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Analysis of the applicability of the classical probabilistic parameters of the Monte Carlo algorithm for problems of light transport in turbid biological media with continuous absorption and discrete scattering
Quantum Electronics Pub Date : 2021-04-28 , DOI: 10.1070/qel17535
A.P. Tarasov 1, 2 , S. Persheyev 2 , D.A. Rogatkin 3
Affiliation  

Simulation of light propagation by the statistical Monte Carlo (MC) method is widely used in many fields, especially in astrophysics, atmospheric optics, ocean optics, and nuclear medicine. In the optics of biological tissues, the MC method is used to simulate the luminous flux, which is formed during various medical therapeutic or diagnostic procedures inside a biological tissue and on its surface. In such calculations, the MC method is commonly considered as a reference one, which ensures an arbitrarily high accuracy with an increase in the number of ‘photons’. However, it can be shown that this is not always the case. In this paper, in the methodological aspect, the idealised one-dimensional problems of the transport theory for a turbid medium with continuous absorption and scattering and a turbid medium with discrete scatterers inside a continuously absorbing medium are considered. Their exact analytical solutions are presented and compared with the results of statistical modelling by the MC method. It is found that the use of classical probabilistic parameters for a medium with continuous absorption and scattering in the MC algorithm leads to a systematic method error in determining the values of radiation fluxes for biological media with discrete scattering, up to 10% for fluxes at the boundary in some cases. The causes of the error are discussed and it is shown how to modify the probabilistic parameters of the MC algorithm to eliminate it.



中文翻译:

蒙特卡罗算法经典概率参数对连续吸收和离散散射的混浊生物介质中光传输问题的适用性分析

统计蒙特卡罗(MC)方法模拟光传播被广泛应用于许多领域,特别是在天体物理学、大气光学、海洋光学和核医学等领域。在生物组织的光学中,MC 方法用于模拟光通量,该光通量是在生物组织内部及其表面的各种医学治疗或诊断过程中形成的。在此类计算中,MC 方法通常被认为是一种参考方法,它可以确保随着“光子”数量的增加而获得任意高的精度。然而,可以证明情况并非总是如此。本文在方法论方面,考虑了具有连续吸收和散射的混浊介质以及在连续吸收介质中具有离散散射体的混浊介质的理想化一维问题。给出了它们的精确解析解,并与 MC 方法的统计建模结果进行了比较。研究发现,在 MC 算法中对具有连续吸收和散射的介质使用经典概率参数会导致在确定具有离散散射的生物介质的辐射通量值时出现系统方法误差,在某些情况下的边界。讨论了错误的原因,并说明了如何修改 MC 算法的概率参数来消除它。给出了它们的精确解析解,并与 MC 方法的统计建模结果进行了比较。研究发现,在 MC 算法中对具有连续吸收和散射的介质使用经典概率参数会导致在确定具有离散散射的生物介质的辐射通量值时出现系统方法误差,在某些情况下的边界。讨论了错误的原因,并说明了如何修改 MC 算法的概率参数来消除它。给出了它们的精确解析解,并与 MC 方法的统计建模结果进行了比较。研究发现,在 MC 算法中对具有连续吸收和散射的介质使用经典概率参数会导致在确定具有离散散射的生物介质的辐射通量值时出现系统方法误差,在某些情况下的边界。讨论了错误的原因,并说明了如何修改 MC 算法的概率参数来消除它。研究发现,在 MC 算法中对具有连续吸收和散射的介质使用经典概率参数会导致在确定具有离散散射的生物介质的辐射通量值时出现系统方法误差,在某些情况下的边界。讨论了错误的原因,并说明了如何修改 MC 算法的概率参数来消除它。研究发现,在 MC 算法中对具有连续吸收和散射的介质使用经典概率参数会导致在确定具有离散散射的生物介质的辐射通量值时出现系统方法误差,在某些情况下的边界。讨论了错误的原因,并说明了如何修改 MC 算法的概率参数来消除它。

更新日期:2021-04-28
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