Neural Network Technique for Diabetic Retinopathy Detection
Prabhjot Kaur1, Somsirsa Chatterjee2, Dilbag Singh3

1Prabhjot Kaur*, Apex Institute of Technology, Chandigarh University, Gharuan, India.
2Somsirsa Chatterjee, Apex Institute of Technology, Chandigarh University, Gharuan, India.
3Dilbag Singh, Apex Institute of Technology, Chandigarh University, Gharuan, India.
Manuscript received on July 20, 2019. | Revised Manuscript received on August 10, 2019. | Manuscript published on August 30, 2019. | PP: 440-445 | Volume-8 Issue-6, August 2019. | Retrieval Number: E7835068519/2019©BEIESP | DOI: 10.35940/ijeat.E7835.088619
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Abstract: The diabetes retinopathy is the application of medical image processing. The retinal images are evaluated to diagnose the DR. It is however, time consuming and resource demanding to manually grade the images such that the severity of DR can be defined. When the tiny blood vessels present within the retina are damaged, only then can one notice this problem. Blood will flow from this tiny blood vessel and features are formed from the fluid that exists on retina. The kinds of features involved here due to the leakage of fluid and blood from the blood vessels are considered to be the most important factors to study this problem. The diabetes retinopathy detection techniques has the three phase which pre-processing, segmentation and classification. In this work, NN approach is used for the classification of diabetes portion from the image. The proposed model is implemented in MATLAB and results are analyzed in terms of certain parameters.
Keywords: Diabetes retinopathy, NN, Optical Disk Segmentation.