Automatic drusen quantification and risk assessment of age-related macular degeneration on color fundus images.

@article{Grinsven2013AutomaticDQ,
  title={Automatic drusen quantification and risk assessment of age-related macular degeneration on color fundus images.},
  author={Mark J. J. P. van Grinsven and Yara T. E. Lechanteur and Johannes P. H. van de Ven and Bram van Ginneken and Carel B. Hoyng and Thomas Theelen and Clara I. S{\'a}nchez},
  journal={Investigative ophthalmology & visual science},
  year={2013},
  volume={54 4},
  pages={3019-27}
}
PURPOSE To evaluate a machine learning algorithm that allows for computer-aided diagnosis (CAD) of nonadvanced age-related macular degeneration (AMD) by providing an accurate detection and quantification of drusen location, area, and size. METHODS Color fundus photographs of 407 eyes without AMD or with early to moderate AMD were randomly selected from a large European multicenter database. A machine learning system was developed to automatically detect and quantify drusen on each image… CONTINUE READING