Correction of out-of-FOV motion artifacts using convolutional neural network

Subject motion during MRI scan can result in severe degradation of image quality. Existing motion correction algorithms rely on the assumption that no information is missing during motions. However, this assumption does not hold when out-of-FOV motion happens. Currently available algorithms are not...

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Veröffentlicht in:	Magnetic resonance imaging 2020-09, Vol.71, p.93-102
Hauptverfasser:	Wang, Chengyan, Liang, Yucheng, Wu, Yuan, Zhao, Siwei, Du, Yiping P.
Format:	Artikel
Sprache:	eng
Schlagworte:	Convolutional neural networks Humans Image Processing, Computer-Assisted - methods Machine learning Magnetic Resonance Imaging Motion correction Neural Networks, Computer Out-of-FOV motion Prior image Signal-To-Noise Ratio
Online-Zugang:	Volltext
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