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Brain MRI super-resolution using generative adversarial networks

Autor
Sánchez, I.; 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
2018-07-05
Llibre d'actes
International conference on Medical Imaging with Deep Learning: Amsterdam, 4 - 6th July 2018
Pàgina inicial
1
Pàgina final
8
Repositori
http://hdl.handle.net/2117/126234 Obrir en finestra nova
https://openreview.net/group?id=MIDL.amsterdam/2018/Conference#oral-papers Obrir en finestra nova
URL
https://midl.amsterdam/scientific-program/ Obrir en finestra nova
Resum
In this work we propose an adversarial learning approach to generate high resolution MRI scans from low resolution images. The architecture, based on the SRGAN model, adopts 3D convolutions to exploit volumetric information. For the discriminator, the adversarial loss uses least squares in order to stabilize the training. For the generator, the loss function is a combination of a least squares adversarial loss and a content term based on mean square error and image gradients in order to improve ...
Citació
Sánchez, I., Vilaplana, V. Brain MRI super-resolution using generative adversarial networks. A: International conference on Medical Imaging with Deep Learning. "International conference on Medical Imaging with Deep Learning: Amsterdam, 4 - 6th July 2018". 2018, p. 1-8.
Grup de recerca
GPI - Grup de Processament d'Imatge i Vídeo
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center

Participants

Arxius