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

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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Bibliographic Details
Main Authors: Sudhir Sornapudi, R Joe Stanley, William V Stoecker, Rodney Long, Zhiyun Xue, Rosemary Zuna, Shellaine R Frazier, Sameer Antani
Format: Article
Language:English
Published: Elsevier 2020-01-01
Series:Journal of Pathology Informatics
Subjects:
attention networks
cervical cancer
cervical intraepithelial neoplasia
classification
convolutional neural networks
digital pathology
fusion-based classification
histology
recurrent neural networks
Online Access: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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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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