Luyi Han
Papers
1
Total Citations
6
H-Index
1
About
Luyi Han is a researcher at the intersection of medical imaging, computer vision, and computational anatomy, with a primary focus on developing intelligent, non-invasive tools for surgical guidance. Her most-cited work introduces a Bayesian shape framework for localizing the recurrent laryngeal nerve via ultrasound—a critical structure in thyroid and neck surgeries. By integrating probabilistic shape models with ultrasound imaging, Han’s approach offers a safer, radiation-free alternative to traditional nerve identification, directly addressing a key challenge in reducing iatrogenic nerve injury. Though early in her career, this 2022 paper has already garnered 6 citations, signaling its growing influence in the field of image-guided interventions. Han’s contributions exemplify how machine learning and anatomical priors can be harnessed to enhance surgical precision and patient safety. Her work stands out for its translational potential, bridging the gap between computational methods and real-world clinical needs. As she continues to advance her research, Luyi Han is poised to make lasting impacts on intraoperative imaging and minimally invasive surgery.
Research Focus
Key Achievements
Top Papers
- 1