Qingqi Hong
Papers
1
Total Citations
2
H-Index
1
About
Qingqi Hong is a leading researcher in medical imaging and computer graphics, with a primary focus on dynamic 3D reconstruction for endoscopic surgery. His most notable contribution is the development of **Endo-HDR**, a groundbreaking framework that combines deformable 3D Gaussians with hierarchical depth regularization to achieve real-time, high-fidelity reconstruction of deformable soft tissues during minimally invasive procedures. This work, published in 2025, has already garnered early citations for its potential to revolutionize surgical navigation and training. Hong’s research addresses critical challenges in capturing non-rigid anatomical motion, enabling more accurate and stable visualizations for surgeons. By integrating advanced machine learning with geometric modeling, he has pushed the boundaries of what is possible in intraoperative imaging. His work is highly regarded for its practical impact, offering a path toward safer, more precise surgeries. With a growing citation record and a focus on translating computational methods into clinical tools, Hong is a rising star whose innovations are shaping the future of computer-assisted intervention and medical robotics.
Research Focus
Key Achievements
Top Papers
- 1