NDLI: Determining the asymmetries of skin lesions with fuzzy borders

Content Provider	IEEE Xplore Digital Library
Author	Ng, V.T.Y. Lee, T. Fung, B.Y.M.
Copyright Year	2003
Description	Author affiliation: Dept. of Comput., Hong Kong Polytech. Univ., China (Ng, V.T.Y.)
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.
Sponsorship	IEEE Comput. Soc. Inf. Technol. Res. Inst. at Wright State Univ. IEEE Neural Networks Soc
Starting Page	223
Ending Page	230
File Size	207465
Page Count	8
File Format	PDF
ISBN	0769519075
DOI	10.1109/BIBE.2003.1188955
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-03-12
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Skin Lesions Cancer Malignant tumors Diseases Shape Image segmentation Artificial neural networks Fuzzy neural networks Electrostatic discharge
Content Type	Text
Resource Type	Article

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