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Virtual Journal for Biomedical Optics

Virtual Journal for Biomedical Optics


  • Editor: Gregory W. Faris
  • Vol. 5, Iss. 2 — Jan. 21, 2010

Random process estimator for laser speckle imaging of cerebral blood flow

Peng Miao, Nan Li, Nitish V. Thakor, and Shanbao Tong  »View Author Affiliations

Optics Express, Vol. 18, Issue 1, pp. 218-236 (2010)

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In this paper, we develop a random process theory to explain the laser speckle phenomena. The relation between the probability distribution of speckle’s integrated intensity random process Y ( t ) and the relative velocity v ( t ) is derived. Based on the random process theory, traditional spatial or temporal laser speckle contrast analysis (i.e. spatial or temporal LASCA) can be derived as the spatial or temporal estimators respectively. Both spatial LASCA and temporal LASCA suffer from noise due to insufficient statistics and nonstationarity in either spatial or temporal domain. Furthermore, either LASCA results in a reduction of spatial or temporal resolution. A new random process estimator is proposed and able to overcome these drawbacks. In an in-vitro study, random process estimator outperforms either spatial LASCA or temporal LASCA by providing much higher SNR (random process estimator vs. spatial LASCA vs. temporal LASCA: 33.64±6.87 ( m e a n ± s . t . d . ) vs. 9.08±2.85 vs. 3.83±1.05). In an in-vivo structural imaging study, random process estimator efficiently suppresses the noise in contrast image and thus improves the distinguishability of small vessels. In a functional imaging study of cerebral blood flow change in the somatosensory cortex induced by rat’s hind paw stimulation, random process estimator provides much lower estimation errors in single trial data (random process estimator vs. temporal LASCA: 0.31±0.03 vs. 1.36±0.09) and finally leads to higher resolution spatiotemporal patterns of cerebral blood flow.

© 2009 OSA

OCIS Codes
(110.4280) Imaging systems : Noise in imaging systems
(110.6150) Imaging systems : Speckle imaging
(170.3880) Medical optics and biotechnology : Medical and biological imaging

ToC Category:
Medical Optics and Biotechnology

Original Manuscript: October 26, 2009
Revised Manuscript: December 7, 2009
Manuscript Accepted: December 14, 2009
Published: December 23, 2009

Virtual Issues
Vol. 5, Iss. 2 Virtual Journal for Biomedical Optics

Peng Miao, Nan Li, Nitish V. Thakor, and Shanbao Tong, "Random process estimator for laser speckle imaging of cerebral blood flow," Opt. Express 18, 218-236 (2010)

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  1. J. Briers, “Laser Doppler, speckle and related techniques for blood perfusion mapping and imaging,” Physiol. Meas. 22(4), 35–66 (2001). [CrossRef]
  2. A. K. Dunn, H. Bolay, M. A. Moskowitz, and D. A. Boas, “Dynamic Imaging of Cerebral Blood Flow Using Laser Speckle,” J. Cereb. Blood Flow Metab. 21(3), 195–201 (2001). [CrossRef] [PubMed]
  3. D. Zhu, W. Lu, Y. Weng, H. Cui, and Q. Luo, “Monitoring thermal-induced changes in tumor blood flow and microvessels with laser speckle contrast imaging,” Appl. Opt. 46(10), 1911–1917 (2007). [CrossRef] [PubMed]
  4. H. Cheng, Y. Yan, and T. Duong, “Temporal statistical analysis of laser speckle images and its application to retinal blood-flow imaging,” Opt. Express 16(14), 214–219 (2008). [CrossRef]
  5. A. Kharlamov, B. R. Brown, K. A. Easley, and S. C. Jones, “Heterogeneous response of cerebral blood flow to hypotension demonstrated by laser speckle imaging flowmetry in rats,” Neurosci. Lett. 368(2), 151–156 (2004). [CrossRef] [PubMed]
  6. T. Durduran, M. G. Burnett, G. Yu, C. Zhou, D. Furuya, A. G. Yodh, J. A. Detre, and J. H. Greenberg, “Spatiotemporal Quantification of Cerebral Blood Flow During Functional Activation in Rat Somatosensory Cortex Using Laser-Speckle Flowmetry,” J. Cereb. Blood Flow Metab. 24(5), 518–525 (2004). [CrossRef] [PubMed]
  7. J. Briers and S. Webster, “Laser speckle contrast analysis (LASCA): a nonscanning, full-field technique for monitoring capillary blood flow,” J. Biomed. Opt. 1(2), 174–179 (1996). [CrossRef]
  8. H. Cheng, Q. Luo, S. Zeng, S. Chen, J. Cen, and H. Gong, “Modified laser speckle imaging method with improved spatial resolution,” J. Biomed. Opt. 8(3), 559–564 (2003). [CrossRef] [PubMed]
  9. P. Miao, M. Li, H. Fontenelle, A. Bezerianos, Y. Qiu, and S. Tong, “Imaging the Cerebral Blood Flow with Enhanced Laser Speckle Contrast Analysis (eLASCA) by Monotonic Point Transformation,” IEEE Trans. Biomed. Eng. 56(4), 1127–1133 (2009). [CrossRef] [PubMed]
  10. P. Lemieux and D. Durian, “Investigating non-Gaussian scattering processes by using nth-order intensity correlation functions,” J. Opt. Soc. Am. A 16(7), 1651–1664 (1999). [CrossRef]
  11. D. Boas and A. Yodh, “Spatially varying dynamical properties of turbid media probed with diffusing temporal light correlation,” J. Opt. Soc. Am. A 14(1), 192–215 (1997). [CrossRef]
  12. B. Berne, and R. Pecora, Dynamic Light Scattering: with Applications to Chemistry, Biology and Physics (Dover Publications, 2000).
  13. A. Fercher and J. Briers, “Flow visualization by means of single-exposure speckle photography,” Opt. Commun. 37(5), 326–330 (1981). [CrossRef]
  14. D. J. Pine, D. A. Weitz, P. M. Chaikin, and E. Herbolzheimer, “Diffusing wave spectroscopy,” Phys. Rev. Lett. 60(12), 1134–1137 (1988). [CrossRef] [PubMed]
  15. R. Bandyopadhyay, A. Gittings, S. Suh, P. Dixon, and D. Durian, “Speckle-visibility spectroscopy: A tool to study time-varying dynamics,” Rev. Sci. Instrum. 76(9), 093110 (2005). [CrossRef]
  16. G. Grimmett, and D. Stirzaker, Probability and random processes (Oxford University Press, 2001).
  17. P. K. Dixon and D. J. Durian, “Speckle Visibility Spectroscopy and Variable Granular Fluidization,” Phys. Rev. Lett. 90(18), 184302 (2003). [CrossRef] [PubMed]
  18. J. W. Goodman, Statistical Optics (Wiley 1985).
  19. P. Zakharov, A. Völker, A. Buck, B. Weber, and F. Scheffold, “Quantitative modeling of laser speckle imaging,” Opt. Lett. 31(23), 3465–3467 (2006). [CrossRef] [PubMed]
  20. A. B. Parthasarathy, W. J. Tom, A. Gopal, X. Zhang, and A. K. Dunn, “Robust flow measurement with multi-exposure speckle imaging,” Opt. Express 16(3), 1975–1989 (2008). [CrossRef] [PubMed]
  21. H. Cheng, Y. Yan, and T. Q. Duong, “Laser speckle imaging of rat retinal blood flow with hybrid temporal and spatial analysis method,” Proc. SPIE 7163, 716304 (2009). [CrossRef]

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