![]() ![]() ![]() Figure 1C shows that g 2(τ = 0 μs) is not spatially uniform, that is, it varies from location to location with (i) larger vessels having a reduced g 2(τ = 0 μs) value and (ii) some of the small vessels having g 2(τ = 0 μs) values larger than the surrounding parenchyma (see fig. For pixels belonging to parenchymal regions, the correlation function decays slower compared with that from the pixels of larger surface vessels, which, in turn, decays slower for the smaller vessels than for the large vessels as the larger vessels generally have faster blood flow (consequently one can expect faster decay for arteries than the veins, even if the vessel diameter is the same). The g 2(τ = 440 μs) shows an example of the intensity autocorrelation function being fully decorrelated for most of the vessels, but not for the parenchymal regions. Examples of the calculated images of g 2(τ = 0 μs) and g 2(τ = 440 μs) and the measured g 2(τ) for different regions of interest are shown in Fig. We apply DLSI to measure the intensity autocorrelation function g 2(τ) in the mouse brain ( Fig. RESULTS Laser speckle intensity temporal autocorrelation function China dynamic light box how to#It allows us to solve the problem of how to quantitatively interpret data measured by methods in which g 1(τ) is assumed beforehand, including LSCI ( 8, 18, 26), MESI ( 9, 10) and LDF ( 7, 27, 28). DLSI permits estimation of the best-fitting light scattering model directly for every pixel individually, resulting in a high-resolution quantitative image of the dynamics and scattering properties of the particles in the sample. It combines (i) the ability to resolve the temporal speckle intensity fluctuations and directly measure g 2(τ), as in dynamic light scattering ( 22, 23) and diffuse correlation spectroscopy ( 24, 25) techniques, with (ii) high-resolution (limited only by the objective) wide-field imaging, typical for LSCI and MESI. Using a high-speed camera and recording back-scattered laser light at more than 20,000 frames/s, we introduce the first wide-field dynamic light scattering imaging (DLSI) for in vivo biomedical applications. ![]() Although these forms of the field correlation functions have been established for over 30 years, there is no agreement nor experimental support on what scattering and motion regimes are relevant for the varied biomedical applications. The form of g 1(τ) depends on the amount of light scattering (i.e., single or multiple scattering) and the type of particle motion (i.e., ordered or unordered) ( 3, 7, 19). The relation between g 2(τ) and g 1(τ) depends on the amount of static scattering present in the sample ( 9– 13), measurement-specific parameters related to source coherence ( 14, 15), detector speckle averaging ( 16) and detector noise ( 9, 17, 18). The latter can be quantitatively related to the dynamics of the light scattering particles including flowing red blood cells ( 7, 8). The model is defined by the form of the intensity autocorrelation function g 2(τ), which is related to the field temporal autocorrelation function g 1(τ). The question of the appropriate model to use to interpret laser speckle fluctuations has been debated for decades, especially in laser Doppler flowmetry (LDF) and laser speckle contrast imaging (LSCI) blood flow measurement applications ( 1– 6). ![]()
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