Longitudinal Prediction of Infant MR Images With Multi-Contrast Perceptual Adversarial Learning

Longitudinal Prediction of Infant MR Images With Multi-Contrast Perceptual Adversarial Learning

The infant brain undergoes a remarkable period of neural development that is crucial for the development of cognitive and behavioral capacities (Hasegawa et al., 2018). Longitudinal magnetic resonance imaging (MRI) is able to characterize the developmental trajectories and is critical in neuroimagin...

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Bibliographic Details
Main Authors: Liying Peng, Lanfen Lin, Yusen Lin, Yen-wei Chen, Zhanhao Mo, Roza M. Vlasova, Sun Hyung Kim, Alan C. Evans, Stephen R. Dager, Annette M. Estes, Robert C. McKinstry, Kelly N. Botteron, Guido Gerig, Robert T. Schultz, Heather C. Hazlett, Joseph Piven, Catherine A. Burrows, Rebecca L. Grzadzinski, Jessica B. Girault, Mark D. Shen, Martin A. Styner
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-09-01
Series:Frontiers in Neuroscience
Subjects:
generative adversarial networks
MRI
longitudinal prediction
machine learning
infant
postnatal brain development
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2021.653213/full

Internet

https://www.frontiersin.org/articles/10.3389/fnins.2021.653213/full

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