Identification and diagnosis of mammographic malignant architectural distortion using a deep learning based mask regional convolutional neural network

Identification and diagnosis of mammographic malignant architectural distortion using a deep learning based mask regional convolutional neural network

BackgroundArchitectural distortion (AD) is a common imaging manifestation of breast cancer, but is also seen in benign lesions. This study aimed to construct deep learning models using mask regional convolutional neural network (Mask-RCNN) for AD identification in full-field digital mammography (FFD...

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Bibliographic Details
Main Authors: Yuanyuan Liu, Yunfei Tong, Yun Wan, Ziqiang Xia, Guoyan Yao, Xiaojing Shang, Yan Huang, Lijun Chen, Daniel Q. Chen, Bo Liu
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-03-01
Series:Frontiers in Oncology
Subjects:
deep learning
convolutional neural network
artificial intelligence
malignant architectural distortion
full-field digital mammography
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2023.1119743/full

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https://www.frontiersin.org/articles/10.3389/fonc.2023.1119743/full

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