Super-resolution Using Flow Estimation in Contrast Enhanced Ultrasound Imaging
Oren Solomon, Ruud J. G. van Sloun, Massimo Mischi, Yonina C. Eldar
Abstract
Ultrasound localization microscopy offers new radiation-free diagnostic tools for vascular imaging deep within the tissue. Despite its high spatial resolution, low microbubble concentrations dictate the acquisition of tens of thousands of images, over the course of several seconds to tens of seconds, to produce a single super-resolved image. To address this limitation, sparsity-based approaches have recently been proposed to significantly reduce the total acquisition time, by resolving the vasculature in settings with considerable microbubble overlap. Here, we report on initial results of improving the spatial resolution and visual vascular reconstruction quality of sparsity-based super-resolution ultrasound imaging from low frame-rate acquisitions, by exploiting the inherent kinematics of microbubbles' flow. Our method relies on simultaneous tracking and sparsity-based detection of individual microbubbles.
BibTeX
@inproceedings{icassp2019_superresolutionu,
title = {Super-resolution Using Flow Estimation in Contrast Enhanced Ultrasound Imaging},
author = {Oren Solomon and Ruud J. G. van Sloun and Massimo Mischi and Yonina C. Eldar},
booktitle = {ICASSP 2019},
year = {2019}
}