A Deep Learning Approach for Assessment of Regional Wall Motion Abnormality From Echocardiographic Images-Reference-Cited by-同舟云学术

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A Deep Learning Approach for Assessment of Regional Wall Motion Abnormality From Echocardiographic Images

Published:2020-02 Issue:2 Volume:13 Page:374-381
ISSN:1936-878X
Container-title:JACC: Cardiovascular Imaging
language:en
Short-container-title:JACC: Cardiovascular Imaging

Author:

Kusunose Kenya,Abe Takashi,Haga Akihiro,Fukuda Daiju,Yamada Hirotsugu,Harada Masafumi,Sata Masataka

Funder

Japan Society for the Promotion of Science

Publisher

Elsevier BV

Subject

Cardiology and Cardiovascular Medicine,Radiology Nuclear Medicine and imaging

Reference32 articles.

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2. 2015 ESC guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation;Roffi;European Heart Journal,2016

3. Quantitative detection of regional left ventricular contraction abnormalities by two-dimensional echocardiography. II. Accuracy in coronary artery disease;Parisi;Circulation,1981

4. Noninvasive myocardial strain measurement by speckle tracking echocardiography: validation against sonomicrometry and tagged magnetic resonance imaging;Amundsen;J Am Coll Cardiol,2006

5. Validation of longitudinal peak systolic strain by speckle tracking echocardiography with visual assessment and myocardial perfusion SPECT in patients with regional asynergy;Kusunose;Circ J,2011

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