Comparative Analysis of Brain Tumor Detection using Different Segmentation Techniques

Abstract

In this study, we would like to present brain tumor detection methods, based on the conventional K-means technique, Expectation Maximization (EM) algorithm and a new Spatial Fuzzy-technique analysis of brain MR images. Though, the Kmeans and EM algorithm were already used in Brain MR image segmentation, as well as image segmentation in general, it fails to utilize the strong spatial correlation between neighboring pixels. A spatial Fuzzy C-means (SFCM’s) technique, which is utilize the spatial information properly and produce high quality segmentation of brain tumor images. Five ground truth images are taken to test the segmentation performance of K-means, EM algorithms and Spatial Fuzzy C-means technique. The segmentation results, which are proved more accurate segmentation by the SFCM’s compared to that of K-means and EM algorithm, are presented statistically and graphically.