Papers
6
Total Citations
422
H-Index
6
About
Xiaofei Du is a leading researcher in surgical vision and computer-assisted interventions, with a focus on deep learning for instrument detection, pose estimation, and tracking in minimally invasive and robotic-assisted surgery. Her most cited work, "Articulated Multi-Instrument 2-D Pose Estimation Using Fully Convolutional Networks" (136 citations), pioneered the use of fully convolutional networks to tackle the challenging problem of articulation detection in surgical videos. She further advanced this field with "Deep Learning Based Robotic Tool Detection and Articulation Estimation With Spatio-Temporal Layers" (115 citations), introducing spatio-temporal layers to improve robustness against varying illumination and background clutter. Du also contributed foundational work in "Combined 2D and 3D tracking of surgical instruments for minimally invasive and robotic-assisted surgery" (62 citations), demonstrating vision-based solutions that minimize hardware dependency. Her comparative evaluation of instrument segmentation and tracking methods (50 citations) has become a key reference for benchmarking in the field. With over 420 total citations, Du’s research directly enables safer, more precise computer-assisted surgeries.
Research Focus
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Top Papers
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