Your Location:
Home >
Browse articles >
Real-time multicenter semantic segmentation for laparoscopic gastrectomy: development, external validation and operating room deployment of an AI navigation system
Real-time multicenter semantic segmentation for laparoscopic gastrectomy: development, external validation and operating room deployment of an AI navigation system
- “A multicenter team developed a real-time AI navigation system for laparoscopic gastrectomy using YOLOv10, which recognizes 18 surgical instruments and organs. The system achieved robust detection across hospitals, operates on standard laptop GPUs with low cognitive burden, and provides on-demand visual overlays without disrupting surgical workflow, laying a foundation for the construction of intelligent surgical assistance systems.”
- Military Medical Research (2026)
DOI: 10.1016/j.mmr.2026.100040
Accepted:13 May 2026
Scan QR Code
AI Introduction
Full Text(HTML)
Figs( 6 ) Tabs( 3 )
References
Publication Info
Metrics
8
Views
4
Downloads
0
CSCD
Alert me when the article has been cited
Submit
Tools
- BibTeXDownload
- EndnoteDownload
- RefMan Download
- NoteExpressDownload
- NoteFirstDownload
Related Articles
Non-invasive evaluation of muscle invasion and survival prognosis in bladder cancer using enhanced CT-based deep learning radiomics: a multi-center real-world cohort study
Enhanced CT-based deep learning radiomics for bladder cancer prognosis
Pathophysiology-guided biomarkers and therapeutics for precision trauma medicine in polytrauma with musculoskeletal injuries
A roadmap for medical large language models: a review of foundations, applications, and challenges
Prioritizing human-AI collaboration in healthcare: the TRIAD framework for trustworthy governance, real-world, and integrated adaptive deployment
Related Author
Yun-Bo He
Jiao Hu
Zhi Liu
Zi-Cheng Xiao
Jin-Hui Liu
Hai-Su Liang
Wen-Zhi Deng
Zhi-Wei Li
Related Institution
Department of Urology, Xiangya Hospital, Central South University
National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University
Department of Urology, the Second Affiliated Hospital, Guizhou Medical University
Department of Pathology, the Third Xiangya Hospital of Central South University
Department of Urology, the Second Hospital of University of South China

