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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. 8, Iss. 9 — Oct. 2, 2013

Methodology to optimize detector geometry in fluorescence tomography of tissue using the minimized curvature of the summed diffuse sensitivity projections

Robert W. Holt, Frederic L. Leblond, and Brian W. Pogue  »View Author Affiliations


JOSA A, Vol. 30, Issue 8, pp. 1613-1619 (2013)
http://dx.doi.org/10.1364/JOSAA.30.001613


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Abstract

The dependence of the sensitivity function in fluorescence tomography on the geometry of the excitation source and detection locations can severely influence an imaging system’s ability to recover fluorescent distributions. Here a methodology for choosing imaging configuration based on the uniformity of the sensitivity function is presented. The uniformity of detection sensitivity is correlated with reconstruction accuracy in silico, and reconstructions in a murine head model show that a detector configuration optimized using Nelder–Mead minimization improves recovery over uniformly sampled tomography.

© 2013 Optical Society of America

OCIS Codes
(120.4570) Instrumentation, measurement, and metrology : Optical design of instruments
(170.0110) Medical optics and biotechnology : Imaging systems
(170.6960) Medical optics and biotechnology : Tomography

ToC Category:
Imaging Systems

History
Original Manuscript: April 25, 2013
Revised Manuscript: June 26, 2013
Manuscript Accepted: June 27, 2013
Published: July 19, 2013

Virtual Issues
Vol. 8, Iss. 9 Virtual Journal for Biomedical Optics

Citation
Robert W. Holt, Frederic L. Leblond, and Brian W. Pogue, "Methodology to optimize detector geometry in fluorescence tomography of tissue using the minimized curvature of the summed diffuse sensitivity projections," J. Opt. Soc. Am. A 30, 1613-1619 (2013)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=josaa-30-8-1613


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References

  1. F. Leblond, K. M. Tichauer, and B. W. Pogue, “Singular value decomposition metrics show limitations of detector design in diffuse fluorescence tomography,” Biomed. Opt. Express 1, 1514–1531 (2010). [CrossRef]
  2. Z. Xu, X. Song, and J. Bai, “Singular value decomposition-based analysis on fluorescence molecular tomography in the mouse atlas,” in Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009 (Institute of Electrical and Electronics Engineers, 2009), pp. 3739–3742.
  3. E. E. Graves, J. P. Culver, J. Ripoll, R. Weissleder, and V. Ntziachristos, “Singular-value analysis and optimization of experimental parameters in fluorescence molecular tomography,” J. Opt. Soc. Am. A 21, 231–241 (2004). [CrossRef]
  4. J. P. Culver, V. Ntziachristos, M. J. Holboke, and A. G. Yodh, “Optimization of optode arrangements for diffuse optical tomography: a singular-value analysis,” Opt. Lett. 26, 701–703 (2001). [CrossRef]
  5. D. Karkala and P. K. Yalavarthy, “Data-resolution based optimization of the data-collection strategy for near infrared diffuse optical tomography,” Med. Phys. 39, 4715–4725 (2012). [CrossRef]
  6. J. Chen, V. Venugopal, F. Lesage, and X. Intes, “Time-resolved diffuse optical tomography with patterned-light illumination and detection,” Opt. Lett. 35, 2121–2123 (2010). [CrossRef]
  7. S. Belanger, M. Abran, X. Intes, C. Casanova, and F. Lesage, “Real-time diffuse optical tomography based on structured illumination,” J. Biomed. Opt. 15, 016006 (2010). [CrossRef]
  8. F. Leblond, S. C. Davis, P. A. Valdes, and B. W. Pogue, “Pre-clinical whole-body fluorescence imaging: review of instruments, methods and applications,” J. Photochem. Photobiol. B 98, 77–94 (2010). [CrossRef]
  9. K. M. Tichauer, R. W. Holt, F. El-Ghussein, Q. Zhu, H. Dehghani, F. Leblond, and B. W. Pogue, “Imaging workflow and calibration for CT-guided time-domain fluorescence tomography,” Biomed. Opt. Express 2, 3021–3036 (2011). [CrossRef]
  10. H. Dehghani, M. E. Eames, P. K. Yalavarthy, S. C. Davis, S. Srinivasan, C. M. Carpenter, B. W. Pogue, and K. D. Paulsen, “Near infrared optical tomography using NIRFAST: algorithm for numerical model and image reconstruction,” Commun. Numer. Methods Eng. 25, 711–732 (2009). [CrossRef]
  11. L. I. Rudin, S. Osher, and E. Fatemi, “Nonlinear total variation based noise removal algorithms,” Phys. Rev. D 60, 259–268 (1992).
  12. M. J. D. Powell, “On search directions for minimization algorithms,” Math. Program. 4, 193–201 (1973). [CrossRef]
  13. J. A. Nelder and R. Mead, “A simplex-method for function minimization,” Comput. J. 7, 308–313 (1965).
  14. J. C. Lagarias, J. A. Reeds, M. H. Wright, and P. E. Wright, “Convergence properties of the Nelder–Mead simplex method in low dimensions,” SIAM J. Optim. 9, 112–147 (1998). [CrossRef]
  15. R. W. Holt, K. M. Tichauer, H. Dehghani, B. W. Pogue, and F. Leblond, “Multiple-gate time domain diffuse fluorescence tomography allows more sparse tissue sampling without compromising image quality,” Opt. Lett. 37, 2559–2561 (2012). [CrossRef]
  16. R. P. Jagannath and P. K. Yalavarthy, “Efficient gradient-free simplex method for estimation of optical properties in image-guided diffuse optical tomography,” J. Biomed. Opt. 18, 030503 (2013). [CrossRef]
  17. C. Vinegoni, D. Razansky, J. L. Figueiredo, M. Nahrendorf, V. Ntziachristos, and R. Weissleder, “Normalized Born ratio for fluorescence optical projection tomography,” Opt. Lett. 34, 319–321 (2009). [CrossRef]

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