Real-time multicenter semantic segmentation for laparoscopic gastrectomy: development, external validation and operating room deployment of an AI navigation system
Ke-Cheng Zhang, Di Wu, Can-Rong Lu, Zhi Qiao, Wen-Tong Xu, Feng-Lin Liu, Jing-Yu Deng, Li Yang, Lei Guo, Tian-Yu Xie · 2026
Read Real-time multicenter semantic segmentation for laparoscopic gastrectomy: development, external validation and operating room deployment of an AI navigation system by Ke-Cheng Zhang, Di Wu, Can-Rong Lu, Zhi Qiao, Wen-Tong Xu, Feng-Lin Liu, Jing-Yu Deng, Li Yang, Lei Guo, Tian-Yu Xie (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13440269.txt.
Description
Ke-Cheng Zhang's team built a real-time AI guide system in 2026 for keyhole stomach removal, where limited sense of the scene breeds errors. Videos from four top centers trained a YOLOv10 model to spot eleven tools and seven organs. Data were split by center for training, internal testing, and external validation, then deployed live in surgery rooms with workload and ease-of-use surveys.
Training accuracy ran high, internal and outside checks held up with moderate precision and recall, and live deployment proved feasible with acceptable surgeon workload and ease of use. Surgical teams get a generalizable vision aid for safer gastrectomy. Broader hospitals, rarer anatomies, and outcome trials will decide clinical value.
Catalog record
| CREATOR | Ke-Cheng Zhang, Di Wu, Can-Rong Lu, Zhi Qiao, Wen-Tong Xu, Feng-Lin Liu, Jing-Yu Deng, Li Yang, Lei Guo, Tian-Yu Xie |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 51 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |