Physics-informed neural network for mapping vascular and tissue dynamics using laser speckle contrast imaging

Significance

Quantitatively mapping both cerebral blood flow and tissue dynamics from laser speckle contrast imaging (LSCI) is powerful for studying cerebral blood flow and neurovascular coupling, particularly in the context of stroke. Conventional multi-exposure fitting is slow and difficult to scale. Efficient, physically grounded methods are needed to extract both vascular and tissue dynamic biomarkers from LSCI data.