Automatic scoring of erythema and scaling severity in psoriasis diagnosis

  • Authors:

  • Juan Lu;Ed Kazmiercazk;Jonathan H. Manton;Rodney Sinclair

  • Affiliations:

  • Department of Computing and Information Systems, University of Melbourne, Australia;Department of Computing and Information Systems, University of Melbourne, Australia;Department of Electrical and Electronic Engineering, University of Melbourne, Australia;Department of Medicine(Dermatology), University of Melbourne, Australia, St. Vincent's Hospital Melbourne, Australia

  • Venue:
  • AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
  • Year:
  • 2012

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Abstract

Psoriasis is a common skin disease with no known cure. It is both subjective and time consuming to evaluate the severity of psoriasis lesions using manual methods. More objective automated methods are in great demand in both psoriasis research and in clinical practice. This paper presents an algorithm for scoring the severity of psoriasis lesions from 2D digital skin images. The algorithm uses the redness of the inflamed skin, or erythema, and the relative area and roughness of the flaky scaled skin, or scaling, in lesions to score lesion severity. The algorithm is validated by comparing the severity scores given by the algorithm against those given by dermatologists and against other automated severity scoring techniques.