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Virtual Journal for Biomedical Optics

Virtual Journal for Biomedical Optics

| EXPLORING THE INTERFACE OF LIGHT AND BIOMEDICINE

  • Editors: Andrew Dunn and Anthony Durkin
  • Vol. 6, Iss. 1 — Jan. 3, 2011

Performance evaluation of adaptive meshing algorithms for fluorescence diffuse optical tomography using experimental data

Lu Zhou, Birsen Yazıcı, Angelique B. F. Ale, and Vasilis Ntziachristos  »View Author Affiliations


Optics Letters, Vol. 35, Issue 22, pp. 3727-3729 (2010)
http://dx.doi.org/10.1364/OL.35.003727


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Abstract

Fluorescence diffuse optical tomography (FDOT) is a computationally demanding imaging problem. The discretizations of FDOT forward and inverse problems pose a trade-off between the accuracy and the computational efficiency of the image reconstruction. To address this trade-off, we analyzed the effect of discretization on the accuracy of FDOT imaging and proposed novel adaptive meshing algorithms for FDOT in a series of studies. In this Letter, we apply these new adaptive meshing algorithms to FDOT imaging using real data from a phantom experiment to demonstrate the practical advantages of our algorithms in FDOT image reconstruction.

© 2010 Optical Society of America

OCIS Codes
(170.3010) Medical optics and biotechnology : Image reconstruction techniques
(170.3880) Medical optics and biotechnology : Medical and biological imaging
(170.6960) Medical optics and biotechnology : Tomography

ToC Category:
Medical Optics and Biotechnology

History
Original Manuscript: May 4, 2010
Revised Manuscript: September 23, 2010
Manuscript Accepted: September 24, 2010
Published: November 2, 2010

Virtual Issues
Vol. 6, Iss. 1 Virtual Journal for Biomedical Optics

Citation
Lu Zhou, Birsen Yazıcı, Angelique B. F. Ale, and Vasilis Ntziachristos, "Performance evaluation of adaptive meshing algorithms for fluorescence diffuse optical tomography using experimental data," Opt. Lett. 35, 3727-3729 (2010)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=ol-35-22-3727


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References

  1. R. Weissleder and V. Ntziachristos, Nat. Med. 9, 123 (2003). [CrossRef] [PubMed]
  2. M. Guven, L. Reilly-Raska, L. Zhou, and B. Yazici, IEEE Trans. Med. Imaging 29, 217 (2010). [CrossRef] [PubMed]
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  5. M. Guven, L. Zhou, L. Reilly-Raska, and B. Yazici, IEEE Trans. Med. Imaging 29, 230 (2010). [CrossRef]
  6. L. Zhou and B. Yazici, “Discretization error analysis and adaptive meshing algorithms for fluorescence diffuse optical tomography in the presence of measurement noise,” IEEE Trans. Image Process. (to be published).
  7. In Eqs. , Dij=[σij2+∫Ωκ(r)ϕi2(r)(gj*)2(r)dr]1/2, where σij2 is the noise variance in Γij, κ represents the variance of μ, πij is the inverse problem solution when Γij=1 and Γkl=0, for all kl≠ij, k=1,…,NS and l=1,…,ND. Note that we use ∥·∥∞,k, ∥·∥0,k, and ∥·∥1,k to denote the L∞, L2, and H1 norms of a function on the kth element, and use ∥·∥∞ and ∥·∥0 to denote the L∞ and L2 norms of a function on the domain Ω.
  8. N. Deliolanis, T. Lasser, D. Hyde, A. Soubret, J. Ripoll, and V. Ntziachristos, Opt. Lett. 32, 382 (2007). [CrossRef] [PubMed]

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