Document Type

Conference Paper

Publication Date




Publication Title

Medical Imaging 2011: Computer-Aided Diagnosis




796330 (6 pp.)

Conference Name

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.


© 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this publication for a fee or for commercial purposes, and modification of the contents of the publication are prohibited.

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.


0000-0003-0091-6986 (Li)