Lu Yujie, Chatziioannou Arion F
David Geffen School of Medicine at UCLA, Crump Institute for Molecular Imaging, University of California, 700 Westwood Plaza, Los Angeles, CA 90095, USA.
Commun Numer Methods Eng. 2009;25(6):751-770. doi: 10.1002/cnm.1167.
Whole-body optical molecular imaging of mouse models in preclinical research is rapidly developing in recent years. In this context, it is essential and necessary to develop novel simulation methods of light propagation for optical imaging, especially when a priori knowledge, large-volume domain and a wide-range of optical properties need to be considered in the reconstruction algorithm. In this paper, we propose a three dimensional parallel adaptive finite element method with simplified spherical harmonics (SP(N)) approximation to simulate optical photon propagation in large-volumes of heterogenous tissues. The simulation speed is significantly improved by a posteriori parallel adaptive mesh refinement and dynamic mesh repartitioning. Compared with the diffusion equation and the Monte Carlo methods, the SP(N) method shows improved performance and the necessity of high-order approximation in heterogeneous domains. Optimal solver selection and time-costing analysis in real mouse geometry further improve the performance of the proposed algorithm and show the superiority of the proposed parallel adaptive framework for whole-body optical molecular imaging in murine models.
近年来,临床前研究中对小鼠模型的全身光学分子成像发展迅速。在此背景下,开发用于光学成像的光传播新模拟方法至关重要且必要,尤其是在重建算法中需要考虑先验知识、大体积域和广泛的光学特性时。在本文中,我们提出了一种具有简化球谐函数(SP(N))近似的三维并行自适应有限元方法,以模拟光光子在大体积异质组织中的传播。通过后验并行自适应网格细化和动态网格重新划分,显著提高了模拟速度。与扩散方程和蒙特卡罗方法相比,SP(N)方法在异质域中表现出更好的性能以及高阶近似的必要性。在真实小鼠几何结构中的最优求解器选择和时间成本分析进一步提高了所提算法的性能,并显示了所提并行自适应框架在小鼠模型全身光学分子成像中的优越性。