Max Robotics — Global Service Robot Directory + US Certification

About

Runze Han is a biomedical engineer and computational researcher specializing in image-guided robotic surgery, surgical planning automation, and intraoperative navigation across orthopedic and neurosurgical domains. His most influential work, garnering 41 citations, introduced an atlas-based algorithm for automatic pedicle screw planning in spinal surgery, leveraging statistical shape models and active shape model registration to enable precise, reproducible trajectory planning without manual segmentation. This contribution has meaningfully advanced robot-assisted spine surgery workflows. Han has also made significant strides in neurosurgical guidance, developing real-time 3D endoscopic reconstruction using SLAM technology to compensate for soft-tissue deformation during transventricular deep-brain procedures—work that addresses a longstanding limitation of conventional neuronavigation. His research extends into orthopedic trauma, where he has pioneered fluoroscopically guided robotic systems for pelvic fracture fixation and k-wire placement, minimizing repeated radiation exposure during surgery. Additional contributions include statistical shape modeling for ankle syndesmosis reduction and robot-assisted ventriculoscopy for deep-brain stimulation electrode placement. Collectively accumulating over 80 citations, Han's body of work bridges advanced computational methods with clinical surgical robotics, positioning him as an emerging voice in precision-guided minimally invasive surgery.