Current Diabetes Reports

, Volume 13, Issue 4, pp 453–459

Automated Analysis of Diabetic Retinopathy Images: Principles, Recent Developments, and Emerging Trends

Microvascular Complications-Retinopathy (JK Sun, Section Editor)

DOI: 10.1007/s11892-013-0393-9

Cite this article as:
Li, B. & Li, H.K. Curr Diab Rep (2013) 13: 453. doi:10.1007/s11892-013-0393-9

Abstract

Diabetic retinopathy (DR) is a vision-threatening complication of diabetes. Timely diagnosis and intervention are essential for treatment that reduces the risk of vision loss. A good color retinal (fundus) photograph can be used as a surrogate for face-to-face evaluation of DR. The use of computers to assist or fully automate DR evaluation from retinal images has been studied for many years. Early work showed promising results for algorithms in detecting and classifying DR pathology. Newer techniques include those that adapt machine learning technology to DR image analysis. Challenges remain, however, that must be overcome before fully automatic DR detection and analysis systems become practical clinical tools.

Keywords

Diabetic retinopathyComputer-aided diagnosisFundus photographyImage analysisMachine learning

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.School of Computing, Informatics & Decision Systems EngineeringArizona State UniversityTempeUSA
  2. 2.Weill Cornell Medical College / The Methodist HospitalHoustonUSA
  3. 3.School of Biomedical InformaticsThe University of Texas Health Science CenterHoustonUSA
  4. 4.Department of OphthalmologyThomas Jefferson UniversityPhiladelphiaUSA