Evidence map›Paper›PMID 38862851›Full record

ArticleJournal of imaging informatics in medicine2025

Multisensory Extended Reality Applications Offer Benefits for Volumetric Biomedical Image Analysis in Research and Medicine.

Kathrin Krieger, Jan Egger, Jens Kleesiek, Matthias Gunzer, Jianxu Chen

Abstract read
In one paragraph

Article in Journal of imaging informatics in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Biomedizinische Technik. Biomedical engineering · 2025
    Article
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.

Kathrin KriegerBiospectroscopy, Leibniz-Institut for Analytical Science-ISAS-e.V., Bunsen-Kirchhoff-Str. 11, Dortmund, 44139, NRW, Germany. kathrin.krieger@isas.de.ORCID http://orcid.org/0000-0003-2837-9887
Jan EggerInstitute for Artificial Intelligence in Medicine (IKIM), University Hospital Essen, University of Duisburg-Essen, Girardetstr. 2, Essen, 45131, NRW, Germany.
Jens KleesiekInstitute for Artificial Intelligence in Medicine (IKIM), University Hospital Essen, University of Duisburg-Essen, Girardetstr. 2, Essen, 45131, NRW, Germany.
Matthias GunzerBiospectroscopy, Leibniz-Institut for Analytical Science-ISAS-e.V., Bunsen-Kirchhoff-Str. 11, Dortmund, 44139, NRW, Germany.
Jianxu ChenBiospectroscopy, Leibniz-Institut for Analytical Science-ISAS-e.V., Bunsen-Kirchhoff-Str. 11, Dortmund, 44139, NRW, Germany.

Funding

Bundesministerium für Bildung und Forschung 161L0272KITE (Plattform für KI-Translation Essen) from the REACT-EU initiative EFRE-0801977Ministerium für Kultur und Wissenschaft des Landes Nordrhein-Westfalen Grant number
6 · The paper itself

Abstract

3D data from high-resolution volumetric imaging is a central resource for diagnosis and treatment in modern medicine. While the fast development of AI enhances imaging and analysis, commonly used visualization methods lag far behind. Recent research used extended reality (XR) for perceiving 3D images with visual depth perception and touch but used restrictive haptic devices. While unrestricted touch benefits volumetric data examination, implementing natural haptic interaction with XR is challenging. The research question is whether a multisensory XR application with intuitive haptic interaction adds value and should be pursued. In a study, 24 experts for biomedical images in research and medicine explored 3D medical shapes with 3 applications: a multisensory virtual reality (VR) prototype using haptic gloves, a simple VR prototype using controllers, and a standard PC application. Results of standardized questionnaires showed no significant differences between all application types regarding usability and no significant difference between both VR applications regarding presence. Participants agreed to statements that VR visualizations provide better depth information, using the hands instead of controllers simplifies data exploration, the multisensory VR prototype allows intuitive data exploration, and it is beneficial over traditional data examination methods. While most participants mentioned manual interaction as the best aspect, they also found it the most improvable. We conclude that a multisensory XR application with improved manual interaction adds value for volumetric biomedical data examination. We will proceed with our open-source research project ISH3DE (Intuitive Stereoptic Haptic 3D Data Exploration) to serve medical education, therapeutic decisions, surgery preparations, or research data analysis.

Indexed as

Biomedical ResearchImage Processing, Computer-AssistedImaging, Three-DimensionalVirtual RealityHumansMaleSurveys and Questionnaires3D visualizationExtended realityHaptic glovesHaptic interactionVirtual realityVolumetric imaging

Identifiers

PMID38862851
PMCPMC11811323

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.