Detecting and grading prostate cancer in radical prostatectomy specimens through deep learning techniques

OBJECTIVES: This study aims to evaluate the ability of deep learning algorithms to detect and grade prostate cancer (PCa) in radical prostatectomy specimens. METHODS: We selected 12 whole-slide images of radical prostatectomy specimens. These images were divided into patches, and then, analyzed and...

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Detalles Bibliográficos
Autores principales: Melo, Petronio Augusto de Souza, Estivallet, Carmen Liane Neubarth, Srougi, Miguel, Nahas, William Carlos, Leite, Katia Ramos Moreira
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Faculdade de Medicina / USP 2021
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8527555/
https://www.ncbi.nlm.nih.gov/pubmed/34730614
http://dx.doi.org/10.6061/clinics/2021/e3198

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8527555/
https://www.ncbi.nlm.nih.gov/pubmed/34730614
http://dx.doi.org/10.6061/clinics/2021/e3198

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