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A coupled finite element-boundary element method for modeling Diffusion equation in 3D multi-modality optical imaging

Three dimensional image reconstruction for multi-modality optical spectroscopy systems needs computationally efficient forward solvers with minimum meshing complexity, while allowing the flexibility to apply spatial constraints. Existing models based on the finite element method (FEM) require full 3...

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Detalles Bibliográficos
Autores principales: Srinivasan, Subhadra, Ghadyani, Hamid R., Pogue, Brian W., Paulsen, Keith D.
Formato: Texto
Lenguaje:English
Publicado: Optical Society of America 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2997710/
https://www.ncbi.nlm.nih.gov/pubmed/21152113
http://dx.doi.org/10.1364/BOE.1.000398
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author Srinivasan, Subhadra
Ghadyani, Hamid R.
Pogue, Brian W.
Paulsen, Keith D.
author_facet Srinivasan, Subhadra
Ghadyani, Hamid R.
Pogue, Brian W.
Paulsen, Keith D.
author_sort Srinivasan, Subhadra
collection PubMed
description Three dimensional image reconstruction for multi-modality optical spectroscopy systems needs computationally efficient forward solvers with minimum meshing complexity, while allowing the flexibility to apply spatial constraints. Existing models based on the finite element method (FEM) require full 3D volume meshing to incorporate constraints related to anatomical structure via techniques such as regularization. Alternate approaches such as the boundary element method (BEM) require only surface discretization but assume homogeneous or piece-wise constant domains that can be limiting. Here, a coupled finite element-boundary element method (coupled FE-BEM) approach is demonstrated for modeling light diffusion in 3D, which uses surfaces to model exterior tissues with BEM and a small number of volume nodes to model interior tissues with FEM. Such a coupled FE-BEM technique combines strengths of FEM and BEM by assuming homogeneous outer tissue regions and heterogeneous inner tissue regions. Results with FE-BEM show agreement with existing numerical models, having RMS differences of less than 0.5 for the logarithm of intensity and 2.5 degrees for phase of frequency domain boundary data. The coupled FE-BEM approach can model heterogeneity using a fraction of the volume nodes (4-22%) required by conventional FEM techniques. Comparisons of computational times showed that the coupled FE-BEM was faster than stand-alone FEM when the ratio of the number of surface to volume nodes in the mesh (N(s)/N(v)) was less than 20% and was comparable to stand-alone BEM ( ± 10%).
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spelling pubmed-29977102011-01-01 A coupled finite element-boundary element method for modeling Diffusion equation in 3D multi-modality optical imaging Srinivasan, Subhadra Ghadyani, Hamid R. Pogue, Brian W. Paulsen, Keith D. Biomed Opt Express Image Reconstruction and Inverse Problems Three dimensional image reconstruction for multi-modality optical spectroscopy systems needs computationally efficient forward solvers with minimum meshing complexity, while allowing the flexibility to apply spatial constraints. Existing models based on the finite element method (FEM) require full 3D volume meshing to incorporate constraints related to anatomical structure via techniques such as regularization. Alternate approaches such as the boundary element method (BEM) require only surface discretization but assume homogeneous or piece-wise constant domains that can be limiting. Here, a coupled finite element-boundary element method (coupled FE-BEM) approach is demonstrated for modeling light diffusion in 3D, which uses surfaces to model exterior tissues with BEM and a small number of volume nodes to model interior tissues with FEM. Such a coupled FE-BEM technique combines strengths of FEM and BEM by assuming homogeneous outer tissue regions and heterogeneous inner tissue regions. Results with FE-BEM show agreement with existing numerical models, having RMS differences of less than 0.5 for the logarithm of intensity and 2.5 degrees for phase of frequency domain boundary data. The coupled FE-BEM approach can model heterogeneity using a fraction of the volume nodes (4-22%) required by conventional FEM techniques. Comparisons of computational times showed that the coupled FE-BEM was faster than stand-alone FEM when the ratio of the number of surface to volume nodes in the mesh (N(s)/N(v)) was less than 20% and was comparable to stand-alone BEM ( ± 10%). Optical Society of America 2010-08-02 /pmc/articles/PMC2997710/ /pubmed/21152113 http://dx.doi.org/10.1364/BOE.1.000398 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
Srinivasan, Subhadra
Ghadyani, Hamid R.
Pogue, Brian W.
Paulsen, Keith D.
A coupled finite element-boundary element method for modeling Diffusion equation in 3D multi-modality optical imaging
title A coupled finite element-boundary element method for modeling Diffusion equation in 3D multi-modality optical imaging
title_full A coupled finite element-boundary element method for modeling Diffusion equation in 3D multi-modality optical imaging
title_fullStr A coupled finite element-boundary element method for modeling Diffusion equation in 3D multi-modality optical imaging
title_full_unstemmed A coupled finite element-boundary element method for modeling Diffusion equation in 3D multi-modality optical imaging
title_short A coupled finite element-boundary element method for modeling Diffusion equation in 3D multi-modality optical imaging
title_sort coupled finite element-boundary element method for modeling diffusion equation in 3d multi-modality optical imaging
topic Image Reconstruction and Inverse Problems
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2997710/
https://www.ncbi.nlm.nih.gov/pubmed/21152113
http://dx.doi.org/10.1364/BOE.1.000398
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