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Random matrix theory provides new insights into multiple scattering in randommedia. In a recent study, we demonstrated the statistical separation of single-and multiple-scattering components based on a Wishart random matrix. The first-and second-order moments were estimated through a Wishart random matrixconstructed using dynamically-backscattered speckle images. In this study, thisnew strategy was applied to laser speckle contrast imaging (LSCI) of in-vivoblood flow. The random matrix-based method was adapted and parameterized usingelectric field Monte Carlo simulations and in-vitro blood flow phantomexperiments. The new method was further applied in in-vivo experiments,demonstrating the benefits of separating the single- and multiple-scatteringcomponents, and was compared with the traditional temporal LASCA method. Morespecifically, the new method captures stimulus-induced functional changes inblood flow and tissue perfusion in the superficial and deeper layers. The newmethod extends the ability of LSCI to image functional and pathologicalchanges.

Extracting single- and multiple-scattering components in laser speckle contrast imaging of tissue blood flow