An Automated In-Depth Feature Learning Algorithm for Breast Abnormality Prognosis and Robust Characterization from Mammography Images Using Deep Transfer Learning

An Automated In-Depth Feature Learning Algorithm for Breast Abnormality Prognosis and Robust Characterization from Mammography Images Using Deep Transfer Learning

Background: Diagnosing breast cancer masses and calcification clusters have paramount significance in mammography, which aids in mitigating the disease’s complexities and curing it at early stages. However, a wrong mammogram interpretation may lead to an unnecessary biopsy of the false-positive find...

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Bibliographic Details
Main Authors: Tariq Mahmood, Jianqiang Li, Yan Pei, Faheem Akhtar
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Biology
Subjects:
breast cancer mass
deep learning
mammography classification
deep transfer learning
augmentation
computer-aided diagnosis
Online Access:https://www.mdpi.com/2079-7737/10/9/859

Internet

https://www.mdpi.com/2079-7737/10/9/859

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