A Novel Approach for Predicting Atrial Fibrillation Recurrence After Ablation Using Deep Convolutional Neural Networks by Assessing Left Atrial Curved M-Mode Speckle-Tracking Images

A Novel Approach for Predicting Atrial Fibrillation Recurrence After Ablation Using Deep Convolutional Neural Networks by Assessing Left Atrial Curved M-Mode Speckle-Tracking Images

Aims: Curved M-mode images of global strain (GS) and strain rate (GSR) provide sufficiently detailed spatiotemporal information of deformation mechanics. This study investigated whether a deep convolutional neural network (CNN) could accurately classify these images in patients with atrial fibrillat...

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Bibliographic Details
Main Authors: Yi-Ting Hwang, Hui-Ling Lee, Cheng-Hui Lu, Po-Cheng Chang, Hung-Ta Wo, Hao-Tien Liu, Ming-Shien Wen, Fen-Chiung Lin, Chung-Chuan Chou
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-01-01
Series:Frontiers in Cardiovascular Medicine
Subjects:
atrial fibrillation
deep convolutional neural network
radiofrequency ablation
speckle tracking longitudinal strain
recurrence
Online Access:https://www.frontiersin.org/articles/10.3389/fcvm.2020.605642/full

Internet

https://www.frontiersin.org/articles/10.3389/fcvm.2020.605642/full

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