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Global versus Hybrid Thresholding for Border Detection in Dermoscopy Images

  • Rahil Garnavi
  • Mohammad Aldeen
  • Sue Finch
  • George Varigos
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6134)

Abstract

In this paper we demonstrate the superiority of the automated hybrid thresholding approach to border detection in dermoscopy images over the global thresholding method through a newly introduced evaluation metric: Performance Index. The approach incorporates optimal color channels into the hybrid thresholding method, which is a combination of global and adaptive local thresholding, to determine the closest border to that drawn by dermatologists. Statistical analysis and optimization procedure are used and shown to be convergent in determining the optimal parameters for the local thresholding procedure in order to obtain the most accurate borders. The effectiveness of the approach is tested on 55 high resolution dermoscopy images of patients, with manual borders drawn by three expert dermatologists, and the union is used as the ground truth. The results demonstrate the significant advantages of the automated hybrid approach over the global thresholding method.

Keywords

Border detection Histogram thresholding Dermoscopy Melanoma Computer-aided diagnosis 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Rahil Garnavi
    • 1
  • Mohammad Aldeen
    • 1
  • Sue Finch
    • 2
  • George Varigos
    • 3
  1. 1.NICTA Victoria Research Laboratory, Department of Electrical and Electronic EngineeringThe University of MelbourneMelbourneAustralia
  2. 2.Department of Mathematics and StatisticsThe University of MelbourneMelbourneAustralia
  3. 3.Department of DermatologyRoyal Melbourne HospitalMelbourneAustralia

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