Fully automated quantification of cardiac chamber and function assessment in 2-D echocardiography: clinical feasibility of deep learning-based algorithms

We aimed to compare the segmentation performance of the current prominent deep learning (DL) algorithms with ground-truth segmentations and to validate the reproducibility of the manually created 2D echocardiographic four cardiac chamber ground-truth annotation. Recently emerged DL based fully-autom...

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Bibliographic Details
Published in:The international journal of cardiovascular imaging Vol. 38; no. 5; pp. 1047 - 1059
Main Authors: Kim, Sekeun, Park, Hyung-Bok, Jeon, Jaeik, Arsanjani, Reza, Heo, Ran, Lee, Sang-Eun, Moon, Inki, Yoo, Sun Kook, Chang, Hyuk-Jae
Format: Journal Article
Language:English
Published: Dordrecht Springer Netherlands 01.05.2022
Springer Nature B.V
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ISSN:1875-8312, 1569-5794, 1875-8312, 1573-0743
Online Access:Get full text
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