High frame-rate cardiac ultrasound imaging with deep learning
Senouf O, Vedula S, Zurakhov G, Bronstein AM, Zibulevsky M, Michailovich O, Adam D, Blondheim D. 2018. High frame-rate cardiac ultrasound imaging with deep learning. International Conference on Medical Image Computing and Computer Assisted Intervention. MICCAI: Medical Image Computing and Computer Assisted Intervention, LNCS, vol. 11070, 126–134.
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Conference Paper
| Published
| English
Scopus indexed
Author
Senouf, Ortal;
Vedula, Sanketh;
Zurakhov, Grigoriy;
Bronstein, Alex M.ISTA 
;
Zibulevsky, Michael;
Michailovich, Oleg;
Adam, Dan;
Blondheim, David
;
Zibulevsky, Michael;
Michailovich, Oleg;
Adam, Dan;
Blondheim, DavidSeries Title
LNCS
Abstract
Cardiac ultrasound imaging requires a high frame rate in order to capture rapid motion. This can be achieved by multi-line acquisition (MLA), where several narrow-focused received lines are obtained from each wide-focused transmitted line. This shortens the acquisition time at the expense of introducing block artifacts. In this paper, we propose a data-driven learning-based approach to improve the MLA image quality. We train an end-to-end convolutional neural network on pairs of real ultrasound cardiac data, acquired through MLA and the corresponding single-line acquisition (SLA). The network achieves a significant improvement in image quality for both 5- and 7-line MLA resulting in a decorrelation measure similar to that of SLA while having the frame rate of MLA.
Publishing Year
Date Published
2018-09-14
Proceedings Title
International Conference on Medical Image Computing and Computer Assisted Intervention
Publisher
Springer Nature
Volume
11070
Issue
Part 1
Page
126 - 134
Conference
MICCAI: Medical Image Computing and Computer Assisted Intervention
Conference Location
Granada, Spain
Conference Date
2018-09-16 – 2018-09-20
ISBN
ISSN
eISSN
IST-REx-ID
Cite this
Senouf O, Vedula S, Zurakhov G, et al. High frame-rate cardiac ultrasound imaging with deep learning. In: International Conference on Medical Image Computing and Computer Assisted Intervention. Vol 11070. Springer Nature; 2018:126-134. doi:10.1007/978-3-030-00928-1_15
Senouf, O., Vedula, S., Zurakhov, G., Bronstein, A. M., Zibulevsky, M., Michailovich, O., … Blondheim, D. (2018). High frame-rate cardiac ultrasound imaging with deep learning. In International Conference on Medical Image Computing and Computer Assisted Intervention (Vol. 11070, pp. 126–134). Granada, Spain: Springer Nature. https://doi.org/10.1007/978-3-030-00928-1_15
Senouf, Ortal, Sanketh Vedula, Grigoriy Zurakhov, Alex M. Bronstein, Michael Zibulevsky, Oleg Michailovich, Dan Adam, and David Blondheim. “High Frame-Rate Cardiac Ultrasound Imaging with Deep Learning.” In International Conference on Medical Image Computing and Computer Assisted Intervention, 11070:126–34. Springer Nature, 2018. https://doi.org/10.1007/978-3-030-00928-1_15.
O. Senouf et al., “High frame-rate cardiac ultrasound imaging with deep learning,” in International Conference on Medical Image Computing and Computer Assisted Intervention, Granada, Spain, 2018, vol. 11070, no. Part 1, pp. 126–134.
Senouf O, Vedula S, Zurakhov G, Bronstein AM, Zibulevsky M, Michailovich O, Adam D, Blondheim D. 2018. High frame-rate cardiac ultrasound imaging with deep learning. International Conference on Medical Image Computing and Computer Assisted Intervention. MICCAI: Medical Image Computing and Computer Assisted Intervention, LNCS, vol. 11070, 126–134.
Senouf, Ortal, et al. “High Frame-Rate Cardiac Ultrasound Imaging with Deep Learning.” International Conference on Medical Image Computing and Computer Assisted Intervention, vol. 11070, no. Part 1, Springer Nature, 2018, pp. 126–34, doi:10.1007/978-3-030-00928-1_15.
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