Open AccessArtificial Intelligence Aids Cardiac Image Quality Assessment for Improving Precision in Strain Measurements
Author(s) -
KuoFeng Huang,
ChiunSheng Huang,
MaoYuan Su,
Chung-Lieh Hung,
Yi-Chin Ethan Tu,
Lung-Chun Lin,
JueyJen Hwang
Publication year - 2021
Publication title -
jacc. cardiovascular imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.79
H-Index - 120
eISSN - 1936-878X
pISSN - 1876-7591
DOI - 10.1016/j.jcmg.2020.08.034
Subject(s) - medicine , reliability (semiconductor) , breast cancer , strain (injury) , feature (linguistics) , image quality , confidence interval , cardiology , cancer , artificial intelligence , computer science , image (mathematics) , power (physics) , linguistics , physics , philosophy , quantum mechanics
The aim of this study was to develop an artificial intelligence tool to assess echocardiographic image quality objectively.
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