New approaches to computer-based interventional neuroradiology training.
Xunlei Wu, Vincent Pegoraro, Vincent Luboz, Paul F. Neumann, Ryan Scott Bardsley, Steven L. Dawson, Stéphane Cotin
Abstract
Xunlei Wu, Vincent Pegoraro, Vincent Luboz, Paul F. Neumann, Ryan Scott Bardsley, Steven L. Dawson, Stéphane Cotin
Abstract
For over 20 years, interventional methods have substantially improved the outcomes of patients with cardiovascular disease. However, these procedures require an intricate combination of visual and tactile feedback and extensive training periods. In this paper, a prototype of endovascular therapy training system is presented. A set of core simulation components applicable to most vascular procedures has been designed and integrated into a real-time high-fidelity interventional neuroradiology training system for the prompt treatment of ischemic stroke. We believe it will improve the quality of training and the speed of learning without putting patients at risk.
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For over 20 years, interventional methods have substantially improved the outcomes of patients with cardiovascular disease. However, these procedures require an intricate combination of visual and tactile feedback and extensive training periods. In this paper, a prototype of endovascular therapy training system is presented. A set of core simulation components applicable to most vascular procedures has been designed and integrated into a real-time high-fidelity interventional neuroradiology training system for the prompt treatment of ischemic stroke. We believe it will improve the quality of training and the speed of learning without putting patients at risk.
Key concepts: Interventional neuroradiology, Neuroradiology, Fidelity, Medical physics, Computer science, Interventional radiology, Medicine, Set (abstract data type)