Improving the efficiency and accuracy of cardiovascular magnetic resonance with artificial intelligence—review of evidence and proposition of a roadmap to clinical translation

Improving the efficiency and accuracy of cardiovascular magnetic resonance with artificial intelligence—review of evidence and proposition of a roadmap to clinical translation

ABSTRACT: Background: Cardiovascular magnetic resonance (CMR) is an important imaging modality for the assessment of heart disease; however, limitations of CMR include long exam times and high complexity compared to other cardiac imaging modalities. Recently advancements in artificial intelligence...

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Bibliographic Details
Main Authors: Qiang Zhang, Anastasia Fotaki, Sona Ghadimi, Yu Wang, Mariya Doneva, Jens Wetzl, Jana G. Delfino, Declan P. O’Regan, Claudia Prieto, Frederick H. Epstein
Format: Article
Language:English
Published: Elsevier 2024-01-01
Series:Journal of Cardiovascular Magnetic Resonance
Subjects:
Cardiovascular magnetic resonance
Artificial intelligence
Deep learning
Clinical translation
Review
Roadmap
Online Access:http://www.sciencedirect.com/science/article/pii/S1097664724010780
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