A Monte-Carlo-Based Network Method for Source Positioning in Bioluminescence Tomography

A Monte-Carlo-Based Network Method for Source Positioning in Bioluminescence Tomography

We present an approach based on the improved Levenberg Marquardt (LM) algorithm of backpropagation (BP) neural network to estimate the light source position in bioluminescent imaging. For solving...

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Bibliographic Details
Main Authors: Zhun Xu, Xiaolei Song, Xiaomeng Zhang, Jing Bai
Format: Article
Language:English
Published: Hindawi Limited 2007-01-01
Series:International Journal of Biomedical Imaging
Online Access:http://dx.doi.org/10.1155/2007/48989
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spelling doaj-89efcc025d0a4d229ffb6c9ee2b12f0a2020-11-25T00:33:01ZengHindawi LimitedInternational Journal of Biomedical Imaging1687-41881687-41962007-01-01200710.1155/2007/4898948989A Monte-Carlo-Based Network Method for Source Positioning in Bioluminescence TomographyZhun Xu0Xiaolei Song1Xiaomeng Zhang2Jing Bai3Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, ChinaDepartment of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, ChinaDepartment of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, ChinaDepartment of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, ChinaWe present an approach based on the improved Levenberg Marquardt (LM) algorithm of backpropagation (BP) neural network to estimate the light source position in bioluminescent imaging. For solving the forward problem, the table-based random sampling algorithm (TBRS), a fast Monte Carlo simulation method we developed before, is employed here. Result shows that BP is an effective method to position the light source.http://dx.doi.org/10.1155/2007/48989
collection DOAJ
language English
format Article
sources DOAJ
author Zhun Xu
Xiaolei Song
Xiaomeng Zhang
Jing Bai
spellingShingle Zhun Xu
Xiaolei Song
Xiaomeng Zhang
Jing Bai
A Monte-Carlo-Based Network Method for Source Positioning in Bioluminescence Tomography
International Journal of Biomedical Imaging
author_facet Zhun Xu
Xiaolei Song
Xiaomeng Zhang
Jing Bai
author_sort Zhun Xu
title A Monte-Carlo-Based Network Method for Source Positioning in Bioluminescence Tomography
title_short A Monte-Carlo-Based Network Method for Source Positioning in Bioluminescence Tomography
title_full A Monte-Carlo-Based Network Method for Source Positioning in Bioluminescence Tomography
title_fullStr A Monte-Carlo-Based Network Method for Source Positioning in Bioluminescence Tomography
title_full_unstemmed A Monte-Carlo-Based Network Method for Source Positioning in Bioluminescence Tomography
title_sort monte-carlo-based network method for source positioning in bioluminescence tomography
publisher Hindawi Limited
series International Journal of Biomedical Imaging
issn 1687-4188
1687-4196
publishDate 2007-01-01
description We present an approach based on the improved Levenberg Marquardt (LM) algorithm of backpropagation (BP) neural network to estimate the light source position in bioluminescent imaging. For solving the forward problem, the table-based random sampling algorithm (TBRS), a fast Monte Carlo simulation method we developed before, is employed here. Result shows that BP is an effective method to position the light source.
url http://dx.doi.org/10.1155/2007/48989
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AT xiaoleisong amontecarlobasednetworkmethodforsourcepositioninginbioluminescencetomography
AT xiaomengzhang amontecarlobasednetworkmethodforsourcepositioninginbioluminescencetomography
AT jingbai amontecarlobasednetworkmethodforsourcepositioninginbioluminescencetomography
AT zhunxu montecarlobasednetworkmethodforsourcepositioninginbioluminescencetomography
AT xiaoleisong montecarlobasednetworkmethodforsourcepositioninginbioluminescencetomography
AT xiaomengzhang montecarlobasednetworkmethodforsourcepositioninginbioluminescencetomography
AT jingbai montecarlobasednetworkmethodforsourcepositioninginbioluminescencetomography
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