TeleOphta: Machine learning and image processing methods for teleophthalmology

E. Decencière, G. Cazuguel, X. Zhang, G. Thibault, J. C. Klein, F. Meyer, B. Marcotegui, G. Quellec, M. Lamard, R. Danno, D. Elie, P. Massin, Z. Viktor, A. Erginay, B. Laÿ, A. Chabouis

Research output: Contribution to journalArticle

138 Scopus citations


A complete prototype for the automatic detection of normal examinations on a teleophthalmology network for diabetic retinopathy screening is presented. The system combines pathological pattern mining methods, with specific lesion detection methods, to extract information from the images. This information, plus patient and other contextual data, is used by a classifier to compute an abnormality risk. Such a system should reduce the burden on readers on teleophthalmology networks.

Original languageEnglish (US)
Pages (from-to)196-203
Number of pages8
Issue number2
StatePublished - Apr 1 2013

ASJC Scopus subject areas

  • Biophysics
  • Biomedical Engineering

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    Decencière, E., Cazuguel, G., Zhang, X., Thibault, G., Klein, J. C., Meyer, F., Marcotegui, B., Quellec, G., Lamard, M., Danno, R., Elie, D., Massin, P., Viktor, Z., Erginay, A., Laÿ, B., & Chabouis, A. (2013). TeleOphta: Machine learning and image processing methods for teleophthalmology. IRBM, 34(2), 196-203.