The role of artificial intelligence in cardiovascular magnetic resonance imaging.

Prog Cardiovasc Dis

Division of Cardiology, Department of Medicine, University of Louisville, Louisville, KY, USA; Center for Artificial Intelligence in Radiological Sciences (CAIRS), Department of Radiology, University of Louisville, Louisville, KY, USA. Electronic address:

Published: October 2024

AI Article Synopsis

  • Cardiovascular magnetic resonance (CMR) imaging is a top method for checking heart tissue and how well heart chambers work, but it can take a long time to analyze.
  • Using artificial intelligence (AI) can help speed up CMR analysis by automatically handling tasks like finding problems in images and calculating heart size and function.
  • The review talks about the challenges of getting AI widely used in heart imaging and suggests some ways to overcome those challenges.

Article Abstract

Cardiovascular magnetic resonance (CMR) imaging is the gold standard test for myocardial tissue characterization and chamber volumetric and functional evaluation. However, manual CMR analysis can be time-consuming and is subject to intra- and inter-observer variability. Artificial intelligence (AI) is a field that permits automated task performance through the identification of high-level and complex data relationships. In this review, we review the rapidly growing role of AI in CMR, including image acquisition, sequence prescription, artifact detection, reconstruction, segmentation, and data reporting and analysis including quantification of volumes, function, myocardial infarction (MI) and scar detection, and prediction of outcomes. We conclude with a discussion of the emerging challenges to widespread adoption and solutions that will allow for successful, broader uptake of this powerful technology.

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Source
http://dx.doi.org/10.1016/j.pcad.2024.06.004DOI Listing

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