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Dynamic light scattering methods6/26/2023 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. Laser speckle intensity temporal autocorrelation function 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. MESI was first used to quantify the impact of static scattering to improve estimates of relative blood flow changes ( 9) but was not able to resolve questions regarding the form of the field correlation function due to insufficient temporal sampling to resolve intensity fluctuations directly. The multiexposure speckle imaging (MESI) technique ( 9, 10, 21) has been introduced to probe the temporal dynamics of the speckles indirectly by changing the exposure time to measure the impact on speckle contrast. 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.Įxperimental approaches and processing schemes have been suggested to address measurement noise ( 9, 17) and static scattering ( 10, 11, 13, 20) as well as to investigate the form of the field correlation function ( 3, 10). 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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