Detection Of Brain Tumor Using Kernel Induced Possiblistic C-Means Clustering

International Journal of Computer Organization Trends and Technology (IJCOT)          
© 2013 by IJCOT Journal
Volume-3 Issue-5                           
Year of Publication : 2013
Authors : D.Napoleon , M.Praneesh


D.Napoleon , M.Praneesh . "Detection Of Brain Tumor Using Kernel Induced Possiblistic C-Means Clustering " . International Journal of Computer organization Trends and Technology (IJCOT), V3(5):40-42 Sep - Oct 2013, ISSN 2249-2593, Published by Seventh Sense Research Group.

Abstract—Brain tumor is a major health problem throughout the world. Magnetic resonance imaging (MRI) scan can be used to produce image of any part of the body and it provides an efficient and fast way for diagnosis of the brain tumor. In the Proposed method an efficient detection of brain tumor region from cerebral image is done using Kernel Induced Possiblistic C-means clustering and histogram. The using Kernel Induced Possiblistic C-means clustering algorithm finds the centroids of the cluster groups together the Brain tumor patterns obtained from MRI images. Segmentation result shows the extract tumor region.The performance evaluation of the proposed system is evaluated and compared with existing approaches.


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Keywords—Tumor, KPCM Algorithm, Statistical Measures, histogram equalization.