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New nonlocal forward model for diffuse optical tomography

机译:新型非局部前向散射光学层析成像模型

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摘要

The forward model in diffuse optical tomography (DOT) describes how light propagates through a turbid medium. It is often approximated by a diffusion equation (DE) that is numerically discretized by the classical finite element method (FEM). We propose a nonlocal diffusion equation (NDE) as a new forward model for DOT, the discretization of which is carried out with an efficient graph-based numerical method (GNM). To quantitatively evaluate the new forward model, we first conduct experiments on a homogeneous slab, where the numerical accuracy of both NDE and DE is compared against the existing analytical solution. We further evaluate NDE by comparing its image reconstruction performance (inverse problem) to that of DE. Our experiments show that NDE is quantitatively comparable to DE and is up to 64% faster due to the efficient graph-based representation that can be implemented identically for geometries in different dimensions. The proposed discretization method can be easily applied to other imaging techniques like diffuse correlation spectroscopy which are normally modeled by the diffusion equation.
机译:漫射光学层析成像(DOT)中的正向模型描述了光如何通过混浊介质传播。它通常由一个扩散方程(DE)近似,该扩散方程通过经典有限元方法(FEM)在数值上离散化。我们提出了一种非局部扩散方程(NDE)作为DOT的新正向模型,其离散化是通过基于图的高效数值方法(GNM)进行的。为了定量评估新的正向模型,我们首先在均质平板上进行实验,将NDE和DE的数值精度与现有的解析解进行比较。我们通过将NDE的图像重建性能(反问题)与DE进行比较来进一步评估NDE。我们的实验表明,NDE在数量上可与DE媲美,并且由于基于图形的有效表示方式(可对不同尺寸的几何图形实现相同的效果),其速度最高可提高64%。所提出的离散化方法可以轻松地应用于其他成像技术,例如通常由扩散方程建模的扩散相关光谱法。

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