An open source convolutional neural network to detect and localize distal radius fractures on plain radiographs.

Journal: European journal of trauma and emergency surgery : official publication of the European Trauma Society
PMID: 39820574

Abstract

PURPOSE: Distal radius fractures (DRFs) are often initially assessed by junior doctors under time constraints, with limited supervision, risking significant consequences if missed. Convolutional Neural Networks (CNNs) can aid in diagnosing fractures. This study aims to internally and externally validate an open source algorithm for the detection and localization of DRFs.

Authors

  • Koen D Oude Nijhuis
    Department of Surgery and Perioperative Care, Dell Medical School at the University of Texas at Austin, Austin, TX, USA.
  • Britt Barvelink
    Department of Orthopedics and Sports Medicine, Erasmus University Medical Centre, Rotterdam, The Netherlands.
  • Jasper Prijs
    Flinders University, Adelaide, Australia.
  • Yang Zhao
    The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia.
  • Zhibin Liao
  • Ruurd L Jaarsma
  • Frank F A Ijpma
    Department of Trauma Surgery, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
  • Joost W Colaris
    Department of Orthopedics, Erasmus University Medical Centre, Rotterdam, The Netherlands.
  • Job N Doornberg
  • Mathieu M E Wijffels
    Trauma Research Unit, Department of Surgery, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2040, 3000 CA, Rotterdam, The Netherlands.

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