Share Email Print
cover

Journal of Biomedical Optics • new

Combining energy and Laplacian regularization to accurately retrieve the depth of brain activity of diffuse optical tomographic data
Author(s): Antonio M. Chiarelli; Edward L. Maclin; Kathy A. Low; Kyle E. Mathewson; Monica Fabiani; Gabriele Gratton
Format Member Price Non-Member Price
PDF $20.00 $25.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Diffuse optical tomography (DOT) provides data about brain function using surface recordings. Despite recent advancements, an unbiased method for estimating the depth of absorption changes and for providing an accurate three-dimensional (3-D) reconstruction remains elusive. DOT involves solving an ill-posed inverse problem, requiring additional criteria for finding unique solutions. The most commonly used criterion is energy minimization (energy constraint). However, as measurements are taken from only one side of the medium (the scalp) and sensitivity is greater at shallow depths, the energy constraint leads to solutions that tend to be small and superficial. To correct for this bias, we combine the energy constraint with another criterion, minimization of spatial derivatives (Laplacian constraint, also used in low resolution electromagnetic tomography, LORETA). Used in isolation, the Laplacian constraint leads to solutions that tend to be large and deep. Using simulated, phantom, and actual brain activation data, we show that combining these two criteria results in accurate (error <2  mm) absorption depth estimates, while maintaining a two-point spatial resolution of <24  mm up to a depth of 30 mm. This indicates that accurate 3-D reconstruction of brain activity up to 30 mm from the scalp can be obtained with DOT.

Paper Details

Date Published: 18 March 2016
PDF: 17 pages
J. Biomed. Opt. 21(3) 036008 doi: 10.1117/1.JBO.21.3.036008
Published in: Journal of Biomedical Optics Volume 21, Issue 3
Show Author Affiliations
Antonio M. Chiarelli, Beckman Institute for Advanced Science and Technology (United States)
Edward L. Maclin, Beckman Institute for Advanced Science and Technology (United States)
Kathy A. Low, Beckman Institute for Advanced Science and Technology (United States)
Kyle E. Mathewson, Univ. of Alberta (Canada)
Monica Fabiani, Beckman Institute for Advanced Science and Technology (United States)
Gabriele Gratton, Beckman Institute for Advanced Science and Technology (United States)


© SPIE. Terms of Use
Back to Top