Classifying Dme Vs Normal Sd-Oct Volumes: A Review

2016 23RD INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR)(2016)

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摘要
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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关键词
Diabetic Macular Edema (DME),Spectral Domain OCT (SD-OCT),Machine Learning (ML),benchmark
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