Please use this identifier to cite or link to this item: https://idr.l1.nitk.ac.in/jspui/handle/123456789/7917
Title: Efficient fuzzy clustering based approach to brain tumor segmentation on MR images
Authors: Arakeri, M.P.
Ram Mohana Reddy, Guddeti
Issue Date: 2011
Citation: Communications in Computer and Information Science, 2011, Vol.250 CCIS, , pp.790-795
Abstract: Image segmentation is one of the most vital and significant step in medical applications. The conventional fuzzy c-means (FCM) clustering is the most widely used unsupervised clustering method for brain tumor segmentation on magnetic resonance (MR) images. However, the major limitation of the conventional FCM is its huge computational time and it is sensitive to initial cluster centers. In this paper, we present a novel efficient FCM algorithm to eliminate the drawback of conventional FCM. The proposed algorithm is formulated by incorporating distribution of the gray level information in the image and a new objective function which ensures better stability and compactness of clusters. Experiments are conducted on brain MR images to investigate the effectiveness of the proposed method in segmenting brain tumor. The conventional FCM and the proposed method are compared to explore the efficiency and accuracy of the proposed method. � 2011 Springer-Verlag.
URI: http://idr.nitk.ac.in/jspui/handle/123456789/7917
Appears in Collections:2. Conference Papers

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