Diagnostic value of mammography density of breast masses by using deep learning.

Chen, Qian-Qian; Lin, Shu-Ting; Ye, Jia-Yi; Tong, Yun-Fei; Lin, Shu; Cai, Si-Qing

Chen, Qian-Qian; Lin, Shu-Ting; Ye, Jia-Yi; Tong, Yun-Fei; Lin, Shu; Cai, Si-Qing.

Afiliación

Chen QQ; Department of Radiology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, China.
Lin ST; Department of Radiology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, China.
Ye JY; Department of Radiology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, China.
Tong YF; Shanghai Yanghe Huajian Artificial Intelligence Technology Co. Ltd., Shanghai, China.
Lin S; Centre of Neurological and Metabolic Research, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, China.
Cai SQ; Department of Neuroendocrinology, Group of Neuroendocrinology, Garvan Institute of Medical Research, Sydney, Australia.

Front Oncol ; 13: 1110657, 2023.

Article en En | MEDLINE | ID: mdl-37333830

Palabras clave

breast mass; convolutional neural network; deep learning model; mammographic density; regions of interest

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Observational_studies / Prognostic_studies Idioma: En Revista: Front Oncol Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza

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