逆漫射光学层析成像的2级域分解算法

Il-Young Son, M. Guven, Xavier Intes, B. Yazıcı
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引用次数: 2

摘要

为了降低计算复杂度,加快光学图像重建的收敛速度,本文研究了逆DOT问题的域分解算法。我们提出了一种两级多网格算法与改进的乘法Schwarz算法的结合,其中共轭梯度作为加速器来解决在每个划分的子域上制定的每个子问题。在我们的实验中,用两个矩形内含物的模拟幻像结构作为测试平台来测量我们的算法的计算效率。除了源和检测器的位置外,不假设任何关于配置的先验信息。对于我们改进的Schwarz算法的单独应用,我们观察到与在全域获得的共轭梯度解相比,效率提高了100%。随着粗网格的加入,这一效率提高到400%。粗网格还用于改善在内含物边界处重建图像的整体外观。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A 2-level domain decomposition algorithm for inverse diffuse optical tomography
In this paper, we explore domain decomposition algorithms for the inverse DOT problem in order to reduce the computational complexity and accelerate the convergence of the optical image reconstruction. We propose a combination of a two-level multigrid algorithm with a modified multiplicative Schwarz algorithm, where a conjugate gradient is used as an accelerator to solve each sub-problem formulated on each of the partitioned sub-domains. For our experiments, simulated phantom configuration with two rectangular inclusions is used as a testbed to measure the computational efficiency of our algorithms. No a priori information about the configuration is assumed except for the source and detector locations. For the application of our modified Schwarz algorithm alone, we observe an increase in efficiency of 100% as compared to the conjugate gradient solution obtained for the full domain. With the addition of the coarse grid, this efficiency rises to 400%. The coarse grid also serves to improve the overall appearance of the reconstructed image at the boundaries of the inclusions.
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