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Beltrán Castañón, César Armando
García Ríos, Emilio Rafael (es_ES)
2018-01-19T21:32:22Z (es_ES)
2018-01-19T21:32:22Z (es_ES)
2017 (es_ES)
2018-01-19 (es_ES)
http://hdl.handle.net/20.500.12404/9905
Tumor-infiltrating lymphocytes (TILs) have received considerable attention in recent years, as evidence suggests they are related to cancer prognosis. Distribution and localization of these and other types of immune cells are of special interest for pathologists, and frequently involve manual examination on Immunohistochemistry (IHC) Images. We present a model based on Deep Convolutional Neural Networks for Automatic lymphocyte detection on IHC images of gastric cancer. The dataset created as part of this work is publicly available for future research. (es_ES)
Tesis (es_ES)
eng (es_ES)
Pontificia Universidad Católica del Perú (es_ES)
info:eu-repo/semantics/openAccess (es_ES)
http://creativecommons.org/licenses/by-nc-nd/2.5/pe/ (*)
Cáncer (es_ES)
Gastroenterología (es_ES)
Aprendizaje automático (Inteligencia artificial) (es_ES)
Automatic lymphocyte detection on gastric cancer IHC images using deep learning (es_ES)
info:eu-repo/semantics/masterThesis (es_ES)
Pontificia Universidad Católica del Perú. Escuela de Posgrado (es_ES)
Informática con mención en Ciencias de la Computación (es_ES)
Maestría (es_ES)
Maestro en Informática con mención en Ciencias de la Computación (es_ES)
PE (es_ES)
https://purl.org/pe-repo/ocde/ford#1.02.00 (es_ES)
https://purl.org/pe-repo/renati/level#maestro (es_ES)
29561260
https://orcid.org/0000-0002-0173-4140 (es_ES)
611087 (es_ES)
http://purl.org/pe-repo/renati/type#tesis (es_ES)
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