MR spectroscopy frequency and phase correction using convolutional neural networks.

Journal: Magnetic resonance in medicine
Published Date: Dec 21, 2021

Abstract

PURPOSE: To introduce a novel convolutional neural network (CNN)-based approach for frequency-and-phase correction (FPC) of MR spectroscopy (MRS) spectra to achieve fast and accurate FPC of single-voxel MEGA-PRESS MRS data.

Authors

  • David J Ma
    Department of Biomedical Engineering, Columbia University, New York, New York, USA.
  • Hortense A-M Le
    Department of Biomedical Engineering, Columbia University, New York, New York, USA.
  • Yuming Ye
    Department of Biomedical Engineering, Columbia University, New York, New York, USA.
  • Andrew F Laine
  • Jeffery A Lieberman
    Department of Psychiatry, Columbia University, New York, New York, USA.
  • Douglas L Rothman
    Radiology and Biomedical Imaging of Biomedical Engineering, Yale University, New Haven, Connecticut, USA.
  • Scott A Small
    Department of Neurology, Columbia University, New York, NY, USA; Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, NY, USA.
  • Jia Guo
    Department of Radiology, Stanford University, Stanford, CA, USA.

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