Abstract
Recently multiple studies have demonstrated microbubble (MB)-based super-resolution imaging (SRI) with ∼λ/10 subwavelength resolution on mice and rats. Clinical translation of SRI, however, faces many technical challenges such as low signal-to-noise-ratio (SNR) of the MB signal and physiologic and operator-induced motion in humans. In this study, we take advantage of the rich spatiotemporal information and high frame rate recording of MB signals by ultrafast imaging, and propose a spatiotemporal nonlocal means (NLM) denoising filter and bipartite graph(BG)-based MB pairing and tracking algorithm to achieve robust SRI.
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