Computer-aided classification of melanocytic lesions using dermoscopic images
Computer-aided classification of melanocytic lesions using dermoscopic images
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DOI：
10.1016/j.jaad.2015.07.028
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发表时间：
2015-11-01
影响因子：
13.8
通讯作者：
Satyanarayanan, Mahadev
中科院分区：
文献类型：
--
作者：
Ferris, Laura K.;Harkes, Jan A.;Satyanarayanan, Mahadev
背景资料：皮肤镜图像的皮肤病变的计算机辅助诊断有可能提高黑色素瘤早期detect.Objective：我们试图评估一种新的分类器的性能，该分类器使用皮肤镜图像的决策森林分类来生成病变严重程度评分。对173个已知组织学诊断的皮肤病变的皮肤镜图像计算严重程度评分（39例黑色素瘤，14例非黑色素瘤皮肤癌和120例良性病变）。阈值分数用于测量分类器灵敏度和特异性。读者的研究进行了比较的敏感性和特异性的分类器与30皮肤科clinics.Results：黑色素瘤的分类器的敏感性为97.4%，特异性为44.2%，在测试集的图像。在阅片者研究中，分类器对黑色素瘤的敏感性高于临床医生（P <0.001），特异性低于临床医生（P <0.001）。局限性：这是一项回顾性研究，主要使用皮肤科医生选择的现有图像进行活检。测试集的大小是small.Conclusions：我们的分类器可以帮助临床医生决定是否皮肤病变应该活检，可以很容易地被纳入一个便携式工具（不使用专有设备），可以帮助临床医生在非侵入性评估皮肤病变。
Background: Computer-assisted diagnosis of dermoscopic images of skin lesions has the potential to improve melanoma early detection.Objective: We sought to evaluate the performance of a novel classifier that uses decision forest classification of dermoscopic images to generate a lesion severity score.Methods: Severity scores were calculated for 173 dermoscopic images of skin lesions with known histologic diagnosis (39 melanomas, 14 nonmelanoma skin cancers, and 120 benign lesions). A threshold score was used to measure classifier sensitivity and specificity. A reader study was conducted to compare the sensitivity and specificity of the classifier with those of 30 dermatology clinicians.Results: The classifier sensitivity for melanoma was 97.4%; specificity was 44.2% in a test set of images. In the reader study, the classifier's sensitivity to melanoma was higher (P < .001) and specificity was lower (P < .001) than that of clinicians.Limitations: This is a retrospective study using existing images primarily chosen for biopsy by a dermatologist. The size of the test set is small.Conclusions: Our classifier may aid clinicians in deciding if a skin lesion should be biopsied and can easily be incorporated into a portable tool (that uses no proprietary equipment) that could aid clinicians in noninvasively evaluating cutaneous lesions.