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Proceedings Paper

BCC skin cancer diagnosis based on texture analysis techniques
Author(s): Shao-Hui Chuang; Xiaoyan Sun; Wen-Yu Chang; Gwo-Shing Chen; Adam Huang; Jiang Li; Frederic D. McKenzie
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Paper Abstract

In this paper, we present a texture analysis based method for diagnosing the Basal Cell Carcinoma (BCC) skin cancer using optical images taken from the suspicious skin regions. We first extracted the Run Length Matrix and Haralick texture features from the images and used a feature selection algorithm to identify the most effective feature set for the diagnosis. We then utilized a Multi-Layer Perceptron (MLP) classifier to classify the images to BCC or normal cases. Experiments showed that detecting BCC cancer based on optical images is feasible. The best sensitivity and specificity we achieved on our data set were 94% and 95%, respectively.

Paper Details

Date Published: 9 March 2011
PDF: 6 pages
Proc. SPIE 7963, Medical Imaging 2011: Computer-Aided Diagnosis, 79633O (9 March 2011); doi: 10.1117/12.878124
Show Author Affiliations
Shao-Hui Chuang, Old Dominion Univ. (United States)
Xiaoyan Sun, Old Dominion Univ. (United States)
Wen-Yu Chang, Kaohsiung Medical Univ. (Taiwan)
Gwo-Shing Chen, Kaohsiung Medical Univ. (Taiwan)
Adam Huang, National Central Univ. (Taiwan)
Jiang Li, Old Dominion Univ. (United States)
Frederic D. McKenzie, Old Dominion Univ. (United States)


Published in SPIE Proceedings Vol. 7963:
Medical Imaging 2011: Computer-Aided Diagnosis
Ronald M. Summers; Bram van Ginneken, Editor(s)

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