Deep Learning Synthesis of White-Blood From Dark-Blood Late Gadolinium Enhancement Cardiac Magnetic Resonance.

Journal: Investigative radiology
PMID: 38687025

Abstract

OBJECTIVES: Dark-blood late gadolinium enhancement (DB-LGE) cardiac magnetic resonance has been proposed as an alternative to standard white-blood LGE (WB-LGE) imaging protocols to enhance scar-to-blood contrast without compromising scar-to-myocardium contrast. In practice, both DB and WB contrasts may have clinical utility, but acquiring both has the drawback of additional acquisition time. The aim of this study was to develop and evaluate a deep learning method to generate synthetic WB-LGE images from DB-LGE, allowing the assessment of both contrasts without additional scan time.

Authors

  • Tim J M Jaspers
    Department of Electrical Engineering, Video Coding & Architectures, Eindhoven University of Technology, Eindhoven, The Netherlands. Electronic address: t.j.m.jaspers@tue.nl.
  • Bibi Martens
  • Richard Crawley
    King's College London, Strand, London, UK.
  • Lamis Jada
  • Sina Amirrajab
    Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands. Electronic address: s.amirrajab@tue.nl.
  • Marcel Breeuwer
    Department of Biomedical Engineering, Medical Image Analysis group, Eindhoven University of Technology, Eindhoven, The Netherlands.
  • Robert J Holtackers
  • Amedeo Chiribiri
    School of Biomedical Engineering and Imaging Sciences, King's College London, UK.
  • Cian M Scannell
    School of Biomedical Engineering and Imaging Sciences, King's College London, UK.

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