View in EDS

Comprehensive deep learning-assisted multi-condition analysis of knee MRI studies improves resident radiologist performance.

Saved in:
Bibliographic Details
Title: Comprehensive deep learning-assisted multi-condition analysis of knee MRI studies improves resident radiologist performance.
Authors: Vuskov R; Lab for Artificial Intelligence in Medicine, Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany. rvuskov@ukaachen.de.; Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany. rvuskov@ukaachen.de., Hermans A; Lab for Artificial Intelligence in Medicine, Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany.; Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany.; Visual Computing Institute (Computer Vision), RWTH Aachen University, Aachen, Germany., Pixberg M; Radiologic Practice Cologne Triangle, Cologne, Germany., Müller-Hübenthal J; Radiologic Practice Cologne Triangle, Cologne, Germany., Brauksiepe A; Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany., Corban E; Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany., Cubukcu M; Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany., Nowak J; Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany., Kargaliev A; Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany., von der Stück M; Lab for Artificial Intelligence in Medicine, Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany.; Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany., Siepmann R; Lab for Artificial Intelligence in Medicine, Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany.; Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany., Kuhl C; Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany., Truhn D; Lab for Artificial Intelligence in Medicine, Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany.; Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany., Nebelung S; Lab for Artificial Intelligence in Medicine, Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany.; Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany.
Source: European radiology [Eur Radiol] 2026 Apr; Vol. 36 (4), pp. 2563-2575. Date of Electronic Publication: 2025 Oct 17.
Publication Type: Journal Article; Multicenter Study
Journal Info: Publisher: Springer International Country of Publication: Germany NLM ID: 9114774 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1432-1084 (Electronic) Linking ISSN: 09387994 NLM ISO Abbreviation: Eur Radiol Subsets: MEDLINE
Database: MEDLINE Ultimate
FullText Text:
  Availability: 0
Header DbId: mdl
DbLabel: MEDLINE Ultimate
An: 41107495
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Comprehensive deep learning-assisted multi-condition analysis of knee MRI studies improves resident radiologist performance.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22Vuskov+R%22">Vuskov R</searchLink>; Lab for Artificial Intelligence in Medicine, Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany. rvuskov@ukaachen.de.; Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany. rvuskov@ukaachen.de.<br /><searchLink fieldCode="AU" term="%22Hermans+A%22">Hermans A</searchLink>; Lab for Artificial Intelligence in Medicine, Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany.; Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany.; Visual Computing Institute (Computer Vision), RWTH Aachen University, Aachen, Germany.<br /><searchLink fieldCode="AU" term="%22Pixberg+M%22">Pixberg M</searchLink>; Radiologic Practice Cologne Triangle, Cologne, Germany.<br /><searchLink fieldCode="AU" term="%22Müller-Hübenthal+J%22">Müller-Hübenthal J</searchLink>; Radiologic Practice Cologne Triangle, Cologne, Germany.<br /><searchLink fieldCode="AU" term="%22Brauksiepe+A%22">Brauksiepe A</searchLink>; Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany.<br /><searchLink fieldCode="AU" term="%22Corban+E%22">Corban E</searchLink>; Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany.<br /><searchLink fieldCode="AU" term="%22Cubukcu+M%22">Cubukcu M</searchLink>; Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany.<br /><searchLink fieldCode="AU" term="%22Nowak+J%22">Nowak J</searchLink>; Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany.<br /><searchLink fieldCode="AU" term="%22Kargaliev+A%22">Kargaliev A</searchLink>; Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany.<br /><searchLink fieldCode="AU" term="%22von+der+Stück+M%22">von der Stück M</searchLink>; Lab for Artificial Intelligence in Medicine, Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany.; Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany.<br /><searchLink fieldCode="AU" term="%22Siepmann+R%22">Siepmann R</searchLink>; Lab for Artificial Intelligence in Medicine, Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany.; Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany.<br /><searchLink fieldCode="AU" term="%22Kuhl+C%22">Kuhl C</searchLink>; Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany.<br /><searchLink fieldCode="AU" term="%22Truhn+D%22">Truhn D</searchLink>; Lab for Artificial Intelligence in Medicine, Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany.; Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany.<br /><searchLink fieldCode="AU" term="%22Nebelung+S%22">Nebelung S</searchLink>; Lab for Artificial Intelligence in Medicine, Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany.; Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany.
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%229114774%22">European radiology</searchLink> [Eur Radiol] 2026 Apr; Vol. 36 (4), pp. 2563-2575. <i>Date of Electronic Publication: </i>2025 Oct 17.
– Name: TypePub
  Label: Publication Type
  Group: TypPub
  Data: Journal Article; Multicenter Study
– Name: TitleSource
  Label: Journal Info
  Group: Src
  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Springer+International%22">Springer International </searchLink><i>Country of Publication: </i>Germany <i>NLM ID: </i>9114774 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1432-1084 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2209387994%22">09387994 </searchLink><i>NLM ISO Abbreviation: </i>Eur Radiol <i>Subsets: </i>MEDLINE
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=41107495
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1007/s00330-025-12052-8
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        StartPage: 2563
    Titles:
      – TitleFull: Comprehensive deep learning-assisted multi-condition analysis of knee MRI studies improves resident radiologist performance.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Vuskov R
      – PersonEntity:
          Name:
            NameFull: Hermans A
      – PersonEntity:
          Name:
            NameFull: Pixberg M
      – PersonEntity:
          Name:
            NameFull: Müller-Hübenthal J
      – PersonEntity:
          Name:
            NameFull: Brauksiepe A
      – PersonEntity:
          Name:
            NameFull: Corban E
      – PersonEntity:
          Name:
            NameFull: Cubukcu M
      – PersonEntity:
          Name:
            NameFull: Nowak J
      – PersonEntity:
          Name:
            NameFull: Kargaliev A
      – PersonEntity:
          Name:
            NameFull: von der Stück M
      – PersonEntity:
          Name:
            NameFull: Siepmann R
      – PersonEntity:
          Name:
            NameFull: Kuhl C
      – PersonEntity:
          Name:
            NameFull: Truhn D
      – PersonEntity:
          Name:
            NameFull: Nebelung S
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 04
              Text: 2026 Apr
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-electronic
              Value: 1432-1084
          Numbering:
            – Type: volume
              Value: 36
            – Type: issue
              Value: 4
          Titles:
            – TitleFull: European radiology
              Type: main
ResultId 1