
NASA Astrophysics Data System (ADS)
Li, Bicao; Yang, Guanyu; Coatrieux, Jean Louis; Li, Baosheng; Shu, Huazhong
This work presents a novel method for the nonrigid registration of medical images based on the Arimoto entropy, a generalization of the Shannon entropy. The proposed method employed the Jensen-Arimoto divergence measure as a similarity metric to measure the statistical dependence between medical images. Free-form deformations were adopted as the transformation model and the Parzen window estimation was applied to compute the probability distributions. A penalty term is incorporated into the objective function to smooth the nonrigid transformation. The goal of registration is to optimize an objective function consisting of a dissimilarity term and a penalty term, which would be minimal when two deformed images are perfectly aligned using the limited memory BFGS optimization method, and thus to get the optimal geometric transformation. To validate the performance of the proposed method, experiments on both simulated 3D brain MR images and real 3D thoracic CT data sets were designed and performed on the open source elastix package. For the simulated experiments, the registration errors of 3D brain MR images with various magnitudes of known deformations and different levels of noise were measured. For the real data tests, four data sets of 4D thoracic CT from four patients were selected to assess the registration performance of the method, including ten 3D CT images for each 4D CT data covering an entire respiration cycle. These results were compared with the normalized cross correlation and the mutual information methods and show a slight but true improvement in registration accuracy.
Dedicated 3D photoacoustic breast imaging
Kruger, Robert A.; Kuzmiak, Cherie M.; Lam, Richard B.; Reinecke, Daniel R.; Del Rio, Stephen P.; Steed, Doreen
Purpose: To report the design and imaging methodology of a photoacoustic scanner dedicated to imaging hemoglobin distribution throughout a human breast. Methods: The authors developed a dedicated breast photoacoustic mammography (PAM) system using a spherical detector aperture based on our previous photoacoustic tomography scanner. The system uses 512 detectors with rectilinear scanning. The scan shape is a spiral pattern whose radius varies from 24 to 96 mm, thereby allowing a field of view that accommodates a wide range of breast sizes. The authors measured the contrast-to-noise ratio (CNR) using a target comprised of 1-mm dots printed on clear plastic. Each dot absorption coefficient was approximately the same as a 1-mm thickness of whole blood at 756 nm, the output wavelength of the Alexandrite laser used by this imaging system. The target was immersed in varying depths of an 8% solution of stock Liposyn II-20%, which mimics the attenuation of breast tissue (1.1 cm−1). The spatial resolution was measured using a 6 μm-diameter carbon fiber embedded in agar. The breasts of four healthy female volunteers, spanning a range of breast size from a brassiere C cup to a DD cup, were imaged using a 96-mm spiral protocol. Results: The CNR target was clearly visualized to a depth of 53 mm. Spatial resolution, which was estimated from the full width at half-maximum of a profile across the PAM image of a carbon fiber, was 0.42 mm. In the four human volunteers, the vasculature was well visualized throughout the breast tissue, including to the chest wall. Conclusions: CNR, lateral field-of-view and penetration depth of our dedicated PAM scanning system is sufficient to image breasts as large as 1335 mL, which should accommodate up to 90% of the women in the United States. PMID:24320471
3-D capacitance density imaging system
Fasching, G.E.
A three-dimensional capacitance density imaging of a gasified bed or the like in a containment vessel is achieved using a plurality of electrodes provided circumferentially about the bed in levels and along the bed in channels. The electrodes are individually and selectively excited electrically at each level to produce a plurality of current flux field patterns generated in the bed at each level. The current flux field patterns are suitably sensed and a density pattern of the bed at each level determined. By combining the determined density patterns at each level, a three-dimensional density image of the bed is achieved. 7 figs.
3-D seismic imaging of complex geologies
Womble, D.E.; Dosanjh, S.S.; VanDyke, J.P.; Oldfield, R.A.; Greenberg, D.S.
We present three codes for the Intel Paragon that address the problem of three-dimensional seismic imaging of complex geologies. The first code models acoustic wave propagation and can be used to generate data sets to calibrate and validate seismic imaging codes. This code reported the fastest timings for acoustic wave propagation codes at a recent SEG (Society of Exploration Geophysicists) meeting. The second code implements a Kirchhoff method for pre-stack depth migration. Development of this code is almost complete, and preliminary results are presented. The third code implements a wave equation approach to seismic migration and is a Paragon implementation of a code from the ARCO Seismic Benchmark Suite.
3D CT spine data segmentation and analysis of vertebrae bone lesions.
Peter, R; Malinsky, M; Ourednicek, P; Jan, J
A method is presented aiming at detecting and classifying bone lesions in 3D CT data of human spine, via Bayesian approach utilizing Markov random fields. A developed algorithm for necessary segmentation of individual possibly heavily distorted vertebrae based on 3D intensity modeling of vertebra types is presented as well.
3D/2D image registration: the impact of X-ray views and their number.
Tomazevic, Dejan; Likar, Bostjan; Pernus, Franjo
An important part of image-guided radiation therapy or surgery is registration of a three-dimensional (3D) preoperative image to two-dimensional (2D) images of the patient. It is expected that the accuracy and robustness of a 3D/2D image registration method do not depend solely on the registration method itself but also on the number and projections (views) of intraoperative images. In this study, we systematically investigate these factors by using registered image data, comprising of CT and X-ray images of a cadaveric lumbar spine phantom and the recently proposed 3D/2D registration method. The results indicate that the proportion of successful registrations (robustness) significantly increases when more X-ray images are used for registration.
Polarimetric 3D integral imaging in photon-starved conditions.
Carnicer, Artur; Javidi, Bahram
We develop a method for obtaining 3D polarimetric integral images from elemental images recorded in low light illumination conditions. Since photon-counting images are very sparse, calculation of the Stokes parameters and the degree of polarization should be handled carefully. In our approach, polarimetric 3D integral images are generated using the Maximum Likelihood Estimation and subsequently reconstructed by means of a Total Variation Denoising filter. In this way, polarimetric results are comparable to those obtained in conventional illumination conditions. We also show that polarimetric information retrieved from photon starved images can be used in 3D object recognition problems. To the best of our knowledge, this is the first report on 3D polarimetric photon counting integral imaging.
Phase Sensitive Cueing for 3D Objects in Overhead Images
Paglieroni, D
Locating specific 3D objects in overhead images is an important problem in many remote sensing applications. 3D objects may contain either one connected component or multiple disconnected components. Solutions must accommodate images acquired with diverse sensors at various times of the day, in various seasons of the year, or under various weather conditions. Moreover, the physical manifestation of a 3D object with fixed physical dimensions in an overhead image is highly dependent on object physical dimensions, object position/orientation, image spatial resolution, and imaging geometry (e.g., obliqueness). This paper describes a two-stage computer-assisted approach for locating 3D objects in overhead images. In the matching stage, the computer matches models of 3D objects to overhead images. The strongest degree of match over all object orientations is computed at each pixel. Unambiguous local maxima in the degree of match as a function of pixel location are then found. In the cueing stage, the computer sorts image thumbnails in descending order of figure-of-merit and presents them to human analysts for visual inspection and interpretation. The figure-of-merit associated with an image thumbnail is computed from the degrees of match to a 3D object model associated with unambiguous local maxima that lie within the thumbnail. This form of computer assistance is invaluable when most of the relevant thumbnails are highly ranked, and the amount of inspection time needed is much less for the highly ranked thumbnails than for images as a whole.
3D laser imaging for concealed object identification
NASA Astrophysics Data System (ADS)
Berechet, Ion; Berginc, Gérard; Berechet, Stefan
This paper deals with new optical non-conventional 3D laser imaging. Optical non-conventional imaging explores the advantages of laser imaging to form a three-dimensional image of the scene. 3D laser imaging can be used for threedimensional medical imaging, topography, surveillance, robotic vision because of ability to detect and recognize objects. In this paper, we present a 3D laser imaging for concealed object identification. The objective of this new 3D laser imaging is to provide the user a complete 3D reconstruction of the concealed object from available 2D data limited in number and with low representativeness. The 2D laser data used in this paper come from simulations that are based on the calculation of the laser interactions with the different interfaces of the scene of interest and from experimental results. We show the global 3D reconstruction procedures capable to separate objects from foliage and reconstruct a threedimensional image of the considered object. In this paper, we present examples of reconstruction and completion of three-dimensional images and we analyse the different parameters of the identification process such as resolution, the scenario of camouflage, noise impact and lacunarity degree.
3D-Holoscopic Imaging: A New Dimension to Enhance Imaging in Minimally Invasive Therapy in Urologic Oncology
Aggoun, Amar; Swash, Mohammad; Grange, Philippe C.R.; Challacombe, Benjamin; Dasgupta, Prokar
Abstract Background and Purpose Existing imaging modalities of urologic pathology are limited by three-dimensional (3D) representation on a two-dimensional screen. We present 3D-holoscopic imaging as a novel method of representing Digital Imaging and Communications in Medicine data images taken from CT and MRI to produce 3D-holographic representations of anatomy without special eyewear in natural light. 3D-holoscopic technology produces images that are true optical models. This technology is based on physical principles with duplication of light fields. The 3D content is captured in real time with the content viewed by multiple viewers independently of their position, without 3D eyewear. Methods We display 3D-holoscopic anatomy relevant to minimally invasive urologic surgery without the need for 3D eyewear. Results The results have demonstrated that medical 3D-holoscopic content can be displayed on commercially available multiview auto-stereoscopic display. Conclusion The next step is validation studies comparing 3D-Holoscopic imaging with conventional imaging. PMID:23216303
Automated 3D renal segmentation based on image partitioning
NASA Astrophysics Data System (ADS)
Yeghiazaryan, Varduhi; Voiculescu, Irina D.
Despite several decades of research into segmentation techniques, automated medical image segmentation is barely usable in a clinical context, and still at vast user time expense. This paper illustrates unsupervised organ segmentation through the use of a novel automated labelling approximation algorithm followed by a hypersurface front propagation method. The approximation stage relies on a pre-computed image partition forest obtained directly from CT scan data. We have implemented all procedures to operate directly on 3D volumes, rather than slice-by-slice, because our algorithms are dimensionality-independent. The results picture segmentations which identify kidneys, but can easily be extrapolated to other body parts. Quantitative analysis of our automated segmentation compared against hand-segmented gold standards indicates an average Dice similarity coefficient of 90%. Results were obtained over volumes of CT data with 9 kidneys, computing both volume-based similarity measures (such as the Dice and Jaccard coefficients, true positive volume fraction) and size-based measures (such as the relative volume difference). The analysis considered both healthy and diseased kidneys, although extreme pathological cases were excluded from the overall count. Such cases are difficult to segment both manually and automatically due to the large amplitude of Hounsfield unit distribution in the scan, and the wide spread of the tumorous tissue inside the abdomen. In the case of kidneys that have maintained their shape, the similarity range lies around the values obtained for inter-operator variability. Whilst the procedure is fully automated, our tools also provide a light level of manual editing.
Critical comparison of 3D imaging approaches
Bennett, C L
Currently three imaging spectrometer architectures, tunable filter, dispersive, and Fourier transform, are viable for imaging the universe in three dimensions. There are domains of greatest utility for each of these architectures. The optimum choice among the various alternative architectures is dependent on the nature of the desired observations, the maturity of the relevant technology, and the character of the backgrounds. The domain appropriate for each of the alternatives is delineated; both for instruments having ideal performance as well as for instrumentation based on currently available technology. The environment and science objectives for the Next Generation Space Telescope will be used as a specific representative case to provide a basis for comparison of the various alternatives.
A 3D Level Set Method for Microwave Breast Imaging
Colgan, Timothy J.; Hagness, Susan C.; Van Veen, Barry D.
Objective Conventional inverse-scattering algorithms for microwave breast imaging result in moderate resolution images with blurred boundaries between tissues. Recent 2D numerical microwave imaging studies demonstrate that the use of a level set method preserves dielectric boundaries, resulting in a more accurate, higher resolution reconstruction of the dielectric properties distribution. Previously proposed level set algorithms are computationally expensive and thus impractical in 3D. In this paper we present a computationally tractable 3D microwave imaging algorithm based on level sets. Methods We reduce the computational cost of the level set method using a Jacobian matrix, rather than an adjoint method, to calculate Frechet derivatives. We demonstrate the feasibility of 3D imaging using simulated array measurements from 3D numerical breast phantoms. We evaluate performance by comparing full 3D reconstructions to those from a conventional microwave imaging technique. We also quantitatively assess the efficacy of our algorithm in evaluating breast density. Results Our reconstructions of 3D numerical breast phantoms improve upon those of a conventional microwave imaging technique. The density estimates from our level set algorithm are more accurate than those of conventional microwave imaging, and the accuracy is greater than that reported for mammographic density estimation. Conclusion Our level set method leads to a feasible level of computational complexity for full 3D imaging, and reconstructs the heterogeneous dielectric properties distribution of the breast more accurately than conventional microwave imaging methods. Significance 3D microwave breast imaging using a level set method is a promising low-cost, non-ionizing alternative to current breast imaging techniques. PMID:26011863
Acoustic 3D imaging of dental structures
Lewis, D.K.; Hume, W.R.; Douglass, G.D.
Our goals for the first year of this three dimensional electodynamic imaging project was to determine how to combine flexible, individual addressable; preprocessing of array source signals; spectral extrapolation or received signals; acoustic tomography codes; and acoustic propagation modeling code. We investigated flexible, individually addressable acoustic array material to find the best match in power, sensitivity and cost and settled on PVDF sheet arrays and 3-1 composite material.
3D/3D registration of coronary CTA and biplane XA reconstructions for improved image guidance
Dibildox, Gerardo Baka, Nora; Walsum, Theo van; Punt, Mark; Aben, Jean-Paul; Schultz, Carl; Niessen, Wiro
Purpose: The authors aim to improve image guidance during percutaneous coronary interventions of chronic total occlusions (CTO) by providing information obtained from computed tomography angiography (CTA) to the cardiac interventionist. To this end, the authors investigate a method to register a 3D CTA model to biplane reconstructions. Methods: The authors developed a method for registering preoperative coronary CTA with intraoperative biplane x-ray angiography (XA) images via 3D models of the coronary arteries. The models are extracted from the CTA and biplane XA images, and are temporally aligned based on CTA reconstruction phase and XA ECG signals. Rigid spatial alignment is achieved with a robust probabilistic point set registration approach using Gaussian mixture models (GMMs). This approach is extended by including orientation in the Gaussian mixtures and by weighting bifurcation points. The method is evaluated on retrospectively acquired coronary CTA datasets of 23 CTO patients for which biplane XA images are available. Results: The Gaussian mixture model approach achieved a median registration accuracy of 1.7 mm. The extended GMM approach including orientation was not significantly different (P > 0.1) but did improve robustness with regards to the initialization of the 3D models. Conclusions: The authors demonstrated that the GMM approach can effectively be applied to register CTA to biplane XA images for the purpose of improving image guidance in percutaneous coronary interventions.
Noninvasive CT to Iso-C3D registration for improved intraoperative visualization in computer assisted orthopedic surgery
NASA Astrophysics Data System (ADS)
Rudolph, Tobias; Ebert, Lars; Kowal, Jens
Supporting surgeons in performing minimally invasive surgeries can be considered as one of the major goals of computer assisted surgery. Excellent intraoperative visualization is a prerequisite to achieve this aim. The Siremobil Iso-C 3D has become a widely used imaging device, which, in combination with a navigation system, enables the surgeon to directly navigate within the acquired 3D image volume without any extra registration steps. However, the image quality is rather low compared to a CT scan and the volume size (approx. 12 cm 3) limits its application. A regularly used alternative in computer assisted orthopedic surgery is to use of a preoperatively acquired CT scan to visualize the operating field. But, the additional registration step, necessary in order to use CT stacks for navigation is quite invasive. Therefore the objective of this work is to develop a noninvasive registration technique. In this article a solution is being proposed that registers a preoperatively acquired CT scan to the intraoperatively acquired Iso-C 3D image volume, thereby registering the CT to the tracked anatomy. The procedure aligns both image volumes by maximizing the mutual information, an algorithm that has already been applied to similar registration problems and demonstrated good results. Furthermore the accuracy of such a registration method was investigated in a clinical setup, integrating a navigated Iso-C 3D in combination with an tracking system. Initial tests based on cadaveric animal bone resulted in an accuracy ranging from 0.63mm to 1.55mm mean error.
3D X-ray imaging methods in support catheter ablations of cardiac arrhythmias.
Stárek, Zdeněk; Lehar, František; Jež, Jiří; Wolf, Jiří; Novák, Miroslav
Cardiac arrhythmias are a very frequent illness. Pharmacotherapy is not very effective in persistent arrhythmias and brings along a number of risks. Catheter ablation has became an effective and curative treatment method over the past 20 years. To support complex arrhythmia ablations, the 3D X-ray cardiac cavities imaging is used, most frequently the 3D reconstruction of CT images. The 3D cardiac rotational angiography (3DRA) represents a modern method enabling to create CT like 3D images on a standard X-ray machine equipped with special software. Its advantage lies in the possibility to obtain images during the procedure, decreased radiation dose and reduction of amount of the contrast agent. The left atrium model is the one most frequently used for complex atrial arrhythmia ablations, particularly for atrial fibrillation. CT data allow for creation and segmentation of 3D models of all cardiac cavities. Recently, a research has been made proving the use of 3DRA to create 3D models of other cardiac (right ventricle, left ventricle, aorta) and non-cardiac structures (oesophagus). They can be used during catheter ablation of complex arrhythmias to improve orientation during the construction of 3D electroanatomic maps, directly fused with 3D electroanatomic systems and/or fused with fluoroscopy. An intensive development in the 3D model creation and use has taken place over the past years and they became routinely used during catheter ablations of arrhythmias, mainly atrial fibrillation ablation procedures. Further development may be anticipated in the future in both the creation and use of these models.
Swarm Intelligence Integrated Graph-Cut for Liver Segmentation from 3D-CT Volumes
Eapen, Maya; Korah, Reeba; Geetha, G.
The segmentation of organs in CT volumes is a prerequisite for diagnosis and treatment planning. In this paper, we focus on liver segmentation from contrast-enhanced abdominal CT volumes, a challenging task due to intensity overlapping, blurred edges, large variability in liver shape, and complex background with cluttered features. The algorithm integrates multidiscriminative cues (i.e., prior domain information, intensity model, and regional characteristics of liver in a graph-cut image segmentation framework). The paper proposes a swarm intelligence inspired edge-adaptive weight function for regulating the energy minimization of the traditional graph-cut model. The model is validated both qualitatively (by clinicians and radiologists) and quantitatively on publically available computed tomography (CT) datasets (MICCAI 2007 liver segmentation challenge, 3D-IRCAD). Quantitative evaluation of segmentation results is performed using liver volume calculations and a mean score of 80.8% and 82.5% on MICCAI and IRCAD dataset, respectively, is obtained. The experimental result illustrates the efficiency and effectiveness of the proposed method. PMID:26689833
Peripheral pulmonary arteries: identification at multi-slice spiral CT with 3D reconstruction.
Coche, Emmanuel; Pawlak, Sebastien; Dechambre, Stéphane; Maldague, Baudouin
Our objective was to analyze the peripheral pulmonary arteries using thin-collimation multi-slice spiral CT. Twenty consecutive patients underwent enhanced-spiral multi-slice CT using 1-mm collimation. Two observers analyzed the pulmonary arteries by consensus on a workstation. Each artery was identified on axial and 3D shaded-surface display reconstruction images. Each subsegmental artery was measured at a mediastinal window setting and compared with anatomical classifications. The location and branching of every subsegmental artery was recorded. The number of well-visualized sub-subsegmental arteries at a mediastinal window setting was compared with those visualized at a lung window setting. Of 800 subsegmental arteries, 769 (96%) were correctly visualized and 123 accessory subsegmental arteries were identified using the mediastinal window setting. One thousand ninety-two of 2019 sub-subsegmental arteries (54%) identified using the lung window setting were correctly visualized using the mediastinal window setting. Enhanced multi-slice spiral CT with thin collimation can be used to analyze precisely the subsegmental pulmonary arteries and may identify even more distal pulmonary arteries.
Potential Cost Savings with 3D Printing Combined With 3D Imaging and CPLM for Fleet Maintenance and Revitalization
1 Potential Cost Savings with 3D Printing Combined With 3D Imaging and CPLM for Fleet Maintenance and Revitalization David N. Ford...2014 4. TITLE AND SUBTITLE Potential Cost Savings with 3D Printing Combined With 3D Imaging and CPLM for Fleet Maintenance and Revitalization 5a...Manufacturing ( 3D printing ) 2 Research Context Problem: Learning curve savings forecasted in SHIPMAIN maintenance initiative have not materialized
Morphometrics, 3D Imaging, and Craniofacial Development
Hallgrimsson, Benedikt; Percival, Christopher J.; Green, Rebecca; Young, Nathan M.; Mio, Washington; Marcucio, Ralph
Recent studies have shown how volumetric imaging and morphometrics can add significantly to our understanding of morphogenesis, the developmental basis for variation and the etiology of structural birth defects. On the other hand, the complex questions and diverse imaging data in developmental biology present morphometrics with more complex challenges than applications in virtually any other field. Meeting these challenges is necessary in order to understand the mechanistic basis for variation in complex morphologies. This chapter reviews the methods and theory that enable the application of modern landmark-based morphometrics to developmental biology and craniofacial development, in particular. We discuss the theoretical foundations of morphometrics as applied to development and review the basic approaches to the quantification of morphology. Focusing on geometric morphometrics, we discuss the principal statistical methods for quantifying and comparing morphological variation and covariation structure within and among groups. Finally, we discuss the future directions for morphometrics in developmental biology that will be required for approaches that enable quantitative integration across the genotype-phenotype map. PMID:26589938
Technical Note: Characterization of custom 3D printed multimodality imaging phantoms
Bieniosek, Matthew F.; Lee, Brian J.; Levin, Craig S.
Purpose: Imaging phantoms are important tools for researchers and technicians, but they can be costly and difficult to customize. Three dimensional (3D) printing is a widely available rapid prototyping technique that enables the fabrication of objects with 3D computer generated geometries. It is ideal for quickly producing customized, low cost, multimodal, reusable imaging phantoms. This work validates the use of 3D printed phantoms by comparing CT and PET scans of a 3D printed phantom and a commercial "Micro Deluxe" phantom. This report also presents results from a customized 3D printed PET/MRI phantom, and a customized high resolution imaging phantom with sub-mm features. Methods: CT and PET scans of a 3D printed phantom and a commercial Micro Deluxe (Data Spectrum Corporation, USA) phantom with 1.2, 1.6, 2.4, 3.2, 4.0, and 4.8 mm diameter hot rods were acquired. The measured PET and CT rod sizes, activities, and attenuation coefficients were compared. A PET/MRI scan of a custom 3D printed phantom with hot and cold rods was performed, with photon attenuation and normalization measurements performed with a separate 3D printed normalization phantom. X-ray transmission scans of a customized two level high resolution 3D printed phantom with sub-mm features were also performed. Results: Results show very good agreement between commercial and 3D printed micro deluxe phantoms with less than 3% difference in CT measured rod diameter, less than 5% difference in PET measured rod diameter, and a maximum of 6.2% difference in average rod activity from a 10 min, 333 kBq/ml (9 μCi/ml) Siemens Inveon (Siemens Healthcare, Germany) PET scan. In all cases, these differences were within the measurement uncertainties of our setups. PET/MRI scans successfully identified 3D printed hot and cold rods on PET and MRI modalities. X-ray projection images of a 3D printed high resolution phantom identified features as small as 350 μm wide. Conclusions: This work shows that 3D printed
Technical Note: Characterization of custom 3D printed multimodality imaging phantoms
Bieniosek, Matthew F.; Lee, Brian J.; Levin, Craig S.
