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Microbubble Axial Localization Errors in Ultrasound Super-Resolution Imaging

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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, Chris; Tang, Meng Xing; Eckersley, Robert J.

In: IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL, Vol. 64, No. 11, 11.2017, p. 1644-1654.

Research output: Contribution to journalArticle

Harvard

Christensen-Jeffries, K, Harput, S, Brown, J, Wells, PNT, Aljabar, P, Dunsby, C, Tang, MX & Eckersley, RJ 2017, 'Microbubble Axial Localization Errors in Ultrasound Super-Resolution Imaging', IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL, vol. 64, no. 11, pp. 1644-1654. https://doi.org/10.1109/TUFFC.2017.2741067

APA

Christensen-Jeffries, K., Harput, S., Brown, J., Wells, P. N. T., Aljabar, P., Dunsby, C., ... Eckersley, R. J. (2017). Microbubble Axial Localization Errors in Ultrasound Super-Resolution Imaging. IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL, 64(11), 1644-1654. https://doi.org/10.1109/TUFFC.2017.2741067

Vancouver

Christensen-Jeffries K, Harput S, Brown J, Wells PNT, Aljabar P, Dunsby C et al. Microbubble Axial Localization Errors in Ultrasound Super-Resolution Imaging. IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL. 2017 Nov;64(11):1644-1654. https://doi.org/10.1109/TUFFC.2017.2741067

Author

Christensen-Jeffries, Kirsten ; Harput, Sevan ; Brown, Jemma ; Wells, Peter N.T. ; Aljabar, Paul ; Dunsby, Chris ; Tang, Meng Xing ; Eckersley, Robert J. / Microbubble Axial Localization Errors in Ultrasound Super-Resolution Imaging. In: IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL. 2017 ; Vol. 64, No. 11. pp. 1644-1654.

Bibtex Download

@article{cfef43faddb7456fa1e71bd9ccd859fa,
title = "Microbubble Axial Localization Errors in Ultrasound Super-Resolution Imaging",
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.",
keywords = "Acoustics, Biomedical imaging, Diffraction, Imaging, Microbubbles, Microvasculature, Resolution., Signal resolution, Spatial resolution, Ultrasonic imaging, Ultrasound",
author = "Kirsten Christensen-Jeffries and Sevan Harput and Jemma Brown and Wells, {Peter N.T.} and Paul Aljabar and Chris Dunsby and Tang, {Meng Xing} and Eckersley, {Robert J.}",
year = "2017",
month = "11",
doi = "10.1109/TUFFC.2017.2741067",
language = "English",
volume = "64",
pages = "1644--1654",
journal = "IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL",
issn = "0885-3010",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "11",

}

RIS (suitable for import to EndNote) Download

TY - JOUR

T1 - Microbubble Axial Localization Errors in Ultrasound Super-Resolution Imaging

AU - Christensen-Jeffries, Kirsten

AU - Harput, Sevan

AU - Brown, Jemma

AU - Wells, Peter N.T.

AU - Aljabar, Paul

AU - Dunsby, Chris

AU - Tang, Meng Xing

AU - Eckersley, Robert J.

PY - 2017/11

Y1 - 2017/11

N2 - 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.

AB - 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.

KW - Acoustics

KW - Biomedical imaging

KW - Diffraction

KW - Imaging

KW - Microbubbles

KW - Microvasculature

KW - Resolution.

KW - Signal resolution

KW - Spatial resolution

KW - Ultrasonic imaging

KW - Ultrasound

UR - http://www.scopus.com/inward/record.url?scp=85028460483&partnerID=8YFLogxK

U2 - 10.1109/TUFFC.2017.2741067

DO - 10.1109/TUFFC.2017.2741067

M3 - Article

AN - SCOPUS:85028460483

VL - 64

SP - 1644

EP - 1654

JO - IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL

JF - IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL

SN - 0885-3010

IS - 11

ER -

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