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...

Полное описание

Библиографические подробности

Главные авторы:	Sudhir Sornapudi, R Joe Stanley, William V Stoecker, Rodney Long, Zhiyun Xue, Rosemary Zuna, Shellaine R Frazier, Sameer Antani
Формат:	Artigo
Язык:	Inglês
Опубликовано:	Elsevier 2020-01-01
Серии:	Journal of Pathology Informatics
Предметы:	attention networks cervical cancer cervical intraepithelial neoplasia classification convolutional neural networks digital pathology fusion-based classification histology recurrent neural networks
Online-ссылка:	http://www.jpathinformatics.org/article.asp?issn=2153-3539;year=2020;volume=11;issue=1;spage=40;epage=40;aulast=Sornapudi
Метки:	Добавить метку Нет меток, Требуется 1-ая метка записи!