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Random process estimator for laser speckle imaging of cerebral blood flow.

Miao P, Li N, Thakor NV, Tong S - Opt Express (2010)

Bottom Line: 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 (mean+/-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.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, P.R. China.

ABSTRACT
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 (mean+/-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.

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Related in: MedlinePlus

Denoising performance of random process estimator for structural imaging: the contrast values  along the vertical line in Fig. 2 (c) estimated from different number of frames: N=2 (a), N=10 (b), N=80 (c) using random process estimator and temporal LASCA.
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g003: Denoising performance of random process estimator for structural imaging: the contrast values along the vertical line in Fig. 2 (c) estimated from different number of frames: N=2 (a), N=10 (b), N=80 (c) using random process estimator and temporal LASCA.

Mentions: The contrast values along the vertical white line in Fig. 2(c) estimated from different number of frames using the two methods is plotted in Fig. 3Fig. 3


Random process estimator for laser speckle imaging of cerebral blood flow.

Miao P, Li N, Thakor NV, Tong S - Opt Express (2010)

Denoising performance of random process estimator for structural imaging: the contrast values  along the vertical line in Fig. 2 (c) estimated from different number of frames: N=2 (a), N=10 (b), N=80 (c) using random process estimator and temporal LASCA.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3369537&req=5

g003: Denoising performance of random process estimator for structural imaging: the contrast values along the vertical line in Fig. 2 (c) estimated from different number of frames: N=2 (a), N=10 (b), N=80 (c) using random process estimator and temporal LASCA.
Mentions: The contrast values along the vertical white line in Fig. 2(c) estimated from different number of frames using the two methods is plotted in Fig. 3Fig. 3

Bottom Line: 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 (mean+/-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.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, P.R. China.

ABSTRACT
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 (mean+/-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.

Show MeSH
Related in: MedlinePlus