Deep learning-assisted model-based off-resonance correction for non-Cartesian SWI.

Journal: Magnetic resonance in medicine
Published Date: Jun 22, 2023

Abstract

PURPOSE: Patient-induced inhomogeneities in the static magnetic field cause distortions and blurring (off-resonance artifacts) during acquisitions with long readouts such as in SWI. Conventional versatile correction methods based on extended Fourier models are too slow for clinical practice in computationally demanding cases such as 3D high-resolution non-Cartesian multi-coil acquisitions.

Authors

  • Guillaume Daval-Frérot
    Siemens Healthineers, Saint-Denis, France.
  • Aurélien Massire
    Siemens Healthcare SAS, Saint-Denis 93200, France.
  • Boris Mailhe
  • Mariappan Nadar
    Digital Technology and Innovation, Siemens Healthineers, Princeton, USA.
  • Blanche Bapst
    Department of Neuroradiology, AP-HP, Henri Mondor University Hospital, Créteil, France.
  • Alain Luciani
    Medical Imaging Department, Henri Mondor University Hospital, AP-HP, Créteil, France, Inserm, U955, Team 18, 94000 Créteil, France.
  • Alexandre Vignaud
    NeuroSpin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France.
  • Philippe Ciuciu
    NeuroSpin, CEA, Paris-Saclay, Gif-sur-Yvette, France.

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