Computer Aided Diagnostic Techniques in Automated Detection of Eye Related Diseases - A Comparative Study

Authors

  • Dr. S. Mohan Kumar  Professor, Department of Information Science and Engineering, New Horizon College of Engineering, Bangalore.
  • Ms. Anisha Rebinth  Research Scholar -Visvesvaraya Technological University, Research Centre, Dept. of Information Science and Engineering, New Horizon College of Engineering, Bangalore.

Keywords:

Retinal abnormalities, Glaucoma, Diabetic retinopathy, Fundus images, Feature detection, Segmentation, Optic disc, Optic cup, KNN, Naïve -bayes, SVM.

Abstract

World Health Organization (WHO) in a new study has recognized eye related defects to be one of the primary health challenges faced by the existing society. Common retinal abnormalities include Glaucoma, Diabetic retinopathy and Macular degeneration. Retinal eye defects have significantly increased in the last decade across developing and developed countries. These defects if not diagnosed and treated at the appropriate time, would result in complete loss of vision. Diabetic retinopathy is predominantly common among diabetic patients. In Macular Degeneration, the central part of the retina is widely affected. In this case, the retinal cells deteriorate and images are not established correctly. The CAD system for eye diseases falls under the Supervised Learning techniques. This technique refers to methods that enable creation of a correlation with different features and labelled outcomes. Few of these include KNN, Naïve Bayes, Adaboost Classifiers, tree-based Classifier, ELM classifier, SVM and LIBSVM classifier etc. The main objective of this paper is to summarize the various CAD techniques adopted for early detection of eye diseases.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2019-12-30

Issue

Volume 4, Issue 9, November-December-2019

Section

Research Articles

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How to Cite

[1]
Dr. S. Mohan Kumar, Ms. Anisha Rebinth, " Computer Aided Diagnostic Techniques in Automated Detection of Eye Related Diseases - A Comparative Study" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 4, Issue 9, pp.698-704, November-December-2019.