Determining the asymmetries of skin lesions with fuzzy borders

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

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

2 Citations (Scopus)


Malignant melanoma is a popular cancer among youth; it is desirable to have a fast and convenience way to determine this disease in its early stage. One of the clinical features in diagnosis is related to the shape of lesions. In previous studies, circularity is commonly used as the asymmetric measurement of skin lesions. However, this measurement depends very much on the accuracy of the segmentation result. In this paper, we present an artificial neural network model to improve the measurements of the asymmetries of lesions that may have fuzzy borders. The main idea is enhancing the symmetric distant (eSD) with a number of variations. Results from experiments, which use the digitized images from the Lesion Clinic in Vancouver, Canada have shown the good discriminating power of the neural network model.
Original languageEnglish
Title of host publicationProceedings - 3rd IEEE Symposium on BioInformatics and BioEngineering, BIBE 2003
Number of pages8
ISBN (Electronic)0769519075, 9780769519074
Publication statusPublished - 1 Jan 2003
Event3rd IEEE Symposium on BioInformatics and BioEngineering, BIBE 2003 - Bethesda, United States
Duration: 10 Mar 200312 Mar 2003


Conference3rd IEEE Symposium on BioInformatics and BioEngineering, BIBE 2003
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing
  • Electrical and Electronic Engineering

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