Classification of asymmetry in mammography via the DenseNet convolutional neural network
European Journal of Radiology Open（2023）
Abstract
The DL system based on the DenseNet convolution neural network has high diagnostic efficiency, which can help junior radiologists evaluate benign and malignant asymmetric lesions more accurately. It can also improve diagnostic accuracy and reduce missed diagnoses caused by inexperienced junior radiologists.
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Key words
Deep learning, Artificial Intelligence, Mammography, Asymmetry
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