Diabetic Retinopathy Detection Dataset

Dataset Features:

1. Balanced Data: The dataset is meticulously balanced to ensure an equal representation of all stages of diabetic retinopathy, facilitating robust training and evaluation of machine learning models.
2. High-Resolution Images: It contains high-resolution retinal images taken under various imaging conditions, ensuring diversity and comprehensiveness.
3. Annotations: Each image is annotated by medical professionals, providing accurate labels for each stage of diabetic retinopathy.

Diabetic Retinopathy Stages:

1. No_Dr: No signs of diabetic retinopathy.
2. Mild: Early signs, with small areas of balloon-like swelling in the retina’s blood vessels.
3. Moderate: Increased swelling and distortion of the blood vessels, leading to a reduced ability to transport blood.
4. Severe: Significant blockage of blood vessels, depriving several areas of the retina of blood supply, leading to the growth of new blood vessels.
5. Proliferative DR: Advanced stage with extensive growth of new, abnormal blood vessels that can cause severe vision problems, including bleeding into the eye.

Applications:

• Medical Research: Ideal for researchers working on automated detection and classification of diabetic retinopathy.
• Machine Learning Models: Perfect for training deep learning models in medical imaging.
• Clinical Decision Support: Can be used to develop systems that assist ophthalmologists in early diagnosis and treatment planning.