A Data Set and Deep Learning Algorithm for the Detection of Masses and Architectural Distortions in Digital Breast Tomosynthesis Images

IMPORTANCE: Breast cancer screening is among the most common radiological tasks, with more than 39 million examinations performed each year. While it has been among the most studied medical imaging applications of artificial intelligence, the development and evaluation of algorithms are hindered by...

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Detalles Bibliográficos
Autores principales: Buda, Mateusz, Saha, Ashirbani, Walsh, Ruth, Ghate, Sujata, Li, Nianyi, Święcicki, Albert, Lo, Joseph Y., Mazurowski, Maciej A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Association 2021
Materias:
Original Investigation
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8369362/
https://www.ncbi.nlm.nih.gov/pubmed/34398205
http://dx.doi.org/10.1001/jamanetworkopen.2021.19100

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8369362/
https://www.ncbi.nlm.nih.gov/pubmed/34398205
http://dx.doi.org/10.1001/jamanetworkopen.2021.19100

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