Chunyang Xu
Papers
3
Total Citations
5
H-Index
1
About
Chunyang Xu is a rising leader in the field of computer-assisted spine surgery, with a focused research program at the intersection of artificial intelligence, robotics, and minimally invasive spinal techniques. His primary contributions center on improving the accuracy and safety of pedicle screw placement—a critical component of spinal fusion procedures. Xu’s most impactful work involves the development and validation of a three-dimensional U-Net algorithm for automated pedicle screw planning, trained on over 1,200 cases from public datasets and Beijing Tongren Hospital. This pioneering study, which has already garnered 3 citations since its 2025 publication, demonstrates the feasibility of deep learning to streamline surgical planning. Additionally, Xu has conducted comparative analyses of robot-assisted versus conventional free-hand techniques, and has identified key risk factors for screw deviation in robot-assisted minimally invasive transforaminal lumbar interbody fusion (MIS-TLIF). By systematically evaluating clinical outcomes and surgical precision, his research provides actionable insights for optimizing robotic workflows and reducing complication rates—work that is shaping the next generation of evidence-based, technology-driven spine surgery.
Research Focus
Key Achievements
Top Papers
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