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Improving the accuracy of the diffusion model in highly absorbing media.

Cong AX, Shen H, Cong W, Wang G - Int J Biomed Imaging (2007)

Bottom Line: It produces satisfactory results in weakly absorbing and highly scattering media, but the accuracy lessens with the decreasing albedo.The diffusion model behaves more closely to the physical model with the actual optical parameters substituted by the optimized optical parameters.The effectiveness of the proposed technique was demonstrated by the numerical experiments using the Monte Carlo simulation data as measurements.

View Article: PubMed Central - PubMed

Affiliation: Biomedical Imaging Division, School of Biomedical Engineering and Sciences, Virginia Polytechnic Institute and State University, 1880 Pratt Drive, Blacksburg, VA 24061, USA.

ABSTRACT
The diffusion approximation of the Boltzmann transport equation is most commonly used for describing the photon propagation in turbid media. It produces satisfactory results in weakly absorbing and highly scattering media, but the accuracy lessens with the decreasing albedo. In this paper, we presented a method to improve the accuracy of the diffusion model in strongly absorbing media by adjusting the optical parameters. Genetic algorithm-based optimization tool is used to find the optimal optical parameters. The diffusion model behaves more closely to the physical model with the actual optical parameters substituted by the optimized optical parameters. The effectiveness of the proposed technique was demonstrated by the numerical experiments using the Monte Carlo simulation data as measurements.

No MeSH data available.


The Monte Carlo process of photon propagation in tissue.
© Copyright Policy - open-access
Related In: Results  -  Collection


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fig1: The Monte Carlo process of photon propagation in tissue.

Mentions: Monte Carlo (MC) simulation models each individual photon's physical interactions with the medium as a stochastic process. As a large number of such stochastic processes of photon propagation are simulated, the signal detected is statistically meaningful and very close to the physical experiment counterpart. MC result can be legitimately considered as the low-noise version of the actual physical measurement.Therefore, we use MC method to produce measurements in numerical experiments.The Monte Carlo process consists of three parts: the photon absorption, the photonscattering and the internal reflection at the boundaries, as illustrated in Figure 1. The absorption of photon for each step can be expressed by [2,3,13](1)ΔW=μaμa+μsW, where is the weight of the photon packet. The scattering of the photon is governed byHenyey-Greenstein (HG) phase function, which is considered as the most appropriatephase function for the photon propergation in tissue. The HG phase function is givenby [2, 3](2)p(cos⁡ θ)=1−g22(1+g2−2gcos⁡θ)3/2, where is the deflection angle, and the anisotropy. The internal reflectance rate due to the refrective index mismatch atthe tissue boundary for unpolarized incident light is given by the Fresnel's formulas[2, 3]:(3)R(ϑi)=12[sin⁡2(ϑi−ϑt)sin⁡2(ϑi+ϑt)+tan⁡2(ϑi−ϑt)tan⁡2(ϑi+ϑt)], where and are the incident and transmit angles, respectively. The incident and transmit anglesobey the Snell's law(4)sin⁡ϑisin⁡ϑt=ntni, where and are the refractive indices for both sides of the boundary, respectively.


Improving the accuracy of the diffusion model in highly absorbing media.

Cong AX, Shen H, Cong W, Wang G - Int J Biomed Imaging (2007)

The Monte Carlo process of photon propagation in tissue.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2194801&req=5

fig1: The Monte Carlo process of photon propagation in tissue.
Mentions: Monte Carlo (MC) simulation models each individual photon's physical interactions with the medium as a stochastic process. As a large number of such stochastic processes of photon propagation are simulated, the signal detected is statistically meaningful and very close to the physical experiment counterpart. MC result can be legitimately considered as the low-noise version of the actual physical measurement.Therefore, we use MC method to produce measurements in numerical experiments.The Monte Carlo process consists of three parts: the photon absorption, the photonscattering and the internal reflection at the boundaries, as illustrated in Figure 1. The absorption of photon for each step can be expressed by [2,3,13](1)ΔW=μaμa+μsW, where is the weight of the photon packet. The scattering of the photon is governed byHenyey-Greenstein (HG) phase function, which is considered as the most appropriatephase function for the photon propergation in tissue. The HG phase function is givenby [2, 3](2)p(cos⁡ θ)=1−g22(1+g2−2gcos⁡θ)3/2, where is the deflection angle, and the anisotropy. The internal reflectance rate due to the refrective index mismatch atthe tissue boundary for unpolarized incident light is given by the Fresnel's formulas[2, 3]:(3)R(ϑi)=12[sin⁡2(ϑi−ϑt)sin⁡2(ϑi+ϑt)+tan⁡2(ϑi−ϑt)tan⁡2(ϑi+ϑt)], where and are the incident and transmit angles, respectively. The incident and transmit anglesobey the Snell's law(4)sin⁡ϑisin⁡ϑt=ntni, where and are the refractive indices for both sides of the boundary, respectively.

Bottom Line: It produces satisfactory results in weakly absorbing and highly scattering media, but the accuracy lessens with the decreasing albedo.The diffusion model behaves more closely to the physical model with the actual optical parameters substituted by the optimized optical parameters.The effectiveness of the proposed technique was demonstrated by the numerical experiments using the Monte Carlo simulation data as measurements.

View Article: PubMed Central - PubMed

Affiliation: Biomedical Imaging Division, School of Biomedical Engineering and Sciences, Virginia Polytechnic Institute and State University, 1880 Pratt Drive, Blacksburg, VA 24061, USA.

ABSTRACT
The diffusion approximation of the Boltzmann transport equation is most commonly used for describing the photon propagation in turbid media. It produces satisfactory results in weakly absorbing and highly scattering media, but the accuracy lessens with the decreasing albedo. In this paper, we presented a method to improve the accuracy of the diffusion model in strongly absorbing media by adjusting the optical parameters. Genetic algorithm-based optimization tool is used to find the optimal optical parameters. The diffusion model behaves more closely to the physical model with the actual optical parameters substituted by the optimized optical parameters. The effectiveness of the proposed technique was demonstrated by the numerical experiments using the Monte Carlo simulation data as measurements.

No MeSH data available.