Application of diffusion approximation in quantitative photoacoustic tomography in the presence of low-scattering regions

被引:5
|
作者
Hanninen, Niko [1 ]
Pulkkinen, Aki [1 ]
Leino, Aleksi [1 ]
Tarvainen, Tanja [1 ,2 ]
机构
[1] Univ Eastern Finland, Dept Appl Phys, POB 1627, Kuopio 70211, Finland
[2] UCL, Dept Comp Sci, Gower St, London WC1E 6BT, England
基金
芬兰科学院;
关键词
Inverse problems; Quantitative photoacoustic tomography; Uncertainty quantification; Bayesian methods; Model reduction; Bayesian approximation error modeling; OPTICAL TOMOGRAPHY; IMAGE-RECONSTRUCTION; TRANSPORT; MODEL; DISTRIBUTIONS; COMPENSATION; BOUNDARY; ERRORS;
D O I
10.1016/j.jqsrt.2020.107065
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
In quantitative photoacoustic tomography, the aim is to reconstruct distributions of optical parameters of an imaged target from an initial pressure distribution obtained from ultrasound measurements. In order to obtain accurate and quantitative information on the optical parameters, modeling light transport in the target is required. Utilizing an approximative model for light transport would be favorable to reduce the computational cost, but the modeling errors of the approximative model can result in significant errors in the reconstructions. In this work, we approach the image reconstruction problem of quantitative photoacoustic tomography in the Bayesian framework. We utilize the Bayesian approximation error method to compensate for the modeling errors between the diffusion approximation and Monte Carlo model for light transport. The approach is studied with two-dimensional numerical simulations with varying optical parameters and noise levels. The results show that Bayesian approximation error method can be used to reduce the effects of the modeling errors in quantitative photoacoustic tomography in a wide range of optical parameters. (C) 2020 Elsevier Ltd. All rights reserved.
引用
收藏
页数:15
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