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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Detalles Bibliográficos
Autores principales: Liao, Tingting, Li, Lin, Ouyang, Rushan, Lin, Xiaohui, Lai, Xiaohui, Cheng, Guanxun, Ma, Jie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10336404/
https://www.ncbi.nlm.nih.gov/pubmed/37448557
http://dx.doi.org/10.1016/j.ejro.2023.100502

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10336404/
https://www.ncbi.nlm.nih.gov/pubmed/37448557
http://dx.doi.org/10.1016/j.ejro.2023.100502

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