Deep learning for accurately recognizing common causes of shoulder pain on radiographs.

Journal: Skeletal radiology
PMID: 33611622

Abstract

OBJECTIVE: Training a convolutional neural network (CNN) to detect the most common causes of shoulder pain on plain radiographs and to assess its potential value in serving as an assistive device to physicians.

Authors

  • Nils F Grauhan
    Department of Radiology, Charité - Universitätsmedizin Berlin, Hindenburgdamm 30, 12203, Berlin, Germany. nils-friedrich.grauhan@charite.de.
  • Stefan M Niehues
    Charité Universitätsmedizin Berlin, Campus Benjamin Franklin, Hindenburgdamm 30, 12203, Berlin, Germany.
  • Robert A Gaudin
    Department of Oral- and Maxillofacial Surgery, Charité, Berlin 12203, Germany.
  • Sarah Keller
    Department of Radiology, Charité, Charitéplatz 1, 10117, Berlin, Germany.
  • Janis L Vahldiek
    Charité Universitätsmedizin Berlin, Campus Benjamin Franklin, Hindenburgdamm 30, 12203, Berlin, Germany.
  • Lisa C Adams
    School of Medicine and Health, Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, TUM University Hospital, Technical University of Munich, Munich, Germany.
  • Keno K Bressem
    School of Medicine and Health, Institute for Cardiovascular Radiology and Nuclear Medicine, German Heart Center Munich, TUM University Hospital, Technical University of Munich, Munich, Germany.

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