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Poisson Statistical Model of Ultrasound Super-Resolution Imaging Acquisition Time

Research output: Contribution to journalArticlepeer-review

Kirsten Mia Christensen-Jeffries, Jemma Brown, Sevan Harput, Ge Zhang, Jiaqi Zhu, Mengxing Tang, Christopher Dunsby, Robert Eckersley

Original languageEnglish
Article number8717715
Pages (from-to)1246-1254
Number of pages9
JournalIEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
Issue number7
Early online date17 May 2019
E-pub ahead of print17 May 2019
Published1 Jul 2019


King's Authors


A number of acoustic super-resolution techniques have recently been developed to visualize microvascular structure and flow beyond the diffraction limit. A crucial aspect of all ultrasound super-resolution (SR) methods using single microbubble localization is time-efficient detection of individual bubble signals. Due to the need for bubbles to circulate through the vasculature during acquisition, slow flows associated with the microcirculation limit the minimum acquisition time needed to obtain adequate spatial information. Here, a model is developed to investigate the combined effects of imaging parameters, bubble signal density, and vascular flow on SR image acquisition time. We find that the estimated minimum time needed for SR increases for slower blood velocities and greater resolution improvement. To improve SR from a resolution of /10 to /20 while imaging the microvasculature structure modelled here, the estimated minimum acquisition time increases by a factor of 14. The maximum useful imaging frame rate to provide new spatial information in each image is set by the bubble velocity at low blood flows (< 150 mm/s for a depth of 5 cm) and by the acoustic wave velocity at higher bubble velocities. Furthermore, the image acquisition procedure, transmit frequency, localization precision, and desired super-resolved image contrast, together determine the optimal acquisition time achievable for a fixed flow velocity. Exploring the effects of both system parameters and details of the target vasculature can allow a better choice of acquisition settings and provide improved understanding of the completeness of SR information.

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