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dc.contributor.authorØstvik, Andreas
dc.contributor.authorSmistad, Erik
dc.contributor.authorAase, Svein Arne
dc.contributor.authorHaugen, Bjørn Olav
dc.contributor.authorLøvstakken, Lasse
dc.identifier.citationUltrasound in Medicine and Biology. 2018, 1-11.nb_NO
dc.description.abstractTransthoracic echocardiography examinations are usually performed according to a protocol comprising different probe postures providing standard views of the heart. These are used as a basis when assessing cardiac function, and it is essential that the morphophysiological representations are correct. Clinical analysis is often initialized with the current view, and automatic classification can thus be useful in improving today's workflow. In this article, convolutional neural networks (CNNs) are used to create classification models predicting up to seven different cardiac views. Data sets of 2-D ultrasound acquired from studies totaling more than 500 patients and 7000 videos were included. State-of-the-art accuracies of 98.3% ± 0.6% and 98.9% ± 0.6% on single frames and sequences, respectively, and real-time performance with 4.4 ± 0.3 ms per frame were achieved. Further, it was found that CNNs have the potential for use in automatic multiplanar reformatting and orientation guidance. Using 3-D data to train models applicable for 2-D classification, we achieved a median deviation of 4° ± 3° from the optimal orientations.nb_NO
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.titleReal-time Standard View Classification in Transthoracic Echocardiography using Convolutional Neural Networksnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.source.journalUltrasound in Medicine and Biologynb_NO
dc.relation.projectNorges forskningsråd: 237887nb_NO
dc.description.localcode© 2018. This is the authors’ accepted and refereed manuscript to the article. Locked until 20.11.2019 due to copyright restrictions. This manuscript version is made available under the CC-BY-NC-ND 4.0 license
cristin.unitnameInstitutt for sirkulasjon og bildediagnostikk

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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal