{'fraction_non_alphanumeric': 0.015306122448979591, 'fraction_numerical': 0.003826530612244898, 'mean_word_length': 5.5103734439834025, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Consistency and Comparison of Medical Image Registration-Segmentation and Mathematical Model for Glioblastoma Volume Progression

Tumor volume progression and calculation is a very common task in cancer research and image processing. Tumor volume analysis can be carried out in two ways. The first way is using different mathematical formulas and the second way is using image registration-segmentation method. In this paper an objective application of registration of multiple brain imaging scans with segmentation is used to investigate brain tumor growth in a 3 dimensional (3D) manner. Using 3D medical image registration-segmentation algorithm, multiple scans of MR images of a patient who has brain tumor are registered with different MR images of the same patient acquired at a different time so that growth of the tumor inside the patient's brain can be investigated. Brain tumor volume measurement is also achieved using mathematical model based formulas in this paper. Medical image registration-segmentation and mathematical based method are implemented to 19 patients and satisfactory results are obtained. An advantageous point of medical image registration-segmentation method for brain tumor investigation is that grown, diminished, and unchanged brain tumor parts of the patients are investigated and computed on an individual basis in a three-dimensional (3D) manner within the time. This paper is intended to provide a comprehensive reference source for researchers involved in medical image registration, segmentation and tumor growth investigation.