4.7 Article

Fuzzy logic color detection: Blue areas in melanoma dermoscopy images

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

  1. National Institutes of Health (NIH) [SBIR R44 CA-101639-02A2]

向作者/读者索取更多资源

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.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据