FetalGAN: Automated Segmentation of Fetal Functional Brain MRI Using Deep Generative Adversarial Learning and Multi-Scale 3D U-Net

FetalGAN: Automated Segmentation of Fetal Functional Brain MRI Using Deep Generative Adversarial Learning and Multi-Scale 3D U-Net

An important step in the preprocessing of resting state functional magnetic resonance images (rs-fMRI) is the separation of brain from non-brain voxels. Widely used imaging tools such as FSL’s BET2 and AFNI’s 3dSkullStrip accomplish this task effectively in children and adults. In fetal functional b...

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Bibliographic Details
Main Authors: Josepheen De Asis-Cruz, Dhineshvikram Krishnamurthy, Chris Jose, Kevin M. Cook, Catherine Limperopoulos
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-06-01
Series:Frontiers in Neuroscience
Subjects:
fetal rs-fMRI
resting state
segmentation
deep learning
generative adversarial networks (GANs)
3D U-Net
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2022.887634/full

Internet

https://www.frontiersin.org/articles/10.3389/fnins.2022.887634/full

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