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In Silico Modeling of Magnetic Resonance Flow Imaging in Complex Vascular Networks

机译:复杂血管网络中磁共振流成像的计算机模拟

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摘要

The paper presents a computational model of magnetic resonance (MR) flow imaging. The model consists of three components. The first component is used to generate complex vascular structures, while the second one provides blood flow characteristics in the generated vascular structures by the lattice Boltzmann method. The third component makes use of the generated vascular structures and flow characteristics to simulate MR flow imaging. To meet computational demands, parallel algorithms are applied in all the components. The proposed approach is verified in three stages. In the first stage, experimental validation is performed by an in vitro phantom. Then, the simulation possibilities of the model are shown. Flow and MR flow imaging in complex vascular structures are presented and evaluated. Finally, the computational performance is tested. Results show that the model is able to reproduce flow behavior in large vascular networks in a relatively short time. Moreover, simulated MR flow images are in accordance with the theoretical considerations and experimental images. The proposed approach is the first such an integrative solution in literature. Moreover, compared to previous works on flow and MR flow imaging, this approach distinguishes itself by its computational efficiency. Such a connection of anatomy, physiology and image formation in a single computer tool could provide an in silico solution to improving our understanding of the processes involved, either considered together or separately.
机译:该论文提出了磁共振(MR)流成像的计算模型。该模型由三个部分组成。第一个组件用于生成复杂的血管结构,而第二个组件通过格子Boltzmann方法在生成的血管结构中提供血流特征。第三个组件利用生成的血管结构和流动特性来模拟MR流动成像。为了满足计算需求,并行算法应用于所有组件。所提出的方法分三个阶段进行了验证。在第一阶段,通过体外体模进行实验验证。然后,显示了模型的仿真可能性。提出并评估了复杂血管结构中的血流和MR血流成像。最后,测试了计算性能。结果表明,该模型能够在较短的时间内重现大型血管网络中的流动行为。而且,模拟的MR流图像符合理论考虑和实验图像。所提出的方法是文献中第一个这样的集成解决方案。此外,与先前在流量和MR流量成像方面的工作相比,该方法的计算效率与众不同。单个计算机工具中的解剖学,生理学和图像形成的这种联系可以提供计算机上的解决方案,以提高我们对所涉及过程的理解,无论是一起考虑还是分开考虑。

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