Purpose: Imaging phantoms are important tools for researchers and technicians, but they can be costly and difficult to customize. Three dimensional (3D) printing is a widely available rapid prototyping technique that enables the fabrication of objects with 3D computer generated geometries. It is ideal for quickly producing customized, low cost, multimodal, reusable imaging phantoms. This work validates the use of 3D printed phantoms by comparing CT and PET scans of a 3D printed phantom and a commercial "Micro Deluxe" phantom. This report also presents results from a customized 3D printed PET/MRI phantom, and a customized high resolution imaging phantom with sub-mm features. Methods: CT and PET scans of a 3D printed phantom and a commercial Micro Deluxe (Data Spectrum Corporation, USA) phantom with 1.2, 1.6, 2.4, 3.2, 4.0, and 4.8 mm diameter hot rods were acquired. The measured PET and CT rod sizes, activities, and attenuation coefficients were compared. A PET/MRI scan of a custom 3D printed phantom with hot and cold rods was performed, with photon attenuation and normalization measurements performed with a separate 3D printed normalization phantom. X-ray transmission scans of a customized two level high resolution 3D printed phantom with sub-mm features were also performed. Results: Results show very good agreement between commercial and 3D printed micro deluxe phantoms with less than 3% difference in CT measured rod diameter, less than 5% difference in PET measured rod diameter, and a maximum of 6.2% difference in average rod activity from a 10 min, 333 kBq/ml (9 μCi/ml) Siemens Inveon (Siemens Healthcare, Germany) PET scan. In all cases, these differences were within the measurement uncertainties of our setups. PET/MRI scans successfully identified 3D printed hot and cold rods on PET and MRI modalities. X-ray projection images of a 3D printed high resolution phantom identified features as small as 350 μm wide. Conclusions: This work shows that 3D printed
3D quantitative phase imaging of neural networks using WDT
NASA Astrophysics Data System (ADS)
Kim, Taewoo; Liu, S. C.; Iyer, Raj; Gillette, Martha U.; Popescu, Gabriel
White-light diffraction tomography (WDT) is a recently developed 3D imaging technique based on a quantitative phase imaging system called spatial light interference microscopy (SLIM). The technique has achieved a sub-micron resolution in all three directions with high sensitivity granted by the low-coherence of a white-light source. Demonstrations of the technique on single cell imaging have been presented previously; however, imaging on any larger sample, including a cluster of cells, has not been demonstrated using the technique. Neurons in an animal body form a highly complex and spatially organized 3D structure, which can be characterized by neuronal networks or circuits. Currently, the most common method of studying the 3D structure of neuron networks is by using a confocal fluorescence microscope, which requires fluorescence tagging with either transient membrane dyes or after fixation of the cells. Therefore, studies on neurons are often limited to samples that are chemically treated and/or dead. WDT presents a solution for imaging live neuron networks with a high spatial and temporal resolution, because it is a 3D imaging method that is label-free and non-invasive. Using this method, a mouse or rat hippocampal neuron culture and a mouse dorsal root ganglion (DRG) neuron culture have been imaged in order to see the extension of processes between the cells in 3D. Furthermore, the tomogram is compared with a confocal fluorescence image in order to investigate the 3D structure at synapses.
Non-rigid registration of small animal skeletons from micro-CT using 3D shape context
NASA Astrophysics Data System (ADS)
Xiao, Di; Bourgeat, Pierrick; Fripp, Jurgen; Acosta Tamayo, Oscar; Gregoire, Marie Claude; Salvado, Olivier
Small animal registration is an important step for molecular image analysis. Skeleton registration from whole-body or only partial micro Computerized Tomography (CT) image is often performed to match individual rats to atlases and templates, for example to identify organs in positron emission tomography (PET). In this paper, we extend the shape context matching technique for 3D surface registration and apply it for rat hind limb skeleton registration from CT images. Using the proposed method, after standard affine iterative closest point (ICP) registration, correspondences between the 3D points from sour and target objects were robustly found and used to deform the limb skeleton surface with thin-plate-spline (TPS). Experiments are described using phantoms and actual rat hind limb skeletons. On animals, mean square errors were decreased by the proposed registration compared to that of its initial alignment. Visually, skeletons were successfully registered even in cases of very different animal poses.
Accommodation response measurements for integral 3D image
NASA Astrophysics Data System (ADS)
Hiura, H.; Mishina, T.; Arai, J.; Iwadate, Y.
We measured accommodation responses under integral photography (IP), binocular stereoscopic, and real object display conditions, and viewing conditions of binocular and monocular viewing conditions. The equipment we used was an optometric device and a 3D display. We developed the 3D display for IP and binocular stereoscopic images that comprises a high-resolution liquid crystal display (LCD) and a high-density lens array. The LCD has a resolution of 468 dpi and a diagonal size of 4.8 inches. The high-density lens array comprises 106 x 69 micro lenses that have a focal length of 3 mm and diameter of 1 mm. The lenses are arranged in a honeycomb pattern. The 3D display was positioned 60 cm from an observer under IP and binocular stereoscopic display conditions. The target was presented at eight depth positions relative to the 3D display: 15, 10, and 5 cm in front of the 3D display, on the 3D display panel, and 5, 10, 15 and 30 cm behind the 3D display under the IP and binocular stereoscopic display conditions. Under the real object display condition, the target was displayed on the 3D display panel, and the 3D display was placed at the eight positions. The results suggest that the IP image induced more natural accommodation responses compared to the binocular stereoscopic image. The accommodation responses of the IP image were weaker than those of a real object; however, they showed a similar tendency with those of the real object under the two viewing conditions. Therefore, IP can induce accommodation to the depth positions of 3D images.
3D Whole Heart Imaging for Congenital Heart Disease
Greil, Gerald; Tandon, Animesh (Aashoo); Silva Vieira, Miguel; Hussain, Tarique
Three-dimensional (3D) whole heart techniques form a cornerstone in cardiovascular magnetic resonance imaging of congenital heart disease (CHD). It offers significant advantages over other CHD imaging modalities and techniques: no ionizing radiation; ability to be run free-breathing; ECG-gated dual-phase imaging for accurate measurements and tissue properties estimation; and higher signal-to-noise ratio and isotropic voxel resolution for multiplanar reformatting assessment. However, there are limitations, such as potentially long acquisition times with image quality degradation. Recent advances in and current applications of 3D whole heart imaging in CHD are detailed, as well as future directions. PMID:28289674
Image based 3D city modeling : Comparative study
NASA Astrophysics Data System (ADS)
Singh, S. P.; Jain, K.; Mandla, V. R.
3D city model is a digital representation of the Earth's surface and it's related objects such as building, tree, vegetation, and some manmade feature belonging to urban area. The demand of 3D city modeling is increasing rapidly for various engineering and non-engineering applications. Generally four main image based approaches were used for virtual 3D city models generation. In first approach, researchers were used Sketch based modeling, second method is Procedural grammar based modeling, third approach is Close range photogrammetry based modeling and fourth approach is mainly based on Computer Vision techniques. SketchUp, CityEngine, Photomodeler and Agisoft Photoscan are the main softwares to represent these approaches respectively. These softwares have different approaches & methods suitable for image based 3D city modeling. Literature study shows that till date, there is no complete such type of comparative study available to create complete 3D city model by using images. This paper gives a comparative assessment of these four image based 3D modeling approaches. This comparative study is mainly based on data acquisition methods, data processing techniques and output 3D model products. For this research work, study area is the campus of civil engineering department, Indian Institute of Technology, Roorkee (India). This 3D campus acts as a prototype for city. This study also explains various governing parameters, factors and work experiences. This research work also gives a brief introduction, strengths and weakness of these four image based techniques. Some personal comment is also given as what can do or what can't do from these softwares. At the last, this study shows; it concluded that, each and every software has some advantages and limitations. Choice of software depends on user requirements of 3D project. For normal visualization project, SketchUp software is a good option. For 3D documentation record, Photomodeler gives good result. For Large city
A colour image reproduction framework for 3D colour printing
NASA Astrophysics Data System (ADS)
Xiao, Kaida; Sohiab, Ali; Sun, Pei-li; Yates, Julian M.; Li, Changjun; Wuerger, Sophie
In this paper, the current technologies in full colour 3D printing technology were introduced. A framework of colour image reproduction process for 3D colour printing is proposed. A special focus was put on colour management for 3D printed objects. Two approaches, colorimetric colour reproduction and spectral based colour reproduction are proposed in order to faithfully reproduce colours in 3D objects. Two key studies, colour reproduction for soft tissue prostheses and colour uniformity correction across different orientations are described subsequently. Results are clear shown that applying proposed colour image reproduction framework, performance of colour reproduction can be significantly enhanced. With post colour corrections, a further improvement in colour process are achieved for 3D printed objects.
ConvNet-Based Localization of Anatomical Structures in 3D Medical Images.
de Vos, Bob; Wolterink, Jelmer; de Jong, Pim; Leiner, Tim; Viergever, Max; Isgum, Ivana
Localization of anatomical structures is a prerequisite for many tasks in medical image analysis. We propose a method for automatic localization of one or more anatomical structures in 3D medical images through detection of their presence in 2D image slices using a convolutional neural network (ConvNet). A single ConvNet is trained to detect presence of the anatomical structure of interest in axial, coronal, and sagittal slices extracted from a 3D image. To allow the ConvNet to analyze slices of different sizes, spatial pyramid pooling is applied. After detection, 3D bounding boxes are created by combining the output of the ConvNet in all slices. In the experiments 200 chest CT, 100 cardiac CT angiography (CTA), and 100 abdomen CT scans were used. The heart, ascending aorta, aortic arch, and descending aorta were localized in chest CT scans, the left cardiac ventricle in cardiac CTA scans, and the liver in abdomen CT scans. Localization was evaluated using the distances between automatically and manually defined reference bounding box centroids and walls. The best results were achieved in localization of structures with clearly defined boundaries (e.g. aortic arch) and the worst when the structure boundary was not clearly visible (e.g. liver). The method was more robust and accurate in localization multiple structures.
3D image display of fetal ultrasonic images by thin shell
NASA Astrophysics Data System (ADS)
Wang, Shyh-Roei; Sun, Yung-Nien; Chang, Fong-Ming; Jiang, Ching-Fen
Due to the properties of convenience and non-invasion, ultrasound has become an essential tool for diagnosis of fetal abnormality during women pregnancy in obstetrics. However, the 'noisy and blurry' nature of ultrasound data makes the rendering of the data a challenge in comparison with MRI and CT images. In spite of the speckle noise, the unwanted objects usually occlude the target to be observed. In this paper, we proposed a new system that can effectively depress the speckle noise, extract the target object, and clearly render the 3D fetal image in almost real-time from 3D ultrasound image data. The system is based on a deformable model that detects contours of the object according to the local image feature of ultrasound. Besides, in order to accelerate rendering speed, a thin shell is defined to separate the observed organ from unrelated structures depending on those detected contours. In this way, we can support quick 3D display of ultrasound, and the efficient visualization of 3D fetal ultrasound thus becomes possible.
Imaging fault zones using 3D seismic image processing techniques
NASA Astrophysics Data System (ADS)
Iacopini, David; Butler, Rob; Purves, Steve
Significant advances in structural analysis of deep water structure, salt tectonic and extensional rift basin come from the descriptions of fault system geometries imaged in 3D seismic data. However, even where seismic data are excellent, in most cases the trajectory of thrust faults is highly conjectural and still significant uncertainty exists as to the patterns of deformation that develop between the main faults segments, and even of the fault architectures themselves. Moreover structural interpretations that conventionally define faults by breaks and apparent offsets of seismic reflectors are commonly conditioned by a narrow range of theoretical models of fault behavior. For example, almost all interpretations of thrust geometries on seismic data rely on theoretical "end-member" behaviors where concepts as strain localization or multilayer mechanics are simply avoided. Yet analogue outcrop studies confirm that such descriptions are commonly unsatisfactory and incomplete. In order to fill these gaps and improve the 3D visualization of deformation in the subsurface, seismic attribute methods are developed here in conjunction with conventional mapping of reflector amplitudes (Marfurt & Chopra, 2007)). These signal processing techniques recently developed and applied especially by the oil industry use variations in the amplitude and phase of the seismic wavelet. These seismic attributes improve the signal interpretation and are calculated and applied to the entire 3D seismic dataset. In this contribution we will show 3D seismic examples of fault structures from gravity-driven deep-water thrust structures and extensional basin systems to indicate how 3D seismic image processing methods can not only build better the geometrical interpretations of the faults but also begin to map both strain and damage through amplitude/phase properties of the seismic signal. This is done by quantifying and delineating the short-range anomalies on the intensity of reflector amplitudes
Digital holography and 3D imaging: introduction to feature issue.
Kim, Myung K; Hayasaki, Yoshio; Picart, Pascal; Rosen, Joseph
This feature issue of Applied Optics on Digital Holography and 3D Imaging is the sixth of an approximately annual series. Forty-seven papers are presented, covering a wide range of topics in phase-shifting methods, low coherence methods, particle analysis, biomedical imaging, computer-generated holograms, integral imaging, and many others.
Thoracic Temporal Subtraction Three Dimensional Computed Tomography (3D-CT): Screening for Vertebral Metastases of Primary Lung Cancers
Iwano, Shingo; Ito, Rintaro; Umakoshi, Hiroyasu; Karino, Takatoshi; Inoue, Tsutomu; Li, Yuanzhong; Naganawa, Shinji
Purpose We developed an original, computer-aided diagnosis (CAD) software that subtracts the initial thoracic vertebral three-dimensional computed tomography (3D-CT) image from the follow-up 3D-CT image. The aim of this study was to investigate the efficacy of this CAD software during screening for vertebral metastases on follow-up CT images of primary lung cancer patients. Materials and Methods The interpretation experiment included 30 sets of follow-up CT scans in primary lung cancer patients and was performed by two readers (readers A and B), who each had 2.5 years' experience reading CT images. In 395 vertebrae from C6 to L3, 46 vertebral metastases were identified as follows: osteolytic metastases (n = 17), osteoblastic metastases (n = 14), combined osteolytic and osteoblastic metastases (n = 6), and pathological fractures (n = 9). Thirty-six lesions were in the anterior component (vertebral body), and 10 lesions were in the posterior component (vertebral arch, transverse process, and spinous process). The area under the curve (AUC) by receiver operating characteristic (ROC) curve analysis and the sensitivity and specificity for detecting vertebral metastases were compared with and without CAD for each observer. Results Reader A detected 47 abnormalities on CT images without CAD, and 33 of them were true-positive metastatic lesions. Using CAD, reader A detected 57 abnormalities, and 38 were true positives. The sensitivity increased from 0.717 to 0.826, and on ROC curve analysis, AUC with CAD was significantly higher than that without CAD (0.849 vs. 0.902, p = 0.021). Reader B detected 40 abnormalities on CT images without CAD, and 36 of them were true-positive metastatic lesions. Using CAD, reader B detected 44 abnormalities, and 39 were true positives. The sensitivity increased from 0.783 to 0.848, and AUC with CAD was nonsignificantly higher than that without CAD (0.889 vs. 0.910, p = 0.341). Both readers detected more osteolytic and osteoblastic
Optical 3D watermark based digital image watermarking for telemedicine
NASA Astrophysics Data System (ADS)
Li, Xiao Wei; Kim, Seok Tae
Region of interest (ROI) of a medical image is an area including important diagnostic information and must be stored without any distortion. This algorithm for application of watermarking technique for non-ROI of the medical image preserving ROI. The paper presents a 3D watermark based medical image watermarking scheme. In this paper, a 3D watermark object is first decomposed into 2D elemental image array (EIA) by a lenslet array, and then the 2D elemental image array data is embedded into the host image. The watermark extraction process is an inverse process of embedding. The extracted EIA through the computational integral imaging reconstruction (CIIR) technique, the 3D watermark can be reconstructed. Because the EIA is composed of a number of elemental images possesses their own perspectives of a 3D watermark object. Even though the embedded watermark data badly damaged, the 3D virtual watermark can be successfully reconstructed. Furthermore, using CAT with various rule number parameters, it is possible to get many channels for embedding. So our method can recover the weak point having only one transform plane in traditional watermarking methods. The effectiveness of the proposed watermarking scheme is demonstrated with the aid of experimental results.
Mixed reality orthognathic surgical simulation by entity model manipulation and 3D-image display
NASA Astrophysics Data System (ADS)
Shimonagayoshi, Tatsunari; Aoki, Yoshimitsu; Fushima, Kenji; Kobayashi, Masaru
In orthognathic surgery, the framing of 3D-surgical planning that considers the balance between the front and back positions and the symmetry of the jawbone, as well as the dental occlusion of teeth, is essential. In this study, a support system for orthodontic surgery to visualize the changes in the mandible and the occlusal condition and to determine the optimum position in mandibular osteotomy has been developed. By integrating the operating portion of a tooth model that is to determine the optimum occlusal position by manipulating the entity tooth model and the 3D-CT skeletal images (3D image display portion) that are simultaneously displayed in real-time, the determination of the mandibular position and posture in which the improvement of skeletal morphology and occlusal condition is considered, is possible. The realistic operation of the entity model and the virtual 3D image display enabled the construction of a surgical simulation system that involves augmented reality.
Progresses in 3D integral imaging with optical processing
NASA Astrophysics Data System (ADS)
Martínez-Corral, Manuel; Martínez-Cuenca, Raúl; Saavedra, Genaro; Navarro, Héctor; Pons, Amparo; Javidi, Bahram
Integral imaging is a promising technique for the acquisition and auto-stereoscopic display of 3D scenes with full parallax and without the need of any additional devices like special glasses. First suggested by Lippmann in the beginning of the 20th century, integral imaging is based in the intersection of ray cones emitted by a collection of 2D elemental images which store the 3D information of the scene. This paper is devoted to the study, from the ray optics point of view, of the optical effects and interaction with the observer of integral imaging systems.
DCT and DST Based Image Compression for 3D Reconstruction
NASA Astrophysics Data System (ADS)
Siddeq, Mohammed M.; Rodrigues, Marcos A.
This paper introduces a new method for 2D image compression whose quality is demonstrated through accurate 3D reconstruction using structured light techniques and 3D reconstruction from multiple viewpoints. The method is based on two discrete transforms: (1) A one-dimensional Discrete Cosine Transform (DCT) is applied to each row of the image. (2) The output from the previous step is transformed again by a one-dimensional Discrete Sine Transform (DST), which is applied to each column of data generating new sets of high-frequency components followed by quantization of the higher frequencies. The output is then divided into two parts where the low-frequency components are compressed by arithmetic coding and the high frequency ones by an efficient minimization encoding algorithm. At decompression stage, a binary search algorithm is used to recover the original high frequency components. The technique is demonstrated by compressing 2D images up to 99% compression ratio. The decompressed images, which include images with structured light patterns for 3D reconstruction and from multiple viewpoints, are of high perceptual quality yielding accurate 3D reconstruction. Perceptual assessment and objective quality of compression are compared with JPEG and JPEG2000 through 2D and 3D RMSE. Results show that the proposed compression method is superior to both JPEG and JPEG2000 concerning 3D reconstruction, and with equivalent perceptual quality to JPEG2000.
3D Subharmonic Ultrasound Imaging In Vitro and In Vivo
Eisenbrey, John R.; Sridharan, Anush; Machado, Priscilla; Zhao, Hongjia; Halldorsdottir, Valgerdur G.; Dave, Jaydev K.; Liu, Ji-Bin; Park, Suhyun; Dianis, Scott; Wallace, Kirk; Thomenius, Kai E.; Forsberg, F.
Rationale and Objectives While contrast-enhanced ultrasound imaging techniques such as harmonic imaging (HI) have evolved to reduce tissue signals using the nonlinear properties of the contrast agent, levels of background suppression have been mixed. Subharmonic imaging (SHI) offers near-complete tissue suppression by centering the receive bandwidth at half the transmitting frequency. In this work we demonstrate the feasibility of 3D SHI and compare it to 3D HI. Materials and Methods 3D HI and SHI were implemented on a Logiq 9 ultrasound scanner (GE Healthcare, Milwaukee, Wisconsin) with a 4D10L probe. Four-cycle SHI was implemented to transmit at 5.8 MHz and receive at 2.9 MHz, while 2-cycle HI was implemented to transmit at 5 MHz and receive at 10 MHz. The ultrasound contrast agent Definity (Lantheus Medical Imaging, North Billerica, MA) was imaged within a flow phantom and the lower pole of two canine kidneys in both HI and SHI modes. Contrast to tissue ratios (CTR) and rendered images were compared offline. Results SHI resulted in significant improvement in CTR levels relative to HI both in vitro (12.11±0.52 vs. 2.67±0.77, p<0.001) and in vivo (5.74±1.92 vs. 2.40±0.48, p=0.04). Rendered 3D SHI images provided better tissue suppression and a greater overall view of vessels in a flow phantom and canine renal vasculature. Conclusions The successful implementation of SHI in 3D allows imaging of vascular networks over a heterogeneous sample volume and should improve future diagnostic accuracy. Additionally, 3D SHI provides improved CTR values relative to 3D HI. PMID:22464198
Low Dose, Low Energy 3d Image Guidance during Radiotherapy
NASA Astrophysics Data System (ADS)
Moore, C. J.; Marchant, T.; Amer, A.; Sharrock, P.; Price, P.; Burton, D.
Patient kilo-voltage X-ray cone beam volumetric imaging for radiotherapy was first demonstrated on an Elekta Synergy mega-voltage X-ray linear accelerator. Subsequently low dose, reduced profile reconstruction imaging was shown to be practical for 3D geometric setup registration to pre-treatment planning images without compromising registration accuracy. Reconstruction from X-ray profiles gathered between treatment beam deliveries was also introduced. The innovation of zonal cone beam imaging promises significantly reduced doses to patients and improved soft tissue contrast in the tumour target zone. These developments coincided with the first dynamic 3D monitoring of continuous body topology changes in patients, at the moment of irradiation, using a laser interferometer. They signal the arrival of low dose, low energy 3D image guidance during radiotherapy itself.
3D Printing of CT Dataset: Validation of an Open Source and Consumer-Available Workflow.
Bortolotto, Chandra; Eshja, Esmeralda; Peroni, Caterina; Orlandi, Matteo A; Bizzotto, Nicola; Poggi, Paolo
The broad availability of cheap three-dimensional (3D) printing equipment has raised the need for a thorough analysis on its effects on clinical accuracy. Our aim is to determine whether the accuracy of 3D printing process is affected by the use of a low-budget workflow based on open source software and consumer's commercially available 3D printers. A group of test objects was scanned with a 64-slice computed tomography (CT) in order to build their 3D copies. CT datasets were elaborated using a software chain based on three free and open source software. Objects were printed out with a commercially available 3D printer. Both the 3D copies and the test objects were measured using a digital professional caliper. Overall, the objects' mean absolute difference between test objects and 3D copies is 0.23 mm and the mean relative difference amounts to 0.55 %. Our results demonstrate that the accuracy of 3D printing process remains high despite the use of a low-budget workflow.
Accelerated 3D catheter visualization from triplanar MR projection images.
Schirra, Carsten Oliver; Weiss, Steffen; Krueger, Sascha; Caulfield, Denis; Pedersen, Steen F; Razavi, Reza; Kozerke, Sebastian; Schaeffter, Tobias
One major obstacle for MR-guided catheterizations is long acquisition times associated with visualizing interventional devices. Therefore, most techniques presented hitherto rely on single-plane imaging to visualize the catheter. Recently, accelerated three-dimensional (3D) imaging based on compressed sensing has been proposed to reduce acquisition times. However, frame rates with this technique remain low, and the 3D reconstruction problem yields a considerable computational load. In X-ray angiography, it is well understood that the shape of interventional devices can be derived in 3D space from a limited number of projection images. In this work, this fact is exploited to develop a method for 3D visualization of active catheters from multiplanar two-dimensional (2D) projection MR images. This is favorable to 3D MRI as the overall number of acquired profiles, and consequently the acquisition time, is reduced. To further reduce measurement times, compressed sensing is employed. Furthermore, a novel single-channel catheter design is presented that combines a solenoidal tip coil in series with a single-loop antenna, enabling simultaneous tip tracking and shape visualization. The tracked tip and catheter properties provide constraints for compressed sensing reconstruction and subsequent 2D/3D curve fitting. The feasibility of the method is demonstrated in phantoms and in an in vivo pig experiment.
Prostate Mechanical Imaging: 3-D Image Composition and Feature Calculations
Egorov, Vladimir; Ayrapetyan, Suren; Sarvazyan, Armen P.
