Paired and Unpaired Deep Generative Models on Multimodal Retinal Image Reconstruction
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Universidade da Coruña
info
- Alberto Alvarellos González (ed. lit.)
- José Joaquim de Moura Ramos (ed. lit.)
- Beatriz Botana Barreiro (ed. lit.)
- Javier Pereira Loureiro (ed. lit.)
- Manuel F. González Penedo (ed. lit.)
Publisher: MDPI
ISBN: 978-3-03921-444-0, 978-3-03921-443-3
Year of publication: 2019
Congress: XoveTIC (2. 2019. A Coruña)
Type: Conference paper
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.