Paired and Unpaired Deep Generative Models on Multimodal Retinal Image Reconstruction

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http://hdl.handle.net/2183/23906Collections
- Investigación (FIC) [1615]
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Paired and Unpaired Deep Generative Models on Multimodal Retinal Image ReconstructionDate
2019-08-07Citation
HERVELLA, Álvaro, et al. Paired and Unpaired Deep Generative Models on Multimodal Retinal Image Reconstruction. En Multidisciplinary Digital Publishing Institute Proceedings. 2019. p. 45.
Abstract
[Abstract] This work explores the use of paired and unpaired data for training deep neural networks in the multimodal reconstruction of retinal images. Particularly, we focus on the reconstruction of fluorescein angiography from retinography, which are two complementary representations of the eye fundus. The performed experiments allow to compare the paired and unpaired alternatives.
Keywords
Deep learning
Generative adversarial networks
Eye fundus
Multimodal
Generative adversarial networks
Eye fundus
Multimodal
Editor version
ISSN
2504-3900