SUSHI: Sparsity-Based Ultrasound Super-Resolution Hemodynamic Imaging

Identifying and visualizing vasculature within organs and tumors has major implications in managing cardiovascular diseases and cancer. Contrast-enhanced ultrasound scans detect slow-flowing blood, facilitating noninvasive perfusion measurements. However, their limited spatial resolution prevents the depiction of microvascular structures. Recently, superlocalization ultrasonography techniques have surpassed this limit. However, they require long acquisition times of several minutes, preventing the detection of hemodynamic changes. We present a fast super-resolution method that exploits sparsity in the underlying vasculature and statistical independence within the measured signals. Similar to super-localization techniques, this approach improves the spatial resolution by up to an order of magnitude compared to standard scans. Unlike super-localization methods, it requires acquisition times of only tens of milliseconds. We demonstrate a temporal resolution of similar to 25 Hz, which may enable functional super-resolution imaging deep within the tissue, surpassing the temporal resolution limitations of current superresolution methods, e. g., in neural imaging. The subsecond acquisitions make our approach robust to motion artifacts, simplifying in vivo use of super-resolution ultrasound.