Non-traumatic brachial plexopathy identification from routine MRIs: Retrospective studies with deep learning networks.

Journal: European journal of radiology
PMID: 39383628

Abstract

PURPOSE: This study aims to seek an optimized deep learning model for differentiating non-traumatic brachial plexopathy from routine MRI scans.

Authors

  • Weiguo Cao
    State University of New York, Department of Radiology, Stony Brook, New York, United States.
  • Benjamin M Howe
    Department of Radiology, Mayo Clinic, Rochester, Minnesota.
  • Sumana Ramanathan
    Department of Radiology, Mayo Clinic, 200 First Street SW, Charlton 1, Rochester, MN 55905, USA.
  • Nicholas G Rhodes
    Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA.
  • Panagiotis Korfiatis
    From the Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905.
  • Kimberly K Amrami
    Department of Radiology, Mayo Clinic, 200 First Street SW, Charlton 1, Rochester, MN 55905, USA.
  • Robert J Spinner
    Department of Neurological Surgery, Mayo Clinic Rochester, Rochester, Minnesota, USA.
  • Timothy L Kline
    Department of Radiology, Mayo Clinic, Rochester, Minn.

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