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Application of Artificial Intelligence to Cardiovascular Computed Tomography

Cardiovascular computed tomography (CT) is among the most active fields with ongoing technical innovation related to image acquisition and analysis. Artificial intelligence can be incorporated into various clinical applications of cardiovascular CT, including imaging of the heart valves and coronary...

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Autor principal: Yang, Dong Hyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Society of Radiology 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8484158/
https://www.ncbi.nlm.nih.gov/pubmed/34402240
http://dx.doi.org/10.3348/kjr.2020.1314
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author Yang, Dong Hyun
author_facet Yang, Dong Hyun
author_sort Yang, Dong Hyun
collection PubMed
description Cardiovascular computed tomography (CT) is among the most active fields with ongoing technical innovation related to image acquisition and analysis. Artificial intelligence can be incorporated into various clinical applications of cardiovascular CT, including imaging of the heart valves and coronary arteries, as well as imaging to evaluate myocardial function and congenital heart disease. This review summarizes the latest research on the application of deep learning to cardiovascular CT. The areas covered range from image quality improvement to automatic analysis of CT images, including methods such as calcium scoring, image segmentation, and coronary artery evaluation.
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spelling pubmed-84841582021-10-01 Application of Artificial Intelligence to Cardiovascular Computed Tomography Yang, Dong Hyun Korean J Radiol Cardiovascular Imaging Cardiovascular computed tomography (CT) is among the most active fields with ongoing technical innovation related to image acquisition and analysis. Artificial intelligence can be incorporated into various clinical applications of cardiovascular CT, including imaging of the heart valves and coronary arteries, as well as imaging to evaluate myocardial function and congenital heart disease. This review summarizes the latest research on the application of deep learning to cardiovascular CT. The areas covered range from image quality improvement to automatic analysis of CT images, including methods such as calcium scoring, image segmentation, and coronary artery evaluation. The Korean Society of Radiology 2021-10 2021-07-26 /pmc/articles/PMC8484158/ /pubmed/34402240 http://dx.doi.org/10.3348/kjr.2020.1314 Text en Copyright © 2021 The Korean Society of Radiology https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Cardiovascular Imaging
Yang, Dong Hyun
Application of Artificial Intelligence to Cardiovascular Computed Tomography
title Application of Artificial Intelligence to Cardiovascular Computed Tomography
title_full Application of Artificial Intelligence to Cardiovascular Computed Tomography
title_fullStr Application of Artificial Intelligence to Cardiovascular Computed Tomography
title_full_unstemmed Application of Artificial Intelligence to Cardiovascular Computed Tomography
title_short Application of Artificial Intelligence to Cardiovascular Computed Tomography
title_sort application of artificial intelligence to cardiovascular computed tomography
topic Cardiovascular Imaging
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8484158/
https://www.ncbi.nlm.nih.gov/pubmed/34402240
http://dx.doi.org/10.3348/kjr.2020.1314
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