A Deep Learning Algorithm for Prediction of Age-Related Eye Disease Study Severity Scale for Age-Related Macular Degeneration from Color Fundus Photography.

Journal: Ophthalmology
Published Date: Sep 1, 2018

Abstract

PURPOSE: Age-related macular degeneration (AMD) is a common threat to vision. While classification of disease stages is critical to understanding disease risk and progression, several systems based on color fundus photographs are known. Most of these require in-depth and time-consuming analysis of fundus images. Herein, we present an automated computer-based classification algorithm.

Authors

  • Felix Grassmann
    Institute of Human Genetics, University of Regensburg, Regensburg, Germany.
  • Judith Mengelkamp
    Institute of Human Genetics, University of Regensburg, Regensburg, Germany; Regensburg Medical Image Computing, Ostbayerische Technische Hochschule Regensburg (OTH Regensburg), Regensburg, Germany.
  • Caroline Brandl
    Institute of Human Genetics, University of Regensburg, Regensburg, Germany; Department of Ophthalmology, University Hospital Regensburg, Regensburg, Germany; Department of Genetic Epidemiology, Institute of Epidemiology, University of Regensburg, Regensburg, Germany.
  • Sebastian Harsch
    Institute of Human Genetics, University of Regensburg, Regensburg, Germany.
  • Martina E Zimmermann
    Department of Ophthalmology, University Hospital Regensburg, Regensburg, Germany.
  • Birgit Linkohr
    Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany.
  • Annette Peters
    Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany.
  • Iris M Heid
    Department of Ophthalmology, University Hospital Regensburg, Regensburg, Germany.
  • Christoph Palm
    Regensburg Medical Image Computing (ReMIC), Ostbayerische Technische Hochschule Regensburg (OTH Regensburg), Germany; Regensburg Center of Biomedical Engineering (RCBE), OTH Regensburg and Regensburg University, Germany.
  • Bernhard H F Weber
    Institute of Human Genetics, University of Regensburg, Regensburg, Germany. Electronic address: bweb@klinik.uni-regensburg.de.

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