A Level Set Based Efficient Brain Tumor Classification Using self Organizing Map

Abstract

This method can segment a tumor provided that the anticipated parameters are set appropriately. This method does not require any initialization while the others require an initialization inside the tumor. The visualization and quantitative evaluations of the segmentation results demonstrate the effectiveness of this approach. We are using level-set algorithm along with centroid optimized self-organization map along with thresholding and morphology for proper classification of medical data. Firstly, the work will carry over to calculate the area of the tumor of single slice of MRI data set and then it is extended to calculate the area of the tumor from multiple image MRI data set.
Keywords: Level set method; self organization map; segmentation; brain tumor.