SUSHI: Sparsity-based Ultrasound Super-resolution Hemodynamic Imaging

TL;DR

This paper introduces a rapid super-resolution ultrasound imaging method that leverages sparsity and statistical independence, achieving high spatial and temporal resolution in under a second, suitable for in-vivo applications.

Contribution

The novel approach significantly reduces acquisition time compared to existing super-localization techniques while maintaining high spatial resolution, enabling real-time functional imaging.

Findings

Achieves up to tenfold spatial resolution improvement.

Operates at 25Hz temporal resolution.

Requires only tens of milliseconds for acquisition.

Abstract

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 non-invasive perfusion measurements. However, their limited spatial resolution prevents the depiction of microvascular structures. Recently, super-localization 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 25Hz, which may enable functional super-resolution imaging deep within the tissue, surpassing the temporal resolution limitations of current super-resolution methods, e.g. in neural imaging. The sub-second acquisitions make our approach robust to motion artifacts, simplifying in-vivo use of super-resolution ultrasound.