Research Papers

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

[+] Author Affiliations
Mathews Jacob, Yoram Bresler, Vlad Toronov

University of Illinois at Urbana-Champaign, Urbana, Illinois 61820

Xiaofeng Zhang, Andrew Webb

Pennsylvania State University, University Park Pennsylvania 16802

J. Biomed. Opt. 11(6), 064029 (December 08, 2006). doi:10.1117/1.2400595
History: Received February 07, 2006; Revised July 11, 2006; Accepted July 12, 2006; Published December 08, 2006; Online December 08, 2006
Text Size: A A A

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.

Figures in this Article
© 2006 Society of Photo-Optical Instrumentation Engineers

Citation

Mathews Jacob ; Yoram Bresler ; Vlad Toronov ; Xiaofeng Zhang and Andrew Webb
"Level-set algorithm for the reconstruction of functional activation in near-infrared spectroscopic imaging", J. Biomed. Opt. 11(6), 064029 (December 08, 2006). ; http://dx.doi.org/10.1117/1.2400595


Tables

Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

PubMed Articles
Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.