Paired and Unpaired Deep Generative Models on Multimodal Retinal Image Reconstruction

• Álvaro S. Hervella ^[1] ; José Rouco ; Jorge Novo ^[1] ; Marcos Ortega ^[1]
  1. [1] Universidade da Coruña

     Universidade da Coruña

     A Coruña, España

     
• Localización: XoveTIC 2019: The 2nd XoveTIC Conference (XoveTIC 2019), A Coruña, Spain, 5–6 September / Alberto Alvarellos González (ed. lit.), Joaquim de Moura (ed. lit.), Beatriz Botana Barreiro (ed. lit.), Javier Pereira-Loureiro (ed. lit.), Manuel Francisco González Penedo (ed. lit.), 2019, ISBN 978-3-03921-444-0
• Idioma: inglés
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• Resumen

  • 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.