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2020, 2(2): 104-118

Published Date:2020-4-20 DOI: 10.1016/j.vrih.2020.04.001

Personalized cardiovascular intervention simulation system


This study proposes a series of geometry and physics modeling methods for personalized cardiovascular intervention procedures, which can be applied to a virtual endovascular simulator.
Based on personalized clinical computed tomography angiography (CTA) data, mesh models of the cardiovascular system were constructed semi-automatically. By coupling 4D magnetic resonance imaging (MRI) sequences corresponding to a complete cardiac cycle with related physics models, a hybrid kinetic model of the cardiovascular system was built to drive kinematics and dynamics simulation. On that basis, the surgical procedures related to intervention instruments were simulated using specially-designed physics models. These models can be solved in real-time; therefore, the complex interactions between blood vessels and instruments can be well simulated. Additionally, X-ray imaging simulation algorithms and realistic rendering algorithms for virtual intervention scenes are also proposed. In particular, instrument tracking hardware with haptic feedback was developed to serve as the interaction interface of real instruments and the virtual intervention system. Finally, a personalized cardiovascular intervention simulation system was developed by integrating the techniques mentioned above.
This system supported instant modeling and simulation of personalized clinical data and significantly improved the visual and haptic immersions of vascular intervention simulation.
It can be used in teaching basic cardiology and effectively satisfying the demands of intervention training, personalized intervention planning, and rehearsing.


Personalized cardiovascular modeling ; Intervention simulation system ; Intervention instrument simulation ; X-ray imaging simulation ; Hybrid model

Cite this article

Aimin HAO, Jiahao CUI, Shuai LI, Qinping ZHAO. Personalized cardiovascular intervention simulation system. Virtual Reality & Intelligent Hardware, 2020, 2(2): 104-118 DOI:10.1016/j.vrih.2020.04.001


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