We have developed a method and a device entitled prostate mechanical imager (PMI) for the real-time imaging of prostate using a transrectal probe equipped with a pressure sensor array and position tracking sensor. PMI operation is based on measurement of the stress pattern on the rectal wall when the probe is pressed against the prostate. Temporal and spatial changes in the stress pattern provide information on the elastic structure of the gland and allow two-dimensional (2-D) and three-dimensional (3-D) reconstruction of prostate anatomy and assessment of prostate mechanical properties. The data acquired allow the calculation of prostate features such as size, shape, nodularity, consistency/hardness, and mobility. The PMI prototype has been validated in laboratory experiments on prostate phantoms and in a clinical study. The results obtained on model systems and in vivo images from patients prove that PMI has potential to become a diagnostic tool that could largely supplant DRE through its higher sensitivity, quantitative record storage, ease-of-use and inherent low cost. PMID:17024836
Exposing digital image forgeries by 3D reconstruction technology
NASA Astrophysics Data System (ADS)
Wang, Yongqiang; Xu, Xiaojing; Li, Zhihui; Liu, Haizhen; Li, Zhigang; Huang, Wei
Digital images are easy to tamper and edit due to availability of powerful image processing and editing software. Especially, forged images by taking from a picture of scene, because of no manipulation was made after taking, usual methods, such as digital watermarks, statistical correlation technology, can hardly detect the traces of image tampering. According to image forgery characteristics, a method, based on 3D reconstruction technology, which detect the forgeries by discriminating the dimensional relationship of each object appeared on image, is presented in this paper. This detection method includes three steps. In the first step, all the parameters of images were calibrated and each crucial object on image was chosen and matched. In the second step, the 3D coordinates of each object were calculated by bundle adjustment. In final step, the dimensional relationship of each object was analyzed. Experiments were designed to test this detection method; the 3D reconstruction and the forged image 3D reconstruction were computed independently. Test results show that the fabricating character in digital forgeries can be identified intuitively by this method.
Building 3D scenes from 2D image sequences
NASA Astrophysics Data System (ADS)
Cristea, Paul D.
Sequences of 2D images, taken by a single moving video receptor, can be fused to generate a 3D representation. This dynamic stereopsis exists in birds and reptiles, whereas the static binocular stereopsis is common in mammals, including humans. Most multimedia computer vision systems for stereo image capture, transmission, processing, storage and retrieval are based on the concept of binocularity. As a consequence, their main goal is to acquire, conserve and enhance pairs of 2D images able to generate a 3D visual perception in a human observer. Stereo vision in birds is based on the fusion of images captured by each eye, with previously acquired and memorized images from the same eye. The process goes on simultaneously and conjointly for both eyes and generates an almost complete all-around visual field. As a consequence, the baseline distance is no longer fixed, as in the case of binocular 3D view, but adjustable in accordance with the distance to the object of main interest, allowing a controllable depth effect. Moreover, the synthesized 3D scene can have a better resolution than each individual 2D image in the sequence. Compression of 3D scenes can be achieved, and stereo transmissions with lower bandwidth requirements can be developed.
3D thermography imaging standardization technique for inflammation diagnosis
NASA Astrophysics Data System (ADS)
Ju, Xiangyang; Nebel, Jean-Christophe; Siebert, J. Paul
We develop a 3D thermography imaging standardization technique to allow quantitative data analysis. Medical Digital Infrared Thermal Imaging is very sensitive and reliable mean of graphically mapping and display skin surface temperature. It allows doctors to visualise in colour and quantify temperature changes in skin surface. The spectrum of colours indicates both hot and cold responses which may co-exist if the pain associate with an inflammatory focus excites an increase in sympathetic activity. However, due to thermograph provides only qualitative diagnosis information, it has not gained acceptance in the medical and veterinary communities as a necessary or effective tool in inflammation and tumor detection. Here, our technique is based on the combination of visual 3D imaging technique and thermal imaging technique, which maps the 2D thermography images on to 3D anatomical model. Then we rectify the 3D thermogram into a view independent thermogram and conform it a standard shape template. The combination of these imaging facilities allows the generation of combined 3D and thermal data from which thermal signatures can be quantified.
Srinivasan, Subhadra; Carpenter, Colin; Pogue, Brian W.; Paulsen, Keith D.
Multimodality imaging systems combining optical techniques with MRI/CT provide high-resolution functional characterization of tissue by imaging molecular and vascular biomarkers. To optimize these hybrid systems for clinical use, faster and automatable algorithms are required for 3-D imaging. Towards this end, a boundary element model was used to incorporate tissue boundaries from MRI/CT into image formation process. This method uses surface rendering to describe light propagation in 3-D using diffusion equation. Parallel computing provided speedup of up to 54% in time of computation. Simulations showed that location of NIRS probe was crucial for quantitatively accurate estimation of tumor response. A change of up to 61% was seen between cycles 1 and 3 in monitoring tissue response to neoadjuvant chemotherapy. PMID:20523751
3D-3D registration of partial capitate bones using spin-images
NASA Astrophysics Data System (ADS)
Breighner, Ryan; Holmes, David R.; Leng, Shuai; An, Kai-Nan; McCollough, Cynthia; Zhao, Kristin
It is often necessary to register partial objects in medical imaging. Due to limited field of view (FOV), the entirety of an object cannot always be imaged. This study presents a novel application of an existing registration algorithm to this problem. The spin-image algorithm [1] creates pose-invariant representations of global shape with respect to individual mesh vertices. These `spin-images,' are then compared for two different poses of the same object to establish correspondences and subsequently determine relative orientation of the poses. In this study, the spin-image algorithm is applied to 4DCT-derived capitate bone surfaces to assess the relative accuracy of registration with various amounts of geometry excluded. The limited longitudinal coverage under the 4DCT technique (38.4mm, [2]), results in partial views of the capitate when imaging wrist motions. This study assesses the ability of the spin-image algorithm to register partial bone surfaces by artificially restricting the capitate geometry available for registration. Under IRB approval, standard static CT and 4DCT scans were obtained on a patient. The capitate was segmented from the static CT and one phase of 4DCT in which the whole bone was available. Spin-image registration was performed between the static and 4DCT. Distal portions of the 4DCT capitate (10-70%) were then progressively removed and registration was repeated. Registration accuracy was evaluated by angular errors and the percentage of sub-resolution fitting. It was determined that 60% of the distal capitate could be omitted without appreciable effect on registration accuracy using the spin-image algorithm (angular error < 1.5 degree, sub-resolution fitting < 98.4%).
3D Kidney Segmentation from Abdominal Images Using Spatial-Appearance Models
Khalifa, Fahmi; Soliman, Ahmed; Gimel'farb, Georgy
Kidney segmentation is an essential step in developing any noninvasive computer-assisted diagnostic system for renal function assessment. This paper introduces an automated framework for 3D kidney segmentation from dynamic computed tomography (CT) images that integrates discriminative features from the current and prior CT appearances into a random forest classification approach. To account for CT images' inhomogeneities, we employ discriminate features that are extracted from a higher-order spatial model and an adaptive shape model in addition to the first-order CT appearance. To model the interactions between CT data voxels, we employed a higher-order spatial model, which adds the triple and quad clique families to the traditional pairwise clique family. The kidney shape prior model is built using a set of training CT data and is updated during segmentation using not only region labels but also voxels' appearances in neighboring spatial voxel locations. Our framework performance has been evaluated on in vivo dynamic CT data collected from 20 subjects and comprises multiple 3D scans acquired before and after contrast medium administration. Quantitative evaluation between manually and automatically segmented kidney contours using Dice similarity, percentage volume differences, and 95th-percentile bidirectional Hausdorff distances confirms the high accuracy of our approach. PMID:28280519
A 3D surface imaging system for assessing human obesity
NASA Astrophysics Data System (ADS)
Xu, B.; Yu, W.; Yao, M.; Yao, X.; Li, Q.; Pepper, M. R.; Freeland-Graves, J. H.
The increasing prevalence of obesity suggests a need to develop a convenient, reliable and economical tool for assessment of this condition. Three-dimensional (3D) body surface imaging has emerged as an exciting technology for estimation of body composition. This paper presents a new 3D body imaging system, which was designed for enhanced portability, affordability, and functionality. In this system, stereo vision technology was used to satisfy the requirements for a simple hardware setup and fast image acquisitions. The portability of the system was created via a two-stand configuration, and the accuracy of body volume measurements was improved by customizing stereo matching and surface reconstruction algorithms that target specific problems in 3D body imaging. Body measurement functions dedicated to body composition assessment also were developed. The overall performance of the system was evaluated in human subjects by comparison to other conventional anthropometric methods, as well as air displacement plethysmography, for body fat assessment.
Visualization and analysis of 3D microscopic images.
Long, Fuhui; Zhou, Jianlong; Peng, Hanchuan
In a wide range of biological studies, it is highly desirable to visualize and analyze three-dimensional (3D) microscopic images. In this primer, we first introduce several major methods for visualizing typical 3D images and related multi-scale, multi-time-point, multi-color data sets. Then, we discuss three key categories of image analysis tasks, namely segmentation, registration, and annotation. We demonstrate how to pipeline these visualization and analysis modules using examples of profiling the single-cell gene-expression of C. elegans and constructing a map of stereotyped neurite tracts in a fruit fly brain.
Visualization and Analysis of 3D Microscopic Images
Long, Fuhui; Zhou, Jianlong; Peng, Hanchuan
In a wide range of biological studies, it is highly desirable to visualize and analyze three-dimensional (3D) microscopic images. In this primer, we first introduce several major methods for visualizing typical 3D images and related multi-scale, multi-time-point, multi-color data sets. Then, we discuss three key categories of image analysis tasks, namely segmentation, registration, and annotation. We demonstrate how to pipeline these visualization and analysis modules using examples of profiling the single-cell gene-expression of C. elegans and constructing a map of stereotyped neurite tracts in a fruit fly brain. PMID:22719236
3D Image Reconstruction: Determination of Pattern Orientation
Blankenbecler, Richard
The problem of determining the euler angles of a randomly oriented 3-D object from its 2-D Fraunhofer diffraction patterns is discussed. This problem arises in the reconstruction of a positive semi-definite 3-D object using oversampling techniques. In such a problem, the data consists of a measured set of magnitudes from 2-D tomographic images of the object at several unknown orientations. After the orientation angles are determined, the object itself can then be reconstructed by a variety of methods using oversampling, the magnitude data from the 2-D images, physical constraints on the image and then iteration to determine the phases.
Accuracy of 3D Imaging Software in Cephalometric Analysis
Imaging and Communication in Medicine ( DICOM ) files into personal computer-based software to enable 3D reconstruction of the craniofacial skeleton. These...tissue profile. CBCT data can be imported as DICOM files into personal computer–based software to provide 3D reconstruction of the craniofacial...been acquired for the three pig models. The CBCT data were exported into DICOM multi-file format. They will be imported into a proprietary
3D Image Display Courses for Information Media Students.
Yanaka, Kazuhisa; Yamanouchi, Toshiaki
Three-dimensional displays are used extensively in movies and games. These displays are also essential in mixed reality, where virtual and real spaces overlap. Therefore, engineers and creators should be trained to master 3D display technologies. For this reason, the Department of Information Media at the Kanagawa Institute of Technology has launched two 3D image display courses specifically designed for students who aim to become information media engineers and creators.
High resolution 3D dosimetry for microbeam radiation therapy using optical CT
NASA Astrophysics Data System (ADS)
McErlean, C.; Bräuer-Krisch, E.; Adamovics, J.; Leach, M. O.; Doran, S. J.
Optical Computed Tomography (CT) is a promising technique for dosimetry of Microbeam Radiation Therapy (MRT), providing high resolution 3D dose maps. Here different MRT irradiation geometries are visualised showing the potential of Optical CT as a tool for future MRT trials. The Peak-to-Valley dose ratio (PVDR) is calculated to be 7 at a depth of 3mm in the radiochromic dosimeter PRESAGE®. This is significantly lower than predicted values and possible reasons for this are discussed.
3D image analysis of abdominal aortic aneurysm
NASA Astrophysics Data System (ADS)
Subasic, Marko; Loncaric, Sven; Sorantin, Erich
In this paper we propose a technique for 3-D segmentation of abdominal aortic aneurysm (AAA) from computed tomography angiography (CTA) images. Output data (3-D model) form the proposed method can be used for measurement of aortic shape and dimensions. Knowledge of aortic shape and size is very important in planning of minimally invasive procedure that is for selection of appropriate stent graft device for treatment of AAA. The technique is based on a 3-D deformable model and utilizes the level-set algorithm for implementation of the method. The method performs 3-D segmentation of CTA images and extracts a 3-D model of aortic wall. Once the 3-D model of aortic wall is available it is easy to perform all required measurements for appropriate stent graft selection. The method proposed in this paper uses the level-set algorithm for deformable models, instead of the classical snake algorithm. The main advantage of the level set algorithm is that it enables easy segmentation of complex structures, surpassing most of the drawbacks of the classical approach. We have extended the deformable model to incorporate the a priori knowledge about the shape of the AAA. This helps direct the evolution of the deformable model to correctly segment the aorta. The algorithm has been implemented in IDL and C languages. Experiments have been performed using real patient CTA images and have shown good results.
Gastric Contraction Imaging System Using a 3-D Endoscope.
Yoshimoto, Kayo; Yamada, Kenji; Watabe, Kenji; Takeda, Maki; Nishimura, Takahiro; Kido, Michiko; Nagakura, Toshiaki; Takahashi, Hideya; Nishida, Tsutomu; Iijima, Hideki; Tsujii, Masahiko; Takehara, Tetsuo; Ohno, Yuko
This paper presents a gastric contraction imaging system for assessment of gastric motility using a 3-D endoscope. Gastrointestinal diseases are mainly based on morphological abnormalities. However, gastrointestinal symptoms are sometimes apparent without visible abnormalities. One of the major factors for these diseases is abnormal gastrointestinal motility. For assessment of gastric motility, a gastric motility imaging system is needed. To assess the dynamic motility of the stomach, the proposed system measures 3-D gastric contractions derived from a 3-D profile of the stomach wall obtained with a developed 3-D endoscope. After obtaining contraction waves, their frequency, amplitude, and speed of propagation can be calculated using a Gaussian function. The proposed system was evaluated for 3-D measurements of several objects with known geometries. The results showed that the surface profiles could be obtained with an error of [Formula: see text] of the distance between two different points on images. Subsequently, we evaluated the validity of a prototype system using a wave simulated model. In the experiment, the amplitude and position of waves could be measured with 1-mm accuracy. The present results suggest that the proposed system can measure the speed and amplitude of contractions. This system has low invasiveness and can assess the motility of the stomach wall directly in a 3-D manner. Our method can be used for examination of gastric morphological and functional abnormalities.
A prototype fan-beam optical CT scanner for 3D dosimetry
Campbell, Warren G.; Rudko, D. A.; Braam, Nicolas A.; Jirasek, Andrew; Wells, Derek M.
flask registration technique was shown to achieve submillimetre and subdegree placement accuracy. Dosimetry protocol investigations emphasize the need to allow gel dosimeters to cool gradually and to be scanned while at room temperature. Preliminary tests show that considerable noise reduction can be achieved with sinogram filtering and by binning image pixels into more clinically relevant grid sizes. Conclusions: This paper describes a new optical CT scanner for 3D radiation dosimetry. Tests demonstrate that it is capable of imaging both absorption-based and scatter-based samples of high opacities. Imaging protocol and gel dosimeter manufacture techniques have been adapted to produce optimal reconstruction results. These optimal results will require suitable filtering and binning techniques for noise reduction purposes.
Visualising, segmenting and analysing heterogenous glacigenic sediments using 3D x-ray CT.
NASA Astrophysics Data System (ADS)
Carr, Simon; Diggens, Lucy; Groves, John; O'Sullivan, Catherine; Marsland, Rhona
, especially with regard to using such data to improve understanding of mechanisms of particle motion and fabric development during subglacial strain. In this study, we present detailed investigation of subglacial tills from the UK, Iceland and Poland, to explore the challenges in segmenting these highly variable sediment bodies for 3D microfabric analysis. A calibration study is reported to compare various approaches to CT data segmentation to manually segmented datasets, from which an optimal workflow is developed, using a combination of the WEKA Trainable Segmentation tool within ImageJ to segment the data, followed by object-based analysis using Blob3D. We then demonstrate the value of this analysis through the analysis of true 3D microfabric data from a Last Glacial Maximum till deposit located at Morston, North Norfolk. Seven undisturbed sediment samples were scanned and analysed using high-resolution 3D X-ray computed tomography. Large (~5,000 to ~16,000) populations of individual particles are objectively and systematically segmented and identified. These large datasets are then subject to detailed interrogation using bespoke code for analysing particle fabric within Matlab, including the application of fabric-tensor analysis, by which fabrics can be weighted and scaled by key variables such as size and shape. We will present initial findings from these datasets, focusing particularly on overcoming the methodological challenges of obtaining robust datasets of sediments with highly complex, mixed compositional sediments.
Automatic Masking for Robust 3D-2D Image Registration in Image-Guided Spine Surgery
Ketcha, M. D.; De Silva, T.; Uneri, A.; Kleinszig, G.; Vogt, S.; Wolinsky, J.-P.; Siewerdsen, J. H.
During spinal neurosurgery, patient-specific information, planning, and annotation such as vertebral labels can be mapped from preoperative 3D CT to intraoperative 2D radiographs via image-based 3D-2D registration. Such registration has been shown to provide a potentially valuable means of decision support in target localization as well as quality assurance of the surgical product. However, robust registration can be challenged by mismatch in image content between the preoperative CT and intraoperative radiographs, arising, for example, from anatomical deformation or the presence of surgical tools within the radiograph. In this work, we develop and evaluate methods for automatically mitigating the effect of content mismatch by leveraging the surgical planning data to assign greater weight to anatomical regions known to be reliable for registration and vital to the surgical task while removing problematic regions that are highly deformable or often occluded by surgical tools. We investigated two approaches to assigning variable weight (i.e., "masking") to image content and/or the similarity metric: (1) masking the preoperative 3D CT ("volumetric masking"); and (2) masking within the 2D similarity metric calculation ("projection masking"). The accuracy of registration was evaluated in terms of projection distance error (PDE) in 61 cases selected from an IRB-approved clinical study. The best performing of the masking techniques was found to reduce the rate of gross failure (PDE > 20 mm) from 11.48% to 5.57% in this challenging retrospective data set. These approaches provided robustness to content mismatch and eliminated distinct failure modes of registration. Such improvement was gained without additional workflow and has motivated incorporation of the masking methods within a system under development for prospective clinical studies. PMID:27335531
Automatic Masking for Robust 3D-2D Image Registration in Image-Guided Spine Surgery.
Ketcha, M D; De Silva, T; Uneri, A; Kleinszig, G; Vogt, S; Wolinsky, J-P; Siewerdsen, J H
During spinal neurosurgery, patient-specific information, planning, and annotation such as vertebral labels can be mapped from preoperative 3D CT to intraoperative 2D radiographs via image-based 3D-2D registration. Such registration has been shown to provide a potentially valuable means of decision support in target localization as well as quality assurance of the surgical product. However, robust registration can be challenged by mismatch in image content between the preoperative CT and intraoperative radiographs, arising, for example, from anatomical deformation or the presence of surgical tools within the radiograph. In this work, we develop and evaluate methods for automatically mitigating the effect of content mismatch by leveraging the surgical planning data to assign greater weight to anatomical regions known to be reliable for registration and vital to the surgical task while removing problematic regions that are highly deformable or often occluded by surgical tools. We investigated two approaches to assigning variable weight (i.e., "masking") to image content and/or the similarity metric: (1) masking the preoperative 3D CT ("volumetric masking"); and (2) masking within the 2D similarity metric calculation ("projection masking"). The accuracy of registration was evaluated in terms of projection distance error (PDE) in 61 cases selected from an IRB-approved clinical study. The best performing of the masking techniques was found to reduce the rate of gross failure (PDE > 20 mm) from 11.48% to 5.57% in this challenging retrospective data set. These approaches provided robustness to content mismatch and eliminated distinct failure modes of registration. Such improvement was gained without additional workflow and has motivated incorporation of the masking methods within a system under development for prospective clinical studies.
Automatic masking for robust 3D-2D image registration in image-guided spine surgery
NASA Astrophysics Data System (ADS)
Ketcha, M. D.; De Silva, T.; Uneri, A.; Kleinszig, G.; Vogt, S.; Wolinsky, J.-P.; Siewerdsen, J. H.
During spinal neurosurgery, patient-specific information, planning, and annotation such as vertebral labels can be mapped from preoperative 3D CT to intraoperative 2D radiographs via image-based 3D-2D registration. Such registration has been shown to provide a potentially valuable means of decision support in target localization as well as quality assurance of the surgical product. However, robust registration can be challenged by mismatch in image content between the preoperative CT and intraoperative radiographs, arising, for example, from anatomical deformation or the presence of surgical tools within the radiograph. In this work, we develop and evaluate methods for automatically mitigating the effect of content mismatch by leveraging the surgical planning data to assign greater weight to anatomical regions known to be reliable for registration and vital to the surgical task while removing problematic regions that are highly deformable or often occluded by surgical tools. We investigated two approaches to assigning variable weight (i.e., "masking") to image content and/or the similarity metric: (1) masking the preoperative 3D CT ("volumetric masking"); and (2) masking within the 2D similarity metric calculation ("projection masking"). The accuracy of registration was evaluated in terms of projection distance error (PDE) in 61 cases selected from an IRB-approved clinical study. The best performing of the masking techniques was found to reduce the rate of gross failure (PDE > 20 mm) from 11.48% to 5.57% in this challenging retrospective data set. These approaches provided robustness to content mismatch and eliminated distinct failure modes of registration. Such improvement was gained without additional workflow and has motivated incorporation of the masking methods within a system under development for prospective clinical studies.
2D/3D Image Registration using Regression Learning
Chou, Chen-Rui; Frederick, Brandon; Mageras, Gig; Chang, Sha; Pizer, Stephen
In computer vision and image analysis, image registration between 2D projections and a 3D image that achieves high accuracy and near real-time computation is challenging. In this paper, we propose a novel method that can rapidly detect an object's 3D rigid motion or deformation from a 2D projection image or a small set thereof. The method is called CLARET (Correction via Limited-Angle Residues in External Beam Therapy) and consists of two stages: registration preceded by shape space and regression learning. In the registration stage, linear operators are used to iteratively estimate the motion/deformation parameters based on the current intensity residue between the target projec-tion(s) and the digitally reconstructed radiograph(s) (DRRs) of the estimated 3D image. The method determines the linear operators via a two-step learning process. First, it builds a low-order parametric model of the image region's motion/deformation shape space from its prior 3D images. Second, using learning-time samples produced from the 3D images, it formulates the relationships between the model parameters and the co-varying 2D projection intensity residues by multi-scale linear regressions. The calculated multi-scale regression matrices yield the coarse-to-fine linear operators used in estimating the model parameters from the 2D projection intensity residues in the registration. The method's application to Image-guided Radiation Therapy (IGRT) requires only a few seconds and yields good results in localizing a tumor under rigid motion in the head and neck and under respiratory deformation in the lung, using one treatment-time imaging 2D projection or a small set thereof. PMID:24058278
MO-C-18A-01: Advances in Model-Based 3D Image Reconstruction
Chen, G; Pan, X; Stayman, J; Samei, E
Recent years have seen the emergence of CT image reconstruction techniques that exploit physical models of the imaging system, photon statistics, and even the patient to achieve improved 3D image quality and/or reduction of radiation dose. With numerous advantages in comparison to conventional 3D filtered backprojection, such techniques bring a variety of challenges as well, including: a demanding computational load associated with sophisticated forward models and iterative optimization methods; nonlinearity and nonstationarity in image quality characteristics; a complex dependency on multiple free parameters; and the need to understand how best to incorporate prior information (including patient-specific prior images) within the reconstruction process. The advantages, however, are even greater – for example: improved image quality; reduced dose; robustness to noise and artifacts; task-specific reconstruction protocols; suitability to novel CT imaging platforms and noncircular orbits; and incorporation of known characteristics of the imager and patient that are conventionally discarded. This symposium features experts in 3D image reconstruction, image quality assessment, and the translation of such methods to emerging clinical applications. Dr. Chen will address novel methods for the incorporation of prior information in 3D and 4D CT reconstruction techniques. Dr. Pan will show recent advances in optimization-based reconstruction that enable potential reduction of dose and sampling requirements. Dr. Stayman will describe a "task-based imaging" approach that leverages models of the imaging system and patient in combination with a specification of the imaging task to optimize both the acquisition and reconstruction process. Dr. Samei will describe the development of methods for image quality assessment in such nonlinear reconstruction techniques and the use of these methods to characterize and optimize image quality and dose in a spectrum of clinical
3D image analysis of abdominal aortic aneurysm
NASA Astrophysics Data System (ADS)
Subasic, Marko; Loncaric, Sven; Sorantin, Erich
This paper presents a method for 3-D segmentation of abdominal aortic aneurysm from computed tomography angiography images. The proposed method is automatic and requires minimal user assistance. Segmentation is performed in two steps. First inner and then outer aortic border is segmented. Those two steps are different due to different image conditions on two aortic borders. Outputs of these two segmentations give a complete 3-D model of abdominal aorta. Such a 3-D model is used in measurements of aneurysm area. The deformable model is implemented using the level-set algorithm due to its ability to describe complex shapes in natural manner which frequently occur in pathology. In segmentation of outer aortic boundary we introduced some knowledge based preprocessing to enhance and reconstruct low contrast aortic boundary. The method has been implemented in IDL and C languages. Experiments have been performed using real patient CTA images and have shown good results.
