Accelerated cardiac magnetic resonance imaging using deep learning for volumetric assessment in children.

Journal: Pediatric radiology
PMID: 39017676

Abstract

BACKGROUND: Ventricular volumetry using a short-axis stack of two-dimensional (D) cine balanced steady-state free precession (bSSFP) sequences is crucial in any cardiac magnetic resonance imaging (MRI) examination. This task becomes particularly challenging in children due to multiple breath-holds.

Authors

  • Melina Koechli
    Department of Diagnostic Imaging, University Children's Hospital Zurich, Zurich, Switzerland.
  • Fraser M Callaghan
    Sydney Translational Imaging Laboratory, University of Sydney, Sydney, NSW, Australia.
  • Barbara E U Burkhardt
    Department of Pediatrics, UT Southwestern Medical Center, 1935 Medical District Dr, Dallas, TX, 75235, USA.
  • Maelene Lohezic
    Applications & Workflow, GE Healthcare, Manchester, UK.
  • Xucheng Zhu
    GE Healthcare, Menlo Park, CA, USA.
  • Beate Rücker
    Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland.
  • Emanuela R Valsangiacomo Buechel
    Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland.
  • Christian J Kellenberger
    Department of Diagnostic Imaging, University Children's Hospital Zurich, Zurich, Switzerland.
  • Julia Geiger
    Department of Diagnostic Imaging, University Children's Hospital Zurich, Zurich, Switzerland. julia.geiger@kispi.uzh.ch.

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