Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/24502
Title: Determining the asymmetries of skin lesions with fuzzy borders
Authors: Ng, VTY 
Lee, T
Fung, BYM
Keywords: Backpropagation
Biomedical optical imaging
Cancer
Image segmentation
Measurement errors
Medical image processing
Neural nets
Skin
Symmetry
Issue Date: 2003
Publisher: IEEE
Source: Third IEEE Symposium on Bioinformatics and Bioengineering, 2003 : proceedings : 10-12 March 2003, p. 223-230 How to cite?
Abstract: 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 front the Lesion Clinic in Vancouver, Canada have shown the good discriminating power of the neural network model.
URI: http://hdl.handle.net/10397/24502
ISBN: 0-7695-1907-5
DOI: 10.1109/BIBE.2003.1188955
Appears in Collections:Conference Paper

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