Artificial intelligence-driven three-dimensional modeling of biliary strictures using magnetic resonance cholangiopancreatography for quantitative assessment and stent planning

doi:10.3748/wjg.125661

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World Journal of Gastroenterology

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1007-9327

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Observational Study

Copyright: ©Author(s) 2027. 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.

World J Gastroenterol. Jan 14, 2027; 33(2): 125661
Published online Jan 14, 2027. doi: 10.3748/wjg.125661

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Figure 3 Representative morphology-restoration examples. A: Original stenotic duct geometry; B: Restored target segment and localization box overlaid on the biliary tree. Arrows explicitly indicate the restored ductal segment and the corresponding ground-truth bounding-box region. The two rows show different representative examples.

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
URL: https://www.wjgnet.com/1007-9327/full/v33/i2/125661.htm
DOI: https://dx.doi.org/10.3748/wjg.125661

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 [DOI: 10.3748/wjg.125661]

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