Abstract
There are no early symptoms associated with retinal diseases. Diabetic retinopathy (DR) is the leading cause of macular degeneration in people with diabetes in their 40s and 50s. It is a critical step in determining the stage of an ophthalmology preliminary abnormality diagnosis. DR lesions detected on images taken with the hospital's high-quality imaging equipment can now be screened and identified automatically by an image processing system. It is proposed to screen for early symptoms of DR by detecting abnormalities within retinal images using computer-based imaging. The purpose of this study is to conduct a review of existing works in the fields of artificial intelligence and image processing to develop an algorithm for an automatic DR screening system. A review paper on the use of deep learning with DR detection was introduced, as well as a section experimenting with DR in retinal fundus images from publicly available datasets. To enhance DR detection performance, feature extraction techniques would be suggested.
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