🏥 Medical Visualization Platform

A professional Flask-based web application for visualizing 3D medical imaging data, fully containerized with Docker.

👉 Live Demo: Try the app directly in your browser on Hugging Face Spaces here.

✨ Features

• 📁 File Upload: Support for NIfTI (.nii, .nii.gz) and NumPy (.npy) formats
• 🔬 2D Slice Viewing: Visualize axial, coronal, and sagittal slices
• 📊 3D Volume Rendering: Interactive volume visualization with customizable opacity
• 🎨 Multiple Colormaps: Gray, Bone, Viridis, Hot, Cool, Plasma
• 🐳 Docker Ready: Fully containerized for deployment on Hugging Face Spaces or anywhere
• ⚡ Fast & Stable: Pure Flask backend with custom frontend

🚀 Quick Start on Hugging Face Spaces

This Space is ready to use! Just click on the application above.

Upload and Visualize

1. Upload a medical imaging file (.nii, .nii.gz, or .npy)
2. Select visualization mode:
   • 2D Slice View (Axial, Coronal, or Sagittal)
   • 3D Volume Rendering
3. Adjust settings (colormap, opacity, slice index)
4. Generate visualization

💻 Local Development

Using Docker Compose

# Clone the repository
git clone [your-repo-url]
cd medical-visualization-platform

# Build and start
docker-compose up --build

Visit http://localhost:5000

Using Docker Manually

# Build the Docker image
docker build -t medical-viz .

# Run the container
docker run -p 5000:5000 medical-viz

Without Docker

# Install dependencies
pip install -r requirements.txt

# Run the Flask application
python app.py

📁 Project Structure

medical-visualization-platform/
├── Dockerfile              # Container configuration
├── app.py                  # Flask application
├── requirements.txt        # Python dependencies
├── templates/
│   └── index.html         # Web interface
├── static/
│   ├── css/style.css      # Styling
│   └── js/app.js          # Frontend logic
├── uploads/               # Uploaded files (auto-created)
└── outputs/               # Generated visualizations (auto-created)

🔧 Technology Stack

Backend:

• Flask 3.0 - Web framework
• PyVista - 3D visualization
• nibabel - Medical imaging I/O
• NumPy - Numerical computing
• Matplotlib - 2D plotting

Frontend:

• Pure HTML5/CSS3/JavaScript
• Modern responsive design

Deployment:

• Docker containerized
• Hugging Face Spaces ready

🔒 Security Notes

• Maximum file size: 500MB
• Supported formats: .nii, .nii.gz, .npy only
• Files are temporarily stored and should be cleaned periodically