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Mesh Optimization for Monte Carlo-Based Optical Tomography
Mesh-based Monte Carlo techniques for optical imaging allow for accurate modeling of light propagation in complex biological tissues. Recently, they have been developed within an efficient computational framework to be used as a forward model in optical tomography. However, commonly employed adaptiv...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4640680/ https://www.ncbi.nlm.nih.gov/pubmed/26566523 http://dx.doi.org/10.3390/photonics2020375 |
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author | Edmans, Andrew Intes, Xavier |
author_facet | Edmans, Andrew Intes, Xavier |
author_sort | Edmans, Andrew |
collection | PubMed |
description | Mesh-based Monte Carlo techniques for optical imaging allow for accurate modeling of light propagation in complex biological tissues. Recently, they have been developed within an efficient computational framework to be used as a forward model in optical tomography. However, commonly employed adaptive mesh discretization techniques have not yet been implemented for Monte Carlo based tomography. Herein, we propose a methodology to optimize the mesh discretization and analytically rescale the associated Jacobian based on the characteristics of the forward model. We demonstrate that this method maintains the accuracy of the forward model even in the case of temporal data sets while allowing for significant coarsening or refinement of the mesh. |
format | Online Article Text |
id | pubmed-4640680 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
record_format | MEDLINE/PubMed |
spelling | pubmed-46406802015-11-10 Mesh Optimization for Monte Carlo-Based Optical Tomography Edmans, Andrew Intes, Xavier Photonics Article Mesh-based Monte Carlo techniques for optical imaging allow for accurate modeling of light propagation in complex biological tissues. Recently, they have been developed within an efficient computational framework to be used as a forward model in optical tomography. However, commonly employed adaptive mesh discretization techniques have not yet been implemented for Monte Carlo based tomography. Herein, we propose a methodology to optimize the mesh discretization and analytically rescale the associated Jacobian based on the characteristics of the forward model. We demonstrate that this method maintains the accuracy of the forward model even in the case of temporal data sets while allowing for significant coarsening or refinement of the mesh. 2015-04-09 2015-06 /pmc/articles/PMC4640680/ /pubmed/26566523 http://dx.doi.org/10.3390/photonics2020375 Text en http://creativecommons.org/licenses/by/4.0/ This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Edmans, Andrew Intes, Xavier Mesh Optimization for Monte Carlo-Based Optical Tomography |
title | Mesh Optimization for Monte Carlo-Based Optical Tomography |
title_full | Mesh Optimization for Monte Carlo-Based Optical Tomography |
title_fullStr | Mesh Optimization for Monte Carlo-Based Optical Tomography |
title_full_unstemmed | Mesh Optimization for Monte Carlo-Based Optical Tomography |
title_short | Mesh Optimization for Monte Carlo-Based Optical Tomography |
title_sort | mesh optimization for monte carlo-based optical tomography |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4640680/ https://www.ncbi.nlm.nih.gov/pubmed/26566523 http://dx.doi.org/10.3390/photonics2020375 |
work_keys_str_mv | AT edmansandrew meshoptimizationformontecarlobasedopticaltomography AT intesxavier meshoptimizationformontecarlobasedopticaltomography |