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首页> 外文期刊>IEEE Transactions on Medical Imaging >Fast Realistic MRI Simulations Based on Generalized Multi-Pool Exchange Tissue Model
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Fast Realistic MRI Simulations Based on Generalized Multi-Pool Exchange Tissue Model

机译:基于广义多池交换组织模型的快速逼真的MRI仿真

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摘要

We present MRiLab, a new comprehensive simulator for large-scale realistic MRI simulations on a regular PC equipped with a modern graphical processing unit (GPU). MRiLab combines realistic tissue modeling with numerical virtualization of an MRI system and scanning experiment to enable assessment of a broad range of MRI approaches including advanced quantitative MRI methods inferring microstructure on a sub-voxel level. A flexible representation of tissue microstructure is achieved in MRiLab by employing the generalized tissue model with multiple exchanging water and macromolecular proton pools rather than a system of independent proton isochromats typically used in previous simulators. The computational power needed for simulation of the biologically relevant tissue models in large 3D objects is gained using parallelized execution on GPU. Three simulated and one actual MRI experiments were performed to demonstrate the ability of the new simulator to accommodate a wide variety of voxel composition scenarios and demonstrate detrimental effects of simplified treatment of tissue micro-organization adapted in previous simulators. GPU execution allowed ∼200× improvement in computational speed over standard CPU. As a cross-platform, open-source, extensible environment for customizing virtual MRI experiments, MRiLab streamlines the development of new MRI methods, especially those aiming to infer quantitatively tissue composition and microstructure.
机译:我们展示了MRiLab,这是一种新型综合仿真器,可在配备了现代图形处理单元(GPU)的常规PC上进行大规模现实MRI仿真。 MRiLab将现实的组织建模与MRI系统的数值虚拟化和扫描实验相结合,从而能够评估各种MRI方法,包括在亚体素水平上推断微观结构的先进定量MRI方法。在MRiLab中,通过采用具有多个交换水和大分子质子池的广义组织模型,而不是以前的模拟器中通常使用的独立质子等色体系统,可以灵活地表示组织的微观结构。使用GPU上的并行执行,可以获得大型3D对象中生物学相关组织模型的仿真所需的计算能力。进行了三个模拟和一个实际的MRI实验,以证明新模拟器能够适应多种体素组成场景,并证明简化适应先前模拟器的组织微观组织的有害影响。 GPU执行使标准CPU的计算速度提高了约200倍。作为用于定制虚拟MRI实验的跨平台,开放源代码,可扩展的环境,MRiLab简化了新MRI方法的开发,尤其是那些旨在定量推断组织组成和微观结构的方法。

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