Cardiovascular Diseases

  • Johan Verjans
  • Wouter B. Veldhuis
  • Gustavo Carneiro
  • Jelmer M. Wolterink
  • Ivana Išgum
  • Tim LeinerEmail author


Cross-sectional imaging techniques—echocardiography, CT, MRI and nuclear medicine—are the diagnostic tools of choice for the diagnosis and workup of cardiovascular disease. Machine learning and deep learning in particular will have a fundamental and lasting impact on all of these modalities. Whereas deep learning is mostly discussed in the context of image interpretation, we show that the impact is much broader than this. The entire imaging chain from choosing the appropriate imaging test to acquiring the proper images, reconstruction of images from raw data, image interpretation, reporting and derivation of prognostic information can be improved by application of machine learning and deep learning techniques. Application of machine learning and deep learning algorithms will be an important step towards fulfilling the promise of truly personalized medicine, especially when information from imaging is combined with other data such as the results from laboratory evaluations, genetic analysis, medication use and personal fitness trackers. Nevertheless, the process of bringing the results to physicians is nontrivial, and we also discuss our experience with deployment of developed algorithms in clinical practice.


Artificial intelligence Machine learning Deep learning Reconstruction Denoising Auto-segmentation Classification Medical imaging Computed tomography (CT) Coronary computed tomography angiography (CCTA) Coronary artery calcium scoring (CACS) Cardiac magnetic resonance (CMR) Magnetic resonance imaging (MRI) Echocardiography Nuclear imaging Myocardial perfusion scintigraphy Heart failure Valvular disease Coronary artery disease Cardiovascular disease Prognosis Future of medical imaging 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Johan Verjans
    • 1
    • 2
  • Wouter B. Veldhuis
    • 3
  • Gustavo Carneiro
    • 1
  • Jelmer M. Wolterink
    • 4
  • Ivana Išgum
    • 4
  • Tim Leiner
    • 3
    Email author
  1. 1.Department of CardiologySouth Australian Health and Medical Research Institute, University of AdelaideAdelaideAustralia
  2. 2.Department of CardiologyUtrecht University Medical CenterUtrechtThe Netherlands
  3. 3.Department of RadiologyUtrecht University Medical CenterUtrechtThe Netherlands
  4. 4.Image Sciences Institute, Utrecht University Medical CenterUtrechtThe Netherlands

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