Importance Sampling Approach for the Nonstationary Approximation Error Method

2010 ◽  
Author(s):  
J. M. J. Huttunen ◽  
A. Lehikoinen ◽  
J. Hämäläinen ◽  
J. P. Kaipio ◽  
Theodore E. Simos ◽  
...  
Keyword(s):  
Importance Sampling ◽  
Approximation Error ◽  
Error Method ◽  
Sampling Approach

Importance sampling approach for the nonstationary approximation error method

2010 ◽  
Vol 26 (12) ◽  
pp. 125003 ◽  
Author(s):  
J M J Huttunen ◽  
A Lehikoinen ◽  
J Hämäläinen ◽  
J P Kaipio
Keyword(s):  
Importance Sampling ◽  
Approximation Error ◽  
Error Method ◽  
Sampling Approach

scholarly journals Image Reconstruction with Reliability Assessment in Quantitative Photoacoustic Tomography

2018 ◽  
Vol 4 (12) ◽  
pp. 148 ◽  
Author(s):  
Niko Hänninen ◽  
Aki Pulkkinen ◽  
Tanja Tarvainen
Keyword(s):  
Approximation Error ◽  
Initial Pressure ◽  
Photoacoustic Tomography ◽  
Imaging Method ◽  
Optical Parameters ◽  
Reconstruction Method ◽  
Reconstruction Procedure ◽  
Modeling Errors ◽  
Bayesian Approximation ◽  
Error Method

Quantitative photoacoustic tomography is a novel imaging method which aims to reconstruct optical parameters of an imaged target based on initial pressure distribution, which can be obtained from ultrasound measurements. In this paper, a method for reconstructing the optical parameters in a Bayesian framework is presented. In addition, evaluating the credibility of the estimates is studied. Furthermore, a Bayesian approximation error method is utilized to compensate the modeling errors caused by coarse discretization of the forward model. The reconstruction method and the reliability of the credibility estimates are investigated with two-dimensional numerical simulations. The results suggest that the Bayesian approach can be used to obtain accurate estimates of the optical parameters and the credibility estimates of these parameters. Furthermore, the Bayesian approximation error method can be used to compensate for the modeling errors caused by a coarse discretization, which can be used to reduce the computational costs of the reconstruction procedure. In addition, taking the modeling errors into account can increase the reliability of the credibility estimates.

Approximation error method for full-wave tomography

2013 ◽  
Vol 133 (5) ◽  
pp. 3230-3230 ◽  
Author(s):  
Janne Koponen ◽  
Tomi Huttunen ◽  
Tanja Tarvainen ◽  
Jari Kaipio
Keyword(s):  
Approximation Error ◽  
Full Wave ◽  
Wave Tomography ◽  
Error Method

Chance-constrained problems and rare events: an importance sampling approach

2015 ◽  
Vol 157 (1) ◽  
pp. 153-189 ◽  
Author(s):  
Javiera Barrera ◽  
Tito Homem-de-Mello ◽  
Eduardo Moreno ◽  
Bernardo K. Pagnoncelli ◽  
Gianpiero Canessa
Keyword(s):  
Importance Sampling ◽  
Rare Events ◽  
Constrained Problems ◽  
Sampling Approach

On an automatic and optimal importance sampling approach with applications in finance

2016 ◽  
Vol 16 (8) ◽  
pp. 1259-1271 ◽  
Author(s):  
Huei-Wen Teng ◽  
Cheng-Der Fuh ◽  
Chun-Chieh Chen
Keyword(s):  
Importance Sampling ◽  
Sampling Approach
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