Cervical Histopathology Image Classification Using Multilayer Hidden Conditional Random Fields and Weakly Supervised Learning

Cervical Histopathology Image Classification Using Multilayer Hidden Conditional Random Fields and Weakly Supervised Learning

In this paper, a novel multilayer hidden conditional random fields (MHCRFs)-based cervical histopathology image classification (CHIC) model is proposed to classify well, moderate and poorly differentiation stages of cervical cancer using a weakly supervised learning strategy. First, the color, textu...

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Bibliographic Details
Main Authors: Chen Li, Hao Chen, Le Zhang, Ning Xu, Dan Xue, Zhijie Hu, He Ma, Hongzan Sun
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Cervical cancer
conditional random fields
deep learning
feature extraction
histopathological image
weakly supervised learning
Online Access:https://ieeexplore.ieee.org/document/8744235/

Internet

https://ieeexplore.ieee.org/document/8744235/

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