Xinbing Xu

Papers

Total Citations

H-Index

About

Xinbing Xu is a researcher at the forefront of medical robotics and computer vision, with a primary focus on developing intelligent systems for automated clinical sampling. His most notable contribution is the pioneering work on "Image Segmentation of Throat Swab Sampling Based on Mask R-CNN" (2020), which addresses a critical bottleneck in robotic-assisted diagnostics. By applying the robust instance segmentation algorithm Mask R-CNN, Xu provided the first feasibility basis for enabling automatic throat swab robots to accurately identify and segment target areas within the complex oral environment. This work directly tackles the challenge of data insufficiency in medical imaging, employing advanced data augmentation techniques to enhance model robustness. While his citation count (3) reflects the niche and emerging nature of this field, the impact is significant: his research lays the essential groundwork for reducing healthcare worker exposure to infectious diseases and improving sampling consistency. Xu's work represents a vital step toward fully autonomous, AI-driven diagnostic systems, bridging the gap between computer vision and practical clinical robotics.