Automating Catheterization Labs with Real-Time Perception
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arXiv
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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Soggetti: | |
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| _version_ | 1866909133453656064 |
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| author | Yang, Fan Planche, Benjamin Zheng, Meng Chen, Cheng Chen, Terrence Wu, Ziyan |
| author_facet | Yang, Fan Planche, Benjamin Zheng, Meng Chen, Cheng Chen, Terrence Wu, Ziyan |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_05758 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Automating Catheterization Labs with Real-Time Perception Yang, Fan Planche, Benjamin Zheng, Meng Chen, Cheng Chen, Terrence Wu, Ziyan Computer Vision and Pattern Recognition 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. |
| title | Automating Catheterization Labs with Real-Time Perception |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2403.05758 |