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Approximation errors and model reduction in three-dimensional diffuse optical tomography

Kolehmainen, V; Schweiger, M; Nissila, I; Tarvainen, T; Arridge, SR; Kaipio, JP; (2009) Approximation errors and model reduction in three-dimensional diffuse optical tomography. J OPT SOC AM A , 26 (10) 2257 - 2268.

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Abstract

Model reduction is often required in diffuse optical tomography (DOT), typically because of limited available computation time or computer memory. In practice, this means that one is bound to use coarse mesh and truncated computation domain in the model for the forward problem. We apply the (Bayesian) approximation error model for the compensation of modeling errors caused by domain truncation and a coarse computation mesh in DOT. The approach is tested with a three-dimensional example using experimental data. The results show that when the approximation error model is employed, it is possible to use mesh densities and computation domains that would be unacceptable with a conventional measurement error model. (C) 2009 Optical Society of America

Type:Article
Title:Approximation errors and model reduction in three-dimensional diffuse optical tomography
Keywords:IMAGE-RECONSTRUCTION
UCL classification:UCL > School of BEAMS > Faculty of Engineering Science > Computer Science

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