Tufts University, Department of Biomedical Engineering, 4 Colby Street, Medford, Massachusetts 02155, USA.
Opt Lett. 2011 Jun 1;36(11):2095-7. doi: 10.1364/OL.36.002095.
We present a two-step Monte Carlo (MC) method that is used to solve the radiative transfer equation in heterogeneous turbid media. The method exploits the one-to-one correspondence between the seed value of a random number generator and the sequence of random numbers. In the first step, a full MC simulation is run for the initial distribution of the optical properties and the "good" seeds (the ones leading to detected photons) are stored in an array. In the second step, we run a new MC simulation with only the good seeds stored in the first step, i.e., we propagate only detected photons. The effect of a change in the optical properties is calculated in a short time by using two scaling relationships. By this method we can increase the speed of a simulation up to a factor of 1300 in typical situations found in near-IR tissue spectroscopy and diffuse optical tomography, with a minimal requirement for hard disk space. Potential applications of this method for imaging of turbid media and the inverse problem are discussed.
我们提出了一种两步蒙特卡罗(MC)方法,用于解决非均相混浊介质中的辐射传输方程。该方法利用随机数生成器的种子值与随机数序列之间的一一对应关系。在第一步中,对光学性质的初始分布进行完整的 MC 模拟,并将“好”种子(导致检测到光子的种子)存储在数组中。在第二步中,我们仅使用第一步中存储的好种子运行新的 MC 模拟,即仅传播检测到的光子。通过使用两个缩放关系,可以在短时间内计算光学性质变化的影响。通过这种方法,我们可以在近红外组织光谱学和漫射光学断层扫描中常见的典型情况下将模拟速度提高 1300 倍,而对硬盘空间的要求最小。讨论了该方法在混浊介质成像和反问题中的潜在应用。