Northeastern Univ., United States.
J Biomed Opt. 2019 Feb;24(2):1-4. doi: 10.1117/1.JBO.24.2.020503.
The mesh-based Monte Carlo (MMC) method is an efficient algorithm to model light propagation inside tissues with complex boundaries, but choosing appropriate mesh density can be challenging. A fine mesh improves the spatial resolution of the output but requires more computation. We propose an improved MMC-dual-grid mesh-based Monte Carlo (DMMC)-to accelerate photon simulations using a coarsely tessellated tetrahedral mesh for ray-tracing computation and an independent voxelated grid for output data storage. The decoupling between ray-tracing and data storage grids allows us to simultaneously achieve faster simulations and improved output spatial accuracy. Furthermore, we developed an optimized ray-tracing technique to eliminate unnecessary ray-tetrahedron intersection tests in optically thick mesh elements. We validate the proposed algorithms using a complex heterogeneous domain and compare the solutions with those from MMC and voxel-based Monte Carlo. We found that DMMC with an unrefined constrained Delaunay tessellation of the boundary nodes yielded the highest speedup, ranging from 1.3 × to 2.9 × for various scattering settings, with nearly no loss in accuracy. In addition, the optimized ray-tracing technique offers excellent acceleration in high-scattering media, reducing the ray-tetrahedron test count by over 100-fold. Our DMMC software can be downloaded at http://mcx.space/mmc.
基于网格的蒙特卡罗（MMC）方法是一种高效的算法，可用于模拟具有复杂边界的组织内的光传播，但选择合适的网格密度可能具有挑战性。精细的网格可以提高输出的空间分辨率，但需要更多的计算。我们提出了一种改进的基于网格的蒙特卡罗-对偶网格（DMMC）方法，通过使用粗三角网格进行光线追踪计算和独立的体素网格进行输出数据存储，来加速光子模拟。光线追踪和数据存储网格的解耦允许我们同时实现更快的模拟和更高的输出空间精度。此外，我们开发了一种优化的光线追踪技术，以消除光厚网格元素中的不必要的光线-四面体相交测试。我们使用复杂的异质域验证了所提出的算法，并将解决方案与 MMC 和体素蒙特卡罗的解决方案进行了比较。我们发现，对于各种散射设置，边界节点的非细化约束 Delaunay 剖分的 DMMC 产生了最高的加速比，范围从 1.3 倍到 2.9 倍，几乎没有精度损失。此外，优化的光线追踪技术在高散射介质中提供了出色的加速效果，将光线-四面体测试计数减少了 100 多倍。我们的 DMMC 软件可以在 http://mcx.space/mmc 下载。
