Publication Name	World Journal of Gastroenterology
Manuscript ID	121592
DOI	10.3748/wjg.121592
Country	China

Category	Surgery
Manuscript Type	Retrospective Study
Article Title	Deep-learning-based object detection of pelvic autonomic nerves during total mesorectal excision
Manuscript Source	Unsolicited Manuscript
All Author List	Qiao Zhang, Jin Li, Tao Meng, Zhi-Fen Chen, Xue-Zhi Zhou and Xing-Rong Lu
Funding Agency and Grant Number	Funding Agency Grant Number The Natural Science Foundation of Fujian Province No. 2022J01726 The Natural Science Foundation of Fujian Province No. 2023J01122895
Corresponding Author	Xing-Rong Lu, Chief Physician, MD, Professor, Department of Colorectal Surgery, Fujian Medical University Union Hospital, No. 29 Xinquan Road, Fuzhou 350001, Fujian Province, China. lynxlxr18@163.com
Key Words	Rectal cancer; Total mesorectal excision; Pelvic autonomic nerve; Deep learning; Object detection
Core Tip	In this study, a deep learning model was developed to recognize five categories of pelvic autonomic nerves during total mesorectal excision. The model was trained, validated and tested on surgical video images, and its performance was compared with surgeons at different levels. The model achieved precision and speed comparable to senior surgeons, with consistent pathological confirmation of all 7 sampled nerve specimens. Ultimately, this model was confirmed to be reliable and may assist nerve preservation and shorten the learning curve for junior surgeons.
Citation	Zhang Q, Li J, Meng T, Chen Z, Zhou X, Lu X. Deep-learning-based object detection of pelvic autonomic nerves During Total Mesorectal Excision: an experimental pilot study. World J Gastroenterol 2026; In press DOI: https://doi.org/10.3748/wjg.121592

Received	2026-03-30 06:17
Peer-Review Started	2026-03-30 06:21
First Decision by Editorial Office Director	2026-04-08 09:21
Return for Revision	2026-04-08 09:21
Revised	2026-04-22 09:57
Publication Fee Transferred	2026-04-29 02:29
Second Decision by Editor	2026-06-03 02:34
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director	2026-06-03 08:38
Articles in Press	2026-06-03 08:38
Edit the Manuscript by Language Editor
Typeset the Manuscript

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.
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