A Lightweight Residual Network for Unsupervised Deformable Image Registration

A Lightweight Residual Network for Unsupervised Deformable Image Registration

Unsupervised deformable volumetric image registration is crucial for various applications, such as medical imaging and diagnosis. Recently, learning-based methods have achieved remarkable success in this domain. Due to their strong global modeling capabilities, transformers outperform convolutional...

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Bibliographic Details
Main Authors: Ahsan Raza Siyal, Astrid Ellen Grams, Markus Haltmeier
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Deformable image registration
unsupervised learning
residual blocks
dilated convolution
limited data
parameter reduction
Online Access:https://ieeexplore.ieee.org/document/10786016/
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