Frequency and phase correction of J-difference edited MR spectra using deep learning.

Journal: Magnetic resonance in medicine
PMID:

Abstract

PURPOSE: To investigate whether a deep learning-based (DL) approach can be used for frequency-and-phase correction (FPC) of MEGA-edited MRS data.

Authors

  • Sofie Tapper
    Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
  • Mark Mikkelsen
    Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
  • Blake E Dewey
    Department of Electrical and Computer Engineering, The Johns Hopkins University, 105 Barton Hall, 3400 N. Charles St., Baltimore, MD 21218, USA; Kirby Center for Functional Brain Imaging Research, Kennedy Krieger Institute, Baltimore, MD, USA. Electronic address: blake.dewey@jhu.edu.
  • Helge J Zöllner
    Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
  • Steve C N Hui
    Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
  • Georg Oeltzschner
    Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
  • Richard A E Edden
    Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.