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Classifying DME vs Normal SD-OCT volumes: A review

Authors :
Carol Y. Cheung
Mojdeh Rastgoo
Joan Massich
Guillaume Lemaitre
Désiré Sidibé
Fabrice Meriaudeau
Tien Yin Wong
Laboratoire Electronique, Informatique et Image ( Le2i )
Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS )
Singapore Eye Research Institute, Singapore National Eye Centre
Centre for Intelligent Signal and Imaging Research (Universiti Teknologi Petronas) ( CISIR )
Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i)
Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM)
Arts et Métiers Sciences et Technologies
HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies
HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement
Centre for Intelligent Signal and Imaging Research [Petronas] (CISIR)
Universiti Teknologi PETRONAS (UTP)
Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM)
HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS)
Lemaitre, Guillaume
Source :
23rd International Conference on Pattern Recognition, 23rd International Conference on Pattern Recognition, Dec 2016, Cancun, Mexico, ICPR
Publication Year :
2016
Publisher :
HAL CCSD, 2016.

Abstract

International audience; This article reviews the current state of automatic classification methodologies to identify Diabetic Macular Edema (DME) versus normal subjects based on Spectral Domain OCT (SD-OCT) data. Addressing this classification problem has valuable interest since early detection and treatment of DME play a major role to prevent eye adverse effects such as blindness. The main contribution of this article is to cover the lack of a public dataset and benchmark suited for classifying DME and normal SD-OCT volumes, providing our own implementation of the most relevant methodologies in the literature. Subsequently, 6 different methods were implemented and evaluated using this common benchmark and dataset to produce reliable comparison.

Details

Language :
English
Database :
OpenAIRE
Journal :
23rd International Conference on Pattern Recognition, 23rd International Conference on Pattern Recognition, Dec 2016, Cancun, Mexico, ICPR
Accession number :
edsair.doi.dedup.....843d8aa48c4fd0605e9b6ed94f3ffd07