Learning deep abdominal CT registration through adaptive loss weighting and synthetic data generation

PURPOSE: This study aims to explore training strategies to improve convolutional neural network-based image-to-image deformable registration for abdominal imaging. METHODS: Different training strategies, loss functions, and transfer learning schemes were considered. Furthermore, an augmentation laye...

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Detalles Bibliográficos
Autores principales: Pérez de Frutos, Javier, Pedersen, André, Pelanis, Egidijus, Bouget, David, Survarachakan, Shanmugapriya, Langø, Thomas, Elle, Ole-Jakob, Lindseth, Frank
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9956065/
https://www.ncbi.nlm.nih.gov/pubmed/36827289
http://dx.doi.org/10.1371/journal.pone.0282110

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9956065/
https://www.ncbi.nlm.nih.gov/pubmed/36827289
http://dx.doi.org/10.1371/journal.pone.0282110

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