Classifying DME vs normal SD-OCT volumes: A review

Massich, J. and Rastgoo, M. and Lemaître, G. and Cheung, C.Y. and Wong, T.Y. and Sidibé, D. and Mériaudeau, F. (2017) Classifying DME vs normal SD-OCT volumes: A review. Proceedings - International Conference on Pattern Recognition. pp. 1297-1302.

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Abstract

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. © 2016 IEEE.

Item Type: Article
Impact Factor: cited By 1
Departments / MOR / COE: Centre of Excellence > Center for Intelligent Signal and Imaging Research
Depositing User: Mr Ahmad Suhairi Mohamed Lazim
Date Deposited: 22 Apr 2018 14:41
Last Modified: 22 Apr 2018 14:41
URI: http://scholars.utp.edu.my/id/eprint/20097

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