Mengchen Xue
Papers
1
Total Citations
3
H-Index
1
About
Mengchen Xue is a researcher specializing in computer vision and medical robotics, with a particular focus on surgical instrument segmentation and intelligent robotic systems. Their most cited work, "Surgical instrument segmentation method based on improved MobileNetV2 network" (2021), addresses a critical challenge in automated surgery: enabling robots to visually identify, classify, and manage surgical instruments in real time. By enhancing the lightweight MobileNetV2 architecture, Xue developed a segmentation framework that balances accuracy with computational efficiency—essential for deployment in time-sensitive surgical environments. This contribution directly supports the core technology of instrument robots, improving their ability to deliver and organize tools during procedures. With 3 citations, this work has laid a foundation for further advances in robotic-assisted surgery, where precise visual analysis is key to safety and automation. Xue’s research bridges deep learning and medical robotics, offering practical solutions for next-generation operating rooms. Their work is particularly relevant for students and engineers interested in applying efficient neural networks to real-world healthcare challenges, demonstrating how lightweight models can drive innovation in surgical automation.
Research Focus
Key Achievements
Top Papers
- 1