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.
Full text not available from this repository.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 |
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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 |