Efficient Fuzzy Clustering Based Approach to Brain Tumor Segmentation on MR Images

  • Megha P. Arakeri
  • G. Ram Mohana Reddy
Part of the Communications in Computer and Information Science book series (CCIS, volume 250)


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.


Segmentation Magnetic resonance image Fuzzy c-means clustering Brain tumor Efficiency 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Megha P. Arakeri
    • 1
  • G. Ram Mohana Reddy
    • 1
  1. 1.National Institute of Technology KarnatakaSurathkalIndia

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