End‐to‐end unsupervised cycle‐consistent fully convolutional network for 3D pelvic CT‐MR deformable registration

OBJECTIVE: To improve the efficiency of computed tomography (CT)‐magnetic resonance (MR) deformable image registration while ensuring the registration accuracy. METHODS: Two fully convolutional networks (FCNs) for generating spatial deformable grids were proposed using the Cycle‐Consistent method to...

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Detalles Bibliográficos
Autores principales: Guo, Yi, Wu, Xiangyi, Wang, Zhi, Pei, Xi, Xu, X. George
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Medical Imaging
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7497923/
https://www.ncbi.nlm.nih.gov/pubmed/32657533
http://dx.doi.org/10.1002/acm2.12968

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7497923/
https://www.ncbi.nlm.nih.gov/pubmed/32657533
http://dx.doi.org/10.1002/acm2.12968

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