Deep-Learning-Based Preprocessing for Quantitative Myocardial Perfusion MRI.

Journal: Journal of magnetic resonance imaging : JMRI
Published Date: Nov 11, 2019

Abstract

BACKGROUND: Quantitative myocardial perfusion cardiac MRI can provide a fast and robust assessment of myocardial perfusion status for the noninvasive diagnosis of myocardial ischemia while being more objective than visual assessment. However, it currently has limited use in clinical practice due to the challenging postprocessing required, particularly the segmentation.

Authors

  • Cian M Scannell
    School of Biomedical Engineering and Imaging Sciences, King's College London, UK.
  • Mitko Veta
    Medical Image Analysis Group, Eindhoven University of Technology, Eindhoven, the Netherlands.
  • Adriana D M Villa
    School of Biomedical Engineering and Imaging Sciences, King's College London, UK.
  • Eva C Sammut
    School of Biomedical Engineering and Imaging Sciences, King's College London, UK.
  • Jack Lee
    Clinical Trials and Biostatistics Lab CUHK Shenzhen Research Institute Shenzhen China.
  • Marcel Breeuwer
    Department of Biomedical Engineering, Medical Image Analysis group, Eindhoven University of Technology, Eindhoven, The Netherlands.
  • Amedeo Chiribiri
    School of Biomedical Engineering and Imaging Sciences, King's College London, UK.

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