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Extraction of Coronary Atherosclerotic Plaques From Computed Tomography Imaging: A Review of Recent Methods

Background: Atherosclerotic plaques are the major cause of coronary artery disease (CAD). Currently, computed tomography (CT) is the most commonly applied imaging technique in the diagnosis of CAD. However, the accurate extraction of coronary plaque geometry from CT images is still challenging. Summ...

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Autores principales: Liu, Haipeng, Wingert, Aleksandra, Wang, Jian'an, Zhang, Jucheng, Wang, Xinhong, Sun, Jianzhong, Chen, Fei, Khalid, Syed Ghufran, Jiang, Jun, Zheng, Dingchang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7903898/
https://www.ncbi.nlm.nih.gov/pubmed/33644127
http://dx.doi.org/10.3389/fcvm.2021.597568
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author Liu, Haipeng
Wingert, Aleksandra
Wang, Jian'an
Zhang, Jucheng
Wang, Xinhong
Sun, Jianzhong
Chen, Fei
Khalid, Syed Ghufran
Jiang, Jun
Zheng, Dingchang
author_facet Liu, Haipeng
Wingert, Aleksandra
Wang, Jian'an
Zhang, Jucheng
Wang, Xinhong
Sun, Jianzhong
Chen, Fei
Khalid, Syed Ghufran
Jiang, Jun
Zheng, Dingchang
author_sort Liu, Haipeng
collection PubMed
description Background: Atherosclerotic plaques are the major cause of coronary artery disease (CAD). Currently, computed tomography (CT) is the most commonly applied imaging technique in the diagnosis of CAD. However, the accurate extraction of coronary plaque geometry from CT images is still challenging. Summary of Review: In this review, we focused on the methods in recent studies on the CT-based coronary plaque extraction. According to the dimension of plaque extraction method, the studies were categorized into two-dimensional (2D) and three-dimensional (3D) ones. In each category, the studies were analyzed in terms of data, methods, and evaluation. We summarized the merits and limitations of current methods, as well as the future directions for efficient and accurate extraction of coronary plaques using CT imaging. Conclusion: The methodological innovations are important for more accurate CT-based assessment of coronary plaques in clinical applications. The large-scale studies, de-blooming algorithms, more standardized datasets, and more detailed classification of non-calcified plaques could improve the accuracy of coronary plaque extraction from CT images. More multidimensional geometric parameters can be derived from the 3D geometry of coronary plaques. Additionally, machine learning and automatic 3D reconstruction could improve the efficiency of coronary plaque extraction in future studies.
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spelling pubmed-79038982021-02-25 Extraction of Coronary Atherosclerotic Plaques From Computed Tomography Imaging: A Review of Recent Methods Liu, Haipeng Wingert, Aleksandra Wang, Jian'an Zhang, Jucheng Wang, Xinhong Sun, Jianzhong Chen, Fei Khalid, Syed Ghufran Jiang, Jun Zheng, Dingchang Front Cardiovasc Med Cardiovascular Medicine Background: Atherosclerotic plaques are the major cause of coronary artery disease (CAD). Currently, computed tomography (CT) is the most commonly applied imaging technique in the diagnosis of CAD. However, the accurate extraction of coronary plaque geometry from CT images is still challenging. Summary of Review: In this review, we focused on the methods in recent studies on the CT-based coronary plaque extraction. According to the dimension of plaque extraction method, the studies were categorized into two-dimensional (2D) and three-dimensional (3D) ones. In each category, the studies were analyzed in terms of data, methods, and evaluation. We summarized the merits and limitations of current methods, as well as the future directions for efficient and accurate extraction of coronary plaques using CT imaging. Conclusion: The methodological innovations are important for more accurate CT-based assessment of coronary plaques in clinical applications. The large-scale studies, de-blooming algorithms, more standardized datasets, and more detailed classification of non-calcified plaques could improve the accuracy of coronary plaque extraction from CT images. More multidimensional geometric parameters can be derived from the 3D geometry of coronary plaques. Additionally, machine learning and automatic 3D reconstruction could improve the efficiency of coronary plaque extraction in future studies. Frontiers Media S.A. 2021-02-10 /pmc/articles/PMC7903898/ /pubmed/33644127 http://dx.doi.org/10.3389/fcvm.2021.597568 Text en Copyright © 2021 Liu, Wingert, Wang, Zhang, Wang, Sun, Chen, Khalid, Jiang and Zheng. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Cardiovascular Medicine
Liu, Haipeng
Wingert, Aleksandra
Wang, Jian'an
Zhang, Jucheng
Wang, Xinhong
Sun, Jianzhong
Chen, Fei
Khalid, Syed Ghufran
Jiang, Jun
Zheng, Dingchang
Extraction of Coronary Atherosclerotic Plaques From Computed Tomography Imaging: A Review of Recent Methods
title Extraction of Coronary Atherosclerotic Plaques From Computed Tomography Imaging: A Review of Recent Methods
title_full Extraction of Coronary Atherosclerotic Plaques From Computed Tomography Imaging: A Review of Recent Methods
title_fullStr Extraction of Coronary Atherosclerotic Plaques From Computed Tomography Imaging: A Review of Recent Methods
title_full_unstemmed Extraction of Coronary Atherosclerotic Plaques From Computed Tomography Imaging: A Review of Recent Methods
title_short Extraction of Coronary Atherosclerotic Plaques From Computed Tomography Imaging: A Review of Recent Methods
title_sort extraction of coronary atherosclerotic plaques from computed tomography imaging: a review of recent methods
topic Cardiovascular Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7903898/
https://www.ncbi.nlm.nih.gov/pubmed/33644127
http://dx.doi.org/10.3389/fcvm.2021.597568
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