A PSO based method for detection of brain tumors from MRI

Detection of brain tumors from MRI is a time consuming and error-prone task. This is due to the diversity in shape, size and appearance of the tumors. In this paper, we propose a clustering algorithm based on Particle Swarm Optimization (PSO). The algorithm finds the centroids of number of clusters, where each cluster groups together brain tumor patterns, obtained from MR Images. The results obtained for three performance measures are compared with those obtained from Support Vector Machine (SVM) and Ada Boost. The performance analysis shows that qualitative results obtained from the proposed model are comparable with those obtained by SVM. However, to obtain better results from the proposed algorithm we need to carefully select the different values of PSO control parameters.