Resumen
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.
| Idioma original | Inglés |
|---|---|
| Título de la publicación alojada | Proceedings - 2017 IEEE 30th International Symposium on Computer-Based Medical Systems, CBMS 2017 |
| Editores | Panagiotis D. Bamidis, Stathis Th. Konstantinidis, Pedro Pereira Rodrigues |
| Editorial | Institute of Electrical and Electronics Engineers Inc. |
| Páginas | 200-204 |
| Número de páginas | 5 |
| ISBN (versión digital) | 9781538617106 |
| DOI | |
| Estado | Publicada - 10 nov. 2017 |
| Evento | 30th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2017 - Thessaloniki, Grecia Duración: 22 jun. 2017 → 24 jun. 2017 |
Serie de la publicación
| Nombre | Proceedings - IEEE Symposium on Computer-Based Medical Systems |
|---|---|
| Volumen | 2017-June |
| ISSN (versión impresa) | 1063-7125 |
Conferencia
| Conferencia | 30th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2017 |
|---|---|
| País/Territorio | Grecia |
| Ciudad | Thessaloniki |
| Período | 22/06/17 → 24/06/17 |
ODS de las Naciones Unidas
Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible
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ODS 3: Salud y bienestar
Huella
Profundice en los temas de investigación de 'Automatic Lymphocyte Detection on Gastric Cancer IHC Images Using Deep Learning'. En conjunto forman una huella única.Citar esto
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