A State-of-the-Art Survey on Deep Learning Methods for Detection of Architectural Distortion From Digital Mammography

A State-of-the-Art Survey on Deep Learning Methods for Detection of Architectural Distortion From Digital Mammography

Breast cancer is a type of cancer that has risen to be the second cause of death among women. Classification of breast tissues into normal, benign, or malignant depends on the presence of abnormalities like microcalcifications, masses, architectural distortions, and asymmetries. Architectural distor...

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Bibliographic Details
Main Authors: Olaide Nathaniel Oyelade, Absalom El-Shamir Ezugwu
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Convolutional neural network
CNN
breast cancer
deep learning
Gabor filters
mammography
Online Access:https://ieeexplore.ieee.org/document/9165720/

Internet

https://ieeexplore.ieee.org/document/9165720/

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