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The Applications of Artificial Intelligence in Cardiovascular Magnetic Resonance—A Comprehensive Review.

Authors :
Argentiero, Adriana
Muscogiuri, Giuseppe
Rabbat, Mark G.
Martini, Chiara
Soldato, Nicolò
Basile, Paolo
Baggiano, Andrea
Mushtaq, Saima
Fusini, Laura
Mancini, Maria Elisabetta
Gaibazzi, Nicola
Santobuono, Vincenzo Ezio
Sironi, Sandro
Pontone, Gianluca
Guaricci, Andrea Igoren
Source :
Journal of Clinical Medicine; May2022, Vol. 11 Issue 10, p2866-2866, 18p
Publication Year :
2022

Abstract

Cardiovascular disease remains an integral field on which new research in both the biomedical and technological fields is based, as it remains the leading cause of mortality and morbidity worldwide. However, despite the progress of cardiac imaging techniques, the heart remains a challenging organ to study. Artificial intelligence (AI) has emerged as one of the major innovations in the field of diagnostic imaging, with a dramatic impact on cardiovascular magnetic resonance imaging (CMR). AI will be increasingly present in the medical world, with strong potential for greater diagnostic efficiency and accuracy. Regarding the use of AI in image acquisition and reconstruction, the main role was to reduce the time of image acquisition and analysis, one of the biggest challenges concerning magnetic resonance; moreover, it has been seen to play a role in the automatic correction of artifacts. The use of these techniques in image segmentation has allowed automatic and accurate quantification of the volumes and masses of the left and right ventricles, with occasional need for manual correction. Furthermore, AI can be a useful tool to directly help the clinician in the diagnosis and derivation of prognostic information of cardiovascular diseases. This review addresses the applications and future prospects of AI in CMR imaging, from image acquisition and reconstruction to image segmentation, tissue characterization, diagnostic evaluation, and prognostication. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20770383
Volume :
11
Issue :
10
Database :
Complementary Index
Journal :
Journal of Clinical Medicine
Publication Type :
Academic Journal
Accession number :
157239372
Full Text :
https://doi.org/10.3390/jcm11102866