DeepCIN: Attention-based cervical histology image classification with sequential feature modeling for pathologist-level accuracy

Background: Cervical cancer is one of the deadliest cancers affecting women globally. Cervical intraepithelial neoplasia (CIN) assessment using histopathological examination of cervical biopsy slides is subject to interobserver variability. Automated processing of digitized histopathology slides has...

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Detalhes bibliográficos

Principais autores:	Sudhir Sornapudi, R Joe Stanley, William V Stoecker, Rodney Long, Zhiyun Xue, Rosemary Zuna, Shellaine R Frazier, Sameer Antani
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Elsevier 2020-01-01
Colecção:	Journal of Pathology Informatics
Assuntos:	attention networks cervical cancer cervical intraepithelial neoplasia classification convolutional neural networks digital pathology fusion-based classification histology recurrent neural networks
Acesso em linha:	http://www.jpathinformatics.org/article.asp?issn=2153-3539;year=2020;volume=11;issue=1;spage=40;epage=40;aulast=Sornapudi
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