Show simple item record

dc.contributor.authorHu, Jieyu
dc.contributor.authorOlaisen, Sindre Hellum
dc.contributor.authorSmistad, Erik
dc.contributor.authorDalen, Håvard
dc.contributor.authorLøvstakken, Lasse
dc.date.accessioned2024-05-31T08:09:40Z
dc.date.available2024-05-31T08:09:40Z
dc.date.created2023-10-20T12:48:24Z
dc.date.issued2023
dc.identifier.citationUltrasound in Medicine and Biology. 2023, 50 (1), 47-56.en_US
dc.identifier.issn0301-5629
dc.identifier.urihttps://hdl.handle.net/11250/3132064
dc.description.abstractObjective: Echocardiography, a critical tool for assessing left atrial (LA) volume, often relies on manual or semi-automated measurements. This study introduces a fully automated, real-time method for measuring LA volume in both 2-D and 3-D imaging, in the aim of offering accuracy comparable to that of expert assessments while saving time and reducing operator variability. Methods: We developed an automated pipeline comprising a network to identify the end-systole (ES) time point and robust 2-D and 3-D U-Nets for segmentation. We employed data sets of 789 2-D images and 286 3-D recordings and explored various training regimes, including recurrent networks and pseudo-labeling, to estimate volume curves. Results: Our baseline results revealed an average volume difference of 2.9 mL for 2-D and 7.8 mL for 3-D, respectively, compared with manual methods. The application of pseudo-labeling to all frames in the cine loop generally led to more robust volume curves and notably improved ES measurement in cases with limited data. Conclusion: Our results highlight the potential of automated LA volume estimation in clinical practice. The proposed prototype application, capable of processing real-time data from a clinical ultrasound scanner, provides valuable temporal volume curve information in the echo lab.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleAutomated 2-D and 3-D Left Atrial Volume Measurements Using Deep Learningen_US
dc.title.alternativeAutomated 2-D and 3-D Left Atrial Volume Measurements Using Deep Learningen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber47-56en_US
dc.source.volume50en_US
dc.source.journalUltrasound in Medicine and Biologyen_US
dc.source.issue1en_US
dc.identifier.doi10.1016/j.ultrasmedbio.2023.08.024
dc.identifier.cristin2186748
dc.relation.projectNorges forskningsråd: 237887en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal