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Normalization of HE-stained histological images using cycle consistent generative adversarial networks
BACKGROUND: Histological images show strong variance (e.g. illumination, color, staining quality) due to differences in image acquisition, tissue processing, staining, etc. This can impede downstream image analysis such as staining intensity evaluation or classification. Methods to reduce these vari...
Autores principales: | Runz, Marlen, Rusche, Daniel, Schmidt, Stefan, Weihrauch, Martin R., Hesser, Jürgen, Weis, Cleo-Aron |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8349020/ https://www.ncbi.nlm.nih.gov/pubmed/34362386 http://dx.doi.org/10.1186/s13000-021-01126-y |
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