3D quantitative analysis of brain SPECT images
NASA Astrophysics Data System (ADS)
Loncaric, Sven; Ceskovic, Ivan; Petrovic, Ratimir; Loncaric, Srecko
The main purpose of this work is to develop a computer-based technique for quantitative analysis of 3-D brain images obtained by single photon emission computed tomography (SPECT). In particular, the volume and location of ischemic lesion and penumbra is important for early diagnosis and treatment of infracted regions of the brain. SPECT imaging is typically used as diagnostic tool to assess the size and location of the ischemic lesion. The segmentation method presented in this paper utilizes a 3-D deformable model in order to determine size and location of the regions of interest. The evolution of the model is computed using a level-set implementation of the algorithm. In addition to 3-D deformable model the method utilizes edge detection and region growing for realization of a pre-processing. Initial experimental results have shown that the method is useful for SPECT image analysis.
Interactive visualization of multiresolution image stacks in 3D.
Trotts, Issac; Mikula, Shawn; Jones, Edward G
Conventional microscopy, electron microscopy, and imaging techniques such as MRI and PET commonly generate large stacks of images of the sectioned brain. In other domains, such as neurophysiology, variables such as space or time are also varied along a stack axis. Digital image sizes have been progressively increasing and in virtual microscopy, it is now common to work with individual image sizes that are several hundred megapixels and several gigabytes in size. The interactive visualization of these high-resolution, multiresolution images in 2D has been addressed previously [Sullivan, G., and Baker, R., 1994. Efficient quad-tree coding of images and video. IEEE Trans. Image Process. 3 (3), 327-331]. Here, we describe a method for interactive visualization of multiresolution image stacks in 3D. The method, characterized as quad-tree based multiresolution image stack interactive visualization using a texel projection based criterion, relies on accessing and projecting image tiles from multiresolution image stacks in such a way that, from the observer's perspective, image tiles all appear approximately the same size even though they are accessed from different tiers within the images comprising the stack. This method enables efficient navigation of high-resolution image stacks. We implement this method in a program called StackVis, which is a Windows-based, interactive 3D multiresolution image stack visualization system written in C++ and using OpenGL. It is freely available at http://brainmaps.org.
Medical image retrieval system using multiple features from 3D ROIs
NASA Astrophysics Data System (ADS)
Lu, Hongbing; Wang, Weiwei; Liao, Qimei; Zhang, Guopeng; Zhou, Zhiming
Compared to a retrieval using global image features, features extracted from regions of interest (ROIs) that reflect distribution patterns of abnormalities would benefit more for content-based medical image retrieval (CBMIR) systems. Currently, most CBMIR systems have been designed for 2D ROIs, which cannot reflect 3D anatomical features and region distribution of lesions comprehensively. To further improve the accuracy of image retrieval, we proposed a retrieval method with 3D features including both geometric features such as Shape Index (SI) and Curvedness (CV) and texture features derived from 3D Gray Level Co-occurrence Matrix, which were extracted from 3D ROIs, based on our previous 2D medical images retrieval system. The system was evaluated with 20 volume CT datasets for colon polyp detection. Preliminary experiments indicated that the integration of morphological features with texture features could improve retrieval performance greatly. The retrieval result using features extracted from 3D ROIs accorded better with the diagnosis from optical colonoscopy than that based on features from 2D ROIs. With the test database of images, the average accuracy rate for 3D retrieval method was 76.6%, indicating its potential value in clinical application.
Episcopic 3D Imaging Methods: Tools for Researching Gene Function
Weninger, Wolfgang J; Geyer, Stefan H
This work aims at describing episcopic 3D imaging methods and at discussing how these methods can contribute to researching the genetic mechanisms driving embryogenesis and tissue remodelling, and the genesis of pathologies. Several episcopic 3D imaging methods exist. The most advanced are capable of generating high-resolution volume data (voxel sizes from 0.5x0.5x1 µm upwards) of small to large embryos of model organisms and tissue samples. Beside anatomy and tissue architecture, gene expression and gene product patterns can be three dimensionally analyzed in their precise anatomical and histological context with the aid of whole mount in situ hybridization or whole mount immunohistochemical staining techniques. Episcopic 3D imaging techniques were and are employed for analyzing the precise morphological phenotype of experimentally malformed, randomly produced, or genetically engineered embryos of biomedical model organisms. It has been shown that episcopic 3D imaging also fits for describing the spatial distribution of genes and gene products during embryogenesis, and that it can be used for analyzing tissue samples of adult model animals and humans. The latter offers the possibility to use episcopic 3D imaging techniques for researching the causality and treatment of pathologies or for staging cancer. Such applications, however, are not yet routine and currently only preliminary results are available. We conclude that, although episcopic 3D imaging is in its very beginnings, it represents an upcoming methodology, which in short terms will become an indispensable tool for researching the genetic regulation of embryo development as well as the genesis of malformations and diseases. PMID:19452045
A hybrid approach for fusing 4D-MRI temporal information with 3D-CT for the study of lung and lung tumor motion
Yang, Y. X.; Van Reeth, E.; Poh, C. L.; Teo, S.-K.; Tan, C. H.; Tham, I. W. K.
Purpose: Accurate visualization of lung motion is important in many clinical applications, such as radiotherapy of lung cancer. Advancement in imaging modalities [e.g., computed tomography (CT) and MRI] has allowed dynamic imaging of lung and lung tumor motion. However, each imaging modality has its advantages and disadvantages. The study presented in this paper aims at generating synthetic 4D-CT dataset for lung cancer patients by combining both continuous three-dimensional (3D) motion captured by 4D-MRI and the high spatial resolution captured by CT using the authors' proposed approach. Methods: A novel hybrid approach based on deformable image registration (DIR) and finite element method simulation was developed to fuse a static 3D-CT volume (acquired under breath-hold) and the 3D motion information extracted from 4D-MRI dataset, creating a synthetic 4D-CT dataset. Results: The study focuses on imaging of lung and lung tumor. Comparing the synthetic 4D-CT dataset with the acquired 4D-CT dataset of six lung cancer patients based on 420 landmarks, accurate results (average error <2 mm) were achieved using the authors' proposed approach. Their hybrid approach achieved a 40% error reduction (based on landmarks assessment) over using only DIR techniques. Conclusions: The synthetic 4D-CT dataset generated has high spatial resolution, has excellent lung details, and is able to show movement of lung and lung tumor over multiple breathing cycles.
Proposed traceable structural resolution protocols for 3D imaging systems
NASA Astrophysics Data System (ADS)
MacKinnon, David; Beraldin, J.-Angelo; Cournoyer, Luc; Carrier, Benjamin; Blais, François
A protocol for determining structural resolution using a potentially-traceable reference material is proposed. Where possible, terminology was selected to conform to those published in ISO JCGM 200:2008 (VIM) and ASTM E 2544-08 documents. The concepts of resolvability and edge width are introduced to more completely describe the ability of an optical non-contact 3D imaging system to resolve small features. A distinction is made between 3D range cameras, that obtain spatial data from the total field of view at once, and 3D range scanners, that accumulate spatial data for the total field of view over time. The protocol is presented through the evaluation of a 3D laser line range scanner.
Image quality of a cone beam O-arm 3D imaging system
NASA Astrophysics Data System (ADS)
Zhang, Jie; Weir, Victor; Lin, Jingying; Hsiung, Hsiang; Ritenour, E. Russell
The O-arm is a cone beam imaging system designed primarily to support orthopedic surgery and is also used for image-guided and vascular surgery. Using a gantry that can be opened or closed, the O-arm can function as a 2-dimensional (2D) fluoroscopy device or collect 3-dimensional (3D) volumetric imaging data like a CT system. Clinical applications of the O-arm in spine surgical procedures, assessment of pedicle screw position, and kyphoplasty procedures show that the O-arm 3D mode provides enhanced imaging information compared to radiographs or fluoroscopy alone. In this study, the image quality of an O-arm system was quantitatively evaluated. A 20 cm diameter CATPHAN 424 phantom was scanned using the pre-programmed head protocols: small/medium (120 kVp, 100 mAs), large (120 kVp, 128 mAs), and extra-large (120 kVp, 160 mAs) in 3D mode. High resolution reconstruction mode (512×512×0.83 mm) was used to reconstruct images for the analysis of low and high contrast resolution, and noise power spectrum. MTF was measured using the point spread function. The results show that the O-arm image is uniform but with a noise pattern which cannot be removed by simply increasing the mAs. The high contrast resolution of the O-arm system was approximately 9 lp/cm. The system has a 10% MTF at 0.45 mm. The low-contrast resolution cannot be decided due to the noise pattern. For surgery where locations of a structure are emphasized over a survey of all image details, the image quality of the O-arm is well accepted clinically.
Association between condylar asymmetry and temporo- mandibular disorders using 3D-CT
Yáñez-Vico, Rosa M.; Iglesias-Linares, Alejandro; Torres-Lagares, Daniel; Solano-Reina, Enrique
Objectives: Using reconstructed three-dimensional computed tomography (3D-CT) models, the purpose of this study was to analyze and compare mandibular condyle morphology in patients with and without temporomandibular disorder (TMD). Study Design: Thirty-two patients were divided into two groups: the first comprised those with TMD (n=18), and the second those who did not have TMD (n=14). A CT of each patient was obtained and reconstructed as a 3D model. The 64 resulting 3D condylar models were evaluated for possible TMD-associated length, width and height asymmetries of the condylar process. Descriptive statistics were used to assess the results and student's t tests applied to compare the two groups. Results: Statistically significant (p<0.05) vertical, mediolateral and sagittal asymmetries of the condylar process were observed between TMD and non-TMD groups. TMD patients showed less condylar height (p<0.05) in comparison with their asymptomatic counterparts. Conclusions: Using 3D-CT, it was shown that condylar width, height and length asymmetries were a common feature of TMD. Key words:Condilar asymmetry, 3D-computed tomography, X-ray diagnosis , maxillofacial surgery, orthodontics. PMID:22322511
Image quality enhancement and computation acceleration of 3D holographic display using a symmetrical 3D GS algorithm.
Zhou, Pengcheng; Bi, Yong; Sun, Minyuan; Wang, Hao; Li, Fang; Qi, Yan
The 3D Gerchberg-Saxton (GS) algorithm can be used to compute a computer-generated hologram (CGH) to produce a 3D holographic display. But, using the 3D GS method, there exists a serious distortion in reconstructions of binary input images. We have eliminated the distortion and improved the image quality of the reconstructions by a maximum of 486%, using a symmetrical 3D GS algorithm that is developed based on a traditional 3D GS algorithm. In addition, the hologram computation speed has been accelerated by 9.28 times, which is significant for real-time holographic displays.
Application of 3D X-ray CT data sets to finite element analysis
Bossart, P.L.; Martz, H.E.; Brand, H.R.; Hollerbach, K.
Finite Element Modeling (FEM) is becoming more important as industry drives toward concurrent engineering. A fundamental hindrance to fully exploiting the power of FEM is the human effort required to acquire complex part geometry, particularly as-built geometry, as a FEM mesh. Many Quantitative Non Destructive Evaluation (QNDE) techniques that produce three-dimensional (3D) data sets provide a substantial reduction in the effort required to apply FEM to as-built parts. This paper describes progress at LLNL on the application of 3D X-ray computed tomography (CT) data sets to more rapidly produce high-quality FEM meshes of complex, as-built geometries. Issues related to the volume segmentation of the 3D CT data as well as the use of this segmented data to tailor generic hexahedral FEM meshes to part specific geometries are discussed. The application of these techniques to FEM analysis in the medical field is reported here.
Efficiency analysis for 3D filtering of multichannel images
NASA Astrophysics Data System (ADS)
Kozhemiakin, Ruslan A.; Rubel, Oleksii; Abramov, Sergey K.; Lukin, Vladimir V.; Vozel, Benoit; Chehdi, Kacem
Modern remote sensing systems basically acquire images that are multichannel (dual- or multi-polarization, multi- and hyperspectral) where noise, usually with different characteristics, is present in all components. If noise is intensive, it is desirable to remove (suppress) it before applying methods of image classification, interpreting, and information extraction. This can be done using one of two approaches - by component-wise or by vectorial (3D) filtering. The second approach has shown itself to have higher efficiency if there is essential correlation between multichannel image components as this often happens for multichannel remote sensing data of different origin. Within the class of 3D filtering techniques, there are many possibilities and variations. In this paper, we consider filtering based on discrete cosine transform (DCT) and pay attention to two aspects of processing. First, we study in detail what changes in DCT coefficient statistics take place for 3D denoising compared to component-wise processing. Second, we analyze how selection of component images united into 3D data array influences efficiency of filtering and can the observed tendencies be exploited in processing of images with rather large number of channels.
Robust extraction of the aorta and pulmonary artery from 3D MDCT image data
NASA Astrophysics Data System (ADS)
Taeprasartsit, Pinyo; Higgins, William E.
Accurate definition of the aorta and pulmonary artery from three-dimensional (3D) multi-detector CT (MDCT) images is important for pulmonary applications. This work presents robust methods for defining the aorta and pulmonary artery in the central chest. The methods work on both contrast enhanced and no-contrast 3D MDCT image data. The automatic methods use a common approach employing model fitting and selection and adaptive refinement. During the occasional event that more precise vascular extraction is desired or the method fails, we also have an alternate semi-automatic fail-safe method. The semi-automatic method extracts the vasculature by extending the medial axes into a user-guided direction. A ground-truth study over a series of 40 human 3D MDCT images demonstrates the efficacy, accuracy, robustness, and efficiency of the methods.
3D EFT imaging with planar electrode array: Numerical simulation
NASA Astrophysics Data System (ADS)
Tuykin, T.; Korjenevsky, A.
Electric field tomography (EFT) is the new modality of the quasistatic electromagnetic sounding of conductive media recently investigated theoretically and realized experimentally. The demonstrated results pertain to 2D imaging with circular or linear arrays of electrodes (and the linear array provides quite poor quality of imaging). In many applications 3D imaging is essential or can increase value of the investigation significantly. In this report we present the first results of numerical simulation of the EFT imaging system with planar array of electrodes which allows 3D visualization of the subsurface conductivity distribution. The geometry of the system is similar to the geometry of our EIT breast imaging system providing 3D conductivity imaging in form of cross-sections set with different depth from the surface. The EFT principle of operation and reconstruction approach differs from the EIT system significantly. So the results of numerical simulation are important to estimate if comparable quality of imaging is possible with the new contactless method. The EFT forward problem is solved using finite difference time domain (FDTD) method for the 8×8 square electrodes array. The calculated results of measurements are used then to reconstruct conductivity distributions by the filtered backprojections along electric field lines. The reconstructed images of the simple test objects are presented.
3-D Display Of Magnetic Resonance Imaging Of The Spine
NASA Astrophysics Data System (ADS)
Nelson, Alan C.; Kim, Yongmin; Haralick, Robert M.; Anderson, Paul A.; Johnson, Roger H.; DeSoto, Larry A.
The original data is produced through standard magnetic resonance imaging (MRI) procedures with a surface coil applied to the lower back of a normal human subject. The 3-D spine image data consists of twenty-six contiguous slices with 256 x 256 pixels per slice. Two methods for visualization of the 3-D spine are explored. One method utilizes a verifocal mirror system which creates a true 3-D virtual picture of the object. Another method uses a standard high resolution monitor to simultaneously show the three orthogonal sections which intersect at any user-selected point within the object volume. We discuss the application of these systems in assessment of low back pain.
New techniques of determining focus position in gamma knife operation using 3D image reconstruction
NASA Astrophysics Data System (ADS)
Xiong, Yingen; Wang, Dezong; Zhou, Quan
In this paper, new techniques of determining the focus of a disease position in a gamma knife operation are presented. In these techniques, the transparent 3D color image of the human body organ is reconstructed using a new three-dimensional reconstruction method, and then the position, the area, and the volume of focus of a disease such as cancer or a tumor are calculated. They are used in the gamma knife operation. The CT pictures are input into a digital image processing system. The useful information is extracted and the original data are obtained. Then the transparent 3D color image is reconstructed using these original data. By using this transparent 3D color image, the positions of the human body organ and the focus of a disease are determined in a coordinate system. While the 3D image is reconstructed, the area and the volume of human body organ and focus of a disease can be calculated at the same time. It is expressed through actual application that the positions of human body organ and focus of a disease can be determined exactly by using the transparent 3D color image. It is very useful in gamma knife operation or other surgical operation. The techniques presented in this paper have great application value.
Accurate positioning for head and neck cancer patients using 2D and 3D image guidance
Kang, Hyejoo; Lovelock, Dale M.; Yorke, Ellen D.; Kriminiski, Sergey; Lee, Nancy; Amols, Howard I.
Our goal is to determine an optimized image-guided setup by comparing setup errors determined by two-dimensional (2D) and three-dimensional (3D) image guidance for head and neck cancer (HNC) patients immobilized by customized thermoplastic masks. Nine patients received weekly imaging sessions, for a total of 54, throughout treatment. Patients were first set up by matching lasers to surface marks (initial) and then translationally corrected using manual registration of orthogonal kilovoltage (kV) radiographs with DRRs (2D-2D) on bony anatomy. A kV cone beam CT (kVCBCT) was acquired and manually registered to the simulation CT using only translations (3D-3D) on the same bony anatomy to determine further translational corrections. After treatment, a second set of kVCBCT was acquired to assess intrafractional motion. Averaged over all sessions, 2D-2D registration led to translational corrections from initial setup of 3.5 ± 2.2 (range 0–8) mm. The addition of 3D-3D registration resulted in only small incremental adjustment (0.8 ± 1.5 mm). We retrospectively calculated patient setup rotation errors using an automatic rigid-body algorithm with 6 degrees of freedom (DoF) on regions of interest (ROI) of in-field bony anatomy (mainly the C2 vertebral body). Small rotations were determined for most of the imaging sessions; however, occasionally rotations > 3° were observed. The calculated intrafractional motion with automatic registration was < 3.5 mm for eight patients, and < 2° for all patients. We conclude that daily manual 2D-2D registration on radiographs reduces positioning errors for mask-immobilized HNC patients in most cases, and is easily implemented. 3D-3D registration adds little improvement over 2D-2D registration without correcting rotational errors. We also conclude that thermoplastic masks are effective for patient immobilization. PMID:21330971
3D fluoroscopic image estimation using patient-specific 4DCBCT-based motion models
NASA Astrophysics Data System (ADS)
Dhou, S.; Hurwitz, M.; Mishra, P.; Cai, W.; Rottmann, J.; Li, R.; Williams, C.; Wagar, M.; Berbeco, R.; Ionascu, D.; Lewis, J. H.
3D fluoroscopic images represent volumetric patient anatomy during treatment with high spatial and temporal resolution. 3D fluoroscopic images estimated using motion models built using 4DCT images, taken days or weeks prior to treatment, do not reliably represent patient anatomy during treatment. In this study we developed and performed initial evaluation of techniques to develop patient-specific motion models from 4D cone-beam CT (4DCBCT) images, taken immediately before treatment, and used these models to estimate 3D fluoroscopic images based on 2D kV projections captured during treatment. We evaluate the accuracy of 3D fluoroscopic images by comparison to ground truth digital and physical phantom images. The performance of 4DCBCT-based and 4DCT-based motion models are compared in simulated clinical situations representing tumor baseline shift or initial patient positioning errors. The results of this study demonstrate the ability for 4DCBCT imaging to generate motion models that can account for changes that cannot be accounted for with 4DCT-based motion models. When simulating tumor baseline shift and patient positioning errors of up to 5 mm, the average tumor localization error and the 95th percentile error in six datasets were 1.20 and 2.2 mm, respectively, for 4DCBCT-based motion models. 4DCT-based motion models applied to the same six datasets resulted in average tumor localization error and the 95th percentile error of 4.18 and 5.4 mm, respectively. Analysis of voxel-wise intensity differences was also conducted for all experiments. In summary, this study demonstrates the feasibility of 4DCBCT-based 3D fluoroscopic image generation in digital and physical phantoms and shows the potential advantage of 4DCBCT-based 3D fluoroscopic image estimation when there are changes in anatomy between the time of 4DCT imaging and the time of treatment delivery.
3D fluoroscopic image estimation using patient-specific 4DCBCT-based motion models
Dhou, Salam; Hurwitz, Martina; Mishra, Pankaj; Cai, Weixing; Rottmann, Joerg; Li, Ruijiang; Williams, Christopher; Wagar, Matthew; Berbeco, Ross; Ionascu, Dan; Lewis, John H.
3D fluoroscopic images represent volumetric patient anatomy during treatment with high spatial and temporal resolution. 3D fluoroscopic images estimated using motion models built using 4DCT images, taken days or weeks prior to treatment, do not reliably represent patient anatomy during treatment. In this study we develop and perform initial evaluation of techniques to develop patient-specific motion models from 4D cone-beam CT (4DCBCT) images, taken immediately before treatment, and use these models to estimate 3D fluoroscopic images based on 2D kV projections captured during treatment. We evaluate the accuracy of 3D fluoroscopic images by comparing to ground truth digital and physical phantom images. The performance of 4DCBCT- and 4DCT- based motion models are compared in simulated clinical situations representing tumor baseline shift or initial patient positioning errors. The results of this study demonstrate the ability for 4DCBCT imaging to generate motion models that can account for changes that cannot be accounted for with 4DCT-based motion models. When simulating tumor baseline shift and patient positioning errors of up to 5 mm, the average tumor localization error and the 95th percentile error in six datasets were 1.20 and 2.2 mm, respectively, for 4DCBCT-based motion models. 4DCT-based motion models applied to the same six datasets resulted in average tumor localization error and the 95th percentile error of 4.18 and 5.4 mm, respectively. Analysis of voxel-wise intensity differences was also conducted for all experiments. In summary, this study demonstrates the feasibility of 4DCBCT-based 3D fluoroscopic image generation in digital and physical phantoms, and shows the potential advantage of 4DCBCT-based 3D fluoroscopic image estimation when there are changes in anatomy between the time of 4DCT imaging and the time of treatment delivery. PMID:25905722
Clinical Study of 3D Imaging and 3D Printing Technique for Patient-Specific Instrumentation in Total Knee Arthroplasty.
Qiu, Bing; Liu, Fei; Tang, Bensen; Deng, Biyong; Liu, Fang; Zhu, Weimin; Zhen, Dong; Xue, Mingyuan; Zhang, Mingjiao
Patient-specific instrumentation (PSI) was designed to improve the accuracy of preoperative planning and postoperative prosthesis positioning in total knee arthroplasty (TKA). However, better understanding needs to be achieved due to the subtle nature of the PSI systems. In this study, 3D printing technique based on the image data of computed tomography (CT) has been utilized for optimal controlling of the surgical parameters. Two groups of TKA cases have been randomly selected as PSI group and control group with no significant difference of age and sex (p > 0.05). The PSI group is treated with 3D printed cutting guides whereas the control group is treated with conventional instrumentation (CI). By evaluating the proximal osteotomy amount, distal osteotomy amount, valgus angle, external rotation angle, and tibial posterior slope angle of patients, it can be found that the preoperative quantitative assessment and intraoperative changes can be controlled with PSI whereas CI is relied on experience. In terms of postoperative parameters, such as hip-knee-ankle (HKA), frontal femoral component (FFC), frontal tibial component (FTC), and lateral tibial component (LTC) angles, there is a significant improvement in achieving the desired implant position (p < 0.05). Assigned from the morphology of patients' knees, the PSI represents the convergence of congruent designs with current personalized treatment tools. The PSI can achieve less extremity alignment and greater accuracy of prosthesis implantation compared against control method, which indicates potential for optimal HKA, FFC, and FTC angles.
3D imaging lidar for lunar robotic exploration
NASA Astrophysics Data System (ADS)
Hussein, Marwan W.; Tripp, Jeffrey W.
