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Clinical Skin Lesion Diagnosis Using Representations Inspired by Dermatologist Criteria

机译:使用皮肤科医生标准启发的表征进行临床皮肤病变诊断

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The skin is the largest organ in human body. Around 30%-70% of individuals worldwide have skin related health problems, for whom effective and efficient diagnosis is necessary. Recently, computer aided diagnosis (CAD) systems have been successfully applied to the recognition of skin cancers in dermatoscopic images. However, little work has concentrated on the commonly encountered skin diseases in clinical images captured by easily-accessed cameras or mobile phones. Meanwhile, for a CAD system, the representations of skin lesions are required to be understandable for dermatologists so that the predictions are convincing. To address this problem, we present effective representations inspired by the accepted dermatological criteria for diagnosing clinical skin lesions. We demonstrate that the dermatological criteria are highly correlated with measurable visual components. Accordingly, we design six medical representations considering different criteria for the recognition of skin lesions, and construct a diagnosis system for clinical skin disease images. Experimental results show that the proposed medical representations can not only capture the manifestations of skin lesions effectively, and consistently with the dermatological criteria, but also improve the prediction performance with respect to the state-of-the-art methods based on uninterpretable features.
机译:皮肤是人体最大的器官。全球约有30%-70%的人患有与皮肤有关的健康问题,因此有必要对其进行有效的诊断。近来,计算机辅助诊断(CAD)系统已成功应用于识别皮肤镜图像中的皮肤癌。但是,很少有工作集中在易于访问的相机或手机捕获的临床图像中的常见皮肤疾病上。同时,对于CAD系统,皮肤病灶的表示要求对于皮肤科医生来说是可以理解的,因此预测是令人信服的。为了解决这个问题,我们提出了受公认的皮肤病学标准诊断临床皮肤病变的有效方法。我们证明皮肤病学标准与可测量的视觉成分高度相关。因此,我们设计了六个医学代表,考虑了不同的皮肤病变识别标准,并构建了临床皮肤疾病图像诊断系统。实验结果表明,提出的医学表征不仅可以有效地捕获皮肤病变的表现,并且符合皮肤病学标准,而且相对于基于不可解释特征的最新方法,还可以提高预测性能。

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