Tuberculosis Detection AI Project

Overview

This project aims to develop an AI-based system for the detection of Tuberculosis (TB) in chest X-ray images. Tuberculosis is a contagious bacterial infection that primarily affects the lungs and can be life-threatening if not diagnosed and treated early. The goal of this project is to assist healthcare professionals in the early detection of TB through automated image analysis.

Features

• Automated classification of chest X-ray images into TB-positive or TB-negative categories.
• User-friendly web application for uploading and analyzing X-ray images.
• Continuous Integration/Continuous Deployment (CI/CD) pipeline for efficient development and deployment.
• Monitoring and alerting to ensure system health and performance.

Technologies Used

• Python
• TensorFlow for AI model development
• Flask for the web application
• Docker for containerization
• Jenkins for CI/CD automation
• Prometheus and Grafana for monitoring

Getting Started

Prerequisites

• Python (3.x)
• Docker
• Git
• Jenkins (if setting up CI/CD)
• Prometheus and Grafana (if setting up monitoring)

Installation

1. Clone this repository to your local machine:

   git clone <repository-url>
   cd TuberculosisAI

2. Develop a simplified TB detection AI model using Python and TensorFlow/Keras:

   python3 tb_detection_model.py

3. Build and run the Docker container:

   docker build -t <docker-image-name> .
   docker run -d -p 5000:5000 <docker-container-name:tag name>

4. Access the web application at http://localhost:5000

Screenshots

Usage

1. Upload a chest X-ray image through the web application.
2. Wait for the AI model to process the image.
3. View the classification result (TB-positive or TB-negative) on the web interface.

Contributing

Contributions are welcome! If you would like to contribute to this project, please open an issue or submit a pull request.

License

This project is licensed under the MIT License.

Author

• Ravi Rajvanshi (AI Enthusiast, DevOps Engineer, Web Developer)

Contributors

• Dr. Rajiv Garg (Professor at KGMU, Lucknow)
• Akshaya Singh (DevOps Engineer)

Contact

For questions or inquiries, please contact at its.ravi@outlook.com.

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