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Diagnosis of diabetic retinopathy using multi level set segmentation algorithm with feature extraction using SVM with selective features

  • J. Pradeep Kandhasamy
  • S. Balamurali
  • Seifedine KadryEmail author
  • Lakshmana Kumar Ramasamy
Article
  • 29 Downloads

Abstract

Diabetic retinopathy is a major cause of blindness in diabetic patients. It is an eye disease caused by diabetes mellitus which affects the retina. Recognition of the severity of this disease at early stage is a challenging factor for the ophthalmologists. In this article, a novel diagnosis system for identifying the severity of diabetic retinopathy is proposed using a multi level set segmentation algorithm and support vector machine with selective features along with genetic algorithm. The proposed system uses some mathematical morphological operations for clustering. After that the clusters are passed to the multi level set segmentation algorithm and some features are extracted using Local Binary Patterns as a texture descriptor for retinal images, color moments and statistical features such as mean, median etc. to detect the major regions of retina. Then the extracted features are given to the support vector machine classifier to classify the disease severity. This system was evaluated and compared using measures of sensitivity and specificity. We obtain sensitivity of 97.14%, specificity of 100% and accuracy of 99.3% on an average. From the seen results, it is observed that our proposed system is suited for the diagnosis of diabetic retinopathy at the early stage.

Keywords

Diabetic retinopathy Fundus images Multi-level set segmentation Genetic algorithm Local binary patterns Support vector machine 

Notes

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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Computer Applications, School of ComputingKalasalingam Academy of Research and EducationKrishnankoilIndia
  2. 2.Department of Mathematics and Computer Science, Faculty of ScienceBeirut Arab UniversityBeirutLebanon
  3. 3.Department of Computer ApplicationsHindusthan College of Engineering and TechnologyCoimbatoreIndia

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