Evaluation of Different Approximations for Correlation Coefficients in Stochastic FDTD to Estimate SAR Variance in a Human Head Model
In this paper, the stochastic finite-difference time domain (S-FDTD) method is employed to calculate the standard deviation of specific absorption rate (SAR) in a two-dimensional (2-D) slice of human head. S-FDTD calculates both the mean and standard deviation of SAR caused by variability or uncertainty in the electrical properties of the human head tissues. The accuracy of the S-FDTD result is controlled by the approximations for correlation coefficients between the electrical properties of the tissues and the fields propagating in them. Hence, different approximations for correlation coefficients are tested in order to evaluate their effect on the standard deviation of SAR. The 1-D Monte Carlo correlation coefficient (MC-CC) approximation reported in our previous work is successfully extended to 2-D and also tested for the head model. Then, all the results are compared with that of full-fledged Monte Carlo method (considered as gold standard in statistical simulations). In order to accelerate the simulations, the proposed algorithm is run on graphics processing unit by exploiting OpenACC application program interface. Using different correlation coefficients shows that the extended 2-D MC-CC S-FDTD results are very close to that of Monte Carlo and yield more accurate results than other approximations in SAR calculations.
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