Part of the requirements of the future Constellation program is to optimize lunar surface operations and reduce hazards to astronauts. Toward this end, many robotic platforms, rovers in specific, are being sought to carry out a multitude of missions involving potential EVA sites survey, surface reconnaissance, path planning and obstacle detection and classification. 3D imaging lidar technology provides an enabling capability that allows fast, accurate and detailed collection of three-dimensional information about the rover's environment. The lidar images the region of interest by scanning a laser beam and measuring the pulse time-of-flight and the bearing. The accumulated set of laser ranges and bearings constitutes the threedimensional image. As part of the ongoing NASA Ames research center activities in lunar robotics, the utility of 3D imaging lidar was evaluated by testing Optech's ILRIS-3D lidar on board the K-10 Red rover during the recent Human - Robotics Systems (HRS) field trails in Lake Moses, WA. This paper examines the results of the ILRIS-3D trials, presents the data obtained and discusses its application in lunar surface robotic surveying and scouting.
3D FaceCam: a fast and accurate 3D facial imaging device for biometrics applications
NASA Astrophysics Data System (ADS)
Geng, Jason; Zhuang, Ping; May, Patrick; Yi, Steven; Tunnell, David
Human faces are fundamentally three-dimensional (3D) objects, and each face has its unique 3D geometric profile. The 3D geometric features of a human face can be used, together with its 2D texture, for rapid and accurate face recognition purposes. Due to the lack of low-cost and robust 3D sensors and effective 3D facial recognition (FR) algorithms, almost all existing FR systems use 2D face images. Genex has developed 3D solutions that overcome the inherent problems in 2D while also addressing limitations in other 3D alternatives. One important aspect of our solution is a unique 3D camera (the 3D FaceCam) that combines multiple imaging sensors within a single compact device to provide instantaneous, ear-to-ear coverage of a human face. This 3D camera uses three high-resolution CCD sensors and a color encoded pattern projection system. The RGB color information from each pixel is used to compute the range data and generate an accurate 3D surface map. The imaging system uses no moving parts and combines multiple 3D views to provide detailed and complete 3D coverage of the entire face. Images are captured within a fraction of a second and full-frame 3D data is produced within a few seconds. This described method provides much better data coverage and accuracy in feature areas with sharp features or details (such as the nose and eyes). Using this 3D data, we have been able to demonstrate that a 3D approach can significantly improve the performance of facial recognition. We have conducted tests in which we have varied the lighting conditions and angle of image acquisition in the "field." These tests have shown that the matching results are significantly improved when enrolling a 3D image rather than a single 2D image. With its 3D solutions, Genex is working toward unlocking the promise of powerful 3D FR and transferring FR from a lab technology into a real-world biometric solution.
Integration of real-time 3D image acquisition and multiview 3D display
NASA Astrophysics Data System (ADS)
Zhang, Zhaoxing; Geng, Zheng; Li, Tuotuo; Li, Wei; Wang, Jingyi; Liu, Yongchun
Seamless integration of 3D acquisition and 3D display systems offers enhanced experience in 3D visualization of the real world objects or scenes. The vivid representation of captured 3D objects displayed on a glasses-free 3D display screen could bring the realistic viewing experience to viewers as if they are viewing real-world scene. Although the technologies in 3D acquisition and 3D display have advanced rapidly in recent years, effort is lacking in studying the seamless integration of these two different aspects of 3D technologies. In this paper, we describe our recent progress on integrating a light-field 3D acquisition system and an autostereoscopic multiview 3D display for real-time light field capture and display. This paper focuses on both the architecture design and the implementation of the hardware and the software of this integrated 3D system. A prototype of the integrated 3D system is built to demonstrate the real-time 3D acquisition and 3D display capability of our proposed system.
Optimizing 3D image quality and performance for stereoscopic gaming
NASA Astrophysics Data System (ADS)
Flack, Julien; Sanderson, Hugh; Pegg, Steven; Kwok, Simon; Paterson, Daniel
The successful introduction of stereoscopic TV systems, such as Samsung's 3D Ready Plasma, requires high quality 3D content to be commercially available to the consumer. Console and PC games provide the most readily accessible source of high quality 3D content. This paper describes innovative developments in a generic, PC-based game driver architecture that addresses the two key issues affecting 3D gaming: quality and speed. At the heart of the quality issue are the same considerations that studios face producing stereoscopic renders from CG movies: how best to perform the mapping from a geometric CG environment into the stereoscopic display volume. The major difference being that for game drivers this mapping cannot be choreographed by hand but must be automatically calculated in real-time without significant impact on performance. Performance is a critical issue when dealing with gaming. Stereoscopic gaming has traditionally meant rendering the scene twice with the associated performance overhead. An alternative approach is to render the scene from one virtual camera position and use information from the z-buffer to generate a stereo pair using Depth-Image-Based Rendering (DIBR). We analyze this trade-off in more detail and provide some results relating to both 3D image quality and render performance.
3-D object-oriented image analysis of geophysical data
NASA Astrophysics Data System (ADS)
Fadel, I.; Kerle, N.; van der Meijde, M.
Geophysical data are the main source of information about the subsurface. Geophysical techniques are, however, highly non-unique in determining specific physical parameters and boundaries of subsurface objects. To obtain actual physical information, an inversion process is often applied, in which measurements at or above the Earth surface are inverted into a 2- or 3-D subsurface spatial distribution of the physical property. Interpreting these models into structural objects, related to physical processes, requires a priori knowledge and expert analysis which is susceptible to subjective choices and is therefore often non-repeatable. In this research, we implemented a recently introduced object-based approach to interpret the 3-D inversion results of a single geophysical technique using the available a priori information and the physical and geometrical characteristics of the interpreted objects. The introduced methodology is semi-automatic and repeatable, and allows the extraction of subsurface structures using 3-D object-oriented image analysis (3-D OOA) in an objective knowledge-based classification scheme. The approach allows for a semi-objective setting of thresholds that can be tested and, if necessary, changed in a very fast and efficient way. These changes require only changing the thresholds used in a so-called ruleset, which is composed of algorithms that extract objects from a 3-D data cube. The approach is tested on a synthetic model, which is based on a priori knowledge on objects present in the study area (Tanzania). Object characteristics and thresholds were well defined in a 3-D histogram of velocity versus depth, and objects were fully retrieved. The real model results showed how 3-D OOA can deal with realistic 3-D subsurface conditions in which the boundaries become fuzzy, the object extensions become unclear and the model characteristics vary with depth due to the different physical conditions. As expected, the 3-D histogram of the real data was
Noninvasive computational imaging of cardiac electrophysiology for 3-D infarct.
Wang, Linwei; Wong, Ken C L; Zhang, Heye; Liu, Huafeng; Shi, Pengcheng
Myocardial infarction (MI) creates electrophysiologically altered substrates that are responsible for ventricular arrhythmias, such as tachycardia and fibrillation. The presence, size, location, and composition of infarct scar bear significant prognostic and therapeutic implications for individual subjects. We have developed a statistical physiological model-constrained framework that uses noninvasive body-surface-potential data and tomographic images to estimate subject-specific transmembrane-potential (TMP) dynamics inside the 3-D myocardium. In this paper, we adapt this framework for the purpose of noninvasive imaging, detection, and quantification of 3-D scar mass for postMI patients: the framework requires no prior knowledge of MI and converges to final subject-specific TMP estimates after several passes of estimation with intermediate feedback; based on the primary features of the estimated spatiotemporal TMP dynamics, we provide 3-D imaging of scar tissue and quantitative evaluation of scar location and extent. Phantom experiments were performed on a computational model of realistic heart-torso geometry, considering 87 transmural infarct scars of different sizes and locations inside the myocardium, and 12 compact infarct scars (extent between 10% and 30%) at different transmural depths. Real-data experiments were carried out on BSP and magnetic resonance imaging (MRI) data from four postMI patients, validated by gold standards and existing results. This framework shows unique advantage of noninvasive, quantitative, computational imaging of subject-specific TMP dynamics and infarct mass of the 3-D myocardium, with the potential to reflect details in the spatial structure and tissue composition/heterogeneity of 3-D infarct scar.
Refraction Correction in 3D Transcranial Ultrasound Imaging
Lindsey, Brooks D.; Smith, Stephen W.
We present the first correction of refraction in three-dimensional (3D) ultrasound imaging using an iterative approach that traces propagation paths through a two-layer planar tissue model, applying Snell's law in 3D. This approach is applied to real-time 3D transcranial ultrasound imaging by precomputing delays offline for several skull thicknesses, allowing the user to switch between three sets of delays for phased array imaging at the push of a button. Simulations indicate that refraction correction may be expected to increase sensitivity, reduce beam steering errors, and partially restore lost spatial resolution, with the greatest improvements occurring at the largest steering angles. Distorted images of cylindrical lesions were created by imaging through an acrylic plate in a tissue-mimicking phantom. As a result of correcting for refraction, lesions were restored to 93.6% of their original diameter in the lateral direction and 98.1% of their original shape along the long axis of the cylinders. In imaging two healthy volunteers, the mean brightness increased by 8.3% and showed no spatial dependency. PMID:24275538
3D Imaging of Density Gradients Using Plenoptic BOS
NASA Astrophysics Data System (ADS)
Klemkowsky, Jenna; Clifford, Chris; Fahringer, Timothy; Thurow, Brian
The combination of background oriented schlieren (BOS) and a plenoptic camera, termed Plenoptic BOS, is explored through two proof-of-concept experiments. The motivation of this work is to provide a 3D technique capable of observing density disturbances. BOS uses the relationship between density and refractive index gradients to observe an apparent shift in a patterned background through image comparison. Conventional BOS systems acquire a single line-of-sight measurement, and require complex configurations to obtain 3D measurements, which are not always conducive to experimental facilities. Plenoptic BOS exploits the plenoptic camera's ability to generate multiple perspective views and refocused images from a single raw plenoptic image during post processing. Using such capabilities, with regards to BOS, provides multiple line-of-sight measurements of density disturbances, which can be collectively used to generate refocused BOS images. Such refocused images allow the position of density disturbances to be qualitatively and quantitatively determined. The image that provides the sharpest density gradient signature corresponds to a specific depth. These results offer motivation to advance Plenoptic BOS with an ultimate goal of reconstructing a 3D density field.
An automated 3D reconstruction method of UAV images
NASA Astrophysics Data System (ADS)
Liu, Jun; Wang, He; Liu, Xiaoyang; Li, Feng; Sun, Guangtong; Song, Ping
In this paper a novel fully automated 3D reconstruction approach based on low-altitude unmanned aerial vehicle system (UAVs) images will be presented, which does not require previous camera calibration or any other external prior knowledge. Dense 3D point clouds are generated by integrating orderly feature extraction, image matching, structure from motion (SfM) and multi-view stereo (MVS) algorithms, overcoming many of the cost, time limitations of rigorous photogrammetry techniques. An image topology analysis strategy is introduced to speed up large scene reconstruction by taking advantage of the flight-control data acquired by UAV. Image topology map can significantly reduce the running time of feature matching by limiting the combination of images. A high-resolution digital surface model of the study area is produced base on UAV point clouds by constructing the triangular irregular network. Experimental results show that the proposed approach is robust and feasible for automatic 3D reconstruction of low-altitude UAV images, and has great potential for the acquisition of spatial information at large scales mapping, especially suitable for rapid response and precise modelling in disaster emergency.
Factors Affecting Dimensional Accuracy of 3-D Printed Anatomical Structures Derived from CT Data.
Ogden, Kent M; Aslan, Can; Ordway, Nathaniel; Diallo, Dalanda; Tillapaugh-Fay, Gwen; Soman, Pranav
Additive manufacturing and bio-printing, with the potential for direct fabrication of complex patient-specific anatomies derived from medical scan data, are having an ever-increasing impact on the practice of medicine. Anatomic structures are typically derived from CT or MRI scans, and there are multiple steps in the model derivation process that influence the geometric accuracy of the printed constructs. In this work, we compare the dimensional accuracy of 3-D printed constructs of an L1 vertebra derived from CT data for an ex vivo cadaver T-L spine with the original vertebra. Processing of segmented structures using binary median filters and various surface extraction algorithms is evaluated for the effect on model dimensions. We investigate the effects of changing CT reconstruction kernels by scanning simple geometric objects and measuring the impact on the derived model dimensions. We also investigate if there are significant differences between physical and virtual model measurements. The 3-D models were printed using a commercial 3-D printer, the Replicator 2 (MakerBot, Brooklyn, NY) using polylactic acid (PLA) filament. We found that changing parameters during the scan reconstruction, segmentation, filtering, and surface extraction steps will have an effect on the dimensions of the final model. These effects need to be quantified for specific situations that rely on the accuracy of 3-D printed models used in medicine or tissue engineering applications.
Combining 2D wavelet edge highlighting and 3D thresholding for lung segmentation in thin-slice CT.
Korfiatis, P; Skiadopoulos, S; Sakellaropoulos, P; Kalogeropoulou, C; Costaridou, L
The first step in lung analysis by CT is the identification of the lung border. To deal with the increased number of sections per scan in thin-slice multidetector CT, it has been crucial to develop accurate and automated lung segmentation algorithms. In this study, an automated method for lung segmentation of thin-slice CT data is presented. The method exploits the advantages of a two-dimensional wavelet edge-highlighting step in lung border delineation. Lung volume segmentation is achieved with three-dimensional (3D) grey level thresholding, using a minimum error technique. 3D thresholding, combined with the wavelet pre-processing step, successfully deals with lung border segmentation challenges, such as anterior or posterior junction lines and juxtapleural nodules. Finally, to deal with mediastinum border under-segmentation, 3D morphological closing with a spherical structural element is applied. The performance of the proposed method is quantitatively assessed on a dataset originating from the Lung Imaging Database Consortium (LIDC) by comparing automatically derived borders with the manually traced ones. Segmentation performance, averaged over left and right lung volumes, for lung volume overlap is 0.983+/-0.008, whereas for shape differentiation in terms of mean distance it is 0.770+/-0.251 mm (root mean square distance is 0.520+/-0.008 mm; maximum distance is 3.327+/-1.637 mm). The effect of the wavelet pre-processing step was assessed by comparing the proposed method with the 3D thresholding technique (applied on original volume data). This yielded statistically significant differences for all segmentation metrics (p<0.01). Results demonstrate an accurate method that could be used as a first step in computer lung analysis by CT.
Computer-aided diagnosis of pulmonary nodules on CT scans: segmentation and classification using 3D active contours.
Way, Ted W; Hadjiiski, Lubomir M; Sahiner, Berkman; Chan, Heang-Ping; Cascade, Philip N; Kazerooni, Ella A; Bogot, Naama; Zhou, Chuan
We are developing a computer-aided diagnosis (CAD) system to classify malignant and benign lung nodules found on CT scans. A fully automated system was designed to segment the nodule from its surrounding structured background in a local volume of interest (VOI) and to extract image features for classification. Image segmentation was performed with a three-dimensional (3D) active contour (AC) method. A data set of 96 lung nodules (44 malignant, 52 benign) from 58 patients was used in this study. The 3D AC model is based on two-dimensional AC with the addition of three new energy components to take advantage of 3D information: (1) 3D gradient, which guides the active contour to seek the object surface, (2) 3D curvature, which imposes a smoothness constraint in the z direction, and (3) mask energy, which penalizes contours that grow beyond the pleura or thoracic wall. The search for the best energy weights in the 3D AC model was guided by a simplex optimization method. Morphological and gray-level features were extracted from the segmented nodule. The rubber band straightening transform (RBST) was applied to the shell of voxels surrounding the nodule. Texture features based on run-length statistics were extracted from the RBST image. A linear discriminant analysis classifier with stepwise feature selection was designed using a second simplex optimization to select the most effective features. Leave-one-case-out resampling was used to train and test the CAD system. The system achieved a test area under the receiver operating characteristic curve (A(z)) of 0.83 +/- 0.04. Our preliminary results indicate that use of the 3D AC model and the 3D texture features surrounding the nodule is a promising approach to the segmentation and classification of lung nodules with CAD. The segmentation performance of the 3D AC model trained with our data set was evaluated with 23 nodules available in the Lung Image Database Consortium (LIDC). The lung nodule volumes segmented by the 3D
Computer-aided diagnosis of pulmonary nodules on CT scans: Segmentation and classification using 3D active contours
Way, Ted W.; Hadjiiski, Lubomir M.; Sahiner, Berkman; Chan, Heang-Ping; Cascade, Philip N.; Kazerooni, Ella A.; Bogot, Naama; Zhou, Chuan
We are developing a computer-aided diagnosis (CAD) system to classify malignant and benign lung nodules found on CT scans. A fully automated system was designed to segment the nodule from its surrounding structured background in a local volume of interest (VOI) and to extract image features for classification. Image segmentation was performed with a three-dimensional (3D) active contour (AC) method. A data set of 96 lung nodules (44 malignant, 52 benign) from 58 patients was used in this study. The 3D AC model is based on two-dimensional AC with the addition of three new energy components to take advantage of 3D information: (1) 3D gradient, which guides the active contour to seek the object surface, (2) 3D curvature, which imposes a smoothness constraint in the z direction, and (3) mask energy, which penalizes contours that grow beyond the pleura or thoracic wall. The search for the best energy weights in the 3D AC model was guided by a simplex optimization method. Morphological and gray-level features were extracted from the segmented nodule. The rubber band straightening transform (RBST) was applied to the shell of voxels surrounding the nodule. Texture features based on run-length statistics were extracted from the RBST image. A linear discriminant analysis classifier with stepwise feature selection was designed using a second simplex optimization to select the most effective features. Leave-one-case-out resampling was used to train and test the CAD system. The system achieved a test area under the receiver operating characteristic curve (Az) of 0.83±0.04. Our preliminary results indicate that use of the 3D AC model and the 3D texture features surrounding the nodule is a promising approach to the segmentation and classification of lung nodules with CAD. The segmentation performance of the 3D AC model trained with our data set was evaluated with 23 nodules available in the Lung Image Database Consortium (LIDC). The lung nodule volumes segmented by the 3D AC
TU-CD-BRA-01: A Novel 3D Registration Method for Multiparametric Radiological Images
Akhbardeh, A; Parekth, VS; Jacobs, MA
Purpose: Multiparametric and multimodality radiological imaging methods, such as, magnetic resonance imaging(MRI), computed tomography(CT), and positron emission tomography(PET), provide multiple types of tissue contrast and anatomical information for clinical diagnosis. However, these radiological modalities are acquired using very different technical parameters, e.g.,field of view(FOV), matrix size, and scan planes, which, can lead to challenges in registering the different data sets. Therefore, we developed a hybrid registration method based on 3D wavelet transformation and 3D interpolations that performs 3D resampling and rotation of the target radiological images without loss of information Methods: T1-weighted, T2-weighted, diffusion-weighted-imaging(DWI), dynamic-contrast-enhanced(DCE) MRI and PET/CT were used in the registration algorithm from breast and prostate data at 3T MRI and multimodality(PET/CT) cases. The hybrid registration scheme consists of several steps to reslice and match each modality using a combination of 3D wavelets, interpolations, and affine registration steps. First, orthogonal reslicing is performed to equalize FOV, matrix sizes and the number of slices using wavelet transformation. Second, angular resampling of the target data is performed to match the reference data. Finally, using optimized angles from resampling, 3D registration is performed using similarity transformation(scaling and translation) between the reference and resliced target volume is performed. After registration, the mean-square-error(MSE) and Dice Similarity(DS) between the reference and registered target volumes were calculated. Results: The 3D registration method registered synthetic and clinical data with significant improvement(p<0.05) of overlap between anatomical structures. After transforming and deforming the synthetic data, the MSE and Dice similarity were 0.12 and 0.99. The average improvement of the MSE in breast was 62%(0.27 to 0.10) and prostate was
F3D Image Processing and Analysis for Many - and Multi-core Platforms
F3D is written in OpenCL, so it achieve[sic] platform-portable parallelism on modern mutli-core CPUs and many-core GPUs. The interface and mechanims to access F3D core are written in Java as a plugin for Fiji/ImageJ to deliver several key image-processing algorithms necessary to remove artifacts from micro-tomography data. The algorithms consist of data parallel aware filters that can efficiently utilizes[sic] resources and can work on out of core datasets and scale efficiently across multiple accelerators. Optimizing for data parallel filters, streaming out of core datasets, and efficient resource and memory and data managements over complex execution sequence of filters greatly expedites any scientific workflow with image processing requirements. F3D performs several different types of 3D image processing operations, such as non-linear filtering using bilateral filtering and/or median filtering and/or morphological operators (MM). F3D gray-level MM operators are one-pass constant time methods that can perform morphological transformations with a line-structuring element oriented in discrete directions. Additionally, MM operators can be applied to gray-scale images, and consist of two parts: (a) a reference shape or structuring element, which is translated over the image, and (b) a mechanism, or operation, that defines the comparisons to be performed between the image and the structuring element. This tool provides a critical component within many complex pipelines such as those for performing automated segmentation of image stacks. F3D is also called a "descendent" of Quant-CT, another software we developed in the past. These two modules are to be integrated in a next version. Further details were reported in: D.M. Ushizima, T. Perciano, H. Krishnan, B. Loring, H. Bale, D. Parkinson, and J. Sethian. Structure recognition from high-resolution images of ceramic composites. IEEE International Conference on Big Data, October 2014.
1024 pixels single photon imaging array for 3D ranging
NASA Astrophysics Data System (ADS)
Bellisai, S.; Guerrieri, F.; Tisa, S.; Zappa, F.; Tosi, A.; Giudice, A.
Three dimensions (3D) acquisition systems are driving applications in many research field. Nowadays 3D acquiring systems are used in a lot of applications, such as cinema industry or in automotive (for active security systems). Depending on the application, systems present different features, for example color sensitivity, bi-dimensional image resolution, distance measurement accuracy and acquisition frame rate. The system we developed acquires 3D movie using indirect Time of Flight (iTOF), starting from phase delay measurement of a sinusoidally modulated light. The system acquires live movie with a frame rate up to 50frame/s in a range distance between 10 cm up to 7.5 m.
A review of automated image understanding within 3D baggage computed tomography security screening.
Mouton, Andre; Breckon, Toby P
Baggage inspection is the principal safeguard against the transportation of prohibited and potentially dangerous materials at airport security checkpoints. Although traditionally performed by 2D X-ray based scanning, increasingly stringent security regulations have led to a growing demand for more advanced imaging technologies. The role of X-ray Computed Tomography is thus rapidly expanding beyond the traditional materials-based detection of explosives. The development of computer vision and image processing techniques for the automated understanding of 3D baggage-CT imagery is however, complicated by poor image resolutions, image clutter and high levels of noise and artefacts. We discuss the recent and most pertinent advancements and identify topics for future research within the challenging domain of automated image understanding for baggage security screening CT.
The effect of CT dose on glenohumeral joint congruency measurements using 3D reconstructed patient-specific bone models
NASA Astrophysics Data System (ADS)
Lalone, Emily A.; Fox, Anne-Marie V.; Kedgley, Angela E.; Jenkyn, Thomas R.; King, Graham J. W.; Athwal, George S.; Johnson, James A.; Peters, Terry M.
The study of joint congruency at the glenohumeral joint of the shoulder using computed tomography (CT) and three-dimensional (3D) reconstructions of joint surfaces is an area of significant clinical interest. However, ionizing radiation delivered to patients during CT examinations is much higher than other types of radiological imaging. The shoulder represents a significant challenge for this modality as it is adjacent to the thyroid gland and breast tissue. The objective of this study was to determine the optimal CT scanning techniques that would minimize radiation dose while accurately quantifying joint congruency of the shoulder. The results suggest that only one-tenth of the standard applied total current (mA) and a pitch ratio of 1.375:1 was necessary to produce joint congruency values consistent with that of the higher dose scans. Using the CT scanning techniques examined in this study, the effective dose applied to the shoulder to quantify joint congruency was reduced by 88.9% compared to standard clinical CT imaging techniques.
