Intelligent laparoscopic grasper with hybrid neural networks for real-time vascular detection in minimally invasive surgery
The FBG sensor-integrated laparoscopic grasper, assisted by the processing of the CNN-LSTM algorithm, demonstrated the ability to identify vessels <i>ex vivo</i> across different models. This technology holds potential for real-time and accurate vessel identification during MIS, which could significantly reduce the occurrence of unnecessary vessel injuries.
Authors
- Wang Zheng-ying
- Ziying Huang
- Zhengyong Liu (ORCID: https://orcid.org/0000-0002-0737-1782)
- Yuanyuan Wu (ORCID: https://orcid.org/0000-0001-6231-2315)
- Yuxin Huang (ORCID: https://orcid.org/0009-0009-4167-1226)
- Dongxian Peng
- Kaichao Chen (ORCID: https://orcid.org/0000-0001-6923-4233)
- Chang Liu (ORCID: https://orcid.org/0000-0002-1232-8308)
- Pingping Wang (ORCID: https://orcid.org/0000-0001-8888-8005)
- Yuting Huang (ORCID: https://orcid.org/0000-0003-1273-4469)
Institutions
- Sun Yat-sen University (CN)
- Zhujiang Hospital (CN)
- Southern Medical University (CN)
Publication Details
- Journal
- Journal of Biomedical Optics
- Published
- 2025-09-16
- DOI
- https://doi.org/10.1117/1.jbo.30.9.097001
- Primary Topic
- Surgical Simulation and Training
- Type
- article
- Field-Weighted Citation Impact
- 0.00