A Siamese network with edge-enhanced attention tracks guidewire tips in DSA video at 57 FPS, with 0.421 mm mean error on three test sequences and 0.148-0.708 mm error on two robotic tasks.
VascularPilot3D: Toward a 3D fully autonomous navigation for endovascular robotics
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abstract
This research reports VascularPilot3D, the first 3D fully autonomous endovascular robot navigation system. As an exploration toward autonomous guidewire navigation, VascularPilot3D is developed as a complete navigation system based on intra-operative imaging systems (fluoroscopic X-ray in this study) and typical endovascular robots. VascularPilot3D adopts previously researched fast 3D-2D vessel registration algorithms and guidewire segmentation methods as its perception modules. We additionally propose three modules: a topology-constrained 2D-3D instrument end-point lifting method, a tree-based fast path planning algorithm, and a prior-free endovascular navigation strategy. VascularPilot3D is compatible with most mainstream endovascular robots. Ex-vivo experiments validate that VascularPilot3D achieves 100% success rate among 25 trials. It reduces the human surgeon's overall control loops by 18.38%. VascularPilot3D is promising for general clinical autonomous endovascular navigations.
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Real-Time Guidewire Tip Tracking Using a Siamese Network for Image-Guided Endovascular Procedures
A Siamese network with edge-enhanced attention tracks guidewire tips in DSA video at 57 FPS, with 0.421 mm mean error on three test sequences and 0.148-0.708 mm error on two robotic tasks.