Abstract :

Cataract is one of the leading causes of preventable blindness worldwide, especially in developing countries where access to ophthalmologists is limited. Early and accurate detection plays a crucial role in timely treatment and vision preservation. This project proposes an Artificial Intelligence (AI)-based cataract detection system using deep learning techniques on eye images. The system automatically analyzes retinal or slit-lamp images to identify cataract presence and severity. By leveraging convolutional neural networks (CNNs), the model achieves high accuracy with minimal human intervention. The proposed approach reduces diagnosis time and cost while improving screening coverage. It is suitable for real-time deployment in hospitals and rural health centers. The system aims to support clinicians with reliable decision assistance.