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Artificial Intelligence in Cardiovascular Atherosclerosis Imaging

At present, artificial intelligence (AI) has already been applied in cardiovascular imaging (e.g., image segmentation, automated measurements, and eventually, automated diagnosis) and it has been propelled to the forefront of cardiovascular medical imaging research. In this review, we presented the...

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Detalles Bibliográficos
Autores principales: Zhang, Jia, Han, Ruijuan, Shao, Guo, Lv, Bin, Sun, Kai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8952318/
https://www.ncbi.nlm.nih.gov/pubmed/35330420
http://dx.doi.org/10.3390/jpm12030420
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author Zhang, Jia
Han, Ruijuan
Shao, Guo
Lv, Bin
Sun, Kai
author_facet Zhang, Jia
Han, Ruijuan
Shao, Guo
Lv, Bin
Sun, Kai
author_sort Zhang, Jia
collection PubMed
description At present, artificial intelligence (AI) has already been applied in cardiovascular imaging (e.g., image segmentation, automated measurements, and eventually, automated diagnosis) and it has been propelled to the forefront of cardiovascular medical imaging research. In this review, we presented the current status of artificial intelligence applied to image analysis of coronary atherosclerotic plaques, covering multiple areas from plaque component analysis (e.g., identification of plaque properties, identification of vulnerable plaque, detection of myocardial function, and risk prediction) to risk prediction. Additionally, we discuss the current evidence, strengths, limitations, and future directions for AI in cardiac imaging of atherosclerotic plaques, as well as lessons that can be learned from other areas. The continuous development of computer science and technology may further promote the development of this field.
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spelling pubmed-89523182022-03-26 Artificial Intelligence in Cardiovascular Atherosclerosis Imaging Zhang, Jia Han, Ruijuan Shao, Guo Lv, Bin Sun, Kai J Pers Med Review At present, artificial intelligence (AI) has already been applied in cardiovascular imaging (e.g., image segmentation, automated measurements, and eventually, automated diagnosis) and it has been propelled to the forefront of cardiovascular medical imaging research. In this review, we presented the current status of artificial intelligence applied to image analysis of coronary atherosclerotic plaques, covering multiple areas from plaque component analysis (e.g., identification of plaque properties, identification of vulnerable plaque, detection of myocardial function, and risk prediction) to risk prediction. Additionally, we discuss the current evidence, strengths, limitations, and future directions for AI in cardiac imaging of atherosclerotic plaques, as well as lessons that can be learned from other areas. The continuous development of computer science and technology may further promote the development of this field. MDPI 2022-03-08 /pmc/articles/PMC8952318/ /pubmed/35330420 http://dx.doi.org/10.3390/jpm12030420 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Zhang, Jia
Han, Ruijuan
Shao, Guo
Lv, Bin
Sun, Kai
Artificial Intelligence in Cardiovascular Atherosclerosis Imaging
title Artificial Intelligence in Cardiovascular Atherosclerosis Imaging
title_full Artificial Intelligence in Cardiovascular Atherosclerosis Imaging
title_fullStr Artificial Intelligence in Cardiovascular Atherosclerosis Imaging
title_full_unstemmed Artificial Intelligence in Cardiovascular Atherosclerosis Imaging
title_short Artificial Intelligence in Cardiovascular Atherosclerosis Imaging
title_sort artificial intelligence in cardiovascular atherosclerosis imaging
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8952318/
https://www.ncbi.nlm.nih.gov/pubmed/35330420
http://dx.doi.org/10.3390/jpm12030420
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