黑色素和血红蛋白在皮肤病分析中的鉴定

Zhao Liu, J. Zerubia
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引用次数: 12

摘要

本文提出了一种基于多层皮肤模型和主要发色团吸光度特征的双侧分解提取人体皮肤中黑色素和血红蛋白浓度的新方法。与目前的方法不同,该方法能够解决在非受控环境下拍摄的肤色图像中通常存在的高光和强阴影问题。衍生的黑色素和血红蛋白指标与病理组织状况直接相关,受外界影像学因素影响较小,可有效描述色素分布。实验验证了该方法对不同皮肤疾病的计算机辅助诊断的价值。与使用其他颜色描述符的技术相比,传统RGB病变图像对黑色素瘤的诊断准确率提高了9-15%。炎症性痤疮和色素沉着的区分可以反映痤疮的分期,有助于痤疮严重程度的评价。预计这种新方法将对其他皮肤病的分析有用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Melanin and Hemoglobin Identification for Skin Disease Analysis
This paper proposes a novel method to extract melanin and hemoglobin concentrations of human skin, using bilateral decomposition with the knowledge of a multiple layered skin model and absorbance characteristics of major chromophores. Different from state-of-art approaches, the proposed method enables to address highlight and strong shading usually existing in skin color images captured under uncontrolled environment. The derived melanin and hemoglobin indices, directly related to the pathological tissue conditions, tend to be less influenced by external imaging factors and are effective for describing pigmentation distributions. Experiments demonstrate the value of the proposed method for computer-aided diagnosis of different skin diseases. The diagnostic accuracy of melanoma increases by 9-15% for conventional RGB lesion images, compared to techniques using other color descriptors. The discrimination of inflammatory acne and hyper pigmentation reveals acne stage, which would be useful for acne severity evaluation. It is expected that this new method will prove useful for other skin disease analysis.
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