Liver CT Image Segmentation with an Optimum Threshold Using Measure of Fuzziness

  • Abder-Rahman Ali
  • Micael Couceiro
  • Ahmed M. Anter
  • Aboul Ella Hassanien
  • Mohamed F. Tolba
  • Václav Snášel
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 303)

Abstract

This paper presents a Fuzzy C-Means based image segmentation approach with an optimum threshold using measure of fuzziness. The optimized version, herein denoted as FCM-t, benefits from an optimum threshold, calculated using measure of fuzziness. This allows the revealing of ambiguous pixels, which are eventually assigned to the appropriate clusters by calculating the rounded average cluster values in the ambiguous pixels neighbourhood. The proposed approach showed significantly better results compared to the traditional Fuzzy C-Means, at the cost of some processing power. By benefiting from the optimum threshold approach, one is able to increase the segmentation performance by approximately three times more than with the traditional FCM.

Keywords

Segmentation fuzzy C-means threshold clustering 
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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Abder-Rahman Ali
    • 1
  • Micael Couceiro
    • 2
    • 3
  • Ahmed M. Anter
    • 4
    • 1
  • Aboul Ella Hassanien
    • 1
    • 5
  • Mohamed F. Tolba
    • 6
  • Václav Snášel
    • 7
  1. 1.Scientific Research Group in Egypt (SRGE)CairoEgypt
  2. 2.Artificial Perception for Intelligent Systems and Robotics (AP4ISR), Institute of Systems and Robotics (ISR)University of CoimbraCoimbraPortugal
  3. 3.Ingeniarius, Lda.MealhadaPortugal
  4. 4.Faculty of Computers and InformationMansoura UniversityMansouraEgypt
  5. 5.Faculty of Computers and InformationCairo UniversityCairoEgypt
  6. 6.Faculty of Computers and InformationAin Shams UniversityCairoEgypt
  7. 7.Electrical Engineering & Computer ScienceVSB-TUOstravaCzech Republic

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