articleFrontiers in Cardiovascular MedicineMar 5, 2020GOLD OA

Deep Learning for Cardiac Image Segmentation: A Review

CCChen ChenCQChen QinHQHuaqi QiuGTGiacomo TarroniJDJinming Duan

Institute of Group Analysis · Imperial College London · +2 more institutions

PubMed
Indexed inarxivcrossrefdoajpubmed

Abstract

Deep learning has become the most widely used approach for cardiac image segmentation in recent years. In this paper, we provide a review of over 100 cardiac image segmentation papers using deep learning, which covers common imaging modalities including magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound and major anatomical structures of interest (ventricles, atria, and vessels). In addition, a summary of publicly available cardiac image datasets and code repositories are included to provide a base for encouraging reproducible research. Finally, we discuss the challenges and limitations with current deep learning-based approaches (scarcity of labels, model generalizability across…

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833
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Authors

7
  • CC
    Chen ChenCorresponding

    Institute of Group Analysis, Imperial College London

  • CQ
    Chen Qin

    Institute of Group Analysis, Imperial College London

  • HQ
    Huaqi Qiu

    Institute of Group Analysis, Imperial College London

  • GT
    Giacomo Tarroni

    Institute of Group Analysis, City, University of London, Imperial College London

  • JD
    Jinming Duan

    University of Birmingham

Topics & keywords

Topics
Keywords
  • Deep learning
  • Segmentation
  • Generalizability theory
  • Magnetic resonance imaging
  • Image (mathematics)
  • Cardiac imaging
  • Modalities
  • Cardiac magnetic resonance
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