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      Algorithms for the automated detection of diabetic retinopathy using digital fundus images : a review

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      Author
      Faust, Oliver
      Acharya, U. Rajendra
      Ng, Eddie Yin-Kwee
      Ng, Kwan-Hoong
      Suri, Jasjit S.
      Date of Issue
      2010
      School
      School of Mechanical and Aerospace Engineering
      Abstract
      Diabetes is a chronic end organ disease that occurs when the pancreas does not secrete enough insulin or the body is unable to process it properly. Over time, diabetes affects the circulatory system, including that of the retina. Diabetic retinopathy is a medical condition where the retina is damaged because fluid leaks from blood vessels into the retina. Ophthalmologists recognize diabetic retinopathy based on features, such as blood vessel area, exudes, hemorrhages, microaneurysms and texture. In this paper we review algorithms used for the extraction of these features from digital fundus images. Furthermore, we discuss systems that use these features to classify individual fundus images. The classifications efficiency of different DR systems is discussed. Most of the reported systems are highly optimized with respect to the analyzed fundus images, therefore a generalization of individual results is difficult. However, this review shows that the classification results improved has improved recently, and it is getting closer to the classification capabilities of human ophthalmologists.
      Type
      Journal Article
      Series/Journal Title
      Journal of medical systems
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      • MAE Journal Articles
      http://dx.doi.org/10.1007/s10916-010-9454-7
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