English

Automating Catheterization Labs with Real-Time Perception

Computer Vision and Pattern Recognition 2024-03-12 v1

Abstract

For decades, three-dimensional C-arm Cone-Beam Computed Tomography (CBCT) imaging system has been a critical component for complex vascular and nonvascular interventional procedures. While it can significantly improve multiplanar soft tissue imaging and provide pre-treatment target lesion roadmapping and guidance, the traditional workflow can be cumbersome and time-consuming, especially for less experienced users. To streamline this process and enhance procedural efficiency overall, we proposed a visual perception system, namely AutoCBCT, seamlessly integrated with an angiography suite. This system dynamically models both the patient's body and the surgical environment in real-time. AutoCBCT enables a novel workflow with automated positioning, navigation and simulated test-runs, eliminating the need for manual operations and interactions. The proposed system has been successfully deployed and studied in both lab and clinical settings, demonstrating significantly improved workflow efficiency.

Keywords

Cite

@article{arxiv.2403.05758,
  title  = {Automating Catheterization Labs with Real-Time Perception},
  author = {Fan Yang and Benjamin Planche and Meng Zheng and Cheng Chen and Terrence Chen and Ziyan Wu},
  journal= {arXiv preprint arXiv:2403.05758},
  year   = {2024}
}
R2 v1 2026-06-28T15:14:16.965Z