End-to-end deep learning nonrigid motion-corrected reconstruction for highly accelerated free-breathing coronary MRA.

Journal: Magnetic resonance in medicine
Published Date: Jun 6, 2021

Abstract

PURPOSE: To develop an end-to-end deep learning technique for nonrigid motion-corrected (MoCo) reconstruction of ninefold undersampled free-breathing whole-heart coronary MRA (CMRA).

Authors

  • Haikun Qi
    School of Biomedical Engineering and Imaging Sciences, King's College London, London, London, United Kingdom.
  • Reza Hajhosseiny
    School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas' Hospital, Lambeth Wing, London, UK.
  • Gastao Cruz
    School of Biomedical Engineering & Imaging Sciences, King's College, London, UK.
  • Thomas Kuestner
  • Karl Kunze
    School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
  • Radhouene Neji
    School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas' Hospital, Lambeth Wing, London, UK.
  • Rene Botnar
    School of Biomedical Engineering & Imaging Sciences, King's College, London, UK.
  • Claudia Prieto
    School of Biomedical Engineering & Imaging Sciences, King's College, London, UK.

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