A border irregularity measure using a modified conditional entropy method as a malignant melanoma predictor

  • Authors:

  • Benjamin S. Aribisala;Ela Claridge

  • Affiliations:

  • School of Computer Sciences, The University or Birmingham, Birmingham, U.K.;School of Computer Sciences, The University or Birmingham, Birmingham, U.K.

  • Venue:
  • ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
  • Year:
  • 2005

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Abstract

In the diagnosis of malignant melanoma, a skin cancer, the degree of irregularity along the skin lesion border is an important diagnostic factor. This paper presents a new measure of border irregularity based on conditional entropy. The measure was tested on 98 skin lesions of which 16 were malignant melanoma. The ROC analysis showed that the measure is 70% sensitive and 84% specific in discriminating the malignant and benign lesions. These results compare favourably with other measures and indicate that conditional entropy captures some distinguishing features in the boundary of malignant lesions.