Ding Yi, Smith Lyndon, Smith Melvyn, Sun Jiuai, Warr Robert
Machine Vision Laboratory, DuPont Building, University of the West of England, Bristol Frenchay Campus, Bristol BS16 1QY, UK.
Skin Res Technol. 2009 Aug;15(3):262-70. doi: 10.1111/j.1600-0846.2009.00352.x.
BACKGROUND/PURPOSE: It has been observed that disruptions in skin patterns are larger for malignant melanoma (MM) than benign lesions. In order to extend the classification results achieved for 2D skin patterns, this work intends to investigate the feasibility of lesion classification using 3D skin surface texture, in the form of surface normals acquired from a previously built six-light photometric stereo device.
The proposed approach seeks to separate MM from benign lesions through analysis of the degree of surface disruptions in the tilt and slant direction of surface normals, so called skin tilt pattern and skin slant pattern. A 2D Gaussian function is used to simulate a normal region of skin for comparison with a lesion's observed tilt and slant patterns. The differences associated with the two patterns are estimated as the disruptions in the tilt and slant pattern respectively for lesion classification.
Preliminary studies on 11 MMs and 28 benign lesions have given Receiver operating characteristic areas of 0.73 and 0.85 for tilt and slant pattern, respectively, which are better than 0.65 previously obtained for the skin line direction using the same samples.
This paper has demonstrated an important application of 3D skin texture for computer-assisted diagnosis of MM in vivo. By taking advantage of the extra dimensional information, preliminary studies suggest that some improvements over the existing 2D skin line pattern approach for the differentiation between MM and benign lesions.
背景/目的：据观察，恶性黑色素瘤（MM）的皮肤模式破坏比良性病变更大。为了扩展二维皮肤模式的分类结果，本研究旨在探讨使用三维皮肤表面纹理进行病变分类的可行性，这种纹理以从先前构建的六光源光度立体装置获取的表面法线形式呈现。
所提出的方法旨在通过分析表面法线在倾斜和倾斜方向上的表面破坏程度（即所谓的皮肤倾斜模式和皮肤倾斜模式），将MM与良性病变区分开来。使用二维高斯函数模拟正常皮肤区域，以便与病变观察到的倾斜和倾斜模式进行比较。与这两种模式相关的差异分别作为病变分类的倾斜和倾斜模式破坏程度进行估计。
对11例MM和28例良性病变的初步研究表明，倾斜模式和倾斜模式的受试者操作特征面积分别为0.73和0.85，优于之前使用相同样本在皮肤线方向上获得的0.65。
本文展示了三维皮肤纹理在体内MM计算机辅助诊断中的重要应用。通过利用额外的维度信息，初步研究表明，与现有的二维皮肤线模式方法相比，在区分MM和良性病变方面有一些改进。
