MR-assisted PET respiratory motion correction using deep-learning based short-scan motion fields.

Journal: Magnetic resonance in medicine
Published Date: Mar 28, 2022

Abstract

PURPOSE: We evaluated the impact of PET respiratory motion correction (MoCo) in a phantom and patients. Moreover, we proposed and examined a PET MoCo approach using motion vector fields (MVFs) from a deep-learning reconstructed short MRI scan.

Authors

  • Sihao Chen
    Department of Biomedical Engineering.
  • Tyler J Fraum
    From the Mallinckrodt Institute of Radiology.
  • Cihat Eldeniz
    Department of Radiology, Washington University School of Medicine, Saint Louis, Missouri.
  • Joyce Mhlanga
    Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA.
  • Weijie Gan
    Department of Computer Science & Engineering.
  • Thomas Vahle
    Siemens Healthcare GmbH, Erlangen, Germany.
  • Uday B Krishnamurthy
    Siemens Medical Solutions USA, Inc., St. Louis, MO, USA.
  • David Faul
    Siemens Medical Solutions USA, Inc., Malvern, PA, USA.
  • H Michael Gach
    Departments of Radiation Oncology and Radiology, Washington University, St. Louis, MO, 63110, USA.
  • Michael M Binkley
    Department of Neurology, Washington University School of Medicine, Saint Louis, Missouri.
  • Ulugbek S Kamilov
    Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, MO, USA.
  • Richard Laforest
    Mallinckrodt Institute of Radiology, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA.
  • Hongyu An
    Department of Radiology, Washington University School of Medicine, Saint Louis, Missouri.

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