Medical Imaging 2011: Computer-Aided Diagnosis
796330 (6 pp.)
Medical Imaging 2011: Computer-Aided Diagnosis, February 15-17, 2011, Lake Buena Vista, Florida
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.
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Original Publication Citation
Chuang, S. H., Sun, X., Chang, W. Y., Chen, G. S., Huang, A., Li, J., & McKenzie, F. D. (2011). BCC skin cancer diagnosis based on texture analysis techniques. In R.M. Summers & B.V. Ginneken (Eds.), Medical Imaging 2011: Computer-Aided Diagnosis, Proceedings of SPIE Vol. 7963 (796330). SPIE of Bellingham, WA. https://doi.org/10.1117/12.878124
Chuang, Shao-Hui; Sun, Xiaoyan; Chang, Wen-Yu; Chen, Gwo-Shing; Huang, Adam; Li, Jiang; and McKenzie, Frederic D., "BCC Skin Cancer Diagnosis Based on Texture Analysis Techniques" (2011). Electrical & Computer Engineering Faculty Publications. 376.