Deep Learning Application to Detect Glaucoma with a Mixed Training Approach: Public Database and Expert-Labeled Glaucoma Population.

Journal: Ophthalmic research
Published Date: Sep 30, 2023

Abstract

INTRODUCTION: Artificial intelligence has real potential for early identification of ocular diseases such as glaucoma. An important challenge is the requirement for large databases properly selected, which are not easily obtained. We used a relatively original strategy: a glaucoma recognition algorithm trained with fundus images from public databases and then tested and retrained with a carefully selected patient database.

Authors

  • Florencia Cellini
    Instituto de Oftalmobiología Aplicada (IOBA), University of Valladolid, Valladolid, Spain.
  • Deborah Caamaño
    Instituto de Oftalmobiología Aplicada (IOBA), University of Valladolid, Valladolid, Spain.
  • Belen Carrasco
    Ophthalmology Department, Hospital Clinico Universitario (HCUV), Valladolid, Spain.
  • José R Juberías
    Instituto de Oftalmobiología Aplicada (IOBA), University of Valladolid, Valladolid, Spain.
  • Carolina Ossa
    Instituto de Oftalmobiología Aplicada (IOBA), University of Valladolid, Valladolid, Spain.
  • Ramón Bringas
    Ophthalmology Department, Hospital Universitario Río Hortega (HURH), Valladolid, Spain.
  • Francisco de la Fuente
    Ophthalmology Department, Hospital Universitario Río Hortega (HURH), Valladolid, Spain.
  • Pablo Franco
    Transmural Biotech, Barcelona, Spain.
  • David Coronado
    Transmural Biotech, Barcelona, Spain.
  • Jose Carlos Pastor
    Instituto de Oftalmobiología Aplicada (IOBA), University of Valladolid, Valladolid, Spain.

Keywords

External Resources

Popular Topics
Recent Journals