Dual consistent pseudo label generation for multi-source domain adaptation without source data for medical image segmentation

INTRODUCTION: Unsupervised domain adaptation (UDA) aims to adapt a model learned from the source domain to the target domain. Thus, the model can obtain transferable knowledge even in target domain that does not have ground truth in this way. In medical image segmentation scenarios, there exist dive...

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Detalles Bibliográficos
Autores principales: Cai, Binke, Ma, Liyan, Sun, Yan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10330808/
https://www.ncbi.nlm.nih.gov/pubmed/37434767
http://dx.doi.org/10.3389/fnins.2023.1209132

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10330808/
https://www.ncbi.nlm.nih.gov/pubmed/37434767
http://dx.doi.org/10.3389/fnins.2023.1209132

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