Microbubble Axial Localization Errors in Ultrasound Super-Resolution Imaging

Journal article


Christensen-Jeffries, K, Harput, S., Brown, J., Wells, P.N.T., Aljabar, P., Dunsby, C.W., Tang, M. and Eckersley, R.J. (2017). Microbubble Axial Localization Errors in Ultrasound Super-Resolution Imaging. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control. 64 (11), p. 2017.
AuthorsChristensen-Jeffries, K, Harput, S., Brown, J., Wells, P.N.T., Aljabar, P., Dunsby, C.W., Tang, M. and Eckersley, R.J.
Abstract

Acoustic super-resolution imaging has allowed visualization of microvascular structure and flow beyond the diffraction limit using standard clinical ultrasound systems through the localization of many spatially isolated microbubble signals. The determination of each microbubble position is typically performed by calculating the centroid, finding a local maximum, or finding the peak of a 2-D Gaussian function fit to the signal. However, the backscattered signal from a microbubble depends not only on diffraction characteristics of the waveform, but also on the microbubble behavior in the acoustic field. Here, we propose a new axial localization method by identifying the onset of the backscattered signal. We compare the accuracy of localization methods using in vitro experiments performed at 7 cm depth and 2.3 MHz center frequency. We corroborate these findings with simulated results based on the Marmottant model. We show experimentally and in simulations that detecting the onset of the returning signal provides considerably increased accuracy for super-resolution. Resulting experimental cross-sectional profiles in super-resolution images demonstrate at least 5.8 times improvement in contrast ratio and more than 1.8 reduction in spatial spread (provided by 90% of the localizations) for the onset method over centroiding, peak detection and 2D Gaussian fitting methods. Simulations estimate that these latter methods could create errors in relative bubble positions as high as 900 μ m at these experimental settings, while the onset method reduced the interquartile range of these errors by a factor of over 2.2. Detecting the signal onset is therefore expected to considerably improve the accuracy of super-resolution.

Year2017
JournalIEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
Journal citation64 (11), p. 2017
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISSN1525-8955
Digital Object Identifier (DOI)doi:10.1109/TUFFC.2017.2741067
Web address (URL)https://ieeexplore.ieee.org/document/8012401
Publication dates
Online17 Aug 2017
Publication process dates
Accepted06 Jul 2017
Deposited09 Aug 2019
Accepted author manuscript
License
CC BY 4.0
File Access Level
Open
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