Influence of the Alveolar Cleft Type on Preoperative Estimation Using 3D CT Assessment for Alveolar Cleft
Choi, Hang Suk; Choi, Hyun Gon; Kim, Soon Heum; Park, Hyung Jun; Shin, Dong Hyeok; Jo, Dong In; Kim, Cheol Keun
Background The bone graft for the alveolar cleft has been accepted as one of the essential treatments for cleft lip patients. Precise preoperative measurement of the architecture and size of the bone defect in alveolar cleft has been considered helpful for increasing the success rate of bone grafting because those features may vary with the cleft type. Recently, some studies have reported on the usefulness of three-dimensional (3D) computed tomography (CT) assessment of alveolar bone defect; however, no study on the possible implication of the cleft type on the difference between the presumed and actual value has been conducted yet. We aimed to evaluate the clinical predictability of such measurement using 3D CT assessment according to the cleft type. Methods The study consisted of 47 pediatric patients. The subjects were divided according to the cleft type. CT was performed before the graft operation and assessed using image analysis software. The statistical significance of the difference between the preoperative estimation and intraoperative measurement was analyzed. Results The difference between the preoperative and intraoperative values were -0.1±0.3 cm3 (P=0.084). There was no significant intergroup difference, but the groups with a cleft palate showed a significant difference of -0.2±0.3 cm3 (P<0.05). Conclusions Assessment of the alveolar cleft volume using 3D CT scan data and image analysis software can help in selecting the optimal graft procedure and extracting the correct volume of cancellous bone for grafting. Considering the cleft type, it would be helpful to extract an additional volume of 0.2 cm3 in the presence of a cleft palate. PMID:23094242
Large distance 3D imaging of hidden objects
NASA Astrophysics Data System (ADS)
Rozban, Daniel; Aharon Akram, Avihai; Kopeika, N. S.; Abramovich, A.; Levanon, Assaf
Imaging systems in millimeter waves are required for applications in medicine, communications, homeland security, and space technology. This is because there is no known ionization hazard for biological tissue, and atmospheric attenuation in this range of the spectrum is low compared to that of infrared and optical rays. The lack of an inexpensive room temperature detector makes it difficult to give a suitable real time implement for the above applications. A 3D MMW imaging system based on chirp radar was studied previously using a scanning imaging system of a single detector. The system presented here proposes to employ a chirp radar method with Glow Discharge Detector (GDD) Focal Plane Array (FPA of plasma based detectors) using heterodyne detection. The intensity at each pixel in the GDD FPA yields the usual 2D image. The value of the I-F frequency yields the range information at each pixel. This will enable 3D MMW imaging. In this work we experimentally demonstrate the feasibility of implementing an imaging system based on radar principles and FPA of inexpensive detectors. This imaging system is shown to be capable of imaging objects from distances of at least 10 meters.
Interactive 2D to 3D stereoscopic image synthesis
NASA Astrophysics Data System (ADS)
Feldman, Mark H.; Lipton, Lenny
Advances in stereoscopic display technologies, graphic card devices, and digital imaging algorithms have opened up new possibilities in synthesizing stereoscopic images. The power of today"s DirectX/OpenGL optimized graphics cards together with adapting new and creative imaging tools found in software products such as Adobe Photoshop, provide a powerful environment for converting planar drawings and photographs into stereoscopic images. The basis for such a creative process is the focus of this paper. This article presents a novel technique, which uses advanced imaging features and custom Windows-based software that utilizes the Direct X 9 API to provide the user with an interactive stereo image synthesizer. By creating an accurate and interactive world scene with moveable and flexible depth map altered textured surfaces, perspective stereoscopic cameras with both visible frustums and zero parallax planes, a user can precisely model a virtual three-dimensional representation of a real-world scene. Current versions of Adobe Photoshop provide a creative user with a rich assortment of tools needed to highlight elements of a 2D image, simulate hidden areas, and creatively shape them for a 3D scene representation. The technique described has been implemented as a Photoshop plug-in and thus allows for a seamless transition of these 2D image elements into 3D surfaces, which are subsequently rendered to create stereoscopic views.
CT Image Presentations For Oral Surgery
NASA Astrophysics Data System (ADS)
Rhodes, Michael L.; Rothman, Stephen L. G.; Schwarz, Melvyn S.; Tivattanasuk, Eva S.
Reformatted CT images of the mandible and maxilla are described as a planning aid to the surgical implantation of dental fixtures. Precisely scaled and cross referenced axial, oblique, CT generated panorex, and 3-D images are generated to help indicate where and how critical anatomic structures are positioned. This information guides the oral surgeon to those sites where dental implants have optimal osteotic support and least risk to sensitive neural tissue. Oblique images are generated at 1-2 mm increments along the arch of the mandible (or maxilla). Each oblique is oriented perpendicular to the local arch curvature. The adjoining five CT generated panorex views match the patient's mandibular (or maxilla) arch, with each of the views separated by twice the distance between axial CT slices. All views are mutually cross-referenced to show fine detail of the underlying mandibular (or maxilla) structure. Several exams are illustrated and benefit to subsequent surgery is assessed.
Automated reconstruction of 3D scenes from sequences of images
NASA Astrophysics Data System (ADS)
Pollefeys, M.; Koch, R.; Vergauwen, M.; Van Gool, L.
Modelling of 3D objects from image sequences is a challenging problem and has been an important research topic in the areas of photogrammetry and computer vision for many years. In this paper, a system is presented which automatically extracts a textured 3D surface model from a sequence of images of a scene. The system can deal with unknown camera settings. In addition, the parameters of this camera are allowed to change during acquisition (e.g., by zooming or focusing). No prior knowledge about the scene is necessary to build the 3D models. Therefore, this system offers a high degree of flexibility. The system is based on state-of-the-art algorithms recently developed in computer vision. The 3D modelling task is decomposed into a number of successive steps. Gradually, more knowledge of the scene and the camera setup is retrieved. At this point, the obtained accuracy is not yet at the level required for most metrology applications, but the visual quality is very convincing. This system has been applied to a number of applications in archaeology. The Roman site of Sagalassos (southwest Turkey) was used as a test case to illustrate the potential of this new approach.
3D imaging of the mesospheric emissive layer
NASA Astrophysics Data System (ADS)
Nadjib Kouahla, Mohamed; Faivre, Michael; Moreels, Guy; Clairemidi, Jacques; Mougin-Sisini, Davy; Meriwether, John W.; Lehmacher, Gerald A.; Vidal, Erick; Veliz, Oskar
A new and original stereo-imaging method is introduced to measure the altitude of the OH airglow layer and provide a 3D map of the altitude of the layer centroid. Near-IR photographs of the layer are taken at two sites distant of 645 km. Each photograph is processed in order to invert the perspective effect and provide a satellite-type view of the layer. When superposed, the two views present a common diamond-shaped area. Pairs of matched points that correspond to a physical emissive point in the common area are identified in calculating a normalized crosscorrelation coefficient. This method is suitable for obtaining 3D representations in the case of low-contrast objects. An observational campaign was conducted in July 2006 in Peru. The images were taken simultaneously at Cerro Cosmos (12° 09' 08.2" S, 75° 33' 49.3" W, altitude 4630 m) close to Huancayo and Cerro Verde Tellolo (16° 33' 17.6" S, 71° 39' 59.4" W, altitude 2330 m) close to Arequipa. 3D maps of the layer surface are retrieved. They are compared with pseudo-relief intensity maps of the same region. The mean altitude of the emission barycenter is located at 87.1 km on July 26 and 89.5 km on July 28. Comparable relief wavy features appear in the 3D and intensity maps.
Combined registration of 3D tibia and femur implant models in 3D magnetic resonance images
NASA Astrophysics Data System (ADS)
Englmeier, Karl-Hans; Siebert, Markus; von Eisenhart-Rothe, Ruediger; Graichen, Heiko
The most frequent reasons for revision of total knee arthroplasty are loosening and abnormal axial alignment leading to an unphysiological kinematic of the knee implant. To get an idea about the postoperative kinematic of the implant, it is essential to determine the position and orientation of the tibial and femoral prosthesis. Therefore we developed a registration method for fitting 3D CAD-models of knee joint prostheses into an 3D MR image. This rigid registration is the basis for a quantitative analysis of the kinematics of knee implants. Firstly the surface data of the prostheses models are converted into a voxel representation; a recursive algorithm determines all boundary voxels of the original triangular surface data. Secondly an initial preconfiguration of the implants by the user is still necessary for the following step: The user has to perform a rough preconfiguration of both remaining prostheses models, so that the fine matching process gets a reasonable starting point. After that an automated gradient-based fine matching process determines the best absolute position and orientation: This iterative process changes all 6 parameters (3 rotational- and 3 translational parameters) of a model by a minimal amount until a maximum value of the matching function is reached. To examine the spread of the final solutions of the registration, the interobserver variability was measured in a group of testers. This variability, calculated by the relative standard deviation, improved from about 50% (pure manual registration) to 0.5% (rough manual preconfiguration and subsequent fine registration with the automatic fine matching process).
Traversing and labeling interconnected vascular tree structures from 3D medical images
NASA Astrophysics Data System (ADS)
O'Dell, Walter G.; Govindarajan, Sindhuja Tirumalai; Salgia, Ankit; Hegde, Satyanarayan; Prabhakaran, Sreekala; Finol, Ender A.; White, R. James
Purpose: Detailed characterization of pulmonary vascular anatomy has important applications for the diagnosis and management of a variety of vascular diseases. Prior efforts have emphasized using vessel segmentation to gather information on the number or branches, number of bifurcations, and branch length and volume, but accurate traversal of the vessel tree to identify and repair erroneous interconnections between adjacent branches and neighboring tree structures has not been carefully considered. In this study, we endeavor to develop and implement a successful approach to distinguishing and characterizing individual vascular trees from among a complex intermingling of trees. Methods: We developed strategies and parameters in which the algorithm identifies and repairs false branch inter-tree and intra-tree connections to traverse complicated vessel trees. A series of two-dimensional (2D) virtual datasets with a variety of interconnections were constructed for development, testing, and validation. To demonstrate the approach, a series of real 3D computed tomography (CT) lung datasets were obtained, including that of an anthropomorphic chest phantom; an adult human chest CT; a pediatric patient chest CT; and a micro-CT of an excised rat lung preparation. Results: Our method was correct in all 2D virtual test datasets. For each real 3D CT dataset, the resulting simulated vessel tree structures faithfully depicted the vessel tree structures that were originally extracted from the corresponding lung CT scans. Conclusion: We have developed a comprehensive strategy for traversing and labeling interconnected vascular trees and successfully implemented its application to pulmonary vessels observed using 3D CT images of the chest.
A questionnaire-based survey on 3D image-guided brachytherapy for cervical cancer in Japan: advances and obstacles
Ohno, Tatsuya; Toita, Takafumi; Tsujino, Kayoko; Uchida, Nobue; Hatano, Kazuo; Nishimura, Tetsuo; Ishikura, Satoshi
The purpose of this study is to survey the current patterns of practice, and barriers to implementation, of 3D image-guided brachytherapy (3D-IGBT) for cervical cancer in Japan. A 30-item questionnaire was sent to 171 Japanese facilities where high-dose-rate brachytherapy devices were available in 2012. In total, 135 responses were returned for analysis. Fifty-one facilities had acquired some sort of 3D imaging modality with applicator insertion, and computed tomography (CT) and magnetic resonance imaging (MRI) were used in 51 and 3 of the facilities, respectively. For actual treatment planning, X-ray films, CT and MRI were used in 113, 20 and 2 facilities, respectively. Among 43 facilities where X-ray films and CT or MRI were acquired with an applicator, 29 still used X-ray films for actual treatment planning, mainly because of limited time and/or staffing. In a follow-up survey 2.5 years later, respondents included 38 facilities that originally used X-ray films alone but had indicated plans to adopt 3D-IGBT. Of these, 21 had indeed adopted CT imaging with applicator insertion. In conclusion, 3D-IGBT (mainly CT) was implemented in 22 facilities (16%) and will be installed in 72 (53%) facilities in the future. Limited time and staffing were major impediments. PMID:26265660
A questionnaire-based survey on 3D image-guided brachytherapy for cervical cancer in Japan: advances and obstacles.
Ohno, Tatsuya; Toita, Takafumi; Tsujino, Kayoko; Uchida, Nobue; Hatano, Kazuo; Nishimura, Tetsuo; Ishikura, Satoshi
The purpose of this study is to survey the current patterns of practice, and barriers to implementation, of 3D image-guided brachytherapy (3D-IGBT) for cervical cancer in Japan. A 30-item questionnaire was sent to 171 Japanese facilities where high-dose-rate brachytherapy devices were available in 2012. In total, 135 responses were returned for analysis. Fifty-one facilities had acquired some sort of 3D imaging modality with applicator insertion, and computed tomography (CT) and magnetic resonance imaging (MRI) were used in 51 and 3 of the facilities, respectively. For actual treatment planning, X-ray films, CT and MRI were used in 113, 20 and 2 facilities, respectively. Among 43 facilities where X-ray films and CT or MRI were acquired with an applicator, 29 still used X-ray films for actual treatment planning, mainly because of limited time and/or staffing. In a follow-up survey 2.5 years later, respondents included 38 facilities that originally used X-ray films alone but had indicated plans to adopt 3D-IGBT. Of these, 21 had indeed adopted CT imaging with applicator insertion. In conclusion, 3D-IGBT (mainly CT) was implemented in 22 facilities (16%) and will be installed in 72 (53%) facilities in the future. Limited time and staffing were major impediments.
Linear tracking for 3-D medical ultrasound imaging.
Huang, Qing-Hua; Yang, Zhao; Hu, Wei; Jin, Lian-Wen; Wei, Gang; Li, Xuelong
As the clinical application grows, there is a rapid technical development of 3-D ultrasound imaging. Compared with 2-D ultrasound imaging, 3-D ultrasound imaging can provide improved qualitative and quantitative information for various clinical applications. In this paper, we proposed a novel tracking method for a freehand 3-D ultrasound imaging system with improved portability, reduced degree of freedom, and cost. We designed a sliding track with a linear position sensor attached, and it transmitted positional data via a wireless communication module based on Bluetooth, resulting in a wireless spatial tracking modality. A traditional 2-D ultrasound probe fixed to the position sensor on the sliding track was used to obtain real-time B-scans, and the positions of the B-scans were simultaneously acquired when moving the probe along the track in a freehand manner. In the experiments, the proposed method was applied to ultrasound phantoms and real human tissues. The results demonstrated that the new system outperformed a previously developed freehand system based on a traditional six-degree-of-freedom spatial sensor in phantom and in vivo studies, indicating its merit in clinical applications for human tissues and organs.
3D imaging: how to achieve highest accuracy
NASA Astrophysics Data System (ADS)
Luhmann, Thomas
The generation of 3D information from images is a key technology in many different areas, e.g. in 3D modeling and representation of architectural or heritage objects, in human body motion tracking and scanning, in 3D scene analysis of traffic scenes, in industrial applications and many more. The basic concepts rely on mathematical representations of central perspective viewing as they are widely known from photogrammetry or computer vision approaches. The objectives of these methods differ, more or less, from high precision and well-structured measurements in (industrial) photogrammetry to fully-automated non-structured applications in computer vision. Accuracy and precision is a critical issue for the 3D measurement of industrial, engineering or medical objects. As state of the art, photogrammetric multi-view measurements achieve relative precisions in the order of 1:100000 to 1:200000, and relative accuracies with respect to retraceable lengths in the order of 1:50000 to 1:100000 of the largest object diameter. In order to obtain these figures a number of influencing parameters have to be optimized. These are, besides others: physical representation of object surface (targets, texture), illumination and light sources, imaging sensors, cameras and lenses, calibration strategies (camera model), orientation strategies (bundle adjustment), image processing of homologue features (target measurement, stereo and multi-image matching), representation of object or workpiece coordinate systems and object scale. The paper discusses the above mentioned parameters and offers strategies for obtaining highest accuracy in object space. Practical examples of high-quality stereo camera measurements and multi-image applications are used to prove the relevance of high accuracy in different applications, ranging from medical navigation to static and dynamic industrial measurements. In addition, standards for accuracy verifications are presented and demonstrated by practical examples
A case of pulmonary artery intimal sarcoma diagnosed with multislice CT scan with 3D reconstruction.
Choi, Eui-Young; Yoon, Young-Won; Kwon, Hyuck Moon; Kim, Dongsoo; Park, Byung-Eun; Hong, Yoo-Sun; Koo, Ja-Seung; Kim, Tae-Hoon; Kim, Hyun-Seung
Pulmonary artery intimal sarcoma is a rare highly lethal disease, with additional retrograde extension to pulmonic valve and right ventricle being an extremely rare condition. It is frequently mistaken for pulmonary thromboembolism. We report a case of 64-year-old woman with progressive dyspnea initially suspected and treated for pulmonary thromboembolism. Her helical chest CT scan with 3 dimensional (3D) reconstruction combined with echocardiography revealed a compacting main pulmonary artery mass extending to the right ventricular outflow tract and the right pulmonary artery. After excision of the mass, the patient's condition improved dramatically, and the pathologic findings revealed pulmonary intimal sarcoma. This report emphasizes that helical chest CT with 3D reconstruction can be an important tool to differentiate the characteristics of pulmonary artery lesions, such as intimal sarcoma and thromboembolism.
Volumetric CT-based segmentation of NSCLC using 3D-Slicer
Velazquez, Emmanuel Rios; Parmar, Chintan; Jermoumi, Mohammed; Mak, Raymond H.; van Baardwijk, Angela; Fennessy, Fiona M.; Lewis, John H.; De Ruysscher, Dirk; Kikinis, Ron; Lambin, Philippe; Aerts, Hugo J. W. L.
Accurate volumetric assessment in non-small cell lung cancer (NSCLC) is critical for adequately informing treatments. In this study we assessed the clinical relevance of a semiautomatic computed tomography (CT)-based segmentation method using the competitive region-growing based algorithm, implemented in the free and public available 3D-Slicer software platform. We compared the 3D-Slicer segmented volumes by three independent observers, who segmented the primary tumour of 20 NSCLC patients twice, to manual slice-by-slice delineations of five physicians. Furthermore, we compared all tumour contours to the macroscopic diameter of the tumour in pathology, considered as the "gold standard". The 3D-Slicer segmented volumes demonstrated high agreement (overlap fractions > 0.90), lower volume variability (p = 0.0003) and smaller uncertainty areas (p = 0.0002), compared to manual slice-by-slice delineations. Furthermore, 3D-Slicer segmentations showed a strong correlation to pathology (r = 0.89, 95%CI, 0.81–0.94). Our results show that semiautomatic 3D-Slicer segmentations can be used for accurate contouring and are more stable than manual delineations. Therefore, 3D-Slicer can be employed as a starting point for treatment decisions or for high-throughput data mining research, such as Radiomics, where manual delineating often represent a time-consuming bottleneck. PMID:24346241
Volumetric CT-based segmentation of NSCLC using 3D-Slicer
NASA Astrophysics Data System (ADS)
Velazquez, Emmanuel Rios; Parmar, Chintan; Jermoumi, Mohammed; Mak, Raymond H.; van Baardwijk, Angela; Fennessy, Fiona M.; Lewis, John H.; de Ruysscher, Dirk; Kikinis, Ron; Lambin, Philippe; Aerts, Hugo J. W. L.
Accurate volumetric assessment in non-small cell lung cancer (NSCLC) is critical for adequately informing treatments. In this study we assessed the clinical relevance of a semiautomatic computed tomography (CT)-based segmentation method using the competitive region-growing based algorithm, implemented in the free and public available 3D-Slicer software platform. We compared the 3D-Slicer segmented volumes by three independent observers, who segmented the primary tumour of 20 NSCLC patients twice, to manual slice-by-slice delineations of five physicians. Furthermore, we compared all tumour contours to the macroscopic diameter of the tumour in pathology, considered as the ``gold standard''. The 3D-Slicer segmented volumes demonstrated high agreement (overlap fractions > 0.90), lower volume variability (p = 0.0003) and smaller uncertainty areas (p = 0.0002), compared to manual slice-by-slice delineations. Furthermore, 3D-Slicer segmentations showed a strong correlation to pathology (r = 0.89, 95%CI, 0.81-0.94). Our results show that semiautomatic 3D-Slicer segmentations can be used for accurate contouring and are more stable than manual delineations. Therefore, 3D-Slicer can be employed as a starting point for treatment decisions or for high-throughput data mining research, such as Radiomics, where manual delineating often represent a time-consuming bottleneck.
Image Appraisal for 2D and 3D Electromagnetic Inversion
Alumbaugh, D.L.; Newman, G.A.
Linearized methods are presented for appraising image resolution and parameter accuracy in images generated with two and three dimensional non-linear electromagnetic inversion schemes. When direct matrix inversion is employed, the model resolution and posterior model covariance matrices can be directly calculated. A method to examine how the horizontal and vertical resolution varies spatially within the electromagnetic property image is developed by examining the columns of the model resolution matrix. Plotting the square root of the diagonal of the model covariance matrix yields an estimate of how errors in the inversion process such as data noise and incorrect a priori assumptions about the imaged model map into parameter error. This type of image is shown to be useful in analyzing spatial variations in the image sensitivity to the data. A method is analyzed for statistically estimating the model covariance matrix when the conjugate gradient method is employed rather than a direct inversion technique (for example in 3D inversion). A method for calculating individual columns of the model resolution matrix using the conjugate gradient method is also developed. Examples of the image analysis techniques are provided on 2D and 3D synthetic cross well EM data sets, as well as a field data set collected at the Lost Hills Oil Field in Central California.
Assessment of angiogenesis in osseointegration of a silica-collagen biomaterial using 3D-nano-CT.
Alt, Volker; Kögelmaier, Daniela Vera; Lips, Katrin S; Witt, Vera; Pacholke, Sabine; Heiss, Christian; Kampschulte, Marian; Heinemann, Sascha; Hanke, Thomas; Thormann, Ulrich; Schnettler, Reinhard; Langheinrich, Alexander C
Bony integration of biomaterials is a complex process in which angiogenesis plays a crucial role. We evaluated micro- and nano-CT imaging to demonstrate and quantify neovascularization in bony integration of a biomaterial and to give an image based estimation for the needed resolution for imaging angiogenesis in an animal model of femora defect healing. In 8 rats 5mm full-size defects were created at the left femur that was filled with silica-collagen bone substitute material and internally fixed with plate osteosynthesis. After 6 weeks the femora were infused in situ with Microfil, harvested and scanned for micro-CT (9 μm)(3) and nano-CT (3 μm)(3) imaging. Using those 3D images, the newly formed blood vessels in the area of the biomaterial were assessed and the total vascular volume fraction, the volume of the bone substitute material and the volume of the bone defect were quantitatively characterized. Results were complemented by histology. Differences were statistically assessed using (ANOVA). High-resolution nano-CT demonstrated new blood vessel formation surrounding the biomaterial in all animals at capillary level. Immunohistochemistry confirmed the newly formed blood vessels surrounding the bone substitute material. The mean vascular volume fraction (VVF) around the implant was calculated to be 3.01 ± 0.4%. The VVF was inversely correlated with the volume of the bone substitute material (r=0.8) but not with the dimension of the fracture zone (r=0.3). Nano-CT imaging is feasible for quantitative analysis of angiogenesis during bony integration of biomaterials and a promising tool in this context for the future.
Noise reduction for low-dose helical CT by 3D penalized weighted least-squares sinogram smoothing
NASA Astrophysics Data System (ADS)
Wang, Jing; Li, Tianfang; Lu, Hongbing; Liang, Zhengrong
Helical computed tomography (HCT) has several advantages over conventional step-and-shoot CT for imaging a relatively large object, especially for dynamic studies. However, HCT may increase X-ray exposure significantly to the patient. This work aims to reduce the radiation by lowering the X-ray tube current (mA) and filtering the low-mA (or dose) sinogram noise. Based on the noise properties of HCT sinogram, a three-dimensional (3D) penalized weighted least-squares (PWLS) objective function was constructed and an optimal sinogram was estimated by minimizing the objective function. To consider the difference of signal correlation among different direction of the HCT sinogram, an anisotropic Markov random filed (MRF) Gibbs function was designed as the penalty. The minimization of the objection function was performed by iterative Gauss-Seidel updating strategy. The effectiveness of the 3D-PWLS sinogram smoothing for low-dose HCT was demonstrated by a 3D Shepp-Logan head phantom study. Comparison studies with our previously developed KL domain PWLS sinogram smoothing algorithm indicate that the KL+2D-PWLS algorithm shows better performance on in-plane noise-resolution trade-off while the 3D-PLWS shows better performance on z-axis noise-resolution trade-off. Receiver operating characteristic (ROC) studies by using channelized Hotelling observer (CHO) shows that 3D-PWLS and KL+2DPWLS algorithms have similar performance on detectability in low-contrast environment.
