Evaluation of the peritumoral features using radiomics and deep learning technology in non-spiculated and noncalcified masses of the breast on mammography

OBJECTIVE: To assess the significance of peritumoral features based on deep learning in classifying non-spiculated and noncalcified masses (NSNCM) on mammography. METHODS: We retrospectively screened the digital mammography data of 2254 patients who underwent surgery for breast lesions in Harbin Med...

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Detalles Bibliográficos
Autores principales: Guo, Fei, Li, Qiyang, Gao, Fei, Huang, Chencui, Zhang, Fandong, Xu, Jingxu, Xu, Ye, Li, Yuanzhou, Sun, Jianghong, Jiang, Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9721450/
https://www.ncbi.nlm.nih.gov/pubmed/36479079
http://dx.doi.org/10.3389/fonc.2022.1026552

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9721450/
https://www.ncbi.nlm.nih.gov/pubmed/36479079
http://dx.doi.org/10.3389/fonc.2022.1026552

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