Now showing items 1-3 of 3

    • Artificial intelligence to identify retinal fundus images, quality validation, laterality evaluation, macular degeneration, and suspected glaucoma 

      Zapata Victori, Miguel Ángel; Royo Fibla, Dídac; Font, Octavi; Vela Segarra, José Ignacio; Marcantonio Santa Cruz, Ivanna Andrea; Moya Sánchez, Eduardo Ulises; Sánchez Pérez, Abraham; Garcia Gasulla, Dario; Cortés García, Claudio Ulises; Ayguadé Parra, Eduard; Labarta Mancho, Jesús José (2020-02-13)
      Open Access
      Purpose: To assess the performance of deep learning algorithms for different tasks in retinal fundus images: (1) detection of retinal fundus images versus optical coherence tomography (OCT) or other images, (2) evaluation ...
    • Data augmentation for deep learning of non-mydriatic screening retinal fundus images 

      Moya Sánchez, Eduardo Ulises; Sánchez Pérez, Abraham; Zapata Victori, Miguel Ángel; Moreno, Jonatan; Garcia Gasulla, Dario; Parés, Ferran; Ayguadé Parra, Eduard; Labarta Mancho, Jesús José; Cortés García, Claudio Ulises (Springer, 2018)
      Conference report
      Restricted access - publisher's policy
      Fundus image is an effective and low-cost tool to screen for common retinal diseases. At the same time, Deep Learning (DL) algorithms have been shown capable of achieving similar or even better performance accuracies than ...
    • Detection, counting, and classification of visual ganglia columns of drosophila pupae 

      Arriaga Varela, Enrique Javier; Moya Sánchez, Eduardo Ulises; Aguilar Meléndez, Armando; Castillo Reyes, Octavio; Vázquez Santacruz, Eduardo; Salazar Colores, Sebastián; Cortés García, Claudio Ulises (2019)
      Open Access
      Many neurobiologists use the fruit fly (Drosophila) as a model to study neuron interaction and neuron organization and then extrapolate this knowledge to the nature of human neurological disorders. Recently, the fluorescence ...