A Modified FCM Algorithm for MRI Brain Image Segmentation

Image segmentation is the first step in the computer aided medical image process, particularly during the clinical analysis of magnetic resonance(MR) brain image. Fuzzy c-means clustering algorithm has been widely used in many medical image segmentations. However, the conventionally standard FCM algorithm is sensitive to noise because of not taking into account the spatial information. To overcome this problem, a modified FCM algorithm for MRI brain image segmentation is presented in this paper. The proposed algorithm is formulated by modifying the objective function of the standard fuzzy c-means algorithm to enhance the noise immunity. The Experimental results on both synthetic and real image which degraded with noise indicate that the proposed algorithm is more accurate and robust to noise than the standard FCM algorithm.