src/demo/README.md

Medical Image Analyzer Demo

This folder contains demo applications for the gradio_medical_image_analyzer custom component.

⚠️ IMPORTANT MEDICAL DISCLAIMER ⚠️

THIS SOFTWARE IS FOR RESEARCH AND EDUCATIONAL PURPOSES ONLY

🚨 DO NOT USE FOR CLINICAL DIAGNOSIS OR MEDICAL DECISION MAKING 🚨

This component is in EARLY DEVELOPMENT and is intended as a proof of concept for medical image analysis integration with Gradio. The results produced by this software:

• ARE NOT validated for clinical use
• ARE NOT FDA approved or CE marked
• SHOULD NOT be used for patient diagnosis or treatment decisions
• SHOULD NOT replace professional medical judgment
• MAY CONTAIN significant errors or inaccuracies
• ARE PROVIDED without any warranty of accuracy or fitness for medical purposes

ALWAYS CONSULT QUALIFIED HEALTHCARE PROFESSIONALS for medical image interpretation and clinical decisions. This software is intended solely for:

• Research and development purposes
• Educational demonstrations
• Technical integration testing
• Non-clinical experimental use

By using this software, you acknowledge that you understand these limitations and agree not to use it for any clinical or medical diagnostic purposes.

Demo Files

• app.py - Main demo application showcasing all features of the medical image analyzer
• space.py - Hugging Face Spaces-optimized version
• app_with_frontend.py - Demo with custom frontend integration
• wrapper_test.py - Test file for component wrapper functionality
• css.css - Custom styling for the demo interface

Installation

pip install -r requirements.txt

Running the Demo

Local Development

python app.py

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

Hugging Face Spaces

python space.py

Features Demonstrated

1. File Upload Support

   • DICOM files (.dcm, .dicom)
   • Standard image formats (PNG, JPG, TIFF, BMP)
   • Files without extensions (e.g., IM_0001)

2. Analysis Tasks

   • 🎯 Point Analysis - Analyze specific ROI in the image
   • 🔬 Fat Segmentation - CT-specific fat tissue analysis
   • 📊 Full Analysis - Comprehensive image analysis

3. Modality Support

   • CT (Computed Tomography)
   • CR (Computed Radiography)
   • DX/RX/DR (Digital X-ray variants)

4. Interactive Features

   • ROI selection with sliders
   • Clinical context input
   • Overlay visualization
   • Real-time analysis

Sample Workflow

1. Upload a medical image (DICOM or standard format)
2. Select the imaging modality (auto-detected for DICOM)
3. Choose an analysis task
4. Adjust ROI if needed
5. Click "Analyze" to get results

Output Formats

• Visual Report: HTML-formatted analysis results
• JSON Output: Structured data for AI agents and integration
• Overlay View: Visual annotations on the original image

Development Notes

• The demo uses a dark medical theme optimized for clinical environments
• All processing is done locally - no data is sent to external servers
• The component is designed for both human interpretation and AI agent integration

Troubleshooting

If you encounter issues:

1. Ensure all dependencies are installed: pip install -r requirements.txt
2. Check that you have the correct Python version (3.8+)
3. For DICOM files, ensure they are valid medical images
4. Report issues at: https://github.com/thedatadudech/gradio-medical-image-analyzer/issues

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