ANALYSIS AND SURVEY ON MEDICAL IMAGE SEGMENTATION USING DIFFERENT CLUSTERING ALGORITHMS

Abstract

Breaking down the medical image in image preparing is the most significant research territory. Catching the image are dissected to recognize distinctive medical imaging issues is the normal factor in this field. Powerful organ segmentation is an essential for computer-aided diagnosis (CAD), quantitative imaging examination, pathology detection and careful help. A portion of the organs in the human body have high anatomical changeability, so segmentation of such organs is exceptionally intricate. Medical images have had an incredible effect on medication, diagnosis, and treatment. The most significant piece of image handling is image segmentation. Many image segmentation techniques for medical image investigation have been exhibited in this paper. In this paper examined to different clustering strategy calculations specifically, K-Nearest Neighbor, K-Means and Fuzzy C-Mean. The Fuzzy C-Mean calculation is a superior execution of different calculations.