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A Table-Based Random Sampling Simulation for Bioluminescence Tomography

As a popular simulation of photon propagation in turbid media, the main problem of Monte Carlo (MC) method is its cumbersome computation. In this work a table-based random sampling simulation (TBRS) is proposed. The key idea of TBRS is to simplify multisteps of scattering to a single-step process, t...

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Detalles Bibliográficos
Autores principales: Zhang, Xiaomeng, Bai, Jing
Formato: Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2324062/
https://www.ncbi.nlm.nih.gov/pubmed/23165050
http://dx.doi.org/10.1155/IJBI/2006/83820
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author Zhang, Xiaomeng
Bai, Jing
author_facet Zhang, Xiaomeng
Bai, Jing
author_sort Zhang, Xiaomeng
collection PubMed
description As a popular simulation of photon propagation in turbid media, the main problem of Monte Carlo (MC) method is its cumbersome computation. In this work a table-based random sampling simulation (TBRS) is proposed. The key idea of TBRS is to simplify multisteps of scattering to a single-step process, through randomly table querying, thus greatly reducing the computing complexity of the conventional MC algorithm and expediting the computation. The TBRS simulation is a fast algorithm of the conventional MC simulation of photon propagation. It retained the merits of flexibility and accuracy of conventional MC method and adapted well to complex geometric media and various source shapes. Both MC simulations were conducted in a homogeneous medium in our work. Also, we present a reconstructing approach to estimate the position of the fluorescent source based on the trial-and-error theory as a validation of the TBRS algorithm. Good agreement is found between the conventional MC simulation and the TBRS simulation.
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spelling pubmed-23240622008-04-22 A Table-Based Random Sampling Simulation for Bioluminescence Tomography Zhang, Xiaomeng Bai, Jing Int J Biomed Imaging Article As a popular simulation of photon propagation in turbid media, the main problem of Monte Carlo (MC) method is its cumbersome computation. In this work a table-based random sampling simulation (TBRS) is proposed. The key idea of TBRS is to simplify multisteps of scattering to a single-step process, through randomly table querying, thus greatly reducing the computing complexity of the conventional MC algorithm and expediting the computation. The TBRS simulation is a fast algorithm of the conventional MC simulation of photon propagation. It retained the merits of flexibility and accuracy of conventional MC method and adapted well to complex geometric media and various source shapes. Both MC simulations were conducted in a homogeneous medium in our work. Also, we present a reconstructing approach to estimate the position of the fluorescent source based on the trial-and-error theory as a validation of the TBRS algorithm. Good agreement is found between the conventional MC simulation and the TBRS simulation. Hindawi Publishing Corporation 2006 2006-11-09 /pmc/articles/PMC2324062/ /pubmed/23165050 http://dx.doi.org/10.1155/IJBI/2006/83820 Text en Copyright © IJBI X. Zhang and J. Bai 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 Article
Zhang, Xiaomeng
Bai, Jing
A Table-Based Random Sampling Simulation for Bioluminescence Tomography
title A Table-Based Random Sampling Simulation for Bioluminescence Tomography
title_full A Table-Based Random Sampling Simulation for Bioluminescence Tomography
title_fullStr A Table-Based Random Sampling Simulation for Bioluminescence Tomography
title_full_unstemmed A Table-Based Random Sampling Simulation for Bioluminescence Tomography
title_short A Table-Based Random Sampling Simulation for Bioluminescence Tomography
title_sort table-based random sampling simulation for bioluminescence tomography
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2324062/
https://www.ncbi.nlm.nih.gov/pubmed/23165050
http://dx.doi.org/10.1155/IJBI/2006/83820
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