EFFICIENT IMAGE SEGMENTTION OF BRAIN TUMOR DETECTION USING FUZZY C-MEAN AND MEAN-SHIFT

Abstract

The brain tumor detection is a very important application of medical image processing, where clustering techniques are used to detect the brain tumor diagnosis with magnetic resonance imaging (MRI). In the MRI has been considered because it provides accurate visualization of anatomical structure of tissues. In this paper initially, noise is removed from the input image using a fuzzy filter. A mean shift based fuzzy c-means algorithm is then utilized to segment the tumor. Experimental results show that the proposed Segmentation method applying on brain tumor MRI images which demonstrates that the presented method detects the brain tumor accurately and efficiently.