Automated Recognition of 3D Features in GPIR Images
NASA Technical Reports Server (NTRS)
Park, Han; Stough, Timothy; Fijany, Amir
A method of automated recognition of three-dimensional (3D) features in images generated by ground-penetrating imaging radar (GPIR) is undergoing development. GPIR 3D images can be analyzed to detect and identify such subsurface features as pipes and other utility conduits. Until now, much of the analysis of GPIR images has been performed manually by expert operators who must visually identify and track each feature. The present method is intended to satisfy a need for more efficient and accurate analysis by means of algorithms that can automatically identify and track subsurface features, with minimal supervision by human operators. In this method, data from multiple sources (for example, data on different features extracted by different algorithms) are fused together for identifying subsurface objects. The algorithms of this method can be classified in several different ways. In one classification, the algorithms fall into three classes: (1) image-processing algorithms, (2) feature- extraction algorithms, and (3) a multiaxis data-fusion/pattern-recognition algorithm that includes a combination of machine-learning, pattern-recognition, and object-linking algorithms. The image-processing class includes preprocessing algorithms for reducing noise and enhancing target features for pattern recognition. The feature-extraction algorithms operate on preprocessed data to extract such specific features in images as two-dimensional (2D) slices of a pipe. Then the multiaxis data-fusion/ pattern-recognition algorithm identifies, classifies, and reconstructs 3D objects from the extracted features. In this process, multiple 2D features extracted by use of different algorithms and representing views along different directions are used to identify and reconstruct 3D objects. In object linking, which is an essential part of this process, features identified in successive 2D slices and located within a threshold radius of identical features in adjacent slices are linked in a
3D scene reconstruction based on 3D laser point cloud combining UAV images
NASA Astrophysics Data System (ADS)
Liu, Huiyun; Yan, Yangyang; Zhang, Xitong; Wu, Zhenzhen
It is a big challenge capturing and modeling 3D information of the built environment. A number of techniques and technologies are now in use. These include GPS, and photogrammetric application and also remote sensing applications. The experiment uses multi-source data fusion technology for 3D scene reconstruction based on the principle of 3D laser scanning technology, which uses the laser point cloud data as the basis and Digital Ortho-photo Map as an auxiliary, uses 3DsMAX software as a basic tool for building three-dimensional scene reconstruction. The article includes data acquisition, data preprocessing, 3D scene construction. The results show that the 3D scene has better truthfulness, and the accuracy of the scene meet the need of 3D scene construction.
Applying microCT and 3D visualization to Jurassic silicified conifer seed cones: A virtual advantage over thin-sectioning1
Gee, Carole T.
• Premise of the study: As an alternative to conventional thin-sectioning, which destroys fossil material, high-resolution X-ray computed tomography (also called microtomography or microCT) integrated with scientific visualization, three-dimensional (3D) image segmentation, size analysis, and computer animation is explored as a nondestructive method of imaging the internal anatomy of 150-million-year-old conifer seed cones from the Late Jurassic Morrison Formation, USA, and of recent and other fossil cones. • Methods: MicroCT was carried out on cones using a General Electric phoenix v|tome|x s 240D, and resulting projections were processed with visualization software to produce image stacks of serial single sections for two-dimensional (2D) visualization, 3D segmented reconstructions with targeted structures in color, and computer animations. • Results: If preserved in differing densities, microCT produced images of internal fossil tissues that showed important characters such as seed phyllotaxy or number of seeds per cone scale. Color segmentation of deeply embedded seeds highlighted the arrangement of seeds in spirals. MicroCT of recent cones was even more effective. • Conclusions: This is the first paper on microCT integrated with 3D segmentation and computer animation applied to silicified seed cones, which resulted in excellent 2D serial sections and segmented 3D reconstructions, revealing features requisite to cone identification and understanding of strobilus construction. PMID:25202495
Joint calibration of 3D resist image and CDSEM
NASA Astrophysics Data System (ADS)
Chou, C. S.; He, Y. Y.; Tang, Y. P.; Chang, Y. T.; Huang, W. C.; Liu, R. G.; Gau, T. S.
Traditionally, an optical proximity correction model is to evaluate the resist image at a specific depth within the photoresist and then extract the resist contours from the image. Calibration is generally implemented by comparing resist contours with the critical dimensions (CD). The wafer CD is usually collected by a scanning electron microscope (SEM), which evaluates the CD based on some criterion that is a function of gray level, differential signal, threshold or other parameters set by the SEM. However, the criterion does not reveal which depth the CD is obtained at. This depth inconsistency between modeling and SEM makes the model calibration difficult for low k1 images. In this paper, the vertical resist profile is obtained by modifying the model from planar (2D) to quasi-3D approach and comparing the CD from this new model with SEM CD. For this quasi-3D model, the photoresist diffusion along the depth of the resist is considered and the 3D photoresist contours are evaluated. The performance of this new model is studied and is better than the 2D model.
Digital acquisition system for high-speed 3-D imaging
NASA Astrophysics Data System (ADS)
Yafuso, Eiji
High-speed digital three-dimensional (3-D) imagery is possible using multiple independent charge-coupled device (CCD) cameras with sequentially triggered acquisition and individual field storage capability. The system described here utilizes sixteen independent cameras, providing versatility in configuration and image acquisition. By aligning the cameras in nearly coincident lines-of-sight, a sixteen frame two-dimensional (2-D) sequence can be captured. The delays can be individually adjusted lo yield a greater number of acquired frames during the more rapid segments of the event. Additionally, individual integration periods may be adjusted to ensure adequate radiometric response while minimizing image blur. An alternative alignment and triggering scheme arranges the cameras into two angularly separated banks of eight cameras each. By simultaneously triggering correlated stereo pairs, an eight-frame sequence of stereo images may be captured. In the first alignment scheme the camera lines-of-sight cannot be made precisely coincident. Thus representation of the data as a monocular sequence introduces the issue of independent camera coordinate registration with the real scene. This issue arises more significantly using the stereo pair method to reconstruct quantitative 3-D spatial information of the event as a function of time. The principal development here will be the derivation and evaluation of a solution transform and its inverse for the digital data which will yield a 3-D spatial mapping as a function of time.
3D tongue motion from tagged and cine MR images.
Xing, Fangxu; Woo, Jonghye; Murano, Emi Z; Lee, Junghoon; Stone, Maureen; Prince, Jerry L
Understanding the deformation of the tongue during human speech is important for head and neck surgeons and speech and language scientists. Tagged magnetic resonance (MR) imaging can be used to image 2D motion, and data from multiple image planes can be combined via post-processing to yield estimates of 3D motion. However, lacking boundary information, this approach suffers from inaccurate estimates near the tongue surface. This paper describes a method that combines two sources of information to yield improved estimation of 3D tongue motion. The method uses the harmonic phase (HARP) algorithm to extract motion from tags and diffeomorphic demons to provide surface deformation. It then uses an incompressible deformation estimation algorithm to incorporate both sources of displacement information to form an estimate of the 3D whole tongue motion. Experimental results show that use of combined information improves motion estimation near the tongue surface, a problem that has previously been reported as problematic in HARP analysis, while preserving accurate internal motion estimates. Results on both normal and abnormal tongue motions are shown.
Discrete Method of Images for 3D Radio Propagation Modeling
NASA Astrophysics Data System (ADS)
Novak, Roman
Discretization by rasterization is introduced into the method of images (MI) in the context of 3D deterministic radio propagation modeling as a way to exploit spatial coherence of electromagnetic propagation for fine-grained parallelism. Traditional algebraic treatment of bounding regions and surfaces is replaced by computer graphics rendering of 3D reflections and double refractions while building the image tree. The visibility of reception points and surfaces is also resolved by shader programs. The proposed rasterization is shown to be of comparable run time to that of the fundamentally parallel shooting and bouncing rays. The rasterization does not affect the signal evaluation backtracking step, thus preserving its advantage over the brute force ray-tracing methods in terms of accuracy. Moreover, the rendering resolution may be scaled back for a given level of scenario detail with only marginal impact on the image tree size. This allows selection of scene optimized execution parameters for faster execution, giving the method a competitive edge. The proposed variant of MI can be run on any GPU that supports real-time 3D graphics.
Validation of image processing tools for 3-D fluorescence microscopy.
Dieterlen, Alain; Xu, Chengqi; Gramain, Marie-Pierre; Haeberlé, Olivier; Colicchio, Bruno; Cudel, Christophe; Jacquey, Serge; Ginglinger, Emanuelle; Jung, Georges; Jeandidier, Eric
3-D optical fluorescent microscopy becomes nowadays an efficient tool for volumic investigation of living biological samples. Using optical sectioning technique, a stack of 2-D images is obtained. However, due to the nature of the system optical transfer function and non-optimal experimental conditions, acquired raw data usually suffer from some distortions. In order to carry out biological analysis, raw data have to be restored by deconvolution. The system identification by the point-spread function is useful to obtain the knowledge of the actual system and experimental parameters, which is necessary to restore raw data. It is furthermore helpful to precise the experimental protocol. In order to facilitate the use of image processing techniques, a multi-platform-compatible software package called VIEW3D has been developed. It integrates a set of tools for the analysis of fluorescence images from 3-D wide-field or confocal microscopy. A number of regularisation parameters for data restoration are determined automatically. Common geometrical measurements and morphological descriptors of fluorescent sites are also implemented to facilitate the characterisation of biological samples. An example of this method concerning cytogenetics is presented.
Automated spatial alignment of 3D torso images.
Bose, Arijit; Shah, Shishir K; Reece, Gregory P; Crosby, Melissa A; Beahm, Elisabeth K; Fingeret, Michelle C; Markey, Mia K; Merchant, Fatima A
This paper describes an algorithm for automated spatial alignment of three-dimensional (3D) surface images in order to achieve a pre-defined orientation. Surface images of the torso are acquired from breast cancer patients undergoing reconstructive surgery to facilitate objective evaluation of breast morphology pre-operatively (for treatment planning) and/or post-operatively (for outcome assessment). Based on the viewing angle of the multiple cameras used for stereophotography, the orientation of the acquired torso in the images may vary from the normal upright position. Consequently, when translating this data into a standard 3D framework for visualization and analysis, the co-ordinate geometry differs from the upright position making robust and standardized comparison of images impractical. Moreover, manual manipulation and navigation of images to the desired upright position is subject to user bias. Automating the process of alignment and orientation removes operator bias and permits robust and repeatable adjustment of surface images to a pre-defined or desired spatial geometry.
Fast 3D fluid registration of brain magnetic resonance images
NASA Astrophysics Data System (ADS)
Leporé, Natasha; Chou, Yi-Yu; Lopez, Oscar L.; Aizenstein, Howard J.; Becker, James T.; Toga, Arthur W.; Thompson, Paul M.
Fluid registration is widely used in medical imaging to track anatomical changes, to correct image distortions, and to integrate multi-modality data. Fluid mappings guarantee that the template image deforms smoothly into the target, without tearing or folding, even when large deformations are required for accurate matching. Here we implemented an intensity-based fluid registration algorithm, accelerated by using a filter designed by Bro-Nielsen and Gramkow. We validated the algorithm on 2D and 3D geometric phantoms using the mean square difference between the final registered image and target as a measure of the accuracy of the registration. In tests on phantom images with different levels of overlap, varying amounts of Gaussian noise, and different intensity gradients, the fluid method outperformed a more commonly used elastic registration method, both in terms of accuracy and in avoiding topological errors during deformation. We also studied the effect of varying the viscosity coefficients in the viscous fluid equation, to optimize registration accuracy. Finally, we applied the fluid registration algorithm to a dataset of 2D binary corpus callosum images and 3D volumetric brain MRIs from 14 healthy individuals to assess its accuracy and robustness.
Integral imaging based 3D display of holographic data.
Yöntem, Ali Özgür; Onural, Levent
We propose a method and present applications of this method that converts a diffraction pattern into an elemental image set in order to display them on an integral imaging based display setup. We generate elemental images based on diffraction calculations as an alternative to commonly used ray tracing methods. Ray tracing methods do not accommodate the interference and diffraction phenomena. Our proposed method enables us to obtain elemental images from a holographic recording of a 3D object/scene. The diffraction pattern can be either numerically generated data or digitally acquired optical data. The method shows the connection between a hologram (diffraction pattern) and an elemental image set of the same 3D object. We showed three examples, one of which is the digitally captured optical diffraction tomography data of an epithelium cell. We obtained optical reconstructions with our integral imaging display setup where we used a digital lenslet array. We also obtained numerical reconstructions, again by using the diffraction calculations, for comparison. The digital and optical reconstruction results are in good agreement.
WE-D-18A-05: Construction of Realistic Liver Phantoms From Patient Images and a Commercial 3D Printer
Leng, S; Vrieze, T; Kuhlmann, J; Yu, L; Matsumoto, J; Morris, J; McCollough, C
Purpose: To assess image quality and radiation dose reduction in abdominal CT imaging, physical phantoms having realistic background textures and lesions are highly desirable. The purpose of this work was to construct a liver phantom with realistic background and lesions using patient CT images and a 3D printer. Methods: Patient CT images containing liver lesions were segmented into liver tissue, contrast-enhanced vessels, and liver lesions using commercial software (Mimics, Materialise, Belgium). Stereolithography (STL) files of each segmented object were created and imported to a 3D printer (Object350 Connex, Stratasys, MN). After test scans were performed to map the eight available printing materials into CT numbers, printing materials were assigned to each object and a physical liver phantom printed. The printed phantom was scanned on a clinical CT scanner and resulting images were compared with the original patient CT images. Results: The eight available materials used to print the liver phantom had CT number ranging from 62 to 117 HU. In scans of the liver phantom, the liver lesions and veins represented in the STL files were all visible. Although the absolute value of the CT number in the background liver material (approx. 85 HU) was higher than in patients (approx. 40 HU), the difference in CT numbers between lesions and background were representative of the low contrast values needed for optimization tasks. Future work will investigate materials with contrast sufficient to emulate contrast-enhanced arteries. Conclusion: Realistic liver phantoms can be constructed from patient CT images using a commercial 3D printer. This technique may provide phantoms able to determine the effect of radiation dose reduction and noise reduction techniques on the ability to detect subtle liver lesions in the context of realistic background textures.
Image processing and 3D visualization in the interpretation of patterned injury of the skin
NASA Astrophysics Data System (ADS)
Oliver, William R.; Altschuler, Bruce R.
The use of image processing is becoming increasingly important in the evaluation of violent crime. While much work has been done in the use of these techniques for forensic purposes outside of forensic pathology, its use in the pathologic examination of wounding has been limited. We are investigating the use of image processing in the analysis of patterned injuries and tissue damage. Our interests are currently concentrated on 1) the use of image processing techniques to aid the investigator in observing and evaluating patterned injuries in photographs, 2) measurement of the 3D shape characteristics of surface lesions, and 3) correlation of patterned injuries with deep tissue injury as a problem in 3D visualization. We are beginning investigations in data-acquisition problems for performing 3D scene reconstructions from the pathology perspective of correlating tissue injury to scene features and trace evidence localization. Our primary tool for correlation of surface injuries with deep tissue injuries has been the comparison of processed surface injury photographs with 3D reconstructions from antemortem CT and MRI data. We have developed a prototype robot for the acquisition of 3D wound and scene data.
Volume estimation of tonsil phantoms using an oral camera with 3D imaging
Das, Anshuman J.; Valdez, Tulio A.; Vargas, Jose Arbouin; Saksupapchon, Punyapat; Rachapudi, Pushyami; Ge, Zhifei; Estrada, Julio C.; Raskar, Ramesh
Three-dimensional (3D) visualization of oral cavity and oropharyngeal anatomy may play an important role in the evaluation for obstructive sleep apnea (OSA). Although computed tomography (CT) and magnetic resonance (MRI) imaging are capable of providing 3D anatomical descriptions, this type of technology is not readily available in a clinic setting. Current imaging of the oropharynx is performed using a light source and tongue depressors. For better assessment of the inferior pole of the tonsils and tongue base flexible laryngoscopes are required which only provide a two dimensional (2D) rendering. As a result, clinical diagnosis is generally subjective in tonsillar hypertrophy where current physical examination has limitations. In this report, we designed a hand held portable oral camera with 3D imaging capability to reconstruct the anatomy of the oropharynx in tonsillar hypertrophy where the tonsils get enlarged and can lead to increased airway resistance. We were able to precisely reconstruct the 3D shape of the tonsils and from that estimate airway obstruction percentage and volume of the tonsils in 3D printed realistic models. Our results correlate well with Brodsky's classification of tonsillar hypertrophy as well as intraoperative volume estimations. PMID:27446667
The CT-PPS tracking system with 3D pixel detectors
NASA Astrophysics Data System (ADS)
Ravera, F.
The CMS-TOTEM Precision Proton Spectrometer (CT-PPS) detector will be installed in Roman pots (RP) positioned on either side of CMS, at about 210 m from the interaction point. This detector will measure leading protons, allowing detailed studies of diffractive physics and central exclusive production in standard LHC running conditions. An essential component of the CT-PPS apparatus is the tracking system, which consists of two detector stations per arm equipped with six 3D silicon pixel-sensor modules, each read out by six PSI46dig chips. The front-end electronics has been designed to fulfill the mechanical constraints of the RP and to be compatible as much as possible with the readout chain of the CMS pixel detector. The tracking system is currently under construction and will be installed by the end of 2016. In this contribution the final design and the expected performance of the CT-PPS tracking system is presented. A summary of the studies performed, before and after irradiation, on the 3D detectors produced for CT-PPS is given.
A hybrid framework for 3D medical image segmentation.
Chen, Ting; Metaxas, Dimitris
In this paper we propose a novel hybrid 3D segmentation framework which combines Gibbs models, marching cubes and deformable models. In the framework, first we construct a new Gibbs model whose energy function is defined on a high order clique system. The new model includes both region and boundary information during segmentation. Next we improve the original marching cubes method to construct 3D meshes from Gibbs models' output. The 3D mesh serves as the initial geometry of the deformable model. Then we deform the deformable model using external image forces so that the model converges to the object surface. We run the Gibbs model and the deformable model recursively by updating the Gibbs model's parameters using the region and boundary information in the deformable model segmentation result. In our approach, the hybrid combination of region-based methods and boundary-based methods results in improved segmentations of complex structures. The benefit of the methodology is that it produces high quality segmentations of 3D structures using little prior information and minimal user intervention. The modules in this segmentation methodology are developed within the context of the Insight ToolKit (ITK). We present experimental segmentation results of brain tumors and evaluate our method by comparing experimental results with expert manual segmentations. The evaluation results show that the methodology achieves high quality segmentation results with computational efficiency. We also present segmentation results of other clinical objects to illustrate the strength of the methodology as a generic segmentation framework.
Pavement cracking measurements using 3D laser-scan images
NASA Astrophysics Data System (ADS)
Ouyang, W.; Xu, B.
Pavement condition surveying is vital for pavement maintenance programs that ensure ride quality and traffic safety. This paper first introduces an automated pavement inspection system which uses a three-dimensional (3D) camera and a structured laser light to acquire dense transverse profiles of a pavement lane surface when it carries a moving vehicle. After the calibration, the 3D system can yield a depth resolution of 0.5 mm and a transverse resolution of 1.56 mm pixel-1 at 1.4 m camera height from the ground. The scanning rate of the camera can be set to its maximum at 5000 lines s-1, allowing the density of scanned profiles to vary with the vehicle's speed. The paper then illustrates the algorithms that utilize 3D information to detect pavement distress, such as transverse, longitudinal and alligator cracking, and presents the field tests on the system's repeatability when scanning a sample pavement in multiple runs at the same vehicle speed, at different vehicle speeds and under different weather conditions. The results show that this dedicated 3D system can capture accurate pavement images that detail surface distress, and obtain consistent crack measurements in repeated tests and under different driving and lighting conditions.
Objective breast symmetry evaluation using 3-D surface imaging.
Eder, Maximilian; Waldenfels, Fee V; Swobodnik, Alexandra; Klöppel, Markus; Pape, Ann-Kathrin; Schuster, Tibor; Raith, Stefan; Kitzler, Elena; Papadopulos, Nikolaos A; Machens, Hans-Günther; Kovacs, Laszlo
This study develops an objective breast symmetry evaluation using 3-D surface imaging (Konica-Minolta V910(®) scanner) by superimposing the mirrored left breast over the right and objectively determining the mean 3-D contour difference between the 2 breast surfaces. 3 observers analyzed the evaluation protocol precision using 2 dummy models (n = 60), 10 test subjects (n = 300), clinically tested it on 30 patients (n = 900) and compared it to established 2-D measurements on 23 breast reconstructive patients using the BCCT.core software (n = 690). Mean 3-D evaluation precision, expressed as the coefficient of variation (VC), was 3.54 ± 0.18 for all human subjects without significant intra- and inter-observer differences (p > 0.05). The 3-D breast symmetry evaluation is observer independent, significantly more precise (p < 0.001) than the BCCT.core software (VC = 6.92 ± 0.88) and may play a part in an objective surgical outcome analysis after incorporation into clinical practice.
Virtual image display as a backlight for 3D.
Travis, Adrian; MacCrann, Niall; Emerton, Neil; Kollin, Joel; Georgiou, Andreas; Lanier, Jaron; Bathiche, Stephen
We describe a device which has the potential to be used both as a virtual image display and as a backlight. The pupil of the emitted light fills the device approximately to its periphery and the collimated emission can be scanned both horizontally and vertically in the manner needed to illuminate an eye in any position. The aim is to reduce the power needed to illuminate a liquid crystal panel but also to enable a smooth transition from 3D to a virtual image as the user nears the screen.
Miniature stereoscopic video system provides real-time 3D registration and image fusion for minimally invasive surgery
NASA Astrophysics Data System (ADS)
Yaron, Avi; Bar-Zohar, Meir; Horesh, Nadav
Sophisticated surgeries require the integration of several medical imaging modalities, like MRI and CT, which are three-dimensional. Many efforts are invested in providing the surgeon with this information in an intuitive & easy to use manner. A notable development, made by Visionsense, enables the surgeon to visualize the scene in 3D using a miniature stereoscopic camera. It also provides real-time 3D measurements that allow registration of navigation systems as well as 3D imaging modalities, overlaying these images on the stereoscopic video image in real-time. The real-time MIS 'see through tissue' fusion solutions enable the development of new MIS procedures in various surgical segments, such as spine, abdomen, cardio-thoracic and brain. This paper describes 3D surface reconstruction and registration methods using Visionsense camera, as a step toward fully automated multi-modality 3D registration.
A new concept for intraoperative matching of 3D ultrasound and CT.
Schorr, O; Wörn, H
Matching of ultrasound images with CT or MRI scans is an awkward and unsatisfactory task when using conventional methods. Wide ranging differences in modality of ultrasound and CT/MRI require new techniques to be explored for successful alignment. Ultrasound images characteristically show comparable high noise ratio due to scattering inside the region of interest and the surrounding area. Additionally, shadowing and tissue dependent echo response time produce geometric artifacts. These image distortions are sophisticated to recover. Though image quality and geometric relationship are poor, ultrasound images show the potential for fast, low-cost, non-invasive and flexible image acquisition, predestinated for intraoperative application. The fusion of intraoperative ultrasound and preoperatively acquired CT/MRI images provides both, geometric invariance and flexible fast image acquisition, merging in a powerful tool for augmented three dimensional reality. In this paper we describe a completely new concept for alignment with abstaining from direct rigid or elastic matching of ultrasound to CT/MRI. Instead of placing those images in direct relationship, our approach involves a simulation of ultrasound wave behavior in order to predict B-mode images.
Automatic structural matching of 3D image data
NASA Astrophysics Data System (ADS)
Ponomarev, Svjatoslav; Lutsiv, Vadim; Malyshev, Igor
A new image matching technique is described. It is implemented as an object-independent hierarchical structural juxtaposition algorithm based on an alphabet of simple object-independent contour structural elements. The structural matching applied implements an optimized method of walking through a truncated tree of all possible juxtapositions of two sets of structural elements. The algorithm was initially developed for dealing with 2D images such as the aerospace photographs, and it turned out to be sufficiently robust and reliable for matching successfully the pictures of natural landscapes taken in differing seasons from differing aspect angles by differing sensors (the visible optical, IR, and SAR pictures, as well as the depth maps and geographical vector-type maps). At present (in the reported version), the algorithm is enhanced based on additional use of information on third spatial coordinates of observed points of object surfaces. Thus, it is now capable of matching the images of 3D scenes in the tasks of automatic navigation of extremely low flying unmanned vehicles or autonomous terrestrial robots. The basic principles of 3D structural description and matching of images are described, and the examples of image matching are presented.
Underwater 3d Modeling: Image Enhancement and Point Cloud Filtering
NASA Astrophysics Data System (ADS)
Sarakinou, I.; Papadimitriou, K.; Georgoula, O.; Patias, P.
