Fan Peng

Capital University, Capital Medical University

Papers

Total Citations

H-Index

About

Fan Peng is a leading researcher in the field of computer-assisted orthopedic surgery, with a primary focus on improving the safety and precision of spinal procedures. His work centers on the critical challenge of pedicle screw path planning, a key step in robot-assisted spinal surgery that, if done incorrectly, can lead to serious complications. Peng’s major contributions include developing novel algorithms for automatic vertebral posture estimation and multi-directional projection-based planning, which enhance the accuracy of screw trajectory determination. His most cited paper, "Improving pedicle screw path planning by vertebral posture estimation" (2023), has already garnered 9 citations, demonstrating its immediate impact on the field. This work, along with his earlier study on optimal path planning from multi-directional projections (2021), addresses the core limitations of current robotic systems by reducing the need for manual planning and minimizing the risk of surgical errors. Peng’s research is pivotal in advancing the next generation of autonomous surgical robotics, promising to reduce hospital readmissions and improve patient outcomes in spinal fusion and deformity correction surgeries.