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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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Formato: | Online Artículo Texto |
Lenguaje: | English |
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The Korean Society of Radiology
2021
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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. |
format | Online Article Text |
id | pubmed-8484158 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Korean Society of Radiology |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT yangdonghyun applicationofartificialintelligencetocardiovascularcomputedtomography |