We have analyzed the image formation and dynamic properties in laser speckle imaging (LSI) both experimentally and with Monte Carlo simulation. We show for the case of a liquid inclusion that the spatial resolution and the signal itself are both significantly affected by scattering from the turbid environment. Multiple scattering leads to blurring of the dynamic inhomogeneity as detected by LSI. The presence of a nonfluctuating component of scattered light results in the significant increase in the measured image contrast and complicates the estimation of the relaxation time. We present a refined processing scheme that allows a correct estimation of the relaxation time from LSI data.

Laser speckle imaging (LSI) based on the speckle contrast analysis is a simple and robust technique for imaging of heterogeneous dynamics. LSI finds frequent application for dynamical mapping of cerebral blood flow, as it features high spatial and temporal resolution. However, the quantitative interpretation of the acquired data is not straightforward for the common case of a speckle field formed by both by moving and localized scatterers such as blood cells and bone or tissue. Here we present a novel processing scheme, we call dynamic laser speckle imaging (dLSI), that can be used to correctly extract the temporal correlation parameters from the speckle contrast measured in the presence of a static or slow-evolving background. The static light contribution is derived from the measurements by cross-correlating sequential speckle images. In-vivo speckle imaging experiments performed in the rodent brain demonstrate that dLSI leads to improved results. The cerebral hemodynamic response observed through the thinned and intact skull are more pronounced in the dLSI images as compared to the standard speckle contrast analysis. The proposed method also yields benefits with respect to the quality of the speckle images by suppressing contributions of non-uniformly distributed specular reflections.Dynamic laser speckle imaging of cerebral blood flow Abstract: Laser speckle imaging (LSI) based on the speckle contrast analysis is a simple and robust technique for imaging of heterogeneous dynamics. LSI finds frequent application for dynamical mapping of cerebral blood flow, as it features high spatial and temporal resolution. However, the quantitative interpretation of the acquired data is not straightforward for the common case of a speckle field formed by both by moving and localized scatterers such as blood cells and bone or tissue. Here we present a novel processing scheme, we call dynamic laser speckle imaging (dLSI), that can be used to correctly extract the temporal correlation parameters from the speckle contrast measured in the presence of a static or slow-evolving background. The static light contribution is derived from the measurements by cross-correlating sequential speckle images. In-vivo speckle imaging experiments performed in the rodent brain demonstrate that dLSI leads to improved results. The cerebral hemodynamic response observed through the thinned and intact skull are more pronounced in the dLSI images as compared to the standard speckle contrast analysis. The proposed method also yields benefits with respect to the quality of the speckle images by suppressing contributions of non-uniformly distributed specular reflections. ©2009 Optical Society of America

We present a detection scheme for diffusing-wave spectroscopy (DWS) based on a two-cell geometry that allows efficient ensemble averaging. This is achieved by putting a fast rotating diffuser in the optical path between laser and sample. We show that the recorded (multispeckle) correlation echoes provide an ensemble averaged signal that does not require additional time averaging. Furthermore, combined with traditional two-cell DWS, the full intensity autocorrelation function can be measured with a single experimental setup. The scheme provides access to a large range of correlation times thus opening an experimental window for the study of slowly relaxing and arrested systems, such as viscoelastic complex fluids, colloidal glasses, and gels.

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We report on a new type of experiment that enables us to monitor spatially and temporally heterogeneous dynamic properties in complex fluids. Our approach is based on the analysis of near-field speckles produced by light diffusely reflected from the superficial volume of a strongly scattering medium. By periodic modulation of an incident speckle beam we obtain pixel-wise ensemble averages of the structure function coefficient, a measure of the dynamic activity. To illustrate the application of our approach we follow the different stages in the drying process of a colloidal thin film. We show that we can access ensemble averaged dynamic properties on length scales as small as ten micrometers over the full field of view.