Robust Image Segmentation Using FCM Based on New Kernel-Induced Distance Measure With Membership Constraints

摘要

The accurate and effective algorithm for segmenting image is very useful in many fields,especially in medical image.In this paper,we present a novel algorithm for fuzzy segmentation of magnetic resonance (MR) images.The algorithm is realized by modifying the objective function in the conventional fuzzy C-means (FCM) algorithm using a kernel-induced distance metric and a membership constraints on the membership functions.With synthetic image and the clinical MR images,the experiments show that our proposed algorithm is effective.