Papers
4
Total Citations
60
H-Index
3
About
YingLiang Ma is a leading researcher at the intersection of medical robotics and interventional imaging, whose work is fundamentally advancing robot-assisted surgery. His primary research areas include real-time catheter segmentation, multi-modal image guidance (particularly hybrid echo and X-ray), and automatic tool detection for minimally invasive procedures. Ma’s most impactful contribution is his pioneering work on end-to-end real-time catheter segmentation using optical flow-guided warping during endovascular intervention (2020, 35 citations), which addresses a critical bottleneck in robot-assisted endovascular procedures by enabling accurate, real-time tracking without reliance on synthetic data. He also demonstrated the feasibility of hybrid echo and X-ray image guidance for cardiac catheterization using a self-tracked robotic arm with haptic feedback (2010, 16 citations), a foundational study that opened new pathways for safer, image-guided interventions. His earlier evaluation of robotic arm-based 3D echo to X-ray registration (2009, 6 citations) laid crucial groundwork for multi-modal fusion in cardiac procedures. Additionally, Ma’s work on automatic tool detection in X-ray images for robotic-assisted joint fracture surgery (2017) addresses a key step in establishing coordinate system links for trauma surgery. With cumulative citations exceeding 60, Ma’s research continues to shape the future of intelligent, image-guided surgical robotics.
Research Focus
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