Towards a better understanding of glaucoma through fundus photography

Glaucoma is one of the leading causes of preventable blindness. Known as “the silent thief of sight”, it is asymptomatic until it produces a permanent and irreversible damage of the retinal nerve fiber layer. A gold standard imaging technique to identify the disease is still missing: currently, glaucoma is diagnosed using multiple studies, including microperimetry, optical coherence tomography and color fundus phography. As a consequence, detecting it at an early stage through screening campaigns is still prohibitive.

In this project we aim to improve the usage of color fundus photography in the context of glaucoma screening. To this end, our purpose is to introduce novel deep learning based approaches to discover novel biomarkers on these images. By means of our techniques, clinicians will be able to diagnose glaucoma with higher sensitivity and specificity using this low-cost imaging technique.

PI: José Ignacio Orlando, PhD


  • Mercedes Leguía, MD - Hospital de Alta Complejidad El Cruce Dr. Néstor Carlos Kirchner, Florencio Varela, PBA, Argentina.
  • Ignacio Larrabide, PhD - CONICET / PLADEMA-UNICEN, Tandil, Argentina.
  • Emmanuel Iarussi, PhD - CONICET / UTN-FRBA, CABA, Argentina.
  • Carlos A. Bulant, PhD - CONICET / PLADEMA-UNICEN, Tandil, Argentina.
  • Karel van Keer, MD PhD - UZ Leuven, Leuven, Belgium.
  • João Barbosa Breda, MD PhD - University of Porto, Porto, Portugal; KU Leuven, Leuven, Belgium.
  • Lautaro Gramuglia, Undergraduate student - Facultad de Ciencias Exactas, UNICEN.

Supported by:

  • PICT 2019-00070 (“CANOA: CAracterización morfológica de la cabeza del Nervio Óptico en fotografías de fondo de ojo mediante Aprendizaje profundo”). Proyectos de Investigación Científica y Tecnológica PICT 2019 Joven Investigador (FONCyT, Agencia I+D+i, Ministerio de Ciencia, Tecnología e Innovación).
  • INI 2020 Scholarship (“Artery/vein segmentation in color fundus pictures using deep learning: applications to simulation of retinal hemodynamics”). Convocatoria Beca INI de Ingreso a la Investigación (Programa de Fortalecimiento a la Ciencia y la Tecnología en las Universidades Nacionales). Becario: Lautaro Gramuglia.
José Ignacio Orlando
José Ignacio Orlando
Assistant Researcher

My research interests include machine learning and computer vision techniques for medical imaging applications, mostly centered in ophthalmology.