Yanheng Li
Papers
1
Total Citations
5
H-Index
1
About
Yanheng Li is an emerging researcher at the intersection of medical imaging, computer vision, and deep learning, with a particular focus on advancing capsule endoscopy technology through intelligent computational methods. His most notable work, "V²-SfMLearner," published in 2025, tackles one of the field's most challenging problems: accurately predicting depth maps and ego-motion from monocular capsule endoscopy videos despite the inherent vibration perturbations caused by capsule collisions within the gastrointestinal tract. This contribution is significant because reliable 3D scene reconstruction and lesion localization within the GI tract have long been constrained by noisy, multimodal imaging conditions that confound standard self-supervised learning approaches. By developing a robust framework capable of handling these real-world perturbations, Li's research pushes the boundaries of what autonomous capsule systems can achieve clinically. Though early in his career with 5 citations to date, his work addresses a genuinely underexplored challenge that bridges wireless sensing, endoscopic vision, and patient diagnostics — positioning him as a promising contributor to the next generation of non-invasive medical imaging and computer-assisted diagnosis research.
Research Focus
Key Achievements
Top Papers
- 1