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Biomedical Optics Express

Biomedical Optics Express

  • Editor: Joseph A. Izatt
  • Vol. 1, Iss. 1 — Aug. 2, 2010
  • pp: 209–222

Corrections to linear methods for diffuse optical tomography using approximation error modelling

Tanja Tarvainen, Ville Kolehmainen, Jari P. Kaipio, and Simon R. Arridge  »View Author Affiliations

Biomedical Optics Express, Vol. 1, Issue 1, pp. 209-222 (2010)

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Linear reconstruction methods in diffuse optical tomography have been found to produce reasonable good images in cases in which the variation in optical properties within the medium is relatively small and a reference measurement with known background optical properties is available. In this paper we examine the correction of errors when using a first order Born approximation with an infinite space Green’s function model as the basis for linear reconstruction in diffuse optical tomography, when real data is generated on a finite domain with possibly unknown background optical properties. We consider the relationship between conventional reference measurement correction and approximation error modelling in reconstruction. It is shown that, using the approximation error modelling, linear reconstruction method can be used to produce good quality images also in situations in which the background optical properties are not known and a reference is not available.

© 2010 Optical Society of America

OCIS Codes
(100.3190) Image processing : Inverse problems
(170.3010) Medical optics and biotechnology : Image reconstruction techniques
(170.6960) Medical optics and biotechnology : Tomography
(290.7050) Scattering : Turbid media

ToC Category:
Image Reconstruction and Inverse Problems

Original Manuscript: June 7, 2010
Revised Manuscript: July 9, 2010
Manuscript Accepted: July 9, 2010
Published: July 16, 2010

Virtual Issues
Optical Imaging and Spectroscopy (2010) Biomedical Optics Express

Tanja Tarvainen, Ville Kolehmainen, Jari P. Kaipio, and Simon R. Arridge, "Corrections to linear methods for diffuse optical tomography using approximation error modelling," Biomed. Opt. Express 1, 209-222 (2010)

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