Generalizable synthetic MRI with physics-informed convolutional networks.

Journal: Medical physics
Published Date: Dec 8, 2023

Abstract

BACKGROUND: Magnetic resonance imaging (MRI) provides state-of-the-art image quality for neuroimaging, consisting of multiple separately acquired contrasts. Synthetic MRI aims to accelerate examinations by synthesizing any desirable contrast from a single acquisition.

Authors

  • Luuk Jacobs
    Department of Radiotherapy, UMC Utrecht, Utrecht, The Netherlands.
  • Stefano Mandija
    Department of Radiotherapy, Division of Imaging & Oncology, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Hongyan Liu
    Department of Gastroenterology, The First Affiliated Hospital of Shandong First Medical University& Shandong Provincial Qianfoshan Hospital, Jinan, China.
  • Cornelis A T van den Berg
    Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Alessandro Sbrizzi
    Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands.
  • Matteo Maspero
    Department of Radiation Oncology, Imaging and Cancer Division, University Medical Center Utrecht, Utrecht, The Netherlands; Computational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands.

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