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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Vol. 42, Iss. 16 — Jun. 1, 2003
  • pp: 3095–3108

Robust inference of baseline optical properties of the human head with three-dimensional segmentation from magnetic resonance imaging

Alex H. Barnett, Joseph P. Culver, A. Gregory Sorensen, Anders Dale, and David A. Boas  »View Author Affiliations


Applied Optics, Vol. 42, Issue 16, pp. 3095-3108 (2003)
http://dx.doi.org/10.1364/AO.42.003095


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Abstract

We model the capability of a small (6-optode) time-resolved diffuse optical tomography (DOT) system to infer baseline absorption and reduced scattering coefficients of the tissues of the human head (scalp, skull, and brain). Our heterogeneous three-dimensional diffusion forward model uses tissue geometry from segmented magnetic resonance (MR) data. Handling the inverse problem by use of Bayesian inference and introducing a realistic noise model, we predict coefficient error bars in terms of detected photon number and assumed model error. We demonstrate the large improvement that a MR-segmented model can provide: 2–10% error in brain coefficients (for 2 × 106 photons, 5% model error). We sample from the exact posterior and show robustness to numerical model error. This opens up the possibility of simultaneous DOT and MR for quantitative cortically constrained functional neuroimaging.

© 2003 Optical Society of America

OCIS Codes
(000.5490) General : Probability theory, stochastic processes, and statistics
(100.3190) Image processing : Inverse problems
(170.3010) Medical optics and biotechnology : Image reconstruction techniques
(170.6920) Medical optics and biotechnology : Time-resolved imaging
(170.7050) Medical optics and biotechnology : Turbid media

History
Original Manuscript: October 7, 2002
Revised Manuscript: January 10, 2003
Published: June 1, 2003

Citation
Alex H. Barnett, Joseph P. Culver, A. Gregory Sorensen, Anders Dale, and David A. Boas, "Robust inference of baseline optical properties of the human head with three-dimensional segmentation from magnetic resonance imaging," Appl. Opt. 42, 3095-3108 (2003)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-42-16-3095

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