[{"publication":"International Conference on Medical Image Computing and Computer Assisted Intervention","title":"High frame-rate cardiac ultrasound imaging with deep learning","doi":"10.1007/978-3-030-00928-1_15","citation":{"ieee":"O. Senouf <i>et al.</i>, “High frame-rate cardiac ultrasound imaging with deep learning,” in <i>International Conference on Medical Image Computing and Computer Assisted Intervention</i>, Granada, Spain, 2018, vol. 11070, no. Part 1, pp. 126–134.","mla":"Senouf, Ortal, et al. “High Frame-Rate Cardiac Ultrasound Imaging with Deep Learning.” <i>International Conference on Medical Image Computing and Computer Assisted Intervention</i>, vol. 11070, no. Part 1, Springer Nature, 2018, pp. 126–34, doi:<a href=\"https://doi.org/10.1007/978-3-030-00928-1_15\">10.1007/978-3-030-00928-1_15</a>.","ista":"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.","ama":"Senouf O, Vedula S, Zurakhov G, et al. High frame-rate cardiac ultrasound imaging with deep learning. In: <i>International Conference on Medical Image Computing and Computer Assisted Intervention</i>. Vol 11070. Springer Nature; 2018:126-134. doi:<a href=\"https://doi.org/10.1007/978-3-030-00928-1_15\">10.1007/978-3-030-00928-1_15</a>","apa":"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 <i>International Conference on Medical Image Computing and Computer Assisted Intervention</i> (Vol. 11070, pp. 126–134). Granada, Spain: Springer Nature. <a href=\"https://doi.org/10.1007/978-3-030-00928-1_15\">https://doi.org/10.1007/978-3-030-00928-1_15</a>","short":"O. Senouf, S. Vedula, G. Zurakhov, A.M. Bronstein, M. Zibulevsky, O. Michailovich, D. Adam, D. Blondheim, in:, International Conference on Medical Image Computing and Computer Assisted Intervention, Springer Nature, 2018, pp. 126–134.","chicago":"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 <i>International Conference on Medical Image Computing and Computer Assisted Intervention</i>, 11070:126–34. Springer Nature, 2018. <a href=\"https://doi.org/10.1007/978-3-030-00928-1_15\">https://doi.org/10.1007/978-3-030-00928-1_15</a>."},"publication_identifier":{"issn":["0302-9743"],"eisbn":["9783030009281"],"isbn":["9783030009274"],"eissn":["1611-3349"]},"quality_controlled":"1","extern":"1","issue":"Part 1","scopus_import":"1","publication_status":"published","date_published":"2018-09-14T00:00:00Z","fulldoi":"https://doi.org/10.1007/978-3-030-00928-1_15","day":"14","date_created":"2024-10-09T07:47:49Z","month":"09","author":[{"last_name":"Senouf","first_name":"Ortal","full_name":"Senouf, Ortal"},{"first_name":"Sanketh","last_name":"Vedula","full_name":"Vedula, Sanketh"},{"last_name":"Zurakhov","first_name":"Grigoriy","full_name":"Zurakhov, Grigoriy"},{"full_name":"Bronstein, Alexander","first_name":"Alexander","orcid":"0000-0001-9699-8730","id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6","last_name":"Bronstein"},{"last_name":"Zibulevsky","first_name":"Michael","full_name":"Zibulevsky, Michael"},{"full_name":"Michailovich, Oleg","last_name":"Michailovich","first_name":"Oleg"},{"first_name":"Dan","last_name":"Adam","full_name":"Adam, Dan"},{"first_name":"David","last_name":"Blondheim","full_name":"Blondheim, David"}],"type":"conference","alternative_title":["LNCS"],"publisher":"Springer Nature","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","conference":{"end_date":"2018-09-20","start_date":"2018-09-16","name":"MICCAI: Medical Image Computing and Computer Assisted Intervention","location":"Granada, Spain"},"volume":11070,"year":"2018","oa_version":"None","language":[{"iso":"eng"}],"abstract":[{"lang":"eng","text":"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."}],"status":"public","date_updated":"2025-01-23T13:13:01Z","article_processing_charge":"No","_id":"18283","page":"126 - 134","intvolume":"     11070"}]