README.md

metadata

title: Medical Phase Simulator Backend
emoji: 🏥
colorFrom: blue
colorTo: purple
sdk: docker
pinned: false

MedTech Image Processing Backend

FastAPI-based backend service for processing medical images with arterial and venous phase filters.

Features

• Arterial Phase Processing: CLAHE-based contrast enhancement for improved visibility
• Venous Phase Processing: Gaussian smoothing/blur for noise reduction
• RESTful API: Simple POST endpoint for image processing
• CORS Enabled: Works with frontend hosted on GitHub Pages
• Docker Ready: Containerized for easy deployment on Hugging Face Spaces

API Endpoints

POST /process

Process a medical image with specified phase filter.

Parameters:

• image (file): Medical image file (JPG/PNG)
• phase (form): Processing phase - "arterial" or "venous"

Response:

• Processed image as PNG

Example using curl:

curl -X POST "http://localhost:7860/process" \
  -F "image=@sample.jpg" \
  -F "phase=arterial" \
  --output processed.png

GET /

Health check and API information.

GET /health

Detailed health check with library versions.

Local Development

Prerequisites

• Python 3.10+
• pip

Setup

1. Install dependencies:

pip install -r requirements.txt

2. Run the server:

python app.py

The API will be available at http://localhost:7860

Using uvicorn directly:

uvicorn app:app --reload --port 7860

Docker Deployment

Build locally:

docker build -t medtech-backend .
docker run -p 7860:7860 medtech-backend

Hugging Face Spaces Deployment

1. Create a new Space at huggingface.co/spaces
2. Select Docker as the SDK
3. Clone the Space repository:

git clone https://huggingface.co/spaces/YOUR-USERNAME/YOUR-SPACE-NAME

4. Copy backend files:

cp app.py Dockerfile requirements.txt YOUR-SPACE-NAME/
cd YOUR-SPACE-NAME

5. Commit and push:

git add .
git commit -m "Initial commit"
git push

6. Your Space will automatically build and deploy at: https://YOUR-USERNAME-YOUR-SPACE-NAME.hf.space

Image Processing Details

Arterial Phase (Contrast Enhancement)

• Uses CLAHE (Contrast Limited Adaptive Histogram Equalization)
• Operates in LAB color space for better results
• Parameters: clipLimit=3.0, tileGridSize=(8,8)

Venous Phase (Gaussian Smoothing)

• Applies Gaussian blur with 15x15 kernel
• Reduces noise and smooths fine details
• Simulates venous phase imaging characteristics

Tech Stack

• FastAPI: Modern Python web framework
• OpenCV: Image processing library
• NumPy: Numerical computing
• Pillow: Image I/O
• Uvicorn: ASGI server

Error Handling

The API includes comprehensive error handling:

• Invalid file types → 400 Bad Request
• Invalid phase parameter → 400 Bad Request
• Processing errors → 500 Internal Server Error

CORS Configuration

CORS is configured to accept requests from:

• GitHub Pages (*.github.io)
• Localhost (development)
• All origins (can be restricted for production)

Testing

Test the API with sample medical images:

import requests

url = "http://localhost:7860/process"
files = {"image": open("sample.jpg", "rb")}
data = {"phase": "arterial"}

response = requests.post(url, files=files, data=data)

with open("output.png", "wb") as f:
    f.write(response.content)

License

This is a demonstration project for educational purposes only. Not intended for clinical use.

Disclaimer

⚠️ Important: This application is for educational and demonstration purposes only. It should NOT be used for actual medical diagnosis or clinical decision-making. Always consult qualified healthcare professionals for medical imaging interpretation.