Baozhen Ren
Papers
3
Total Citations
33
H-Index
2
About
Baozhen Ren is a leading researcher at the forefront of vascular interventional surgery (VIS) robotics and autonomous surgical systems. Her primary research areas include robotic catheterization technologies, force-sensing mechanisms for minimally invasive procedures, and deep learning-based image guidance for surgical robots. Ren’s major contributions are highlighted in her highly cited 2023 review, "The Critical Technologies of Vascular Interventional Robotic Catheterization," which has garnered 29 citations and provides a comprehensive analysis of slave robots, master controllers, and key VIS operations such as drug delivery, coil filling, and thrombectomy. This work has become a foundational reference for advancing robotic precision in vascular interventions. In 2024, she introduced a novel "Multi-point bending operation force detection method of catheter-based on rotary clamping delivery," enhancing real-time force feedback during catheterization. Her 2025 review on deep learning-based image guidance, though recent with 1 citation, underscores her forward-looking focus on achieving full surgical autonomy. Ren’s work bridges critical gaps in robotic dexterity and perception, positioning her as a pivotal figure in the evolution of next-generation surgical robotics.
Research Focus
Key Achievements
Top Papers
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