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Publication Name Artificial Intelligence in Medical Imaging
Manuscript ID 56556
Country/Territory China
Received
2020-05-07 10:34
Peer-Review Started
2020-05-07 10:35
To Make the First Decision
Return for Revision
2020-06-04 04:16
Revised
2020-06-12 05:20
Second Decision
2020-06-16 09:33
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief
2020-06-16 22:52
Articles in Press
2020-06-16 22:52
Publication Fee Transferred
Edit the Manuscript by Language Editor
2020-06-23 03:13
Typeset the Manuscript
2020-07-09 06:16
Publish the Manuscript Online
2020-07-10 05:53
ISSN 2644-3260 (online)
Open Access This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Copyright © The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved.
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Publisher Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
Website http://www.wjgnet.com
Category Cardiac & Cardiovascular Systems
Manuscript Type Minireviews
Article Title Machine learning for diagnosis of coronary artery disease in computed tomography angiography: A survey
Manuscript Source Invited Manuscript
All Author List Feng-Jun Zhao, Si-Qi Fan, Jing-Fang Ren, Karen M von Deneen, Xiao-Wei He and Xue-Li Chen
ORCID
Author(s) ORCID Number
Feng-Jun Zhao http://orcid.org/0000-0001-8658-8412
Si-Qi Fan http://orcid.org/0000-0002-8805-7962
Jing-Fang Ren http://orcid.org/0000-0002-8070-1282
Karen M von Deneen http://orcid.org/0000-0002-5310-1003
Xiao-Wei He http://orcid.org/0000-0003-2126-178X
Xue-Li Chen http://orcid.org/0000-0002-3898-9892
Funding Agency and Grant Number
Funding Agency Grant Number
National Natural Science Foundation of China 61971350
National Natural Science Foundation of China 81627807
National Natural Science Foundation of China 11727813
National Key R&D Program of China 2016YFC1300300
China Postdoctoral Science Foundation 2019M653717
Fok Ying Tung Education Foundation 161104
Program for the Young Top-notch Talent of Shaanxi Province
Corresponding Author Xue-Li Chen, PhD, Professor, Engineering Research Center of Molecular and Neuro Imaging, Ministry of Education, School of Life Science and Technology, Xidian University, 266 Xinglong Section of Xifeng Road, Xi’an 710126, Shaanxi Province, China. xlchen@xidian.edu.cn
Key Words Machine learning; Deep learning; Coronary artery disease; Atherosclerotic plaque; Vulnerability; Stenosis
Core Tip There are reviews that contributed to the segmentation of the coronary artery, detection of calcified plaques, and calculation of fractional flow reserve. To the best of our knowledge, this is the first paper to report a survey of the machine learning (ML) algorithms for the diagnosis of coronary artery disease in computed tomography angiography images, including extraction of coronary arteries, detection of calcified, soft and mixed plaques, identification of plaque vulnerability features including low density plaque, positive remodeling, spot calcification and napkin ring sign, assessment of both anatomically and hemodynamically significant stenosis, and the challenges and perspectives of these ML-based analysis methods.
Publish Date 2020-07-10 05:53
Citation Zhao FJ, Fan SQ, Ren JF, von Deneen KM, He XW, Chen XL. Machine learning for diagnosis of coronary artery disease in computed tomography angiography: A survey. Artif Intell Med Imaging 2020; 1(1): 31-39
URL https://www.wjgnet.com/2644-3260/full/v1/i1/31.htm
DOI https://dx.doi.org/10.35711/aimi.v1.i1.31
Full Article (PDF) AIMI-1-31.pdf
Full Article (Word) AIMI-1-31.docx
Manuscript File 56556-Review-Filipodia.docx
Answering Reviewers 56556-Answering reviewers.pdf
Audio Core Tip 56556-Audio core tip.m4a
Conflict-of-Interest Disclosure Form 56556-Conflict-of-interest statement.pdf
Copyright License Agreement 56556-Copyright license agreement.pdf
Approved Grant Application Form(s) or Funding Agency Copy of any Approval Document(s) 56556-Grant application form(s).pdf
Non-Native Speakers of English Editing Certificate 56556-Language certificate.pdf
Peer-review Report 56556-Peer-review(s).pdf
Scientific Misconduct Check 56556-Scientific misconduct check.pdf
Scientific Editor Work List 56556-Scientific editor work list.pdf