Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10351897 | Computers in Biology and Medicine | 2005 | 18 Pages |
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%.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Vincent T.Y. Ng, Benny Y.M. Fung, Tim K. Lee,