Non-Rigid Cycle Consistent Bidirectional Network with Transformer for Unsupervised Deformable Functional Magnetic Resonance Imaging Registration

Non-Rigid Cycle Consistent Bidirectional Network with Transformer for Unsupervised Deformable Functional Magnetic Resonance Imaging Registration

Background: In neuroscience research about functional magnetic resonance imaging (fMRI), accurate inter-subject image registration is the basis for effective statistical analysis. Traditional fMRI registration methods are usually based on high-resolution structural MRI with clear anatomical structur...

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Bibliographic Details
Main Authors: Yingying Wang, Yu Feng, Weiming Zeng
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Brain Sciences
Subjects:
fMRI
image registration
deep learning
unsupervised
Transformer
Online Access:https://www.mdpi.com/2076-3425/15/1/46
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