Automated cardiovascular magnetic resonance image analysis with fully convolutional networks.

Journal: Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
Published Date: Sep 14, 2018

Abstract

BACKGROUND: Cardiovascular resonance (CMR) imaging is a standard imaging modality for assessing cardiovascular diseases (CVDs), the leading cause of death globally. CMR enables accurate quantification of the cardiac chamber volume, ejection fraction and myocardial mass, providing information for diagnosis and monitoring of CVDs. However, for years, clinicians have been relying on manual approaches for CMR image analysis, which is time consuming and prone to subjective errors. It is a major clinical challenge to automatically derive quantitative and clinically relevant information from CMR images.

Authors

  • Wenjia Bai
    Department of Computing Imperial College London London UK.
  • Matthew Sinclair
    Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom.
  • Giacomo Tarroni
    Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, UK.
  • Ozan Oktay
  • Martin Rajchl
  • Ghislain Vaillant
    Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, UK.
  • Aaron M Lee
    NIHR Biomedical Research Centre at Barts, Queen Mary University of London, London, UK.
  • Nay Aung
    NIHR Barts Biomedical Research Centre, William Harvey Research Institute, Queen Mary University, London, United Kingdom.
  • Elena Lukaschuk
    Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
  • Mihir M Sanghvi
    NIHR Biomedical Research Centre at Barts, Queen Mary University of London, London, UK.
  • Filip Zemrak
    NIHR Biomedical Research Centre at Barts, Queen Mary University of London, London, UK.
  • Kenneth Fung
    NIHR Barts Biomedical Research Centre, William Harvey Research Institute, Queen Mary University, London, United Kingdom.
  • Jose Miguel Paiva
    Circle Cardiovascular Imaging, Calgary, AB, Canada.
  • Valentina Carapella
    Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
  • Young Jin Kim
    Department of Surgery, Chonnam National University Hwasun Hospital, Chonnam National University Medical School, Hwasun, Korea.
  • Hideaki Suzuki
    Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK.
  • Bernhard Kainz
    Biomedical Image Analysis (BioMedIA) Group, Department of Computing, Imperial College London, UK.
  • Paul M Matthews
    Division of Brain Sciences, Imperial College London, London, UK.
  • Steffen E Petersen
    Cardiac Imaging Department, Barts Heart Centre, St Bartholomew's Hospital, London, UK; William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, UK.
  • Stefan K Piechnik
    Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
  • Stefan Neubauer
    Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
  • Ben Glocker
    Kheiron Medical Technologies, London, UK.
  • Daniel Rueckert
    Biomedical Image Analysis (BioMedIA) Group, Department of Computing, Imperial College London, UK. Electronic address: d.rueckert@imperial.ac.uk.

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