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Peer-Reviewed Publication
Proc SPIE Int Soc Opt Eng2020;11319February 1, 2020Journal Article

Unsupervised Motion Tracking of Left Ventricle in Echocardiography.

Shawn S Ahn1, Kevinminh Ta1, Allen Lu2, John C Stendahl3, Albert J Sinusas4,3, James S Duncan1,5,4
1Department of Biomedical Engineering, Yale University, New Haven, CT, USA.
2EchoNous Inc., Redmond, WA, U.S.A.
3Department of Internal Medicine, Yale University, New Haven, CT, USA.
4Department of Diagnostic Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA.
5Department of Electrical Engineering, Yale University, New Haven, CT, USA.
PubMed PMC PDF

Abstract

Accurate motion tracking of the left ventricle is critical in detecting wall motion abnormalities in the heart after an injury such as a myocardial infarction. We propose an unsupervised motion tracking framework with physiological constraints to learn dense displacement fields between sequential pairs of 2-D B-mode echocardiography images. Current deep-learning motion-tracking algorithms require…

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