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An algorithm for automatically generating gas, bone and foreign body visualizations from postmortem computed tomography data

Ebert, Lars C; Seckiner, Dilan; Sieberth, Till; Thali, Michael J; Franckenberg, Sabine (2021). An algorithm for automatically generating gas, bone and foreign body visualizations from postmortem computed tomography data. Forensic Science, Medicine, and Pathology, 17(2):254-261.

Abstract

Post mortem computed tomography (PMCT) can aid in localizing foreign bodies, bone fractures, and gas accumulations. The visualization of these findings play an important role in the communication of radiological findings. In this article, we present an algorithm for automated visualization of gas distributions on PMCT image data of the thorax and abdomen. The algorithm uses a combination of region growing segmentation and layering of different visualization methods to automatically generate overview images that depict radiopaque foreign bodies, bones and gas distributions in one image. The presented method was tested on 955 PMCT scans of the thorax and abdomen. The algorithm managed to generate useful images for all cases, visualizing foreign bodies as well as gas distribution. The most interesting cases are presented in this article. While this type of visualization cannot replace a real radiological analysis of the image data, it can provide a quick overview for briefings and image reports.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Institute of Legal Medicine
Dewey Decimal Classification:340 Law
610 Medicine & health
510 Mathematics
Scopus Subject Areas:Health Sciences > Pathology and Forensic Medicine
Uncontrolled Keywords:Pathology and Forensic Medicine, General Medicine
Language:English
Date:1 June 2021
Deposited On:19 Jul 2021 11:38
Last Modified:25 Jan 2025 02:39
Publisher:Springer
ISSN:1547-769X
OA Status:Hybrid
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1007/s12024-021-00363-3
PubMed ID:33905073
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  • Content: Published Version
  • Language: English
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)

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