Deep learning features encode interpretable morphologies within histological images

Convolutional neural networks (CNNs) are revolutionizing digital pathology by enabling machine learning-based classification of a variety of phenotypes from hematoxylin and eosin (H&E) whole slide images (WSIs), but the interpretation of CNNs remains difficult. Most studies have considered inter...

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Detalles Bibliográficos
Autores principales: Foroughi pour, Ali, White, Brian S., Park, Jonghanne, Sheridan, Todd B., Chuang, Jeffrey H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9177767/
https://www.ncbi.nlm.nih.gov/pubmed/35676395
http://dx.doi.org/10.1038/s41598-022-13541-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9177767/
https://www.ncbi.nlm.nih.gov/pubmed/35676395
http://dx.doi.org/10.1038/s41598-022-13541-2

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