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GMCNet: A Generative Multi-Resolution Framework for Cardiac Registration

Deformable image registration plays a crucial role in estimating cardiac deformation from a sequence of images. However, existing registration methods primarily process images as pairs instead of processing all images in a sequence together. This study proposes a novel end-to-end learning-free gener...

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Autori principali: Ameneh Sheikhjafari, Michelle Noga, Ahmed Ahmed, Nilanjan Ray, Kumaradevan Punithakumar
Natura: Artigo
Lingua:Inglês
Pubblicazione: IEEE 2023-01-01
Serie:IEEE Access
Soggetti:
Convolutional neural networks
cardiac cine MRI
deformable registration
generative network
learning-free framework
multi resolution
Accesso online:https://ieeexplore.ieee.org/document/10021322/
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