Detection of asymmetric blotches (asymmetric structureless areas) in dermoscopy images of malignant melanoma using relative color
Detection of asymmetric blotches (asymmetric structureless areas) in dermoscopy images of malignant melanoma using relative color
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DOI：
10.1111/j.1600-0846.2005.00117.x
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发表时间：
2005-08-01
影响因子：
2.2
通讯作者：
Shrestha, B
中科院分区：
文献类型：
--
作者：
Stoecker, WV;Gupta, K;Shrestha, B
背景资料：皮肤镜检查，也称为皮肤镜检查或表皮发光显微镜检查（ELM），是一种非侵入性的体内技术，其允许通过肉眼检查无法辨别的色素性黑色素细胞肿瘤的特征的可视化。皮肤镜图像中黑色素瘤检测的一个显著特征是非对称斑点（非对称无结构区域）.方法：采用相对和绝对颜色，在红、绿色颜色平面上使用阈值自动检测斑点。计算了几个斑点指数，包括最大斑点质心与病变质心之间的缩放距离、总斑点面积与病变面积之比、最大斑点面积与病变面积之比、斑点总数、最大斑点大小和最大斑点不规则性。检查了绝对和相对色斑特征对黑色素瘤的有效性。使用留一法神经网络方法对包含165个黑素瘤（151个侵袭性黑素瘤和14个原位黑素瘤）和347个良性病变（124个无发育不良的痣细胞痣和223个发育不良痣）的皮肤镜检查图像集进行良性病变辨别。显示了受试者工作特征曲线结果，突出了黑色素瘤检测的灵敏度和特异性。结论：神经网络和统计分析表明，斑点检测方法是更有效地使用相对颜色比使用绝对颜色。相对色斑点检测法的诊断准确率约为77%。
Background: Dermoscopy, also known as dermatoscopy or epiluminescence microscopy (ELM), is a non-invasive, in vivo technique, which permits visualization of features of pigmented melanocytic neoplasms that are not discernable by examination with the naked eye. One prominent feature useful for melanoma detection in dermoscopy images is the asymmetric blotch (asymmetric structureless area).Method: Using both relative and absolute colors, blotches are detected in this research automatically by using thresholds in the red and green color planes. Several blotch indices are computed, including the scaled distance between the largest blotch centroid and the lesion centroid, ratio of total blotch areas to lesion area, ratio of largest blotch area to lesion area, total number of blotches, size of largest blotch, and irregularity of largest blotch.Results: The effectiveness of the absolute and relative color blotch features was examined for melanoma/benign lesion discrimination over a dermoscopy image set containing 165 melanomas (151 invasive melanomas and 14 melanomas in situ) and 347 benign lesions (124 nevocellular nevi without dysplasia and 223 dysplastic nevi) using a leave-one-out neural network approach. Receiver operating characteristic curve results are shown, highlighting the sensitivity and specificity of melanoma detection. Statistical analysis of the blotch features are also presented.Conclusion: Neural network and statistical analysis showed that the blotch detection method was somewhat more effective using relative color than using absolute color. The relative-color blotch detection method gave a diagnostic accuracy of about 77%.