Image reconstruction for diffuse optical tomography based on radiative transfer equation
type: Item
instance of: scholarly article
title: Image reconstruction for diffuse optical tomography based on radiative transfer equation
zbMATH Open document ID: 1343.92257
DOI: 10.1155/2015/286161
author: Bo Bi
author: Bo Han
author: Weimin Han
author: Jinping Tang
author: Li Li
published in: Computational \& Mathematical Methods in Medicine
publication date: 2016-09-02T00:00:00Z
review text: Summary: Diffuse optical tomography is a novel molecular imaging technology for small animal studies. Most known reconstruction methods use the diffusion equation (DA) as forward model, although the validation of DA breaks down in certain situations. In this work, we use the radiative transfer equation as forward model which provides an accurate description of the light propagation within biological media and investigate the potential of sparsity constraints in solving the diffuse optical tomography inverse problem. The feasibility of the sparsity reconstruction approach is evaluated by boundary angular-averaged measurement data and internal angular-averaged measurement data. Simulation results demonstrate that in most of the test cases the reconstructions with sparsity regularization are both qualitatively and quantitatively more reliable than those with standard \(L_2\) regularization. Results also show the competitive performance of the split Bregman algorithm for the DOT image reconstruction with sparsity regularization compared with other existing \(L_1\) algorithms.
Mathematics Subject Classification ID: 92C55
Mathematics Subject Classification ID: 94A08
zbMATH DE Number: 6622118
zbMATH Keywords: radiative transfer equation
zbMATH Keywords: diffuse optical tomography
zbMATH Keywords: sparsity reconstruction
zbMATH Keywords: \(L_2\) regularization
Wikidata QID: Q35025826
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2015/286161
OpenAlex ID: W2005819206
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description: scientific article; zbMATH DE number 6622118