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Improving the Accuracy of the Diffusion Model in Highly Absorbing Media
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 presen...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2007
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2194801/ https://www.ncbi.nlm.nih.gov/pubmed/18273379 http://dx.doi.org/10.1155/2007/38168 |
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author | Cong, Alexander X. Shen, Haiou Cong, Wenxiang Wang, Ge |
author_facet | Cong, Alexander X. Shen, Haiou Cong, Wenxiang Wang, Ge |
author_sort | Cong, Alexander X. |
collection | PubMed |
description | 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. |
format | Text |
id | pubmed-2194801 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-21948012008-02-13 Improving the Accuracy of the Diffusion Model in Highly Absorbing Media Cong, Alexander X. Shen, Haiou Cong, Wenxiang Wang, Ge Int J Biomed Imaging Research Article 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. Hindawi Publishing Corporation 2007 2007-08-30 /pmc/articles/PMC2194801/ /pubmed/18273379 http://dx.doi.org/10.1155/2007/38168 Text en Copyright © 2007 Alexander X. Cong et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Cong, Alexander X. Shen, Haiou Cong, Wenxiang Wang, Ge Improving the Accuracy of the Diffusion Model in Highly Absorbing Media |
title | Improving the Accuracy of the Diffusion Model in Highly Absorbing Media |
title_full | Improving the Accuracy of the Diffusion Model in Highly Absorbing Media |
title_fullStr | Improving the Accuracy of the Diffusion Model in Highly Absorbing Media |
title_full_unstemmed | Improving the Accuracy of the Diffusion Model in Highly Absorbing Media |
title_short | Improving the Accuracy of the Diffusion Model in Highly Absorbing Media |
title_sort | improving the accuracy of the diffusion model in highly absorbing media |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2194801/ https://www.ncbi.nlm.nih.gov/pubmed/18273379 http://dx.doi.org/10.1155/2007/38168 |
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