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Conference papers

RetinOpTIC-Automatic Evaluation of Diabetic Retinopathy

Abstract : Purpose: The RetinOpTIC project performs mass screening of color fundus images and assesses image quality and Diabetic Retinopathy (DR) grade. Algorithm performance is evaluated on the Messidor-2 image database. Methods: Based on artificial intelligence (AI) solutions, referable DR is detected using convolutional neural networks (CNNs). The solution includes first the automatic assessment of the quality of the photography, and then the DR grade
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Contributor : Etienne Decencière Connect in order to contact the contributor
Submitted on : Monday, January 6, 2020 - 12:00:00 PM
Last modification on : Monday, April 4, 2022 - 9:28:20 AM


  • HAL Id : hal-02428873, version 1


Bruno Laÿ, Ronan Danno, Gwenolé Quellec, Etienne Decencière, Ali Erginay, et al.. RetinOpTIC-Automatic Evaluation of Diabetic Retinopathy. ARVO, 2019, Vancouver, Canada. ⟨hal-02428873⟩



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