Poisson Statistical Model of Ultrasound Super-Resolution Imaging Acquisition Time
Journal article
Christensen-Jeffries, K., Brown, J., Harput, S., Zhang, G., Zhu, J., Tang, M-X., Dunsby, C. and Eckersley, R.J. (2019). Poisson Statistical Model of Ultrasound Super-Resolution Imaging Acquisition Time. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control. https://doi.org/10.1109/tuffc.2019.2916603
Authors | Christensen-Jeffries, K., Brown, J., Harput, S., Zhang, G., Zhu, J., Tang, M-X., Dunsby, C. and Eckersley, R.J. |
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Abstract | 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 λ10 to λ20 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. © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Year | 2019 |
Journal | IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
ISSN | 1525-8955 |
Digital Object Identifier (DOI) | https://doi.org/10.1109/tuffc.2019.2916603 |
Funder/Client | Engineering and Physical Sciences Research Council (EPSRC) |
Publication dates | |
Online | 17 May 2019 |
Publication process dates | |
Accepted | 29 Apr 2019 |
Deposited | 04 Nov 2019 |
Accepted author manuscript | License File Access Level Open |
https://openresearch.lsbu.ac.uk/item/885ww
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Accepted author manuscript
PoissonSimulationManuscript_v9AfterAccept.pdf | ||
License: CC BY 4.0 | ||
File access level: Open |
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