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Articles Published Processes
11/11/2026 5:49:19 AM | Browse: 0 | Download: 0
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Received |
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2026-07-14 02:40 |
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Peer-Review Started |
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2026-07-14 02:41 |
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First Decision by Editorial Office Director |
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Return for Revision |
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2026-07-27 06:29 |
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Revised |
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2026-08-05 12:33 |
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Publication Fee Transferred |
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2026-08-19 10:04 |
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Second Decision by Editor |
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2026-09-17 02:42 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2026-09-17 09:30 |
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Articles in Press |
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2026-09-17 09:30 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2026-09-28 07:02 |
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Publish the Manuscript Online |
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2026-11-11 05:49 |
| ISSN |
1007-9327 (print) and 2219-2840 (online) |
| Open Access |
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc. |
| Copyright |
©Author(s) (or their employer(s)) 2026. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc. |
| 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 |
Observational Study |
| Article Title |
Artificial intelligence-driven three-dimensional modeling of biliary strictures using magnetic resonance cholangiopancreatography for quantitative assessment and stent planning
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Ji-Hun Chun, Jin-Woo Hong, Jong-Uk Hou, Kyong Joo Lee, Da Hae Park, Hye Won Cha, Se Woo Park, Seon Jeong Min and Wooyoung Yu |
| ORCID |
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| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| the National Research Foundation of Korea (NRF) grant funded by the Korean Government (Ministry of Science and ICT, MSIT) |
No. RS-2026-25477876 |
| the Hallym University Medical Center Research Fund (Mighty Hallym 4.0) |
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| Corresponding Author |
Se Woo Park, MD, PhD, Professor, Division of Gastroenterology, Department of Internal Medicine, Hallym University Dongtan Sacred Heart Hospital, Hallym University College of Medicine, 7 Keunjaebong-gil, Hwaseong 18450, South Korea. britnepak@hallym.or.kr |
| Key Words |
Biliary stricture; Magnetic resonance cholangiopancreatography; Artificial intelligence; Three-dimensional reconstruction; Stent planning |
| Core Tip |
This proof-of-concept study shows that magnetic resonance cholangiopancreatography-derived biliary anatomy can be transformed by an integrated artificial-intelligence workflow into a quantitative three-dimensional model of biliary strictures. By combining region-of-interest localization, transformer-based segmentation, projection-based multi-view classification, synthetic morphology restoration, and centerline-guided mesh generation, the pipeline reframes biliary stricture analysis from qualitative image review toward reproducible structural modeling and candidate stent-planning geometry. Binary stricture detection was highly accurate internally, whereas reconstruction of complex hilar or intrahepatic anatomy remained challenging and requires external validation before clinical use. |
| Publish Date |
2026-11-11 05:49 |
| Citation |
Chun JH, Hong JW, Hou JU, Lee KJ, Park DH, Cha HW, Park SW, Min SJ, Yu W. Artificial intelligence-driven three-dimensional modeling of biliary strictures using magnetic resonance cholangiopancreatography for quantitative assessment and stent planning. World J Gastroenterol 2027; 33(2): 125661
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| URL |
https://www.wjgnet.com/1007-9327/full/v33/i2/125661.htm |
| DOI |
https://doi.org/10.3748/wjg.125661 |
Copyright © 1993-2026 Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA. All rights reserved, including rights relating to text and data mining, AI training, and similar technologies. For open-access content, the applicable copyright and licensing terms govern.
