Clinical utility of deep learning motion correction for T1 weighted MPRAGE MR images.

Journal: European journal of radiology
Published Date: Oct 27, 2020

Abstract

PURPOSE: To evaluate the clinical utility of the application of a deep learning motion correction technique on 3D MPRAGE magnetic resonance images acquired in routine clinical practice.

Authors

  • Kamlesh Pawar
    Monash Biomedical Imaging, Monash University, Building 220, Clayton Campus, 770 Blackburn Rd, Clayton, Victoria, 3168, Australia.
  • Zhaolin Chen
    Monash Biomedical Imaging, Monash University, Building 220, Clayton Campus, 770 Blackburn Rd, Clayton, Victoria, 3168, Australia. zhaolin.chen@monash.edu.
  • Jarrel Seah
    Department of Neuroscience, Monash University, Melbourne, Australia; Radiology and Nuclear Medicine, Alfred Health, Melbourne, Australia.
  • Meng Law
    Department of Neuroscience, Monash University, Melbourne, Australia; Radiology and Nuclear Medicine, Alfred Health, Melbourne, Australia; Department of Electrical and Computer Systems Engineering, Monash University, Melbourne, Australia.
  • Tom Close
    Monash Biomedical Imaging, Monash University, Melbourne, Australia.
  • Gary Egan
    Monash Biomedical Imaging, Monash University, Building 220, Clayton Campus, 770 Blackburn Rd, Clayton, Victoria, 3168, Australia.

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