Papers
2
Total Citations
8
H-Index
2
About
Sitong Teng is a researcher at the forefront of robot-assisted cardiovascular interventions, specializing in computer vision and medical image analysis. Their work focuses on enhancing the safety and precision of minimally invasive procedures through advanced guidewire tracking and segmentation techniques. Teng’s major contributions include developing novel frameworks that address the critical challenge of distinguishing guidewire tips from complex curvilinear structures in X-ray images—a task essential for preventing vascular injury during robotic interventions. Their most cited papers, "PixelTopoIS: a pixel-topology-coupled guidewire tip segmentation framework for robot-assisted intervention" and "A Multi-Stage Guidewire Tip Tracking Framework for Cardiovascular Robotic Interventions," each have garnered 4 citations, reflecting their foundational role in this niche field. By integrating pixel-level and topological information, Teng’s work provides a safety-critical mechanism that improves guidewire visibility for interventionalists, directly impacting the reliability of autonomous robotic systems. This research is particularly notable for its potential to reduce procedural risks and enhance outcomes in cardiovascular care, positioning Teng as a key contributor to the evolving landscape of intelligent surgical robotics.
Research Focus
Key Achievements
Top Papers
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