The Transmitting and storing every moving object in position an object's trajectory; The qualitative comparison of Fuzzy and k-Means segmentation, with histogram guided initialization, on tumor edema complex MR images. . The Transmitting and storing every moving object in position an object's trajectory; The qualitative comparison of Fuzzy and k-Means segmentation, with histogram guided initialization, on tumor edema complex MR images. The conventional FCM algorithm and some existing variants are either sensitive to noise or prone to loss of details. In this thesis, presents a modified FCM algorithm that incorporates bilateral filtering for medical image segmentation. The experimental results and quantitative analyses suggest that, compared to the conventional FCM, the proposed method improves clustering performance with higher standard of noise-resistance and detail-preservation. Medical image pixels are highly correlated, i.e. the pixels in the immediate neighbors possess similar feature data. In other words, the probability that adjacent pixels belong to the same cluster is great. In this paper, we represented an image is corrupted by noise; the intensity value of some pixels may differ dramatically from that of their neighbors. Due to the fact that FCM algorithm does not take neighboring image pixels into account, neighboring pixels could be wrongly grouped into different clusters.