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Monte-Carlo sampling applied to multiple instance learning for whole slide image classification

Autor
Combalia, M.; Vilaplana, V.
Tipus d'activitat
Presentació treball a congrés
Nom de l'edició
First International conference on Medical Imaging with Deep Learning
Any de l'edició
2018
Data de presentació
2018-07-04
Llibre d'actes
International conference on Medical Imaging with Deep Learning: Amsterdam, 4 - 6th July 2018
Pàgina inicial
1
Pàgina final
3
Repositori
http://hdl.handle.net/2117/126236 Obrir en finestra nova
URL
https://midl.amsterdam/scientific-program/ Obrir en finestra nova
Resum
In this paper we propose a patch sampling strategy based on sequential Monte-Carlo methods for Whole Slide Image classification in the context of Multiple Instance Learning and show its capability to achieve high generalization performance on the differentiation between sun exposed and not sun exposed pieces of skin tissue.
Citació
Combalia, M., Vilaplana, V. Monte-Carlo sampling applied to multiple instance learning for whole slide image classification. A: International conference on Medical Imaging with Deep Learning. "International conference on Medical Imaging with Deep Learning: Amsterdam, 4 - 6th July 2018". 2018, p. 1-3.
Paraules clau
deep learning, histological imaging, monte-carlo sampling, multiple instance learning
Grup de recerca
GPI - Grup de Processament d'Imatge i Vídeo
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center

Participants

Arxius