Automated quantification of levels of breast terminal duct lobular (TDLU) involution using deep learning

Convolutional neural networks (CNNs) offer the potential to generate comprehensive quantitative analysis of histologic features. Diagnostic reporting of benign breast disease (BBD) biopsies is usually limited to subjective assessment of the most severe lesion in a sample, while ignoring the vast maj...

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Detalles Bibliográficos
Autores principales: de Bel, Thomas, Litjens, Geert, Ogony, Joshua, Stallings-Mann, Melody, Carter, Jodi M., Hilton, Tracy, Radisky, Derek C., Vierkant, Robert A., Broderick, Brendan, Hoskin, Tanya L., Winham, Stacey J., Frost, Marlene H., Visscher, Daniel W., Allers, Teresa, Degnim, Amy C., Sherman, Mark E., van der Laak, Jeroen A. W. M.
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/PMC8770616/
https://www.ncbi.nlm.nih.gov/pubmed/35046392
http://dx.doi.org/10.1038/s41523-021-00378-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8770616/
https://www.ncbi.nlm.nih.gov/pubmed/35046392
http://dx.doi.org/10.1038/s41523-021-00378-7

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