• Darshan Kapadia
• Akhilesh Dhiman
• Prathamesh Gangurde
• Osama Ansari

Diabetic Retinopathy is major disease that has affected over 290 million people globally and 69.2 million people in India, rate of people getting affected will increase exponentially in the coming years. Diabetic Retinopathy is an ailment linked to fundus of eye and have adverse effects on the patient, if at all left undiagnosed respectively. Despite years of clinical and laboratory investigation, diabetic Retinopathy remains the leading cause of vision disability and blindness among working-age adults, yet the fundamental causes remains uncertain. Retinal photo-coagulation to reduce neovascularization and macular edema was developed in the 1950s and is still the standard of care . The number of people worldwide at risk of developing vision loss from diabetes is predicted to double over next 30 years, so it is vital to develop better means to identify, prevent, and treat Retinopathy in its earliest stages rather than wait for onset of vision-threatening lesions. Progress in these areas requires new perspective on problem that includes roles of the neural retina, diminished insulin action, and inflammation. In this way, established neurobiological principles can inform us how diabetes weaken vision, and knowledge of metabolism, inflammation, and renewal medicine may lead to new treatments. Diabetic Retinopathy affects up to 80 percent of those who have had diabetes for 20 years or more. At least 90% of new cases could be reduced with proper treatment and observing of the eyes. The longer person has diabetes, higher his or her chances of developing Diabetic Retinopathy. Each year in the United States, diabetic Retinopathy accounts for 12% of all new cases of blindness. It is also leading cause of blindness in people aged 18 to 64. Our project aims to construct a graphical user interface that can integrate image processing techniques together in order to predict whether input fundus/retinal image collected from patient is affected with Diabetic Retinopathy or not; if affected, the graphical user interface (GUI) will display the severity along with the required action needed to be undertaken by patient. This essentially reduces processing time involved in the process of detecting the disease and also the ophthalmologists can also have our graphical user interface as a backup that can be used for validating in detecting the disease

Diabetic Retinopathy, Fundus, Exudate.

"Detection of Diabetic Retinopathy Using Image Processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 5, page no.c269-c277, May-2021, Available :http://www.jetir.org/papers/JETIR2105289.pdf

"Detection of Diabetic Retinopathy Using Image Processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 5, page no. ppc269-c277, May-2021, Available at : http://www.jetir.org/papers/JETIR2105289.pdf