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

Abstract

Random matrix theory provides new insights into multiple scattering in random media. 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 matrix constructed using dynamically-backscattered speckle images. In this study, this new strategy was applied to laser speckle contrast imaging (LSCI) of in-vivo blood flow. The random matrix-based method was adapted and parameterized using electric field Monte Carlo simulations and in-vitro blood flow phantom experiments. The new method was further applied in in-vivo experiments, demonstrating the benefits of separating the single- and multiple-scattering components, and was compared with the traditional temporal LASCA method. More specifically, the new method captures stimulus-induced functional changes in blood flow and tissue perfusion in the superficial and deeper layers. The new method extends the ability of LSCI to image functional and pathological changes.