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ACS Style

Álvaro Hervella; José Rouco; Jorge Novo; Marcos Ortega. Paired and Unpaired Deep Generative Models on Multimodal Retinal Image Reconstruction. Proceedings 2019, 21, 45 .

AMA Style

Álvaro Hervella, José Rouco, Jorge Novo, Marcos Ortega. Paired and Unpaired Deep Generative Models on Multimodal Retinal Image Reconstruction. Proceedings. 2019; 21 (1):45.

Chicago/Turabian Style

Álvaro Hervella; José Rouco; Jorge Novo; Marcos Ortega. 2019. "Paired and Unpaired Deep Generative Models on Multimodal Retinal Image Reconstruction." Proceedings 21, no. 1: 45.

Paired and Unpaired Deep Generative Models on Multimodal Retinal Image Reconstruction

Department of Computer Science, Universidade da Coruña, 17051 A Coruña, Spain

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, multimodal, Eye Fundus, Generative Adversarial Networks

Published: 07 August 2019 in Proceedings

https://doi.org/10.3390/proceedings2019021045

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