Equitable modelling of brain imaging by counterfactual augmentation with morphologically constrained 3D deep generative models

We describe CounterSynth, a conditional generative model of diffeomorphic deformations that induce label-driven, biologically plausible changes in volumetric brain images. The model is intended to synthesise counterfactual training data augmentations for downstream discriminative modelling tasks whe...

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Detalles Bibliográficos
Autores principales: Pombo, Guilherme, Gray, Robert, Cardoso, M. Jorge, Ourselin, Sebastien, Rees, Geraint, Ashburner, John, Nachev, Parashkev
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10591114/
https://www.ncbi.nlm.nih.gov/pubmed/36542907
http://dx.doi.org/10.1016/j.media.2022.102723

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10591114/
https://www.ncbi.nlm.nih.gov/pubmed/36542907
http://dx.doi.org/10.1016/j.media.2022.102723

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