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Peer-Reviewed Publication
Proc IEEE Int Symp Biomed Imaging2020;20201734-1737.April 1, 2020Journal Article

A SEMI-SUPERVISED JOINT LEARNING APPROACH TO LEFT VENTRICULAR SEGMENTATION AND MOTION TRACKING IN ECHOCARDIOGRAPHY.

Kevinminh Ta1, Shawn S Ahn1, Allen Lu2, John C Stendahl3, Albert J Sinusas3,4, James S Duncan1,5,4
1Department of Biomedical Engineering, Yale University, New Haven, CT, USA.
2EchoNous Inc., Redmond, WA, USA.
3Department of Internal Medicine, Yale University, New Haven, CT, USA.
4Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA.
5Department of Electrical Engineering, Yale University, New Haven, CT, USA.
PubMed PMC DOI PDF

Abstract

Accurate interpretation and analysis of echocardiography is important in assessing cardiovascular health. However, motion tracking often relies on accurate segmentation of the myocardium, which can be difficult to obtain due to inherent ultrasound properties. In order to address this limitation, we propose a semi-supervised joint learning network that exploits overlapping features in motion tracki…

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