Determining the asymmetry of skin lesion with fuzzy borders

Vincent To Yee Ng, Benny Y.M. Fung, Tim K. Lee

Research output: Journal article publicationJournal articleAcademic researchpeer-review

42 Citations (Scopus)

Abstract

It is highly desirable to identify malignant melanoma, a common cancer, at an early stage. One important clinical feature of this cancer is asymmetrical skin lesions. In this paper, we propose an adaptive fuzzy approach that uses symmetric distance (SD) to measure lesions with fuzzy borders. The use of a number of SD variations and the adoption of a backpropagation neural network enhances the discriminative power of the approach. Digitized images from the Lesion Clinic in Vancouver, Canada, demonstrate the accurate classification of asymmetric lesions at around 80%.
Original languageEnglish
Pages (from-to)103-120
Number of pages18
JournalComputers in Biology and Medicine
Volume35
Issue number2
DOIs
Publication statusPublished - 1 Feb 2005

Keywords

  • Asymmetry measurement
  • Medical imaging
  • Melanoma
  • Skin lesion

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics

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