Machine Learning for Assessment of Coronary Artery Disease in Cardiac CT: A Survey

Nils Hampe*, Jelmer M. Wolterink, Sanne G.M. van Velzen, Tim Leiner, Ivana Išgum

*Corresponding author for this work

Research output: Contribution to journalReview articleAcademicpeer-review

2 Citations (Scopus)
1 Downloads (Pure)

Abstract

Cardiac computed tomography (CT) allows rapid visualization of the heart and coronary arteries with high spatial resolution. However, analysis of cardiac CT scans for manifestation of coronary artery disease is time-consuming and challenging. Machine learning (ML) approaches have the potential to address these challenges with high accuracy and consistent performance. In this mini review, we present a survey of the literature on ML-based analysis of coronary artery disease in cardiac CT. We summarize ML methods for detection and characterization of atherosclerotic plaque as well as anatomically and functionally significant coronary artery stenosis.

Original languageEnglish
Article number172
Number of pages8
JournalFrontiers in Cardiovascular Medicine
Volume6
DOIs
Publication statusPublished - 26 Nov 2019
Externally publishedYes

Keywords

  • Atherosclerotic plaque
  • Cardiac CT
  • Coronary artery disease
  • Coronary artery stenosis
  • Machine learning

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