Improved implementation of brain MR image segmentation using Meta heuristic algorithms

Brain Image Segmentation is a complex and challenging part in the Medical Image Processing. This paper describes two new approaches for brain tumor detection using Meta heuristic algorithms. MRI scan has become a particularly useful medical diagnostic tool for cases involving brain tissue. The aim of this research is to develop an effective algorithm for the segmentation of brain MRI images. This paper is divided in to three phases, namely preprocessing, enhancement, segmentation. In first phase, film artifacts and unwanted portions of MRI Brain image are removed. Secondly, the noise and high frequency components are removed using weighted median filter (WM). Final one is segmentation phase. It has two different approaches like block based (non algorithmic) and ACO algorithm segmentation. Finally the performance of the above two approaches are evaluated.