Paper Title
MR Image Segmentation Based on Fuzzy Markov Random Field

Imaging modality provides detailed information about anatomy. It is also helpful in diagnosing disease and helps in progressive treatment. We present suitable algorithms for thresholding, fuzzy k-means, fuzzy c-means and fuzzy Markov random field (MRF) that could improve results. Since the k-means and c-means aims to minimize the sum of squared distances from all the points to their cluster centre, it should results in compact clusters. For this purpose we use intra-cluster distance measure which calculates the median distance between a point and its clustered centre. The proposed algorithms are evaluated and compared with fuzzy k-means, c- means and MRF methods both qualitatively and quantitatively to improve their efficiency. From the proposed work, it is obvious that, these evaluations are not easy to specify in the absence of any prior knowledge about resulted clusters. Keywords— Segmentation, Thresholding, Fuzzy-k means,(FKM) Fuzzy-c means(FCM), Markov random field(MRF).