A novel approach for segmentation and classification of brain MR images using cluster deformable based fusion approach

Abstract

Segmentation of tumor form brain MR images is the most important and tedious task in the medical field. In this paper, A Cluster deformable based fusion approach which uses both deformable and K-Means clustering scheme for Segmentation is discussed. The features of tumor and non tumor cases are extracted with the use of the Power Local Binary Pattern (LBP) Operator after completion of the segmentation process. The extracted features are fed to Naive Bayes classifier to perform the process of classification. Here, the validation of the proposed system is done using standard validation methods such as accuracy, specificity, sensitivity and RoC metrics. The developed method is applied for MR images collected from standard SimBRATS database. Experimentation results shows that the proposed method performs better when compared to the traditional clustering and deformable methods and this scheme got accuracy of 84.8%.