CT Scan Image Analyzer

A web-based application for performing basic analysis on CT scan images using computer vision and image processing techniques. This educational tool demonstrates fundamental image analysis concepts applied to medical imaging.

Screenshot of the CT-Scan-Image-Analyzer Web Application

🚨 Important Disclaimer

⚠️ FOR EDUCATIONAL PURPOSES ONLY
This application is designed for educational and demonstration purposes only. It does NOT provide medical diagnoses and should NEVER be used for actual medical decision-making. Always consult qualified medical professionals for proper interpretation of medical images.

Features

• 📤 Image Upload: Support for common image formats (PNG, JPG, JPEG, etc.)
• 🔍 Basic Analysis: Performs fundamental image processing analysis
• 📊 Statistical Metrics: Calculates mean intensity, standard deviation, and edge detection
• 🎯 Pattern Detection: Identifies basic structural patterns in images
• 📱 Responsive Design: Works on desktop and mobile devices
• ⚡ Real-time Processing: Instant analysis results

Technology Stack

• Backend: Python Flask
• Image Processing: OpenCV, Pillow
• Frontend: HTML5, CSS3, JavaScript
• Styling: Modern CSS with responsive design

Installation

Prerequisites

• Python 3.7 or higher
• pip package manager

Setup Instructions

1. Clone the repository

   git clone https://github.com/shakiliitju/CT-Scan-Image-Analyzer
   cd CT-Scan-Image-Analyzer

2. Create a virtual environment (recommended)

   python -m venv venv
   
   # On Windows
   venv\Scripts\activate
   
   # On macOS/Linux
   source venv/bin/activate

3. Install dependencies

   pip install -r requirements.txt

4. Run the application

   python app.py

5. Access the application Open your web browser and navigate to http://127.0.0.1:5000

Usage

1. Upload Image: Click on the file input and select a CT scan image
2. Preview: The selected image will be displayed for preview
3. Analyze: Click the "Analyze Image" button to start processing
4. View Results: Review the analysis results including:
   • Mean intensity values
   • Standard deviation metrics
   • Edge structure count
   • Basic findings and observations

Project Structure

CT-Scan-Image-Analyzer/
│
├── app.py                 # Main Flask application
├── requirements.txt       # Python dependencies
├── README.md             # Project documentation
│
├── templates/
│   └── index.html        # Main HTML template
│
├── test images/
│   └──         
│
├── screenshots/
│   └── 1.png
│   ├── 2.png
│   ├── 3.png
│   └── 4.png
│
├── static/
│   ├── style.css         # CSS styling
│   └── script.js         # JavaScript functionality
│
└── uploads/              # Directory for uploaded images

Analysis Features

The application performs the following basic analyses:

• Intensity Analysis: Calculates mean and standard deviation of pixel intensities
• Edge Detection: Uses Canny edge detection to identify structural boundaries
• Contrast Assessment: Evaluates high and low contrast regions
• Density Analysis: Identifies potential high-density areas (bones, contrast material)

Dependencies

• Flask==2.3.3 - Web framework
• opencv-python==4.8.1.78 - Computer vision library
• Pillow==10.0.1 - Image processing library
• numpy==1.24.3 - Numerical computing library

Screenshots

Screenshot of the CT-Scan-Image-Analyzer Screenshot of the CT-Scan-Image-Analyzer Screenshot of the CT-Scan-Image-Analyzer

Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/new-feature)
3. Commit your changes (git commit -am 'Add new feature')
4. Push to the branch (git push origin feature/new-feature)
5. Create a Pull Request

Future Enhancements

• DICOM file support
• Advanced image filters
• Multi-image batch processing
• Export analysis reports
• Enhanced visualization tools

Educational Context

This project demonstrates:

• Web application development with Flask
• Image processing with OpenCV
• Computer vision techniques
• Medical imaging concepts
• Responsive web design

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgements

• OpenCV for computer vision tools
• Flask for the web framework
• Medical imaging community for educational resources

Contact

Developer: Md. Shakil Hossain
GitHub: @shakiliitju
Project Link: https://github.com/shakiliitju/CT-Scan-Image-Analyzer

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Remember: This tool is for educational purposes only and should never replace professional medical consultation.