IEEE J Biomed Health Inform. 2018 Sep;22(5):1497-1511. doi: 10.1109/JBHI.2017.2754861. Epub 2017 Oct 5.
Automatic medical diagnosis is an emerging center of interest in computer vision as it provides unobtrusive objective information on a patient's condition. The face, as a mirror of health status, can reveal symptomatic indications of specific diseases. Thus, the detection of facial abnormalities or atypical features is at upmost importance when it comes to medical diagnostics. This survey aims to give an overview of the recent developments in medical diagnostics from facial images based on computer vision methods. Various approaches have been considered to assess facial symptoms and to eventually provide further help to the practitioners. However, the developed tools are still seldom used in clinical practice, since their reliability is still a concern due to the lack of clinical validation of the methodologies and their inadequate applicability. Nonetheless, efforts are being made to provide robust solutions suitable for healthcare environments, by dealing with practical issues such as real-time assessment or patients positioning. This survey provides an updated collection of the most relevant and innovative solutions in facial images analysis. The findings show that with the help of computer vision methods, over 30 medical conditions can be preliminarily diagnosed from the automatic detection of some of their symptoms. Furthermore, future perspectives, such as the need for interdisciplinary collaboration and collecting publicly available databases, are highlighted.
自动医学诊断是计算机视觉领域一个新兴的研究热点，因为它可以为患者的病情提供非侵入性的客观信息。面部作为健康状况的一面镜子，可以揭示特定疾病的症状迹象。因此，在医学诊断中，对面部异常或非典型特征的检测至关重要。本调查旨在概述基于计算机视觉方法从面部图像进行医学诊断的最新进展。已经考虑了各种方法来评估面部症状，并最终为从业者提供进一步的帮助。然而，由于缺乏对方法的临床验证以及其适用性不足，开发的工具在临床实践中仍然很少使用。尽管如此，人们仍在努力提供适合医疗保健环境的稳健解决方案，通过解决实时评估或患者定位等实际问题。本调查提供了一个最新的、最相关和最具创新性的面部图像分析解决方案集合。研究结果表明，借助计算机视觉方法，可以通过自动检测某些症状，初步诊断出 30 多种疾病。此外，还强调了未来的发展方向，如需要跨学科合作和收集公开可用的数据库。
