An Artificial Intelligence Tool for Clinical Decision Support and Protocol Selection for Brain MRI.

Journal: AJNR. American journal of neuroradiology
Published Date: Dec 15, 2022

Abstract

BACKGROUND AND PURPOSE: Protocolling, the process of determining the most appropriate acquisition parameters for an imaging study, is time-consuming and produces variable results depending on the performing physician. The purpose of this study was to assess the potential of an artificial intelligence-based semiautomated tool in reducing the workload and decreasing unwarranted variation in the protocolling process.

Authors

  • K A Wong
    From the Department of Radiology (K.A.W., A.H., J.L.R., X.V.N., M.S.M., L.M.P.), The Ohio State University College of Medicine, Columbus, Ohio.
  • A Hatef
    From the Department of Radiology (K.A.W., A.H., J.L.R., X.V.N., M.S.M., L.M.P.), The Ohio State University College of Medicine, Columbus, Ohio.
  • J L Ryu
    From the Department of Radiology (K.A.W., A.H., J.L.R., X.V.N., M.S.M., L.M.P.), The Ohio State University College of Medicine, Columbus, Ohio.
  • X V Nguyen
    From the Department of Radiology (K.A.W., A.H., J.L.R., X.V.N., M.S.M., L.M.P.), The Ohio State University College of Medicine, Columbus, Ohio.
  • M S Makary
    From the Department of Radiology (K.A.W., A.H., J.L.R., X.V.N., M.S.M., L.M.P.), The Ohio State University College of Medicine, Columbus, Ohio.
  • L M Prevedello
    Department of Radiology, The Ohio State University College of Medicine, 452 Doan Tower, 395 West 12th Avenue, Columbus, OH 43210, USA.

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