Retrospective motion artifact correction of structural MRI images using deep learning improves the quality of cortical surface reconstructions

Head motion during MRI acquisition presents significant challenges for neuroimaging analyses. In this work, we present a retrospective motion correction framework built on a Fourier domain motion simulation model combined with established 3D convolutional neural network (CNN) architectures. Quantita...

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Главные авторы:	Ben A Duffy, Lu Zhao, Farshid Sepehrband, Joyce Min, Danny JJ Wang, Yonggang Shi, Arthur W Toga, Hosung Kim
Формат:	Artigo
Язык:	Inglês
Опубликовано:	Elsevier 2021-04-01
Серии:	NeuroImage
Предметы:	Motion artifact T1 Image quality Cortical surface Cortical thickness Parkinson's disease
Online-ссылка:	http://www.sciencedirect.com/science/article/pii/S1053811921000331
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