Automatic lymphocyte detection on gastric cancer IHC images using deep learning

Descripción del Articulo

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 examin...

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Detalles Bibliográficos
Autor: García Ríos, Emilio Rafael
Formato: tesis de maestría
Fecha de Publicación:2017
Institución:Pontificia Universidad Católica del Perú
Repositorio:PUCP-Tesis
Lenguaje:inglés
OAI Identifier:oai:tesis.pucp.edu.pe:20.500.12404/9905
Enlace del recurso:http://hdl.handle.net/20.500.12404/9905
Nivel de acceso:acceso abierto
Materia:Cáncer
Gastroenterología
Aprendizaje automático (Inteligencia artificial)
https://purl.org/pe-repo/ocde/ford#1.02.00
Descripción
Sumario: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.
Automatic lymphocyte detection on gastric cancer IHC images using deep learning
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