Brain MRI segmentation using the mixture of FCM and RBF neural network

Abstract

One of the most commonly used methods for Magnetic Resonance Imaging (MRI) segmentation is Fuzzy C-Means (FCM). This method in comparison with other methods preserves more information of the images. Because of using the intensity of pixels as a key feature for clustering, Standard FCM is sensitive to noise. In this study in addition to intensity, mean of neighbourhood of pixels and largest singular value of neighbourhood of pixels are used as features. Also a method for segmenting MRI images is presented which uses both FCM and Radial Basis Function (RBF) neural network and partly decreases the limitation of standard FCM.