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Articles Published Processes
9/4/2026 2:12:31 AM | Browse: 0 | Download: 0
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Received |
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2026-04-01 06:29 |
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Peer-Review Started |
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2026-04-01 06:29 |
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First Decision by Editorial Office Director |
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2026-04-29 09:05 |
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Return for Revision |
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2026-05-01 12:06 |
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Revised |
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2026-05-19 18:12 |
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Publication Fee Transferred |
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Second Decision by Editor |
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2026-06-15 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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2026-06-15 08:39 |
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Articles in Press |
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2026-06-15 08:39 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2026-09-03 00:14 |
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Publish the Manuscript Online |
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2026-09-04 02:12 |
| ISSN |
2689-7164 (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 |
Surgery |
| Manuscript Type |
Minireviews |
| Article Title |
Improving precision of laparoscopic cholecystectomy: A review on the role of newer intraoperative imaging aids and artificial intelligence
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Priya Hazrah, Varun Singh Rautela, Vishal Sharma, Sonali Mittal, Ravi Raj Madan and Deborshi Sharma |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Priya Hazrah, Professor, Department of Surgery, Lady Hardinge Medical College, Shaheed Bhagat Singh Marg, New Delhi 110001, Delhi, India. priya.hazrah39@lhmc-hosp.gov.in |
| Key Words |
Laparoscopic cholecystectomy; Indocyanine green near infrared cholangiography; Yellow enhancement; Artificial intelligence; Critical view of safety; R4U line; Culture of safety cholecystectomy; Anatomic segmentation; Semantic segmentation; Instance segmentation; Go/No-Go zones |
| Core Tip |
Endovision technology coupled with multispectral imaging, such as indocyanine green near infra-red, yellow enhancement, and artificial intelligence (AI), has potential to improve the precision of laparoscopic cholecystectomy by enhancing tissue differentiation. AI architectures can predict difficult cholecystectomy, assess surgical workflow, achieve anatomic segmentation, identify safe dissection zones, and assist in coaching/training. By leveraging multispectral imaging along with advanced AI architecture-convolutional neural networks for segmentation, graph neural networks for relational anatomical mapping, and transformers for temporal workflow analytics-surgical platforms can achieve context-aware surgery, ultimately bridging the gap between intraoperative imaging and enhanced patient safety through automated surgical coaching and decision support. |
| Publish Date |
2026-09-04 02:12 |
| Citation |
Hazrah P, Rautela VS, Sharma V, Mittal S, Madan RR, Sharma D. Improving precision of laparoscopic cholecystectomy: A review on the role of newer intraoperative imaging aids and artificial intelligence. Artif Intell Gastrointest Endosc 2026; 7(2): 121644
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| URL |
https://www.wjgnet.com/2689-7164/full/v7/i2/121644.htm |
| DOI |
https://doi.org/10.37126/aige.121644 |
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.
