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Articles Published Processes
7/23/2026 6:25:03 AM | Browse: 2 | Download: 0
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Received |
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2026-03-30 06:17 |
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Peer-Review Started |
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2026-03-30 06:21 |
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First Decision by Editorial Office Director |
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2026-04-08 09:21 |
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Return for Revision |
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2026-04-08 09:21 |
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Revised |
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2026-04-22 09:57 |
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Publication Fee Transferred |
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2026-04-29 02:29 |
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Second Decision by Editor |
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2026-06-03 02:34 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2026-06-03 08:38 |
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Articles in Press |
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2026-06-03 08:38 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2026-07-20 06:34 |
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Publish the Manuscript Online |
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2026-07-23 06:25 |
| 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 |
Surgery |
| Manuscript Type |
Retrospective Study |
| Article Title |
Deep-learning-based object detection of pelvic autonomic nerves during total mesorectal excision
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Qiao Zhang, Jin Li, Tao Meng, Zhi-Fen Chen, Xue-Zhi Zhou and Xing-Rong Lu |
| ORCID |
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| 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 |
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| 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. |
| Publish Date |
2026-07-23 06:25 |
| Citation |
Zhang Q, Li J, Meng T, Chen ZF, Zhou XZ, Lu XR. Deep-learning-based object detection of pelvic autonomic nerves during total mesorectal excision. World J Gastroenterol 2026; 32(30): 121592
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| URL |
https://www.wjgnet.com/1007-9327/full/v32/i30/121592.htm |
| DOI |
https://doi.org/10.3748/wjg.121592 |
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