Multilayer Perceptron Model- A Novel Methodology towards the Advance Determination of Diabetic Retinal Infirmity in Kids

Rosy Mishra¹ , K. Baishnabi² , Lopamudra Sahu³ , J.S. Amartya Bania⁴

Section:Research Paper, Product Type: Journal-Paper
Vol.6 , Issue.9 , pp.77-85, Sep-2020

Online published on Sep 30, 2020

Copyright © Rosy Mishra, K. Baishnabi, Lopamudra Sahu, J.S. Amartya Bania . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
The diabetic retinal infirmity is a very complex as well as chronic disease that affects many people including children. In this paper we have introduced an advance method for the detection of Diabetic retinal infirmity in children (age 1-12). Diabetic retinal infirmity is a type of diabetic complication caused due to increase in blood sugar level {hyperglycemia}, as it weakens and damages the delicate blood vessels present in retina. The early stage of diabetic retinal infirmity doesn’t exhibit any difficulties in vision but later on over time, if it kept untreated the vision level get dwindled accordingly and could leads to poor vision and blindness. It includes symptoms like appearance of dark patches and dots during the vision. Moreover, fogyish and vibrate vision, dark and impaired color visions. Hence proper observation and identification in the initial stage of this disease is indispensable. However, its identification is a tough task for the ophthalmologist. So, in this paper, various images of retina mainly the fundus of eye is examined by the technique of digital image processing done by the MATLAB and employing Multilayer Perceptron Model of artificial neural network (ANN), where by carefully observing the hemorrhages in the rear part of eye(retina), we can get confirmation about the diseases.

Key-Words / Index Term :
Diabetic retinal infirmity, Retina, ANN, Hyperglycemia, MLP, Fuzzy C-means

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