Guanlin Yi
Papers
6
Total Citations
49
H-Index
4
About
Guanlin Yi is at the forefront of advancing robot-assisted vascular interventional surgery, a field critical for treating cardiovascular diseases with greater precision and safety. His research centers on developing intelligent systems for teleoperated catheterization, with key contributions in motion recognition, tool segmentation, and error compensation. Yi’s most cited work, “Design and Evaluation of a Learning-Based Vascular Interventional Surgery Robot” (2022, 15 citations), establishes a framework for precise intravascular tool navigation, directly addressing the limitations of manual surgery. He further innovated with neural-based models for position error compensation in robotic catheter systems (2022, 13 citations), enhancing patient safety during complex procedures. His 2023 study on interventionalist hand motion recognition using convolutional neural networks (10 citations) provides a novel approach to training and evaluating cardiology fellows, reducing reliance on expert supervision. Yi’s recent in vivo work on guidewire endpoint detection (2024, 6 citations) tackles the challenge of low-signal X-ray imaging, while his analysis of surgeon-robot cooperative performance (2024) highlights his commitment to optimizing human-robot collaboration. With a growing citation impact, Yi is shaping the next generation of safer, more effective robotic interventions.
Research Focus
Key Achievements
Top Papers
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