Papers

2

Total Citations

28

H-Index

2

About

Lei Zang is a pioneering researcher at the forefront of robotic-assisted spinal surgery, with a primary focus on enhancing precision and safety in minimally invasive procedures. His major contributions lie in the design and development of intelligent surgical systems, particularly for transforaminal percutaneous endoscopic lumbar surgeries (PELS). Zang’s seminal 2020 study protocol, which has garnered 25 citations, addresses critical challenges in PELS—such as nerve and blood vessel injuries and excessive radiation exposure—by introducing a novel robot-assisted system that improves working channel establishment and foraminoplasty. Building on this, his recent 2024 work (3 citations) advances the field by developing a software system for surgical robots based on multimodal image fusion. This innovation overcomes the limitations of unimodal CT imaging, which only visualizes vertebral bone structures, by integrating multiple imaging modalities to provide richer anatomical context. Zang’s research is notable for directly tackling real-world clinical problems, aiming to reduce complications and radiation while boosting surgical accuracy. His work is essential reading for students and researchers interested in the intersection of robotics, image-guided surgery, and orthopedics, marking him as a key innovator in next-generation spinal care.

Research Focus

Key Achievements

2
H-Index
2
Papers
28
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
Design of a robot-assisted system for transforaminal percutaneous endoscopic lumbar surgeries: study protocol
25 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: Beijing Academy of Artificial Intelligence, Capital Medical University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago