Zurich Institute of Forensic Medicine, University of Zurich, Winterthurerstrasse 190/52, CH-8057, Zurich, Switzerland.
Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, CH-8057, Zurich, Switzerland.
Forensic Sci Med Pathol. 2020 Dec;16(4):671-679. doi: 10.1007/s12024-020-00307-3. Epub 2020 Sep 29.
The use of postmortem computed tomography in forensic medicine, in addition to conventional autopsy, is now a standard procedure in several countries. However, the large number of cases, the large amount of data, and the lack of postmortem radiology experts have pushed researchers to develop solutions that are able to automate diagnosis by applying deep learning techniques to postmortem computed tomography images. While deep learning techniques require a good understanding of image analysis and mathematical optimization, the goal of this review was to provide to the community of postmortem radiology experts the key concepts needed to assess the potential of such techniques and how they could impact their work.
在法医领域，除了传统的尸检外，现在在一些国家使用死后 CT 检查已经成为标准程序。然而，由于案例数量众多、数据量大以及缺乏死后放射学专家，研究人员不得不开发解决方案，通过将深度学习技术应用于死后 CT 图像来实现诊断自动化。虽然深度学习技术需要对图像分析和数学优化有很好的理解，但本篇综述的目的是向死后放射学专家社区提供评估这些技术潜力所需的关键概念，以及这些技术可能对他们的工作产生怎样的影响。
