Improving Fuzzy C-Means for MRIs Segmentation

Abstract: In this paper, a new modified fuzzy c-means algorithm is presented that could improve the medical image segmentation. The proposed algorithm is realized by modifying the objective function of the conventional FCM algorithm with a flexible penalty. This penalty is based on a data shape and data size used for the generation of fuzzy terms. The complexity of the proposed algorithm is reduced using initial seed information into the objective function instead of whole data set. The performance of the proposed algorithm is tested on noisy real images. The results of the conducted experiments show that the efficiency of the proposed method in preserving the regions homogeneity and its robustness in segmenting noisy images is better than other FCM-based methods