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Bioluminescence tomography with Gaussian prior
Parameterizing the bioluminescent source globally in Gaussians provides several advantages over voxel representation in bioluminescence tomography. It is mathematically unique to recover Gaussians [Med. Phys. 31(8), 2289 (2004)] and practically sufficient to approximate various shapes by Gaussians i...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Optical Society of America
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3018113/ https://www.ncbi.nlm.nih.gov/pubmed/21258547 http://dx.doi.org/10.1364/BOE.1.001259 |
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author | Gao, Hao Zhao, Hongkai Cong, Wenxiang Wang, Ge |
author_facet | Gao, Hao Zhao, Hongkai Cong, Wenxiang Wang, Ge |
author_sort | Gao, Hao |
collection | PubMed |
description | Parameterizing the bioluminescent source globally in Gaussians provides several advantages over voxel representation in bioluminescence tomography. It is mathematically unique to recover Gaussians [Med. Phys. 31(8), 2289 (2004)] and practically sufficient to approximate various shapes by Gaussians in diffusive medium. The computational burden is significantly reduced since much fewer unknowns are required. Besides, there are physiological evidences that the source can be modeled by Gaussians. The simulations show that the proposed model and algorithm significantly improves accuracy and stability in the presence of Gaussian or non- Gaussian sources, noisy data or the optical background mismatch. It is also validated through in vivo experimental data. |
format | Text |
id | pubmed-3018113 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Optical Society of America |
record_format | MEDLINE/PubMed |
spelling | pubmed-30181132011-01-21 Bioluminescence tomography with Gaussian prior Gao, Hao Zhao, Hongkai Cong, Wenxiang Wang, Ge Biomed Opt Express Image Reconstruction and Inverse Problems Parameterizing the bioluminescent source globally in Gaussians provides several advantages over voxel representation in bioluminescence tomography. It is mathematically unique to recover Gaussians [Med. Phys. 31(8), 2289 (2004)] and practically sufficient to approximate various shapes by Gaussians in diffusive medium. The computational burden is significantly reduced since much fewer unknowns are required. Besides, there are physiological evidences that the source can be modeled by Gaussians. The simulations show that the proposed model and algorithm significantly improves accuracy and stability in the presence of Gaussian or non- Gaussian sources, noisy data or the optical background mismatch. It is also validated through in vivo experimental data. Optical Society of America 2010-10-29 /pmc/articles/PMC3018113/ /pubmed/21258547 http://dx.doi.org/10.1364/BOE.1.001259 Text en ©2010 Optical Society of America http://creativecommons.org/licenses/by-nc-nd/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 Unported License, which permits download and redistribution, provided that the original work is properly cited. This license restricts the article from being modified or used commercially. |
spellingShingle | Image Reconstruction and Inverse Problems Gao, Hao Zhao, Hongkai Cong, Wenxiang Wang, Ge Bioluminescence tomography with Gaussian prior |
title | Bioluminescence tomography with Gaussian prior |
title_full | Bioluminescence tomography with Gaussian prior |
title_fullStr | Bioluminescence tomography with Gaussian prior |
title_full_unstemmed | Bioluminescence tomography with Gaussian prior |
title_short | Bioluminescence tomography with Gaussian prior |
title_sort | bioluminescence tomography with gaussian prior |
topic | Image Reconstruction and Inverse Problems |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3018113/ https://www.ncbi.nlm.nih.gov/pubmed/21258547 http://dx.doi.org/10.1364/BOE.1.001259 |
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