Papers
2
Total Citations
15
H-Index
2
About
Siru Feng is an emerging researcher in the field of orthopedic biomechanics and computer-assisted surgical planning. Their work focuses on developing automated, image-guided solutions to improve the precision and efficiency of complex surgical procedures, particularly in pelvic fracture fixation. A key contribution is the introduction of a novel arc screw design for pelvic fracture internal fixation, supported by computer-aided automatic planning and biomechanical analysis—a study that has garnered 13 citations and demonstrates a clear impact on surgical technique innovation. Feng also addresses a critical bottleneck in robotic-assisted surgery: the laborious, manual preoperative registration process. By proposing a simplified KiU-Net deep learning model for automated segmentation of passive marker spheres in CT images, their work reduces the need for surgeon intervention and enhances registration accuracy. This contribution, though early in its citation history (2 citations), tackles a practical challenge in surgical robotics. Feng’s research sits at the intersection of medical imaging, biomechanics, and artificial intelligence, with a clear trajectory toward making minimally invasive orthopedic surgeries safer, faster, and more reproducible. Their work holds promise for advancing both surgical planning tools and intraoperative automation.
Research Focus
Key Achievements
Top Papers
- 1
- 2