Paper Title
BRAIN TUMOR DETECTION USING CLASS BASED CLUSTERING (WCBC) ALGORITHM

Abstract
Abstract - Medical data mining is very important field as it has significant utility in healthcare domain in the real world. Brain tumor is a life threatening disease which produces problems like brain damage, loss of memory etc. Clustering and Classification are the popular data mining methods used to understand the different features of the brain data set. Clustering is used for segmentation of dataset. Using WCBC the image is segmented into important regions. Segmentation is fundamentally a pixel classification predicament where classification of the pixels into different classes is performed. The main idea of this is to analyze a brain tumor detector using K-Means and WCBC algorithm on basis of correlation, contrasts, homogeneity and accuracy parameters. Keywords - Brain Tumor, Image Segmentation, K-Means Clustering, WCBC Clustering, Performance Measures.