Diagnosis of Diabetic Retinopathy Using Artificial Intelligence Techniques
DOI:
https://doi.org/10.5281/Keywords:
Diabetic Retinopathy, Fundus Images, Retina, Support vector machine, K-Means ClusteringAbstract
The complication of diabetics causes an illness known as Diabetic Retinopathy (DR). It is very widespread among middle-aged and older people. As diabetes progresses, the vision of patients may start to deteriorate and cause DR. People lose their eye visions because of this illness. To cope with DR, an early detection is needed. Patients will have to be checked by doctors regularly which is a waste of time and energy. DR can be divided into two groups; one is non-proliferative (NPDR) while the other is proliferative (PDR). In this study, Artificial Intelligence (AI) techniques are used to diagnose DR at an early stage. These are PNN, SVM, Bayesian Classification and K-Means Clustering. These techniques will be evaluated and compared with each other to choose the best methodology. A total of 300 fundus photographs are processed for training and testing. The features are extracted from these raw images using the image processing techniques. After an experiment, it is concluded that PNN has an accuracy of about 89%, Bayes Classifications 94%, SVM 97% and K-Means Clustering 87%. The preliminary results prove that SVM is the best technique for early detection of DR.
Published
Issue
Section
License
Copyright (c) 2022 AINTELIA Science Notes Journal
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
COPYRIGHT NOTICE
Authors submitting a manuscript do so on the understanding that if accepted for publication, copyright of the article shall be assigned to Aintelia® Science Notes Journal (ASNJ).
By submitting their work, authors agree to the following terms:
-
Copyright Transfer: Copyright of the published article is transferred to Aintelia® Science Notes Journal. The journal reserves the right to publish, reproduce, distribute, and archive the work.
-
Licensing: While the journal retains the copyright, the article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). This allows third parties to share and adapt the work for non-commercial purposes, provided the original work and the journal are properly cited.
-
Author Rights: Authors retain the right to use their article for their own scholarly needs, such as including it in a thesis or dissertation, presenting it at conferences, or distributing it to students for educational purposes, provided that the journal is cited as the original publisher.
