IEEE J Biomed Health Inform. 2019 Mar;23(2):586-598. doi: 10.1109/JBHI.2018.2855409. Epub 2018 Jul 12.
Total body photography is used for early detection of malignant melanoma, primarily as a means of temporal skin surface monitoring. In a prior work, we presented a scanner with a set of algorithms to map and detect changes in pigmented skin lesions, thus demonstrating that it is possible to fully automate the process of total body image acquisition and processing. The key procedure in these algorithms is skin lesion matching that determines whether two images depict the same real lesion. In this paper, we aim to improve it with respect to false positive and negative outcomes. To this end, we developed two novel methods: one based on successive rigid transformations of three-dimensional point clouds and one based on nonrigid coordinate plane deformations in regions of interest around the lesions. In both approaches, we applied a robust outlier rejection procedure based on progressive graph matching. Using the images obtained from the scanner, we created a ground truth dataset tailored to diversify false positive match scenarios. The algorithms were evaluated according to their precision and recall values, and the results demonstrated the superiority of the second approach in all the tests. In the complete interpositional matching experiment, it reached a precision and recall as high as 99.92% and 81.65%, respectively, showing a significant improvement over our original method.
全身摄影用于早期检测恶性黑色素瘤，主要作为一种监测皮肤表面随时间变化的手段。在之前的工作中，我们提出了一种带有一组算法的扫描仪，可以对色素性皮肤病变进行映射和检测，从而证明了完全自动化全身图像采集和处理过程是可行的。这些算法中的关键步骤是皮肤病变匹配，它决定了两幅图像是否描绘了相同的真实病变。在本文中，我们旨在针对假阳性和假阴性结果来改进它。为此，我们开发了两种新方法：一种基于三维点云的连续刚性变换，另一种基于病变周围感兴趣区域的非刚性坐标平面变形。在这两种方法中，我们应用了基于渐进图匹配的稳健异常值拒绝过程。使用从扫描仪获得的图像，我们创建了一个专门用于多样化假阳性匹配场景的真实数据集。根据精度和召回率对算法进行了评估，结果表明第二种方法在所有测试中都具有优越性。在完全插入式匹配实验中，它达到了高达 99.92%的精度和 81.65%的召回率，与我们的原始方法相比有了显著的提高。
