Analysing Diabetic hypertensive retinopathy in ocular image

Project Description

Developed an image analysis system to detect and classify signs of diabetic and hypertensive retinopathy from retinal (fundus) images. The project focused on identifying abnormalities such as microaneurysms, hemorrhages, exudates, and blood vessel changes associated with diabetes and hypertension. Applied image processing and machine learning techniques to enhance retinal images, extract relevant features, and support early diagnosis. The system aims to assist healthcare professionals in screening patients efficiently, improving disease detection accuracy, and reducing the risk of vision loss through timely intervention.

Technology Used

Output

This project you will get

• Project zip file
• Execution guide
• Report