Combining morphometric features and convolutional networks fusion for glaucoma diagnosis

Oscar Perdomo, John Arevalo, Fabio A. González

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Glaucoma is an eye condition that leads to loss of vision and blindness. Ophthalmoscopy exam evaluates the shape, color and proportion between the optic disc and physiologic cup, but the lack of agreement among experts is still the main diagnosis problem. The application of deep convolutional neural networks combined with automatic extraction of features such as: the cup-to-disc distance in the four quadrants, the perimeter, area, eccentricity, the major radio, the minor radio in optic disc and cup, in addition to all the ratios among the previous parameters may help with a better automatic grading of glaucoma. This paper presents a strategy to merge morphological features and deep convolutional neural networks as a novel methodology to support the glaucoma diagnosis in eye fundus images.

Original languageEnglish (US)
Title of host publication13th International Conference on Medical Information Processing and Analysis
EditorsNatasha Lepore, Jorge Brieva, Juan David Garcia, Eduardo Romero
PublisherSPIE
ISBN (Electronic)9781510616332
DOIs
StatePublished - 2017
Externally publishedYes
Event13th International Conference on Medical Information Processing and Analysis, SIPAIM 2017 - San Andres Island, Colombia
Duration: Oct 5 2017Oct 7 2017

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume10572
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference13th International Conference on Medical Information Processing and Analysis, SIPAIM 2017
Country/TerritoryColombia
CitySan Andres Island
Period10/5/1710/7/17

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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