Evidence map›Paper›PMID 40940538›Full record

ArticleInternational journal of computer assisted radiology and surgery2026

A mobile robotic approach to autonomous surface scanning in legal medicine.

Sarah Grube, Sarah Latus, Martin Fischer, Vidas Raudonis, Axel Heinemann, Benjamin Ondruschka, Alexander Schlaefer

Abstract read
In one paragraph

Article in International journal of computer assisted radiology and surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Sarah GrubeInstitute of Medical Technology and Intelligent Systems, Hamburg University of Technology, Hamburg, Germany. sarah.grube@tuhh.de.ORCID http://orcid.org/0000-0003-3125-8605
Sarah LatusInstitute of Medical Technology and Intelligent Systems, Hamburg University of Technology, Hamburg, Germany.
Martin FischerInstitute of Medical Technology and Intelligent Systems, Hamburg University of Technology, Hamburg, Germany.
Vidas RaudonisFaculty of Electricity and Electronics, Kaunas University of Technology, Kaunas, Lithuania.
Axel HeinemannInstitute of Legal Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Benjamin OndruschkaInstitute of Legal Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Alexander SchlaeferInstitute of Medical Technology and Intelligent Systems, Hamburg University of Technology, Hamburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeComprehensive legal medicine documentation includes internal and external examination of the corpse. Typically, this documentation is conducted manually during conventional autopsy. Systematic digital documentation would be desirable, especially for external wound examination, which is becoming more relevant for legal medicine analysis. For this purpose, RGB surface scanning has been introduced. While manual full-surface scanning using a handheld camera is time-consuming and operator-dependent, floor or ceiling-mounted robotic systems require specialized rooms. Hence, we consider whether a mobile robotic system can be used for external documentation.

methodsWe develop a mobile robotic system that enables full-body RGB-D surface scanning. Our work includes a detailed configuration space analysis to identify the environmental parameters that must be considered for a successful surface scan. We validate our findings through an experimental study in the lab and demonstrate the systems application in legal medicine.

resultsOur configuration space analysis shows that a good trade-off between coverage and time is reached with three robot base positions, leading to a coverage of 94.96 %. Experiments validate the effectiveness of the system in accurately capturing body surface geometry with an average surface coverage of

conclusionThis work demonstrates the potential of a mobile robotic system to automate RGB-D surface scanning in legal medicine, complementing post-mortem CT scans for inner documentation. Our results indicate that the proposed system can contribute to more efficient, autonomous legal medicine documentation, reducing the need for manual intervention.

Indexed as

Forensic MedicineRoboticsEquipment DesignHumansConfiguration space analysisLegal medicineParametric studyPatient documentationPoint cloud stitching

Identifiers

PMID40940538
PMCPMC13035680

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LicenceCC BY
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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.