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Role of Deep Learning in Computed Tomography
Computed tomography has played an instrumental role in the understanding of the pathophysiology of atherosclerosis in coronary artery disease. It enables visualization of the plaque obstruction and vessel stenosis in a comprehensive manner. As technology for computed tomography is constantly evolvin...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cureus
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10275744/ https://www.ncbi.nlm.nih.gov/pubmed/37332431 http://dx.doi.org/10.7759/cureus.39160 |
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author | Garg, Yash Seetharam, Karthik Sharma, Manjari Rohita, Dipesh K Nabi, Waseem |
author_facet | Garg, Yash Seetharam, Karthik Sharma, Manjari Rohita, Dipesh K Nabi, Waseem |
author_sort | Garg, Yash |
collection | PubMed |
description | Computed tomography has played an instrumental role in the understanding of the pathophysiology of atherosclerosis in coronary artery disease. It enables visualization of the plaque obstruction and vessel stenosis in a comprehensive manner. As technology for computed tomography is constantly evolving, coronary applications and possibilities are constantly expanding. This influx of information can overwhelm a physician's ability to interpret information in this era of big data. Machine learning is a revolutionary approach that can help provide limitless pathways in patient management. Within these machine algorithms, deep learning has tremendous potential and can revolutionize computed tomography and cardiovascular imaging. In this review article, we highlight the role of deep learning in various aspects of computed tomography. |
format | Online Article Text |
id | pubmed-10275744 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cureus |
record_format | MEDLINE/PubMed |
spelling | pubmed-102757442023-06-18 Role of Deep Learning in Computed Tomography Garg, Yash Seetharam, Karthik Sharma, Manjari Rohita, Dipesh K Nabi, Waseem Cureus Cardiology Computed tomography has played an instrumental role in the understanding of the pathophysiology of atherosclerosis in coronary artery disease. It enables visualization of the plaque obstruction and vessel stenosis in a comprehensive manner. As technology for computed tomography is constantly evolving, coronary applications and possibilities are constantly expanding. This influx of information can overwhelm a physician's ability to interpret information in this era of big data. Machine learning is a revolutionary approach that can help provide limitless pathways in patient management. Within these machine algorithms, deep learning has tremendous potential and can revolutionize computed tomography and cardiovascular imaging. In this review article, we highlight the role of deep learning in various aspects of computed tomography. Cureus 2023-05-17 /pmc/articles/PMC10275744/ /pubmed/37332431 http://dx.doi.org/10.7759/cureus.39160 Text en Copyright © 2023, Garg et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Cardiology Garg, Yash Seetharam, Karthik Sharma, Manjari Rohita, Dipesh K Nabi, Waseem Role of Deep Learning in Computed Tomography |
title | Role of Deep Learning in Computed Tomography |
title_full | Role of Deep Learning in Computed Tomography |
title_fullStr | Role of Deep Learning in Computed Tomography |
title_full_unstemmed | Role of Deep Learning in Computed Tomography |
title_short | Role of Deep Learning in Computed Tomography |
title_sort | role of deep learning in computed tomography |
topic | Cardiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10275744/ https://www.ncbi.nlm.nih.gov/pubmed/37332431 http://dx.doi.org/10.7759/cureus.39160 |
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