<p>Imaging plays an important role in medical field like medical diagnosis, treatment planning and patient follow up. Image segmentation is the backbone process to accomplish these tasks by dividing an image in to meaningful parts which share similar properties. Medical Resonance Imaging (MRI) is primary diagnostic technique to do image segmentation. There are several techniques proposed for image segmentation of different parts of body like Region growing, Thresholding, Clustering methods and Soft computing techniques (Fuzzy Logic, Neural Network, Genetic Algorithm).The proposed research work uses Grey level Co-occurrence Matrix (GLCM) for texture feature extraction, ANFIS(Adaptive Network Fuzzy inference System) plus Genetic Algorithm for feature selection and FCM(Fuzzy C-Means) for segmentation of Astrocytoma (Brain Tumor) with all four Grades. The comparative study between FCM, FCM plus K-mean, Genetic Algorithm, ANFIS and proposed technique shows improved Accuracy, Sensitivity and Specificity.</p>
Brain tumor classification using the diffusion tensor image segmentation (D-SEG) technique
