Classifying DME vs Normal SD-OCT volumes: A review

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.
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Communication dans un congrès
23rd International Conference on Pattern Recognition, Dec 2016, Cancun, Mexico
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Joan Massich, Mojdeh Rastgoo, Guillaume Lemaître, Carol Cheung, Tien Wong, et al.. Classifying DME vs Normal SD-OCT volumes: A review. 23rd International Conference on Pattern Recognition, Dec 2016, Cancun, Mexico. 〈hal-01376469〉

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