Automatic Classification of Simulated Breast Tomosynthesis Whole Images for the Presence of Microcalcification Clusters Using Deep CNNs

Microcalcification clusters (MCs) are among the most important biomarkers for breast cancer, especially in cases of nonpalpable lesions. The vast majority of deep learning studies on digital breast tomosynthesis (DBT) are focused on detecting and classifying lesions, especially soft-tissue lesions,...

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Detalles Bibliográficos
Autores principales: Mota, Ana M., Clarkson, Matthew J., Almeida, Pedro, Matela, Nuno
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9503015/
https://www.ncbi.nlm.nih.gov/pubmed/36135397
http://dx.doi.org/10.3390/jimaging8090231

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9503015/
https://www.ncbi.nlm.nih.gov/pubmed/36135397
http://dx.doi.org/10.3390/jimaging8090231

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