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Stochastic Sensitivity Analysis for Dosimetry of Head Tissues for the Three Compartment Head Model

机译:三室头模型的头部组织剂量学的随机敏感性分析

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This paper presents a stochastic framework for the assessment of stochastic sensitivity of electric parameters in the three-compartment model of the human head. The electric parameters of scalp, skull and brain are modelled as random variables with uniform distribution. The propagation of uncertainties from input parameters to the output of interest, i.e. induced electric field is carried out by using the non-intrusive Lagrange stochastic collocation method. The sparse grid interpolation in the multidimensional random space is used to generate the simulation points thus speeding up the calculation compared to traditional Monte Carlo sampling methods or full tensor stochastic collocation methods. The impact of the conductivity and relative permittivity of all three tissues to the induced electric field in the skull and scalp, respectively, is obtained. The presented approach provides a satisfactory insight into the behaviour of the model output with respect to parameter variations and allows the ranking of the input parameters from the most to the least influential ones, respectively.
机译:本文提出了一种用于评估人头三室模型中电参数随机敏感性的随机框架。头皮,头骨和大脑的电参数被建模为具有均匀分布的随机变量。通过使用非侵入式拉格朗日随机配置方法,可以将不确定性从输入参数传播到目标输出,即感应电场。与传统的蒙特卡洛采样方法或全张量随机配置方法相比,多维随机空间中的稀疏网格插值用于生成模拟点,从而加快了计算速度。获得了所有三种组织的电导率和相对介电常数分别对头骨和头皮中感应电场的影响。所提出的方法提供了关于模型输出相对于参数变化的行为的令人满意的见解,并且允许分别从影响力最大到影响力最小的参数对输入参数进行排序。

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