MRI brain image segmentation for spotting tumors using improved mountain clustering approach

This paper presents improved mountain clustering technique based MRI (magnetic resonance imaging) brain image segmentation for spotting tumors. The proposed technique is compared with some existing techniques such as K-Means and FCM, clustering. The performance of all these clustering techniques is compared in terms of cluster entropy as a measure of information and also is visually compared for image segmentation of various brain tumor MRI images. The cluster entropy is heuristically determined, but is found to be effective in forming correct clusters as verified by visual assessment.