Publication Name	Artificial Intelligence in Gastrointestinal Endoscopy
Manuscript ID	121644
DOI	10.37126/aige.121644
Country	India

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
Manuscript Source	Invited Manuscript
All Author List	Priya Hazrah, Varun Singh Rautela, Vishal Sharma, Sonali Mittal, Ravi Raj Madan and Deborshi Sharma
Funding Agency and Grant Number
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.
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; In press DOI: https://doi.org/10.37126/aige.121644
PDF	121644-in-press.pdf

Received	2026-04-01 06:29
Peer-Review Started	2026-04-01 06:29
First Decision by Editorial Office Director	2026-04-29 09:05
Return for Revision	2026-05-01 12:06
Revised	2026-05-19 18:12
Publication Fee Transferred
Second Decision by Editor	2026-06-15 02:42
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director	2026-06-15 08:39
Articles in Press	2026-06-15 08:39
Edit the Manuscript by Language Editor
Typeset the Manuscript

ISSN	2689-7164 (online)
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