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Updated: Dec 7, 2025

Image Rendering Techniques in Postmortem Computed Tomography: Evaluation of Biological Health and Profile in Stranded Cetaceans
Published on: September 27, 2020
Potential use of deep learning techniques for postmortem imaging
Akos Dobay1,2, Jonathan Ford3, Summer Decker3
1Zurich Institute of Forensic Medicine, University of Zurich, Winterthurerstrasse 190/52, CH-8057, Zurich, Switzerland. akos.dobay@uzh.ch.
Abstract:
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.
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