Correction of Arterial-Phase Motion Artifacts in Gadoxetic Acid-Enhanced Liver MRI Using an Innovative Unsupervised Network

Correction of Arterial-Phase Motion Artifacts in Gadoxetic Acid-Enhanced Liver MRI Using an Innovative Unsupervised Network

This study aims to propose and evaluate DR-CycleGAN, a disentangled unsupervised network by introducing a novel content-consistency loss, for removing arterial-phase motion artifacts in gadoxetic acid-enhanced liver MRI examinations. From June 2020 to July 2021, gadoxetic acid-enhanced liver MRI dat...

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Bibliographic Details
Main Authors: Feng Pan, Qianqian Fan, Han Xie, Chongxin Bai, Zhi Zhang, Hebing Chen, Lian Yang, Xin Zhou, Qingjia Bao, Chaoyang Liu
Format: Article
Language:English
Published: MDPI AG 2023-10-01
Series:Bioengineering
Subjects:
artifacts
gadoxetic acid
unsupervised machine learning
magnetic resonance imaging
Online Access:https://www.mdpi.com/2306-5354/10/10/1192

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https://www.mdpi.com/2306-5354/10/10/1192

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