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...
| Auteurs principaux: | , , , , , , , |
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| Format: | Article |
| Langue: | English |
| Publié: |
Elsevier
2021-04-01
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| Collection: | NeuroImage |
| Sujets: | |
| Accès en ligne: | http://www.sciencedirect.com/science/article/pii/S1053811921000331 |