AI-Powered CXR Diagnostic System

Overview

Welcome to the AI-Powered CXR Diagnostic System! This project utilizes advanced AI and machine learning techniques to streamline the radiologist workflow by automating the analysis of chest X-ray (CXR) images. Built with PyTorch and Flask, this system uses a DenseNet121 pretrained model from torchxrayvision to detect 14 different pathologies with high accuracy, making the diagnostic process faster and more efficient.

Features

• Accurate Detection: Leverages the DenseNet121 model from torchxrayvision for precise identification of 14 different pathologies in CXR images.
• User-Friendly Interface: Simple and intuitive web interface for uploading and analyzing images.
• Real-Time Results: Provides quick diagnostic results to assist radiologists in making informed decisions.

Pathologies Detected

This system can detect the following 14 pathologies from the NIH ChestX-ray14 dataset:

1. Atelectasis
2. Cardiomegaly
3. Effusion
4. Infiltration
5. Mass
6. Nodule
7. Pneumonia
8. Pneumothorax
9. Consolidation
10. Edema
11. Emphysema
12. Fibrosis
13. Pleural Thickening
14. Hernia

Technologies Used

Installation

1. Clone the Repository:

   git clone https://github.com/HuzaifaKhaan/AI-Powered-CXR-Diagnostic-System.git
   cd AI-Powered-CXR-Diagnostic-System

2. Create a Virtual Environment and Activate It:

   python -m venv venv
   source venv/bin/activate  # On Windows, use `venv\Scripts\activate`

3. Install the Dependencies:

   pip install -r requirements.txt

Usage

1. Run the Flask Application:

   python app.py

2. Open Your Browser and Navigate to:

   http://127.0.0.1:5000
   

3. Upload a CXR Image:

   • Click on the "Upload" button and select a CXR image from your local machine.

4. Get Diagnostic Results:

   • The system will analyze the image using the DenseNet121 model and display the diagnostic results on the screen.

Project Structure

.
├── app.py                # Main application file
├── requirements.txt      # Project dependencies
├── static/               # Static files (CSS, JS, images)
├── templates/            # HTML templates
├── testing_images/       # Directory for test images
└── .vscode/              # VSCode configuration files

Feel free to reach out if you have any questions or suggestions!