Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10351226 | Computerized Medical Imaging and Graphics | 2005 | 10 Pages |
Abstract
The sensitivity and specificity of melanoma diagnosis can be improved by adding the lesion depth and structure information obtained from the multi-spectral, trans-illumination images to the surface characteristic information obtained from the epi-illumination images. Wavelet transform based bi-modal channel energy features obtained from the images are used in the analysis. Methods using both crisp and fuzzy membership based partitioning of the feature space are evaluated. For this purpose, the ADWAT classification method that uses crisp partitioning is extended to handle multi-spectral image data. Also, multi-dimensional fuzzy membership functions with Gaussian and Bell profiles are proposed for classification. Results show that the fuzzy membership functions with Bell profile are more effective than the extended ADWAT method in discriminating melanoma from dysplastic nevus.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Sachin V. Patwardhan, Shuangshuang Dai, Atam P. Dhawan,