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Microbubble axial localization errors in ultrasound super-resolution imaging

Christensen-Jeffries, Kirsten, Harput, Sevan, Brown, Jemma, Wells, Peter N. T., Aljabar, Paul, Dunsby, Christopher, Tang, Meng-Xing and Eckersley, Robert J. 2017. Microbubble axial localization errors in ultrasound super-resolution imaging. IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control 64 (11) , pp. 1644-1654. 10.1109/TUFFC.2017.2741067

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Abstract

Acoustic super-resolution imaging has allowed the 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 simulation 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 crosssectional profiles in super-resolution images demonstrate at least 5.8 times improvement in contrast ratio and more than 1.8 times reduction in spatial spread (provided by 90% of the localizations) for the onset method over centroiding, peak detection, and 2-D Gaussian fitting methods. Simulations estimate that these latter methods could create errors in relative bubble positions as high as 900 μm 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.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
ISSN: 0885-3010
Date of Acceptance: 6 July 2017
Last Modified: 17 Jul 2019 14:21
URI: http://orca-mwe.cf.ac.uk/id/eprint/120480

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