Level-set algorithm for the reconstruction of functional activation in near-infrared spectroscopic imaging

Mathews Jacob; Yoram Bresler; Vlad Toronov; Xiaofeng Zhang; Andrew Webb

doi:10.1117/1.2400595

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Level-set algorithm for the reconstruction of functional activation in near-infrared spectroscopic imaging

Journal article

Open access

Peer reviewed

Level-set algorithm for the reconstruction of functional activation in near-infrared spectroscopic imaging

Mathews Jacob, Yoram Bresler, Vlad Toronov, Xiaofeng Zhang and Andrew Webb

Journal of biomedical optics, Vol.11(6), pp.064029-064029

2006

DOI: 10.1117/1.2400595

PMCID: PMC2778259

PMID: 17212552

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https://doi.org/10.1117/1.2400595View

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Abstract

We introduce a new algorithm for the reconstruction of functional brain activations from near-infrared spectroscopic imaging (NIRSI) data. While NIRSI offers remarkable biochemical specificity, the attainable spatial resolution with this technique is rather limited, mainly due to the highly scattering nature of brain tissue and the low number of measurement channels. Our approach exploits the support-limited (spatially concentrated) nature of the activations to make the reconstruction problem well-posed. The new algorithm considers both the support and the function values of the activations as unknowns and estimates them from the data. The support of the activations is represented using a level-set scheme. We use a two-step alternating iterative scheme to solve for the activations. Since our approach uses the inherent nature of functional activations to make the problem well-posed, it provides reconstructions with better spatial resolution, fewer artifacts, and is more robust to noise than existing techniques. Numerical simulations and experimental data indicate a significant improvement in the quality (resolution and robustness to noise) over standard techniques such as truncated conjugate gradients (TCG) and simultaneous iterative reconstruction technique (SIRT) algorithms. Furthermore, results on experimental data obtained from simultaneous functional magnetic resonance imaging (fMRI) and optical measurements show much closer agreement of the optical reconstruction using the new approach with fMRI images than TCG and SIRT.

inverse problems

image reconstruction

infrared spectroscopy

Details

Title: Subtitle: Level-set algorithm for the reconstruction of functional activation in near-infrared spectroscopic imaging
Creators: Mathews Jacob - University of Illinois at Urbana-Champaign Urbana, Illinois 61820
Yoram Bresler - University of Illinois at Urbana-Champaign Urbana, Illinois 61820
Vlad Toronov - University of Illinois at Urbana-Champaign Urbana, Illinois 61820
Xiaofeng Zhang - Pennsylvania State University, University Park, Pennsylvania 16802
Andrew Webb - Pennsylvania State University, University Park, Pennsylvania 16802
Resource Type: Journal article
Publication Details: Journal of biomedical optics, Vol.11(6), pp.064029-064029
DOI: 10.1117/1.2400595
PMID: 17212552
PMCID: PMC2778259
NLM abbreviation: J Biomed Opt
ISSN: 1083-3668
eISSN: 1560-2281
Language: English
Date published: 2006
Academic Unit: Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Iowa Neuroscience Institute; Radiation Oncology
Record Identifier: 9984070102902771

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