articleOphthalmology RetinaFeb 13, 2017HYBRID OA

Deep Learning Is Effective for Classifying Normal versus Age-Related Macular Degeneration OCT Images

University of Washington

PubMed
Indexed incrossrefpubmed

Abstract

Objective

The advent of Electronic Medical Records (EMR) with large electronic imaging databases along with advances in deep neural networks with machine learning has provided a unique opportunity to achieve milestones in automated image analysis. Optical coherence tomography (OCT) is the most commonly obtained imaging modality in ophthalmology and represents a dense and rich dataset when combined with labels derived from the EMR. We sought to determine if deep learning could be utilized to distinguish normal OCT images from images from patients with Age-related Macular Degeneration (AMD).

Design

EMR and OCT database study. SUBJECTS: Normal and AMD patients who had a macular OCT.

Citation impact

651
total citations
FWCI
46.05
Percentile
100%
References
27
Citations per year

Authors

3

Topics & keywords

Keywords
  • Optical coherence tomography
  • Medicine
  • Macular degeneration
  • Receiver operating characteristic
  • Artificial intelligence
  • Deep learning
  • Ophthalmology
  • Computer science
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