Convolutional neural network for automated mass segmentation in mammography

BACKGROUND: Automatic segmentation and localization of lesions in mammogram (MG) images are challenging even with employing advanced methods such as deep learning (DL) methods. We developed a new model based on the architecture of the semantic segmentation U-Net model to precisely segment mass lesio...

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Detalles Bibliográficos
Autores principales: Abdelhafiz, Dina, Bi, Jinbo, Ammar, Reda, Yang, Clifford, Nabavi, Sheida
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Methodology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7724817/
https://www.ncbi.nlm.nih.gov/pubmed/33297952
http://dx.doi.org/10.1186/s12859-020-3521-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7724817/
https://www.ncbi.nlm.nih.gov/pubmed/33297952
http://dx.doi.org/10.1186/s12859-020-3521-y

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