Which data subset should be augmented for deep learning? a simulation study using urothelial cell carcinoma histopathology images

BACKGROUND: Applying deep learning to digital histopathology is hindered by the scarcity of manually annotated datasets. While data augmentation can ameliorate this obstacle, its methods are far from standardized. Our aim was to systematically explore the effects of skipping data augmentation; apply...

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Detalles Bibliográficos
Autores principales: Ameen, Yusra A., Badary, Dalia M., Abonnoor, Ahmad Elbadry I., Hussain, Khaled F., Sewisy, Adel A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9983182/
https://www.ncbi.nlm.nih.gov/pubmed/36869300
http://dx.doi.org/10.1186/s12859-023-05199-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9983182/
https://www.ncbi.nlm.nih.gov/pubmed/36869300
http://dx.doi.org/10.1186/s12859-023-05199-y

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