Research Papers: Imaging

Combining energy and Laplacian regularization to accurately retrieve the depth of brain activity of diffuse optical tomographic data

[+] Author Affiliations
Antonio M. Chiarelli, Edward L. Maclin, Kathy A. Low, Monica Fabiani, Gabriele Gratton

University of Illinois, Beckman Institute, 405 North Mathews Avenue, Urbana, Illinois 61801, United States

Kyle E. Mathewson

University of Alberta, Department of Psychology, P217 Biological Sciences Building, Edmonton, Alberta T6G 2E9, Canada

J. Biomed. Opt. 21(3), 036008 (Mar 18, 2016). doi:10.1117/1.JBO.21.3.036008
History: Received December 2, 2015; Accepted February 22, 2016
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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.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Antonio M. Chiarelli ; Edward L. Maclin ; Kathy A. Low ; Kyle E. Mathewson ; Monica Fabiani, et al.
"Combining energy and Laplacian regularization to accurately retrieve the depth of brain activity of diffuse optical tomographic data", J. Biomed. Opt. 21(3), 036008 (Mar 18, 2016). ; http://dx.doi.org/10.1117/1.JBO.21.3.036008


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