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A New Tool for Automatic Assessment of Segmental Wall Motion Based on Longitudinal 2D Strain
Author(s) -
Noah LielCohen,
Yossi Tsadok,
Rоnen Beeri,
Peter Lysyansky,
Yoram Agmon,
Micha S. Feinberg,
Wolfgang Fehske,
Dan Gilon,
Ilan Hay,
Rafael Kuperstein,
Marina Leitman,
Lisa Deutsch,
David Rosenmann,
Alik Sagie,
Sarah Shimoni,
Mordehay Vaturi,
Zvi Friedman,
David S. Blondheim
Publication year - 2009
Publication title -
circulation cardiovascular imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.584
H-Index - 99
eISSN - 1942-0080
pISSN - 1941-9651
DOI - 10.1161/circimaging.108.841874
Subject(s) - interclass correlation , medicine , reliability (semiconductor) , culprit , positive predicative value , intraclass correlation , strain (injury) , cardiology , motion (physics) , correlation , nuclear medicine , artificial intelligence , predictive value , radiology , mathematics , computer science , geometry , clinical psychology , myocardial infarction , psychometrics , power (physics) , physics , quantum mechanics
Identification and quantification of segmental left ventricular wall motion abnormalities on echocardiograms is of paramount clinical importance but is still performed by a subjective visual method. We constructed an automatic tool for assessment of wall motion based on longitudinal strain.

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