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- W2013754472 abstract "We present a novel fully automated algorithm for the detection of retinal diseases via optical coherence tomography (OCT) imaging. Our algorithm utilizes multiscale histograms of oriented gradient descriptors as feature vectors of a support vector machine based classifier. The spectral domain OCT data sets used for cross-validation consisted of volumetric scans acquired from 45 subjects: 15 normal subjects, 15 patients with dry age-related macular degeneration (AMD), and 15 patients with diabetic macular edema (DME). Our classifier correctly identified 100% of cases with AMD, 100% cases with DME, and 86.67% cases of normal subjects. This algorithm is a potentially impactful tool for the remote diagnosis of ophthalmic diseases." @default.
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- W2013754472 date "2014-09-12" @default.
- W2013754472 modified "2023-10-04" @default.
- W2013754472 title "Fully automated detection of diabetic macular edema and dry age-related macular degeneration from optical coherence tomography images" @default.
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- W2013754472 doi "https://doi.org/10.1364/boe.5.003568" @default.
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