A new segmentation system for brain MR images based on fuzzy techniques

This work concerns a new method called fuzzy membership C-means (FMCMs) for segmentation of magnetic resonance images (MRI), and an efficient program implementation of it to the segmentation of MRI. Classical unsupervised clustering methods including the FCM by Bezdek, suffer many problems that can be partially treated with a proper rule to construct the initial membership matrix to clusters. This work develops a specific method to construct the initial membership matrix to clusters in order to improve the strength of the clusters. The new FMCM is tested on a set of benchmarks and then the application to the segmentation of MR images is presented and compared with the results obtained using FCM.