Deep learning-based Lorentzian fitting of water saturation shift referencing spectra in MRI.

Journal: Magnetic resonance in medicine
Published Date: Jun 6, 2023

Abstract

PURPOSE: Water saturation shift referencing (WASSR) Z-spectra are used commonly for field referencing in chemical exchange saturation transfer (CEST) MRI. However, their analysis using least-squares (LS) Lorentzian fitting is time-consuming and prone to errors because of the unavoidable noise in vivo. A deep learning-based single Lorentzian Fitting Network (sLoFNet) is proposed to overcome these shortcomings.

Authors

  • Sajad Mohammed Ali
    Department of Medical Radiation Physics, Lund University, Lund, Sweden.
  • Nirbhay N Yadav
    The Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
  • Ronnie Wirestam
    Department of Medical Radiation Physics, Lund University, Lund, Sweden.
  • Munendra Singh
    Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA.
  • Hye-Young Heo
    Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA. Electronic address: hheo1@jhmi.edu.
  • Peter C van Zijl
    Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
  • Linda Knutsson
    Department of Medical Radiation Physics, Lund University, Lund, Sweden.

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