A fuzzy-based histogram analysis technique for skin lesion discrimination in dermatology clinical images
A fuzzy-based histogram analysis technique for skin lesion discrimination in dermatology clinical images
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DOI：
10.1016/s0895-6111(03)00030-2
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发表时间：
2003-09-01
影响因子：
5.7
通讯作者：
Aggarwal, C
中科院分区：
文献类型：
--
作者：
Stanley, RJ;Moss, RH;Aggarwal, C
提出了一种基于模糊逻辑的颜色直方图分析技术，用于区分皮肤科临床图像中的良性皮肤病变和恶性黑色素瘤。该方法利用一个模糊集的良性皮肤病变的颜色，α-切割和支持集基数量化的模糊比率皮肤病变的颜色特征。皮肤病变的歧视结果报告的模糊比和融合与先前确定的百分比黑色素瘤颜色特征超过258个临床图像的数据集。对于融合技术，可以选择模糊比率的α切割来识别超过93.30%的黑色素瘤，具有大约15.67%的假阳性病变。(C)2003爱思唯尔科技有限公司。保留所有权利。
A fuzzy logic-based color histogram analysis technique is presented for discriminating benign skin lesions from malignant melanomas in dermatology clinical images. The approach utilizes a fuzzy set for benign skin lesion color, and alpha-cut and support set cardinality for quantifying a fuzzy ratio skin lesion color feature. Skin lesion discrimination results are reported for the fuzzy ratio and fusion with a previously determined percent melanoma color feature over a data set of 258 clinical images. For the fusion technique, alpha-cuts for the fuzzy ratio can be chosen to recognize over 93.30% of melanomas with approximately 15.67% false positive lesions. (C) 2003 Elsevier Science Ltd. All rights reserved.