Diabetic Retinopathy Diagnosing using Fuzzy Image Processing
Himal Chitara1, Raksha K Patel2, Tejas V Bhatt3

1Himal Chitara*, Department of Biomedical Engineering, U. V. Patel College of Engineering, Ganpat University, India.
2Prof. Raksha K Patel, Department of Biomedical Engineering, U. V. Patel College of Engineering, Ganpat University, India.
3Prof. Tejas V Bhatt, Department of Biomedical Engineering, U. V. Patel College of Engineering, Ganpat University, India.
Manuscript received on March 15, 2020. | Revised Manuscript received on March 24, 2020. | Manuscript published on March 30, 2020. | PP: 4210-4215 | Volume-8 Issue-6, March 2020. | Retrieval Number: F9240038620/2020©BEIESP | DOI: 10.35940/ijrte.F9240.038620

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Aim: To design diagnostic expert system using fuzzy image processing for diabetic retinopathy, measures diabetic eye morbidity. Method: From this research paper, diagnosing diabetic retinopathy using fuzzy image processing for diabetic patients. Firstly collection of OCT images of the patient who has diabetic retinopathy. Author’s proposed method finds out the edge detection of the OCT image. Then fuzzy logic is applied on that result of image processing. Design a fuzzy rules and input- output parameter. This method gives accurate diagnosing the diabetic retinopathy from the image of the patient’s retina images. Result: This diagnostic system gives patient’s eye morbidity, vision threatening of the diabetic patients. In the result, edges of the retina images, and from that retinal ruptures, thickness of the proliferative in the retina. From these result, diagnostic of diabetic retinopathy conditions such as PDR, NPDR, and NORMAL, and CSME in the diabetic patients. Conclusion: author has design diagnostic system for endocrinologist and ophthalmology to diagnosed diabetic retinopathy in the patients. From this system doctors don’t need patients for diagnosing purposed.
Keywords: Diabetic Retinopathy, Fuzzy Inference System, Image Processing, Fuzzy Image Processing.
Scope of the Article: Signal and Image Processing.