A two-stage approach for discriminating melanocytic skin lesions using standard cameras

被引:36
作者
Cavalcanti, Pablo G. [1 ]
Scharcanski, Jacob [1 ]
Baranoski, Gladimir V. G. [2 ]
机构
[1] Univ Fed Rio Grande do Sul, Inst Informat, BR-91501970 Porto Alegre, RS, Brazil
[2] Univ Waterloo, Nat Phenomena Simulat Grp, Sch Comp Sci, Waterloo, ON N2L 3G1, Canada
关键词
Computer-aided diagnosis; Melanocytic skin lesion; Melanoma; Melanin; Classification; Standard cameras; MELANOMA DIAGNOSIS; DECISION-SUPPORT; BORDER DETECTION; ABCD RULE; DERMOSCOPY; SYSTEM; SEGMENTATION; DERMATOSCOPY; TELEDERMATOLOGY; IMAGES;
D O I
10.1016/j.eswa.2013.01.002
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we propose a novel approach to discriminate malignant melanomas and benign atypical nevi, since both types of melanocytic skin lesions have very similar characteristics. Recent studies involving the non-invasive diagnosis of melanoma indicate that the concentrations of the two main classes of melanin present in the human skin, eumelanin and pheomelanin, can potentially be used in the computation of relevant features to differentiate these lesions. So, we describe how these features can be estimated using only standard camera images. Moreover, we demonstrate that using these features in conjunction with features based on the well known ABCD rule, it is possible to achieve 100% of sensitivity and more than 99% accuracy in melanocytic skin lesion discrimination, which is a highly desirable characteristic in a prescreening system. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:4054 / 4064
页数:11
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