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Sparsity-driven super-resolution in clinical contrast-enhanced ultrasound

Super-resolution ultrasound enables detailed assessment of the fine vascular network by pinpointing individual microbubbles, using ultrasound contrast agents. The fidelity and achieved resolution of this technique is determined by the density of localized microbubbles and their localization accuracy. To obtain high densities, one can evaluate extremely sparse subsets of microbubbles across thousands of frames by using a very low microbubble dose and imaging for a very long time, which is impractical for clinical routine. While ultrafast imaging somewhat alleviates this problem, long acquisition times are still required to enhance the full vascular bed. As a result, localization accuracy remains hampered by patient motion. Recently, sparsity-based ultrasonic super resolution hemodynamic imaging was proposed, featuring a high spatial as well as temporal resolution by exploiting the temporal correlation structure of flowing microbubbles. However, when using clinical scanners operating at low framerates, this pixel-wise correlation across imaging frames may vanish. The aim of this work is hence twofold. First, to attain high microbubble localization accuracy on dense contrast-enhanced ultrasound data using a clinical dose of ultrasound contrast agents and a standard clinical scanner. Second, to retain a high resolution by adequate motion compensation.