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10/27/2021 7:25:49 AM | Browse: 260 | Download: 433
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Received |
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2021-02-06 17:28 |
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Peer-Review Started |
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2021-02-06 17:31 |
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To Make the First Decision |
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Return for Revision |
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2021-03-29 00:12 |
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Revised |
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2021-04-16 16:25 |
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Second Decision |
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2021-09-30 04:22 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Company Editor-in-Chief |
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2021-09-30 07:55 |
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Articles in Press |
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2021-09-30 07:55 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2021-10-25 00:27 |
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Publish the Manuscript Online |
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2021-10-27 07:14 |
| ISSN |
1007-9327 (print) and 2219-2840 (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) 2021. Published by Baishideng Publishing Group Inc. All rights reserved. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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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 |
Gastroenterology & Hepatology |
| Manuscript Type |
Minireviews |
| Article Title |
Emerging artificial intelligence applications in liver magnetic resonance imaging
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Charles E Hill, Luca Biasiolli, Matthew D Robson, Vicente Grau and Michael Pavlides |
| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| the Engineering and Physical Sciences Research Council and Medical Research Council |
EP/L016052/1 |
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| Corresponding Author |
Michael Pavlides, BSc, DPhil, MBBS, MRCP, Consultant Physician-Scientist, Doctor, Oxford Centre for Clinical Magnetic Resonance Research, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Level 0, John Radcliffe Hospital, Headley Way, Headington, Oxford OX3 9DU, United Kingdom. michael.pavlides@cardiov.ox.ac.uk |
| Key Words |
Liver diseases; Magnetic resonance imaging; Machine learning; Deep learning; Artificial intelligence; Computer vision |
| Core Tip |
Artificial Intelligence (AI) algorithms are becoming increasingly prevalent in magnetic resonance imaging (MRI) after their proven success in computer vision tasks. With regards to liver MRI, these methods have been shown to be successful in tasks from hepatocellular carcinoma detection, to motion reduction to improve undiagnostic scans. They have also been shown in some cases to outperform radiographer level performance. The widespread use of these techniques could positively aid clinicians for years to come, if implemented properly into clinical workflows. |
| Publish Date |
2021-10-27 07:14 |
| Citation |
Hill CE, Biasiolli L, Robson MD, Grau V, Pavlides M. Emerging artificial intelligence applications in liver magnetic resonance imaging. World J Gastroenterol 2021; 27(40): 6825-6843 |
| URL |
https://www.wjgnet.com/1007-9327/full/v27/i40/6825.htm |
| DOI |
https://dx.doi.org/10.3748/wjg.v27.i40.6825 |
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