Classification of asymmetry in mammography via the DenseNet convolutional neural network

Classification of asymmetry in mammography via the DenseNet convolutional neural network

Purpose: To investigate the effectiveness of a deep learning system based on the DenseNet convolutional neural network in diagnosing benign and malignant asymmetric lesions in mammography. Methods: Clinical and image data from 460 women aged 23–82 years (47.57 ± 8.73 years) with asymmetric lesions w...

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Bibliographic Details
Main Authors: Tingting Liao, Lin Li, Rushan Ouyang, Xiaohui Lin, Xiaohui Lai, Guanxun Cheng, Jie Ma
Format: Article
Language:English
Published: Elsevier 2023-12-01
Series:European Journal of Radiology Open
Subjects:
Deep learning
Artificial Intelligence
Mammography
Asymmetry
Online Access:http://www.sciencedirect.com/science/article/pii/S235204772300028X

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http://www.sciencedirect.com/science/article/pii/S235204772300028X

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