Automated quantitative analysis of Ki-67 staining and HE images recognition and registration based on whole tissue sections in breast carcinoma

Automated quantitative analysis of Ki-67 staining and HE images recognition and registration based on whole tissue sections in breast carcinoma

Abstract Background The scoring of Ki-67 is highly relevant for the diagnosis, classification, prognosis, and treatment in breast invasive ductal carcinoma (IDC). Traditional scoring method of Ki-67 staining followed by manual counting, is time-consumption and inter−/intra observer variability, whic...

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Bibliographic Details
Main Authors: Min Feng, Yang Deng, Libo Yang, Qiuyang Jing, Zhang Zhang, Lian Xu, Xiaoxia Wei, Yanyan Zhou, Diwei Wu, Fei Xiang, Yizhe Wang, Ji Bao, Hong Bu
Format: Article
Language:English
Published: BMC 2020-05-01
Series:Diagnostic Pathology
Subjects:
Convolutional neural network
Whole tissue sections
Breast invasive ductal carcinoma
Automatic recognition
Ki-67 counting
Online Access:http://link.springer.com/article/10.1186/s13000-020-00957-5

Internet

http://link.springer.com/article/10.1186/s13000-020-00957-5

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