First-Stage Prostate Cancer Identification on Histopathological Images: Hand-Driven versus Automatic Learning

Analysis of histopathological image supposes the most reliable procedure to identify prostate cancer. Most studies try to develop computer aid-systems to face the Gleason grading problem. On the contrary, we delve into the discrimination between healthy and cancerous tissues in its earliest stage, o...

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Detalles Bibliográficos
Autores principales: García, Gabriel, Colomer, Adrián, Naranjo, Valery
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514840/
https://www.ncbi.nlm.nih.gov/pubmed/33267070
http://dx.doi.org/10.3390/e21040356

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514840/
https://www.ncbi.nlm.nih.gov/pubmed/33267070
http://dx.doi.org/10.3390/e21040356

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