Journals Proceedings

Abstract

Over the past few decades we have seen tremendous growth in the field of Magnetic Resonance Imaging (MRI) Brain image processing. It requires various steps to ensure that the desired result is obtained. One of the constituent processes for the basic study of the brain parts is the edge detection, which is the initial module for all other post processing procedures. These edges characterize the abnormalities existing in the human brain. Hence it should be done with utmost care for obtaining worthy result. In this paper, a new approach to MRI brain edge detection problem is presented. It consists of two stages. First the original MRI image is passed through image segmentation block and in the second stage edge detection algorithm is applied to the segmented image. Image segmentation is done using Genetic algorithm incorporating Fuzzy C means clustering (GAFCM) and Canny edge detection Algorithm is used for edge detection. Although this approach has high computational complexity it greatly improves the accuracy of the segmentation on medical image that produces precise edge detected image of the Human Brain.