Institute of Arts, Science & Technology, Glyndwr University, Wrexham, UK.
Skin Res Technol. 2013 Feb;19(1):e305-11. doi: 10.1111/j.1600-0846.2012.00644.x. Epub 2012 Jun 4.
BACKGROUND/PURPOSE: Current non-invasive diagnostic procedures to detect skin cancer rely on two-dimensional (2D) views of the skin surface. For example, the most commonly-used ABCD features are extracted from the 2D images of skin lesion. However, because the skin surface is an object in three-dimensional (3D) space, valuable additional information can be obtained from a perspective of 3D skin objects. The aim of this work is to discover the new diagnostic features by considering 3D views of skin artefacts.
A surface tilt orientation parameter was proposed to quantify the skin and the lesion in 3D space. The skin pattern was first extracted from simply captured white light optical clinical (WLC) skin images by high-pass filtering. Then the directions of the projected skin lines were determined by skin pattern analysis. Next the surface tilt orientations of skin and lesion were estimated using the shape from texture technique. Finally the difference of tilt orientation in the lesion and normal skin areas, combined with the ABCD features, was used as a lesion classifier.
The proposed method was validated by processing a set of images of malignant melanoma and benign naevi. The scatter plot of classification using the feature of surface tilt orientation alone showed the potential of the new 3D feature, enclosing an area of 0.78 under the ROC curve. The scatter plot of classification, combining the new feature with the ABCD features by use of Principal Component Analysis (PCA), demonstrated an excellent separation of benign and malignant lesions. An ROC plot for this case enclosed an area of 0.85. Compared with the ABCD analysis where the area under the ROC curve was 0.65, it indicated that the surface tilt orientation (3D information) was able to enhance the classification results significantly.
The initial classification results show that the surface tilt orientation has a potential to increase lesion classifier accuracy. Combined with the ABCD features, it is very promising to distinguish malignant melanoma from benign lesions.
背景/目的：当前用于检测皮肤癌的非侵入性诊断程序依赖于皮肤表面的二维（2D）视图。例如，最常用的 ABCD 特征是从皮肤病变的 2D 图像中提取的。然而，由于皮肤表面是三维（3D）空间中的物体，因此可以从 3D 皮肤物体的角度获得有价值的附加信息。这项工作的目的是通过考虑皮肤伪影的 3D 视图来发现新的诊断特征。
提出了表面倾斜方向参数来量化 3D 空间中的皮肤和病变。首先通过高通滤波从简单捕获的白光光学临床（WLC）皮肤图像中提取皮肤图案。然后通过皮肤图案分析确定投影皮肤线的方向。接下来，使用纹理形状技术估计皮肤和病变的表面倾斜方向。最后，将病变和正常皮肤区域的倾斜方向差异与 ABCD 特征结合起来作为病变分类器。
该方法通过处理一组恶性黑素瘤和良性痣的图像进行了验证。仅使用表面倾斜方向特征的分类散点图显示了新 3D 特征的潜力，在 ROC 曲线下包含了 0.78 的面积。通过使用主成分分析（PCA）将新特征与 ABCD 特征相结合的分类散点图，展示了良性和恶性病变的极好分离。这种情况下的 ROC 图包含了 0.85 的面积。与 ABCD 分析中 ROC 曲线下的面积为 0.65 相比，这表明表面倾斜方向（3D 信息）能够显著提高分类结果的准确性。
初步分类结果表明，表面倾斜方向具有提高病变分类器准确性的潜力。与 ABCD 特征相结合，区分恶性黑素瘤和良性病变非常有前景。
