Unravelling the effect of data augmentation transformations in polyp segmentation

PURPOSE: Data augmentation is a common technique to overcome the lack of large annotated databases, a usual situation when applying deep learning to medical imaging problems. Nevertheless, there is no consensus on which transformations to apply for a particular field. This work aims at identifying t...

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Detalles Bibliográficos
Autores principales: Sánchez-Peralta, Luisa F., Picón, Artzai, Sánchez-Margallo, Francisco M., Pagador, J. Blas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2020
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7671995/
https://www.ncbi.nlm.nih.gov/pubmed/32989680
http://dx.doi.org/10.1007/s11548-020-02262-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7671995/
https://www.ncbi.nlm.nih.gov/pubmed/32989680
http://dx.doi.org/10.1007/s11548-020-02262-4

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