Enhanced Fuzzy-Based Models for ROI Extraction in Medical Images

  • Yasser El-Sonbaty
  • Sherin M. Youssef
  • Karma M. Fathalla
Part of the Communications in Computer and Information Science book series (CCIS, volume 260)


Standard Fuzzy C-Means (FCM) clustering has been widely used as an effective method for image segmentation. However, FCM is sensitive to initialization and is easily trapped in local optima. In this paper, several enhanced models for FCM clustering were proposed, namely W_SS_FCM, LAWS_SS_FCM and H_FCM, to promote the performance of standard FCM. The proposed algorithms merge partial supervision with spatial locality to increase conventional FCM’s robustness. A comparison study was conducted to validate the proposed methods’ performance applying well established measures on three datasets. Experimental results show considerable improvement over standard FCM and other variants of the algorithm. It also manifests high robustness against noise attacks.


FCM clustering segmentation spatial locality partial supervision 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Yasser El-Sonbaty
    • 1
  • Sherin M. Youssef
    • 2
  • Karma M. Fathalla
    • 2
  1. 1.College of Computing and ITArab Academy for Science and TechnologyEgypt
  2. 2.College of EngineeringArab Academy for Science and TechnologyEgypt

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