期刊
COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
卷 38, 期 5, 页码 403-410出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compmedimag.2014.03.007
关键词
Fuzzy logic; Dermoscopy; Blue area; Image analysis; Melanoma; Dysplastic nevi
资金
- National Institutes of Health (NIH) [SBIR R44 CA-101639-02A2]
Fuzzy logic image analysis techniques were used to analyze three shades of blue (lavender blue, light blue, and dark blue) in dermoscopic images for melanoma detection. A logistic regression model provided up to 82.7% accuracy for melanoma discrimination for 866 images. With a support vector machines (SVM) classifier, lower accuracy was obtained for individual shades (79.9-80.1%) compared with up to 81.4% accuracy with multiple shades. All fuzzy blue logic alpha cuts scored higher than the crisp case. Fuzzy logic techniques applied to multiple shades of blue can assist in melanoma detection. These vector-based fuzzy logic techniques can be extended to other image analysis problems involving multiple colors or color shades. (C) 2014 Elsevier Ltd. All rights reserved.
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