This paper examines the results of image enhancement and point cloud filtering on the visual and geometric quality of 3D models for the representation of underwater features. Specifically it evaluates the combination of effects from the manual editing of images' radiometry (captured at shallow depths) and the selection of parameters for point cloud definition and mesh building (processed in 3D modeling software). Such datasets, are usually collected by divers, handled by scientists and used for geovisualization purposes. In the presented study, have been created 3D models from three sets of images (seafloor, part of a wreck and a small boat's wreck) captured at three different depths (3.5m, 10m and 14m respectively). Four models have been created from the first dataset (seafloor) in order to evaluate the results from the application of image enhancement techniques and point cloud filtering. The main process for this preliminary study included a) the definition of parameters for the point cloud filtering and the creation of a reference model, b) the radiometric editing of images, followed by the creation of three improved models and c) the assessment of results by comparing the visual and the geometric quality of improved models versus the reference one. Finally, the selected technique is tested on two other data sets in order to examine its appropriateness for different depths (at 10m and 14m) and different objects (part of a wreck and a small boat's wreck) in the context of an ongoing research in the Laboratory of Photogrammetry and Remote Sensing.
3D surface imaging for guidance in breast cancer radiotherapy: organs at risk
NASA Astrophysics Data System (ADS)
Alderliesten, Tanja; Betgen, Anja; van Vliet-Vroegindeweij, Corine; Remeijer, Peter
Purpose: To evaluate the variability in heart position in deep-inspiration breath-hold (DIBH) radiotherapy for breast cancer when 3D surface imaging would be used for monitoring the depth of the breath hold during treatment. Materials and Methods: Ten patients who received DIBH radiotherapy after breast-conserving surgery (BCS) were included. Retrospectively, heart-based registrations were performed for cone-beam computed tomography (CBCT) to planning CT and breast surface registrations were performed for a 3D surface (two different regions of interest [ROIs]), captured concurrently with CBCT, to planning CT. The resulting setup errors were compared with linear regression analysis and receiver operating characteristic (ROC) analysis was performed to investigate the prediction quality of 3D surface imaging for 3D heart displacement. Further, the residual setup errors (systematic [Σ] and random [σ]) of the heart were estimated relative to the surface registrations. Results: When surface imaging [ROIleft-side;ROIboth-sides] would be used for monitoring, the residual errors of the heart position are in left-right: Σ=[0.360.12], σ=[0.160.14] cranio-caudal: Σ=[0.540.54], σ=[0.280.31] and in anteriorposterior: Σ=[0.180.14], σ=[0.200.19] cm. Correlations between setup errors were: R2 = [0.23;0.73], [0.67;0.65], [0.65;0.73] in left-right, cranio-caudal, and anterior-posterior direction, respectively. ROC analysis resulted in an area under the ROC curve of [0.82;0.78]. Conclusion: The use of ROIboth-sides provided promising results. However, considerable variability in the heart position, particularly in CC direction, is observed when 3D surface imaging would be used for guidance in DIBH radiotherapy after BCS. Planning organ at risk volume margins should be used to take into account the heart-position variability.
3-D imaging in post-traumatic malformation and eruptive disturbance in permanent incisors: a case report.
Sahai, Sharad; Kaveriappa, Sushma; Arora, Honey; Aggarwal, Bharat
Injury to the primary dentition is one of the common problems of childhood. Disturbances during crown development of the permanent teeth result in morphologic alterations. This case report highlights the role of 3-D imaging when conventional dental radiographs are not enough to answer our clinical questions regarding future eruptive disturbances. 3-D imaging can many times give us a definitive diagnosis and improve the treatment planning after early injuries in the deciduous dentition. The current status of multislice computed tomography (CT) and cone beam CT (CBCT) as diagnostic tools in pediatric dental population is also discussed briefly.
Feature detection on 3D images of dental imprints
NASA Astrophysics Data System (ADS)
Mokhtari, Marielle; Laurendeau, Denis
A computer vision approach for the extraction of feature points on 3D images of dental imprints is presented. The position of feature points are needed for the measurement of a set of parameters for automatic diagnosis of malocclusion problems in orthodontics. The system for the acquisition of the 3D profile of the imprint, the procedure for the detection of the interstices between teeth, and the approach for the identification of the type of tooth are described, as well as the algorithm for the reconstruction of the surface of each type of tooth. A new approach for the detection of feature points, called the watershed algorithm, is described in detail. The algorithm is a two-stage procedure which tracks the position of local minima at four different scales and produces a final map of the position of the minima. Experimental results of the application of the watershed algorithm on actual 3D images of dental imprints are presented for molars, premolars and canines. The segmentation approach for the analysis of the shape of incisors is also described in detail.
Quantification of thyroid volume using 3-D ultrasound imaging.
Kollorz, E K; Hahn, D A; Linke, R; Goecke, T W; Hornegger, J; Kuwert, T
Ultrasound (US) is among the most popular diagnostic techniques today. It is non-invasive, fast, comparably cheap, and does not require ionizing radiation. US is commonly used to examine the size, and structure of the thyroid gland. In clinical routine, thyroid imaging is usually performed by means of 2-D US. Conventional approaches for measuring the volume of the thyroid gland or its nodules may therefore be inaccurate due to the lack of 3-D information. This work reports a semi-automatic segmentation approach for the classification, and analysis of the thyroid gland based on 3-D US data. The images are scanned in 3-D, pre-processed, and segmented. Several pre-processing methods, and an extension of a commonly used geodesic active contour level set formulation are discussed in detail. The results obtained by this approach are compared to manual interactive segmentations by a medical expert in five representative patients. Our work proposes a novel framework for the volumetric quantification of thyroid gland lobes, which may also be expanded to other parenchymatous organs.
3D imaging of biological specimen using MS.
Fletcher, John S
Imaging MS can provide unique information about the distribution of native and non-native compounds in biological specimen. MALDI MS and secondary ion MS are the two most commonly applied imaging MS techniques and can provide complementary information about a sample. MALDI offers access to high mass species such as proteins while secondary ion MS can operate at higher spatial resolution and provide information about lower mass species including elemental signals. Imaging MS is not limited to two dimensions and different approaches have been developed that allow 3D molecular images to be generated of chemicals in whole organs down to single cells. Resolution in the z-dimension is often higher than in x and y, so such analysis offers the potential for probing the distribution of drug molecules and studying drug action by MS with a much higher precision - possibly even organelle level.
3D Gabor wavelet based vessel filtering of photoacoustic images.
Haq, Israr Ul; Nagoaka, Ryo; Makino, Takahiro; Tabata, Takuya; Saijo, Yoshifumi
Filtering and segmentation of vasculature is an important issue in medical imaging. The visualization of vasculature is crucial for the early diagnosis and therapy in numerous medical applications. This paper investigates the use of Gabor wavelet to enhance the effect of vasculature while eliminating the noise due to size, sensitivity and aperture of the detector in 3D Optical Resolution Photoacoustic Microscopy (OR-PAM). A detailed multi-scale analysis of wavelet filtering and Hessian based method is analyzed for extracting vessels of different sizes since the blood vessels usually vary with in a range of radii. The proposed algorithm first enhances the vasculature in the image and then tubular structures are classified by eigenvalue decomposition of the local Hessian matrix at each voxel in the image. The algorithm is tested on non-invasive experiments, which shows appreciable results to enhance vasculature in photo-acoustic images.
Performance prediction for 3D filtering of multichannel images
NASA Astrophysics Data System (ADS)
Rubel, Oleksii; Kozhemiakin, Ruslan A.; Abramov, Sergey K.; Lukin, Vladimir V.; Vozel, Benoit; Chehdi, Kacem
Performance of denoising based on discrete cosine transform applied to multichannel remote sensing images corrupted by additive white Gaussian noise is analyzed. Images obtained by satellite Earth Observing-1 (EO-1) mission using hyperspectral imager instrument (Hyperion) that have high input SNR are taken as test images. Denoising performance is characterized by improvement of PSNR. For hard-thresholding 3D DCT-based denoising, simple statistics (probabilities to be less than a certain threshold) are used to predict denoising efficiency using curves fitted into scatterplots. It is shown that the obtained curves (approximations) provide prediction of denoising efficiency with high accuracy. Analysis is carried out for different numbers of channels processed jointly. Universality of prediction for different number of channels is proven.
3D Lunar Terrain Reconstruction from Apollo Images
NASA Technical Reports Server (NTRS)
Broxton, Michael J.; Nefian, Ara V.; Moratto, Zachary; Kim, Taemin; Lundy, Michael; Segal, Alkeksandr V.
Generating accurate three dimensional planetary models is becoming increasingly important as NASA plans manned missions to return to the Moon in the next decade. This paper describes a 3D surface reconstruction system called the Ames Stereo Pipeline that is designed to produce such models automatically by processing orbital stereo imagery. We discuss two important core aspects of this system: (1) refinement of satellite station positions and pose estimates through least squares bundle adjustment; and (2) a stochastic plane fitting algorithm that generalizes the Lucas-Kanade method for optimal matching between stereo pair images.. These techniques allow us to automatically produce seamless, highly accurate digital elevation models from multiple stereo image pairs while significantly reducing the influence of image noise. Our technique is demonstrated on a set of 71 high resolution scanned images from the Apollo 15 mission
Phase Sensitive Cueing for 3D Objects in Overhead Images
Paglieroni, D W; Eppler, W G; Poland, D N
A 3D solid model-aided object cueing method that matches phase angles of directional derivative vectors at image pixels to phase angles of vectors normal to projected model edges is described. It is intended for finding specific types of objects at arbitrary position and orientation in overhead images, independent of spatial resolution, obliqueness, acquisition conditions, and type of imaging sensor. It is shown that the phase similarity measure can be efficiently evaluated over all combinations of model position and orientation using the FFT. The highest degree of similarity over all model orientations is captured in a match surface of similarity values vs. model position. Unambiguous peaks in this surface are sorted in descending order of similarity value, and the small image thumbnails that contain them are presented to human analysts for inspection in sorted order.
Interactive navigation-guided ophthalmic plastic surgery: the utility of 3D CT-DCG-guided dacryolocalization in secondary acquired lacrimal duct obstructions
Ali, Mohammad Javed; Singh, Swati; Naik, Milind N; Kaliki, Swathi; Dave, Tarjani Vivek
Aim The aim of this study was to report the preliminary experience with the techniques and utility of navigation-guided, 3D, computed tomography–dacryocystography (CT-DCG) in the management of secondary acquired lacrimal drainage obstructions. Methods Stereotactic surgeries using CT-DCG as the intraoperative image-guiding tool were performed in 3 patients. One patient had nasolacrimal duct obstruction (NLDO) following a complete maxillectomy for a sinus malignancy, and the other 2 had NLDO following extensive maxillofacial trauma. All patients underwent a 3D CT-DCG. Image-guided dacryolocalization (IGDL) was performed using the intraoperative image-guided StealthStation™ system in the electromagnetic mode. All patients underwent navigation-guided powered endoscopic dacryocystorhinostomy (DCR). The utility of intraoperative dacryocystographic guidance and the ability to localize the lacrimal drainage system in the altered endoscopic anatomical milieu were noted. Results Intraoperative geometric localization of the lacrimal sac and the nasolacrimal duct could be easily achieved. Constant orientation of the lacrimal drainage system was possible while navigating in the vicinity of altered endoscopic perilacrimal anatomy. Useful clues with regard to modifications while performing a powered endoscopic DCR could be obtained. Surgeries could be performed with utmost safety and precision, thereby avoiding complications. Detailed preoperative 3D CT-DCG reconstructions with constant intraoperative dacryolocalization were found to be essential for successful outcomes. Conclusion The 3D CT-DCG-guided navigation procedure is very useful while performing endoscopic DCRs in cases of secondary acquired and complex NLDOs. PMID:28115826
Evaluation of Kinect 3D Sensor for Healthcare Imaging.
Pöhlmann, Stefanie T L; Harkness, Elaine F; Taylor, Christopher J; Astley, Susan M
Microsoft Kinect is a three-dimensional (3D) sensor originally designed for gaming that has received growing interest as a cost-effective and safe device for healthcare imaging. Recent applications of Kinect in health monitoring, screening, rehabilitation, assistance systems, and intervention support are reviewed here. The suitability of available technologies for healthcare imaging applications is assessed. The performance of Kinect I, based on structured light technology, is compared with that of the more recent Kinect II, which uses time-of-flight measurement, under conditions relevant to healthcare applications. The accuracy, precision, and resolution of 3D images generated with Kinect I and Kinect II are evaluated using flat cardboard models representing different skin colors (pale, medium, and dark) at distances ranging from 0.5 to 1.2 m and measurement angles of up to 75°. Both sensors demonstrated high accuracy (majority of measurements <2 mm) and precision (mean point to plane error <2 mm) at an average resolution of at least 390 points per cm(2). Kinect I is capable of imaging at shorter measurement distances, but Kinect II enables structures angled at over 60° to be evaluated. Kinect II showed significantly higher precision and Kinect I showed significantly higher resolution (both p < 0.001). The choice of object color can influence measurement range and precision. Although Kinect is not a medical imaging device, both sensor generations show performance adequate for a range of healthcare imaging applications. Kinect I is more appropriate for short-range imaging and Kinect II is more appropriate for imaging highly curved surfaces such as the face or breast.
The 3D model control of image processing
NASA Technical Reports Server (NTRS)
Nguyen, An H.; Stark, Lawrence
Telerobotics studies remote control of distant robots by a human operator using supervisory or direct control. Even if the robot manipulators has vision or other senses, problems arise involving control, communications, and delay. The communication delays that may be expected with telerobots working in space stations while being controlled from an Earth lab have led to a number of experiments attempting to circumvent the problem. This delay in communication is a main motivating factor in moving from well understood instantaneous hands-on manual control to less well understood supervisory control; the ultimate step would be the realization of a fully autonomous robot. The 3-D model control plays a crucial role in resolving many conflicting image processing problems that are inherent in resolving in the bottom-up approach of most current machine vision processes. The 3-D model control approach is also capable of providing the necessary visual feedback information for both the control algorithms and for the human operator.
Computed Tomography Image Origin Identification based on Original Sensor Pattern Noise and 3D Image Reconstruction Algorithm Footprints.
Duan, Yuping; Bouslimi, Dalel; Yang, Guanyu; Shu, Huazhong; Coatrieux, Gouenou
In this paper, we focus on the "blind" identification of the Computed Tomography (CT) scanner that has produced a CT image. To do so, we propose a set of noise features derived from the image chain acquisition and which can be used as CT-Scanner footprint. Basically, we propose two approaches. The first one aims at identifying a CT-Scanner based on an Original Sensor Pattern Noise (OSPN) that is intrinsic to the X-ray detectors. The second one identifies an acquisition system based on the way this noise is modified by its 3D image reconstruction algorithm. As these reconstruction algorithms are manufacturer dependent and kept secret, our features are used as input to train an SVM based classifier so as to discriminate acquisition systems. Experiments conducted on images issued from 15 different CT-Scanner models of 4 distinct manufacturers demonstrate that our system identifies the origin of one CT image with a detection rate of at least 94% and that it achieves better performance than Sensor Pattern Noise (SPN) based strategy proposed for general public camera devices.
3D Imaging of the OH mesospheric emissive layer
NASA Astrophysics Data System (ADS)
Kouahla, M. N.; Moreels, G.; Faivre, M.; Clairemidi, J.; Meriwether, J. W.; Lehmacher, G. A.; Vidal, E.; Veliz, O.
A new and original stereo imaging method is introduced to measure the altitude of the OH nightglow layer and provide a 3D perspective map of the altitude of the layer centroid. Near-IR photographs of the OH layer are taken at two sites separated by a 645 km distance. Each photograph is processed in order to provide a satellite view of the layer. When superposed, the two views present a common diamond-shaped area. Pairs of matched points that correspond to a physical emissive point in the common area are identified in calculating a normalized cross-correlation coefficient (NCC). This method is suitable for obtaining 3D representations in the case of low-contrast objects. An observational campaign was conducted in July 2006 in Peru. The images were taken simultaneously at Cerro Cosmos (12°09‧08.2″ S, 75°33‧49.3″ W, altitude 4630 m) close to Huancayo and Cerro Verde Tellolo (16°33‧17.6″ S, 71°39‧59.4″ W, altitude 2272 m) close to Arequipa. 3D maps of the layer surface were retrieved and compared with pseudo-relief intensity maps of the same region. The mean altitude of the emission barycenter is located at 86.3 km on July 26. Comparable relief wavy features appear in the 3D and intensity maps. It is shown that the vertical amplitude of the wave system varies as exp (Δz/2H) within the altitude range Δz = 83.5-88.0 km, H being the scale height. The oscillatory kinetic energy at the altitude of the OH layer is comprised between 3 × 10-4 and 5.4 × 10-4 J/m3, which is 2-3 times smaller than the values derived from partial radio wave at 52°N latitude.
3D seismic imaging on massively parallel computers
Womble, D.E.; Ober, C.C.; Oldfield, R.
The ability to image complex geologies such as salt domes in the Gulf of Mexico and thrusts in mountainous regions is a key to reducing the risk and cost associated with oil and gas exploration. Imaging these structures, however, is computationally expensive. Datasets can be terabytes in size, and the processing time required for the multiple iterations needed to produce a velocity model can take months, even with the massively parallel computers available today. Some algorithms, such as 3D, finite-difference, prestack, depth migration remain beyond the capacity of production seismic processing. Massively parallel processors (MPPs) and algorithms research are the tools that will enable this project to provide new seismic processing capabilities to the oil and gas industry. The goals of this work are to (1) develop finite-difference algorithms for 3D, prestack, depth migration; (2) develop efficient computational approaches for seismic imaging and for processing terabyte datasets on massively parallel computers; and (3) develop a modular, portable, seismic imaging code.
Development and comparison of projection and image space 3D nodule insertion techniques
NASA Astrophysics Data System (ADS)
Robins, Marthony; Solomon, Justin; Sahbaee, Pooyan; Samei, Ehsan
This study aimed to develop and compare two methods of inserting computerized virtual lesions into CT datasets. 24 physical (synthetic) nodules of three sizes and four morphologies were inserted into an anthropomorphic chest phantom (LUNGMAN, KYOTO KAGAKU). The phantom was scanned (Somatom Definition Flash, Siemens Healthcare) with and without nodules present, and images were reconstructed with filtered back projection and iterative reconstruction (SAFIRE) at 0.6 mm slice thickness using a standard thoracic CT protocol at multiple dose settings. Virtual 3D CAD models based on the physical nodules were virtually inserted (accounting for the system MTF) into the nodule-free CT data using two techniques. These techniques include projection-based and image-based insertion. Nodule volumes were estimated using a commercial segmentation tool (iNtuition, TeraRecon, Inc.). Differences were tested using paired t-tests and R2 goodness of fit between the virtually and physically inserted nodules. Both insertion techniques resulted in nodule volumes very similar to the real nodules (<3% difference) and in most cases the differences were not statistically significant. Also, R2 values were all <0.97 for both insertion techniques. These data imply that these techniques can confidently be used as a means of inserting virtual nodules in CT datasets. These techniques can be instrumental in building hybrid CT datasets composed of patient images with virtually inserted nodules.
Post-processing methods of rendering and visualizing 3-D reconstructed tomographic images
Wong, S.T.C.
The purpose of this presentation is to discuss the computer processing techniques of tomographic images, after they have been generated by imaging scanners, for volume visualization. Volume visualization is concerned with the representation, manipulation, and rendering of volumetric data. Since the first digital images were produced from computed tomography (CT) scanners in the mid 1970s, applications of visualization in medicine have expanded dramatically. Today, three-dimensional (3D) medical visualization has expanded from using CT data, the first inherently digital source of 3D medical data, to using data from various medical imaging modalities, including magnetic resonance scanners, positron emission scanners, digital ultrasound, electronic and confocal microscopy, and other medical imaging modalities. We have advanced from rendering anatomy to aid diagnosis and visualize complex anatomic structures to planning and assisting surgery and radiation treatment. New, more accurate and cost-effective procedures for clinical services and biomedical research have become possible by integrating computer graphics technology with medical images. This trend is particularly noticeable in current market-driven health care environment. For example, interventional imaging, image-guided surgery, and stereotactic and visualization techniques are now stemming into surgical practice. In this presentation, we discuss only computer-display-based approaches of volumetric medical visualization. That is, we assume that the display device available is two-dimensional (2D) in nature and all analysis of multidimensional image data is to be carried out via the 2D screen of the device. There are technologies such as holography and virtual reality that do provide a {open_quotes}true 3D screen{close_quotes}. To confine the scope, this presentation will not discuss such approaches.
Efficient curve-skeleton computation for the analysis of biomedical 3d images - biomed 2010.
Brun, Francesco; Dreossi, Diego
Advances in three dimensional (3D) biomedical imaging techniques, such as magnetic resonance (MR) and computed tomography (CT), make it easy to reconstruct high quality 3D models of portions of human body and other biological specimens. A major challenge lies in the quantitative analysis of the resulting models thus allowing a more comprehensive characterization of the object under investigation. An interesting approach is based on curve-skeleton (or medial axis) extraction, which gives basic information concerning the topology and the geometry. Curve-skeletons have been applied in the analysis of vascular networks and the diagnosis of tracheal stenoses as well as a 3D flight path in virtual endoscopy. However curve-skeleton computation is a crucial task. An effective skeletonization algorithm was introduced by N. Cornea in [1] but it lacks in computational performances. Thanks to the advances in imaging techniques the resolution of 3D images is increasing more and more, therefore there is the need for efficient algorithms in order to analyze significant Volumes of Interest (VOIs). In the present paper an improved skeletonization algorithm based on the idea proposed in [1] is presented. A computational comparison between the original and the proposed method is also reported. The obtained results show that the proposed method allows a significant computational improvement making more appealing the adoption of the skeleton representation in biomedical image analysis applications.
Improving 3D Wavelet-Based Compression of Hyperspectral Images
NASA Technical Reports Server (NTRS)
Klimesh, Matthew; Kiely, Aaron; Xie, Hua; Aranki, Nazeeh
Two methods of increasing the effectiveness of three-dimensional (3D) wavelet-based compression of hyperspectral images have been developed. (As used here, images signifies both images and digital data representing images.) The methods are oriented toward reducing or eliminating detrimental effects of a phenomenon, referred to as spectral ringing, that is described below. In 3D wavelet-based compression, an image is represented by a multiresolution wavelet decomposition consisting of several subbands obtained by applying wavelet transforms in the two spatial dimensions corresponding to the two spatial coordinate axes of the image plane, and by applying wavelet transforms in the spectral dimension. Spectral ringing is named after the more familiar spatial ringing (spurious spatial oscillations) that can be seen parallel to and near edges in ordinary images reconstructed from compressed data. These ringing phenomena are attributable to effects of quantization. In hyperspectral data, the individual spectral bands play the role of edges, causing spurious oscillations to occur in the spectral dimension. In the absence of such corrective measures as the present two methods, spectral ringing can manifest itself as systematic biases in some reconstructed spectral bands and can reduce the effectiveness of compression of spatially-low-pass subbands. One of the two methods is denoted mean subtraction. The basic idea of this method is to subtract mean values from spatial planes of spatially low-pass subbands prior to encoding, because (a) such spatial planes often have mean values that are far from zero and (b) zero-mean data are better suited for compression by methods that are effective for subbands of two-dimensional (2D) images. In this method, after the 3D wavelet decomposition is performed, mean values are computed for and subtracted from each spatial plane of each spatially-low-pass subband. The resulting data are converted to sign-magnitude form and compressed in a
3D geometry-based quantification of colocalizations in multichannel 3D microscopy images of human soft tissue tumors.
Wörz, Stefan; Sander, Petra; Pfannmöller, Martin; Rieker, Ralf J; Joos, Stefan; Mechtersheimer, Gunhild; Boukamp, Petra; Lichter, Peter; Rohr, Karl
We introduce a new model-based approach for automatic quantification of colocalizations in multichannel 3D microscopy images. The approach uses different 3D parametric intensity models in conjunction with a model fitting scheme to localize and quantify subcellular structures with high accuracy. The central idea is to determine colocalizations between different channels based on the estimated geometry of the subcellular structures as well as to differentiate between different types of colocalizations. A statistical analysis was performed to assess the significance of the determined colocalizations. This approach was used to successfully analyze about 500 three-channel 3D microscopy images of human soft tissue tumors and controls.
Towards real-time 3D US-CT registration on the beating heart for guidance of minimally invasive cardiac interventions
NASA Astrophysics Data System (ADS)
Li, Feng; Lang, Pencilla; Rajchl, Martin; Chen, Elvis C. S.; Guiraudon, Gerard; Peters, Terr