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Separability Analysis of Color Classes on Dermoscopic Images

  • Cátia S. P. Silva
  • André R. S. Marcal
  • Marta A. Pereira
  • Teresa Mendonça
  • Jorge Rozeira
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7325)

Abstract

Dermoscopy is a non-invasive diagnostic technique for the in vivo observation of pigmented skin lesions used in dermatology. There is currently a great interest in the prospects of automatic image analysis methods for dermoscopy, both to provide quantitative information about a lesion, which can be of relevance for the clinician, and as a stand alone early warning tool. The standard approach in automatic dermoscopic image analysis has usually three stages: (i) segmentation, (ii) feature extraction and selection, (iii) lesion classification. This paper evaluates the potential of an alternative approach based on the Menzies method - presence of 1 or more of 6 color classes, indicating that the lesion should be considered a potential melanoma. This method does not require stages (i) and (ii) - lesion segmentation and feature extraction. The Jeffries-Matusita and Transformed Divergence metrics were used to evaluate the color class separability. The preliminary results presented in this paper suggest that a system based on the Menzies method could provide valuable information for automatic dermoscopic image analysis.

Keywords

Dermoscopy Menzies method separability analysis Jeffries-Matusita Tranformed Divergence 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Cátia S. P. Silva
    • 1
  • André R. S. Marcal
    • 2
  • Marta A. Pereira
    • 3
  • Teresa Mendonça
    • 2
  • Jorge Rozeira
    • 3
  1. 1.Faculdade de Engenharia, Dep. Engenharia Eletrotécnica e de ComputadoresUniv. PortoPortoPortugal
  2. 2.Faculdade de Ciências, Dep. MatemáticaUniv. PortoPortoPortugal
  3. 3.Servicco de DermatologiaHospital Pedro HispanoSenhora da HoraPortugal

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