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

118 Scopus citations

Abstract

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
JournalIRBM
Volume34
Issue number2
DOIs
StatePublished - Apr 1 2013

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ASJC Scopus subject areas

  • Biophysics
  • Biomedical Engineering

Cite this

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. https://doi.org/10.1016/j.irbm.2013.01.010