Fully automated detection of diabetic macular edema and dry age-related macular degeneration from optical coherence tomography images.

Published

Journal Article

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.

Full Text

Duke Authors

Cited Authors

  • Srinivasan, PP; Kim, LA; Mettu, PS; Cousins, SW; Comer, GM; Izatt, JA; Farsiu, S

Published Date

  • October 2014

Published In

Volume / Issue

  • 5 / 10

Start / End Page

  • 3568 - 3577

PubMed ID

  • 25360373

Pubmed Central ID

  • 25360373

Electronic International Standard Serial Number (EISSN)

  • 2156-7085

International Standard Serial Number (ISSN)

  • 2156-7085

Digital Object Identifier (DOI)

  • 10.1364/BOE.5.003568

Language

  • eng