Quantitative laser speckle auto-inverse covariance imaging for robust estimation of blood flow

We present a quantitative model to provide robust estimation of the decorrelation time using laser speckle auto-inverse covariance. It has the advantages of independence from the statistical sample size, speckle size, static scattering, and detector noise. We have shown cerebral blood flow imaging through an intact mouse skull using this model. Phantom experiments and two animal models, middle cerebral artery occlusion, and cortical spreading depression were used to evaluate its performance.