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Textural Feature Extraction and Analysis for Brain Tumors using MRI

The proposed research work is to perform textural analysis of the brain tumor on MRI images and this process aims by giving correct decisions towards medication and providing tools for automated extraction of the most discerning features of regions of interest in human brain. The detection of tumor in human brain (MRI) is performed through segmentation and for region characterization we use texture information. Based on extracted information the textural analysis of tumor is done. For the selection of region of interest we use FCM and Level set segmentation. After selecting region of interest we extract GLCM features from the segmented brain tumor image. The textural information is captured from the region of interest using Haralick textural descriptor features. To train and classify the tumor into benign or malignant we use SVM classifier. The ultimate aim is to develop an automated classification of region into one of the classes as benign or malignant. The digital medical imaging and clinical data associating on daily data are witnessed by the hospitals all over the world. The expertise will be able to analyze, inspect quickly the images.