Improving Xenon-129 lung ventilation image SNR with deep-learning based image reconstruction.

Journal: Magnetic resonance in medicine
PMID: 39155454

Abstract

PURPOSE: To evaluate the feasibility and utility of a deep learning (DL)-based reconstruction for improving the SNR of hyperpolarized Xe lung ventilation MRI.

Authors

  • Neil J Stewart
    POLARIS, Division of Clinical Medicine, School of Medicine & Population Health, Faculty of Health, The University of Sheffield, Sheffield, UK.
  • Jose de Arcos
    GE HealthCare, Little Chalfont, Amersham, UK.
  • Alberto M Biancardi
    POLARIS, Department of Infection, Immunity and Cardiovascular Disease, The University of Sheffield, Sheffield, UK.
  • Guilhem J Collier
    POLARIS, Department of Infection, Immunity and Cardiovascular Disease, The University of Sheffield, Sheffield, UK.
  • Laurie J Smith
    POLARIS, Department of Infection, Immunity and Cardiovascular Disease, The University of Sheffield, Sheffield, UK.
  • Graham Norquay
    POLARIS, Department of Infection, Immunity & Cardiovascular Disease, The University of Sheffield, Sheffield, UK.
  • Helen Marshall
    POLARIS, Department of Infection, Immunity and Cardiovascular Disease, The University of Sheffield, Sheffield, UK.
  • Anja C S Brau
    GE HealthCare, Menlo Park, California, USA.
  • R Marc Lebel
    GE Healthcare, Calgary, Canada.
  • Jim M Wild
    Department of Oncology and Metabolism, The University of Sheffield, Sheffield, United Kingdom.

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