Deep learning in fracture detection: a narrative review

Authors

  • Pishtiwan H S Kalmet Maastricht University Medical Center+, Department of Trauma Surgery, Maastricht
  • Sebastian Sanduleanu The D-Lab: Decision Support for Precision Medicine, GROW— School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht
  • Sergey Primakov The D-Lab: Decision Support for Precision Medicine, GROW— School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht
  • Guangyao Wu The D-Lab: Decision Support for Precision Medicine, GROW— School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht
  • Arthur Jochems The D-Lab: Decision Support for Precision Medicine, GROW— School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht
  • Turkey Refaee The D-Lab: Decision Support for Precision Medicine, GROW— School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht
  • Abdalla Ibrahim The D-Lab: Decision Support for Precision Medicine, GROW— School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht; Department of Radiology and Nuclear Medicine, GROW – School for Oncology and Developmental Biology, Maastricht University Medical Centre+, Maastricht, The Netherlands; Division of Nuclear Medicine and Oncological Imaging, Department of Medical Physics, Hospital Center Universitaire De Liege, Liege, Belgium; Department of Nuclear Medicine and Comprehensive diagnostic center Aachen (CDCA), University Hospital RWTH Aachen University, Aachen, Germany
  • Luca v. Hulst Maastricht University Medical Center+, Department of Trauma Surgery, Maastricht
  • Philippe Lambin The D-Lab: Decision Support for Precision Medicine, GROW— School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht; Department of Radiology and Nuclear Medicine, GROW – School for Oncology and Developmental Biology, Maastricht University Medical Centre+, Maastricht, The Netherlands
  • Martijn Poeze Maastricht University Medical Center+, Department of Trauma Surgery, Maastricht; School for Nutrition, Toxicology and Metabolism, Maastricht University, Maastricht, The Netherlands

DOI:

https://doi.org/10.1080/17453674.2020.1723292

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Published

2020-02-05

How to Cite

Kalmet, P. H. S., Sanduleanu, S., Primakov, S., Wu, G., Jochems, A., Refaee, T., Ibrahim, A., Hulst, L. v., Lambin, P., & Poeze, M. (2020). Deep learning in fracture detection: a narrative review. Acta Orthopaedica, 91(3), 362. https://doi.org/10.1080/17453674.2020.1723292

Issue

Acta Orthopaedica, Volume 91, Issue 3 (2020)

Section

Erratum/Corrigendum

License

Copyright (c) 2020 Pishtiwan H S Kalmet*, Sebastian Sanduleanu*, Sergey Primakov, Guangyao Wu, Arthur Jochems, Turkey Refaee, Abdalla Ibrahim, Luca v. Hulst, Philippe Lambin, Martijn Poeze

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Acta Orthopaedica (Scandinavica) content is available freely online as from volume 1, 1930. The journal owner owns the copyright for all material published until volume 80, 2009. As of June 2009, the journal has however been published fully Open Access, meaning the authors retain copyright to their work. As of June 2009, articles have been published under CC-BY-NC or CC-BY licenses, unless otherwise specified.
 
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