DeepStrain: A Deep Learning Workflow for the Automated Characterization of Cardiac Mechanics

DeepStrain: A Deep Learning Workflow for the Automated Characterization of Cardiac Mechanics

Myocardial strain analysis from cinematic magnetic resonance imaging (cine-MRI) data provides a more thorough characterization of cardiac mechanics than volumetric parameters such as left-ventricular ejection fraction, but sources of variation including segmentation and motion estimation have limite...

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Bibliographic Details
Main Authors: Manuel A. Morales, Maaike van den Boomen, Christopher Nguyen, Jayashree Kalpathy-Cramer, Bruce R. Rosen, Collin M. Stultz, David Izquierdo-Garcia, Ciprian Catana
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-09-01
Series:Frontiers in Cardiovascular Medicine
Subjects:
cine-MRI
deep learning
segmentation
motion estimation
myocardial strain
Online Access:https://www.frontiersin.org/articles/10.3389/fcvm.2021.730316/full

Internet

https://www.frontiersin.org/articles/10.3389/fcvm.2021.730316/full

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