We have developed a multipoint laser Doppler velocimeter (MLDV) that can measure blood flow velocity non‐invasively. The device can acquire blood flow velocity in absolute value and image the blood flow distribution. Absolute values of blood flow velocity indicated a follow‐up on the affected area. Therefore, we have performed a follow‐up for melanoma and breast cancer. However, this device does not have the ability to determine whether a measurement site is cancerous or not. Thus, in this study, we built a deep learning system with blood flow distribution images as input and tested whether it can discriminate melanoma or not. The results showed that this technique was particularly effective in the early stages of the disease when no abnormalities were found on the skin surface. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

中文翻译：

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使用血流分布图像识别黑素瘤的深度学习方法

我们开发了一种多点激光多普勒测速仪（MLDV），可以无创地测量血流速度。该设备可以获取绝对值的血流速度并对血流分布进行成像。血流速度的绝对值表明对患处进行了随访。因此，我们对黑色素瘤和乳腺癌进行了随访。但是，该设备无法确定测量部位是否癌变。因此，在这项研究中，我们建立了以血流分布图像为输入的深度学习系统，并测试了该系统是否可以区分黑色素瘤。结果表明，当在皮肤表面未发现异常时，该技术在疾病的早期阶段特别有效。©2021日本电气工程师学会。