Accelerated 4D-flow MRI with 3-point encoding enabled by machine learning.

Journal: Magnetic resonance in medicine
Published Date: Oct 5, 2022

Abstract

PURPOSE: To investigate the acceleration of 4D-flow MRI using a convolutional neural network (CNN) that produces three directional velocities from three flow encodings, without requiring a fourth reference scan measuring background phase.

Authors

  • Dahan Kim
    Department of Physics, University of Wisconsin, Madison, Wisconsin, USA.
  • Mu-Lan Jen
    Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.
  • Laura B Eisenmenger
    Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.
  • Kevin M Johnson
    From the Department of Radiology and Biomedical Imaging, Yale University School of Medicine, 333 Cedar St, Thompkins East 2, New Haven, CT 06520 (K.M.J., H.E.J., Y.Z., L.H.S.); College of Electronic Information and Automation, Civil Aviation University of China, Tianjin, China (Y.Z.); Upstate Carolina Radiology PA, Spartanburg, SC (D.A.D.); and Department of Biomedical Engineering, Yale University, New Haven, Conn (L.H.S.).

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