Deep learning for the standardized classification of Ki-67 in vulva carcinoma: A feasibility study

BACKGROUND: The aim of this study is to demonstrate the feasibility of automatic classification of Ki-67 histological immunostainings in patients with squamous cell carcinoma of the vulva using a deep convolutional neural network (dCNN). MATERIAL AND METHODS: For evaluation of the dCNN, we used 55 w...

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Detalles Bibliográficos
Autores principales: Choschzick, Matthias, Alyahiaoui, Mariam, Ciritsis, Alexander, Rossi, Cristina, Gut, André, Hejduk, Patryk, Boss, Andreas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8346648/
https://www.ncbi.nlm.nih.gov/pubmed/34386617
http://dx.doi.org/10.1016/j.heliyon.2021.e07577

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8346648/
https://www.ncbi.nlm.nih.gov/pubmed/34386617
http://dx.doi.org/10.1016/j.heliyon.2021.e07577

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