Deep Learning Based Cataract Detection System

Deep Learning-Based Cataract Detection System.

A state-of-the-art cataract detection system that can analyze eye images with unparalleled accuracy and efficiency.

Mission.

"Our mission is to revolutionize the approach to cataract detection and treatment by leveraging the power of deep learning and artificial intelligence. We are committed to developing an automated cataract detection system that is accurate, efficient, and accessible to healthcare providers."

Objective

The primary objective is to design and develop a mobile application that detects cataracts through analyzing uploaded eye images.

The goals of the system are ;

To use well trained deep learning models to ensure high accuracy in cataract detection.
To develop a user-friendly interface that allows healthcare providers to easily upload eye images and access diagnostic results.
To design the application to be accessible and easy to use across diverse healthcare settings, ensuring it benefits a wide range of users regardless of their technical expertise.

Concept Paper

This entails a brief overview of the project's purpose and potential benefits

Data Collection Plan

This document outlines the process and methodology for collecting data .

Software Requirement Specification

This provides a clear and shared understanding of what needs to be built. It serves as a reference point for developers, testers, and other stakeholders throughout the project's lifecycle

Final Report and Software Design Document

TEAM GALLERY

Click the button below to access the Software Design Document and the Final Report