Papers
29
Total Citations
504
H-Index
14
About
Xiaozhi Qi is a prominent researcher at the intersection of medical robotics, surgical planning, and autonomous control systems, with a body of work that has significantly advanced the safety and precision of robot-assisted surgery. His research is particularly focused on spinal and nasal surgical procedures, where he has developed innovative solutions to some of the field's most persistent challenges. Qi's most influential contribution—cited 58 times—introduced an analytical milling force model for intraoperative cutting depth monitoring during robot-assisted laminectomy, directly addressing patient safety concerns in spinal decompression surgery. Building on this foundation, he has pioneered automated path planning methods for pedicle screw placement and laminectomy procedures grounded in preoperative CT imaging, reducing reliance on manual, error-prone planning processes. His work on stability and safety control accounting for respiratory motion and spinal deformation further demonstrates his commitment to clinically realistic robotic systems. Beyond spinal surgery, Qi has made notable contributions to robot-assisted endoscopic nasal surgery, developing collision-aware path planning and autonomous field-of-view control systems. His dual-arm robotic coordination and ultrasound–CT fusion guidance work reflect a broader versatility across surgical robotics. Collectively, his papers have accumulated over 300 citations, establishing him as an impactful voice in intelligent surgical robotics research.
Research Focus
Key Achievements
Top Papers
- 1
- 2Robot-Assisted Decompressive Laminectomy Planning Based on 3D Medical Image45 citations · 2018
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- 6Endoscopic Path Planning in Robot-Assisted Endoscopic Nasal Surgery27 citations · 2020
- 7Robotic Needle Insertion With 2D Ultrasound–3D CT Fusion Guidance25 citations · 2023
- 8Automatic Surgical Field of View Control in Robot-Assisted Nasal Surgery25 citations · 2020
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