White Patch Detection in Brain MRI Image Using Evolutionary Clustering Algorithm

Though image segmentation is a fundamental task in image analysis; it plays a vital role in the area of image processing. Its value increases in case of medical diagnostics through medical images like X-ray, PET, CT and MRI. In this chapter, an attempt is taken to analyze an MRI brain image. It has been segmented for a particular patch in the brain MRI image that may be one of the tumors in the brain. The purpose of segmentation is to partition an image into meaningful regions with respect to a particular application. Image segmentation is a method of separating the image from the background, read the contents and isolating it. In this chapter both the concept of clustering and thresholding technique have been used. The standard methods such as Sobel, Prewitt edge detectors is applied initially. Then the result is optimized using GA for efficient minimization of the objective function and for improved classification of clusters. Further the segmented result is passed through a Gaussian filter to obtain a smoothed image.