Nuclear atypia grading in breast cancer histopathological images based on CNN feature extraction and LSTM classification

Nuclear atypia grading in breast cancer histopathological images based on CNN feature extraction and LSTM classification

Abstract Early diagnosis of breast cancer, the most common disease among women around the world, increases the chance of treatment and is highly important. Nuclear atypia grading in histopathological images plays an important role in the final diagnosis and grading of breast cancer. Grading images b...

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Bibliographic Details
Main Authors: Sanaz Karimi Jafarbigloo, Habibollah Danyali
Format: article
Language:EN
Published: Wiley 2021
Subjects:
breast cancer
CNN
histopathological image
LSTM networks
nuclear atypia
Computational linguistics. Natural language processing
P98-98.5
Computer software
QA76.75-76.765
Online Access:https://doaj.org/article/b41f54d631924deb839c3c22f8f18f36
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https://doaj.org/article/b41f54d631924deb839c3c22f8f18f36

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