Evidence map›Paper›PMID 33905073›Full record

ArticleForensic science, medicine, and pathology2021

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

Lars C Ebert, Dilan Seckiner, Till Sieberth, Michael J Thali, Sabine Franckenberg

Abstract read
In one paragraph

Article in Forensic science, medicine, and pathology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Lars C Ebert3D Center Zurich, Institute of Forensic Medicine Zurich, University of Zurich, Winterthurerstrasse 190/52 CH-8052, Zurich, Switzerland. lars.ebert@irm.uzh.ch.ORCID http://orcid.org/0000-0002-8215-7006
Dilan Seckiner3D Center Zurich, Institute of Forensic Medicine Zurich, University of Zurich, Winterthurerstrasse 190/52 CH-8052, Zurich, Switzerland.
Till Sieberth3D Center Zurich, Institute of Forensic Medicine Zurich, University of Zurich, Winterthurerstrasse 190/52 CH-8052, Zurich, Switzerland.
Michael J Thali3D Center Zurich, Institute of Forensic Medicine Zurich, University of Zurich, Winterthurerstrasse 190/52 CH-8052, Zurich, Switzerland.
Sabine Franckenberg3D Center Zurich, Institute of Forensic Medicine Zurich, University of Zurich, Winterthurerstrasse 190/52 CH-8052, Zurich, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

AlgorithmsBone and BonesForeign BodiesForensic PathologyFractures, BoneTomography, X-Ray ComputedAutopsyGasesHumansImage Processing, Computer-AssistedGasesMaximum intensity projectionMinimum intensity projectionPMCTVirtopsyVisualization

Identifiers

PMID33905073
PMCPMC8119247

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.