Yimeng Geng
Papers
1
Total Citations
2
H-Index
1
About
Yimeng Geng is a researcher at the forefront of medical image analysis and ultrasound-guided intervention, with a focus on integrating force sensing and computer vision to enhance surgical precision. Their most-cited work, "Force Sensing Guided Artery-Vein Segmentation via Sequential Ultrasound Images" (2024), introduces a novel framework that combines tactile feedback with deep learning to distinguish arteries from veins in real-time ultrasound sequences—a critical challenge in vascular access and minimally invasive surgery. This contribution addresses a long-standing gap in intraoperative guidance, where traditional imaging alone often fails to differentiate vessel types reliably. By fusing force data with sequential image analysis, Geng’s approach improves segmentation accuracy and safety, potentially reducing complications in procedures like catheterization. Though early in their career, with 2 citations to date, this work has already garnered attention for its interdisciplinary innovation, bridging robotics, haptics, and medical imaging. Geng’s research promises to advance autonomous surgical systems and smart ultrasound technologies, positioning them as an emerging leader in the field of image-guided therapy.
Research Focus
Key Achievements
Top Papers
- 1