A convolutional deep learning model for improving mammographic breast-microcalcification diagnosis

This study aimed to assess the diagnostic performance of deep convolutional neural networks (DCNNs) in classifying breast microcalcification in screening mammograms. To this end, 1579 mammographic images were collected retrospectively from patients exhibiting suspicious microcalcification in screeni...

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Detalles Bibliográficos
Autores principales: Kang, Daesung, Gweon, Hye Mi, Eun, Na Lae, Youk, Ji Hyun, Kim, Jeong-Ah, Son, Eun Ju
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8671560/
https://www.ncbi.nlm.nih.gov/pubmed/34907330
http://dx.doi.org/10.1038/s41598-021-03516-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8671560/
https://www.ncbi.nlm.nih.gov/pubmed/34907330
http://dx.doi.org/10.1038/s41598-021-03516-0

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