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An Effective Detection Mechanism for Localizing Macular Region and Grading Maculopathy

  • C. R. DhivyaaEmail author
  • M. Vijayakumar
Mobile & Wireless Health
  • 22 Downloads
Part of the following topical collections:
  1. Wearable Computing Techniques for Smart Health

Abstract

The eye disease is prominent in many nations including India and is said to affect up to 80% patients having diabetes. Diabetic Retinopathy is the medical term for denoting the damages to retina caused due to diabetes mellitus. Implying K means Clustering algorithm for coarse segmentation, hard distils are identified with better accuracy than the classical approaches. The variance based methods for segmenting hard distils are reviewed in the surveys and had to be improved. To remove the background features from the picture and conserve computational costs, a mathematical morphological method is used to reconstruct the image features for better segmentation. The results obtained for 96.4% sensitivity and 97.2% specificity. Along with this advantage, a graphical user interface is developed which will simplify the usage of this system. This model will divide the fragments into regions of interests having lesions and normal regions carrying normal features. After this segmentation, ophthalmologists will utilize the results to grade diabetic retinopathy and devise a treatment plan.

Keywords

Retinal images K-means clustering macular region GUI 

Notes

Compliance with Ethical Standards

Conflict of Interests

The authors declare that this article content has no conflict of interest.

Ethical Approval

This article does not contain any studies with human participants or animals performed by any of the author.

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Copyright information

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

Authors and Affiliations

  1. 1.Computer Science and EngineeringNandha College of TechnologyErodeIndia
  2. 2.Computer Science and EngineeringNandha College of TechnologyErodeIndia

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