README.md

metadata

title: MedGemma Radiology Report Generator
emoji: 🩻
colorFrom: purple
colorTo: indigo
sdk: gradio
python_version: '3.10'
app_file: app.py
sdk_version: 5.39.0

🏥 MedGemma Radiology Report Generator

Created by CultriX

This Hugging Face Space demonstrates the capabilities of Google's MedGemma 4b-it model, a medical-focused LLM designed for both image comprehension and medical text generation.

The application is accelerated by ZeroGPU for fast inference and features a dual-tab interface for different clinical workflows.

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✨ Features

1. 🩻 X-Ray Analysis Tab

   • Multimodal Analysis: Upload an X-ray to receive a structured radiology report (Findings, Impression, Recommendations).
   • Clinical Context: Optionally provide patient history (e.g., "65M, cough for 3 weeks") to guide the model's interpretation.
   • Interactive Chat: Ask follow-up questions about specific findings directly in the chat window after the report is generated.
   • Token Management: Real-time token counting ensures your input stays within the model's context window.

2. 💬 Medical Assistant Tab

   • Text-Only Mode: Chat with the MedGemma model about general medical concepts, differential diagnoses, or terminology without uploading an image.

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🕹️ How to Use

For X-Ray Analysis:

1. Go to the "🩻 X-Ray Analysis" tab.
2. Upload a chest X-ray image (PNG or JPEG).
3. (Optional) Enter relevant Clinical Information in the text box.
4. Click "🔬 Generate Report".
5. Once the report appears, use the chat box below it to ask follow-up questions (e.g., "Can you explain the pleural effusion finding?").

For General Questions:

1. Switch to the "💬 Medical Assistant" tab.
2. Type your medical question and hit Enter.

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🧠 Model Information

• Model: google/medgemma-4b-it
• Architecture: MedGemma is built on top of Gemma 3, fine-tuned with medical instruction data.
• Hardware: Powered by Hugging Face ZeroGPU (dynamic H100/A100 allocation) for efficient inference.
• Requirements: This Space uses sentencepiece and protobuf for tokenizer handling.

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⚠️ Disclaimer

This application is intended for research and demonstration purposes only.

• It should not be used for clinical decision-making.
• The model may hallucinate findings or miss critical anomalies.
• All generated reports must be reviewed and validated by a qualified medical professional.

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🔧 Known Limitations

• Image Formats: DICOM files are not yet supported — please convert to PNG or JPEG before uploading.
• Model Size: This demo uses the 4B parameter version. While fast, it may be less accurate than the larger 27B variant.
• ZeroGPU Quotas: Inference speed and availability depend on the current load of the ZeroGPU cluster.

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Feel free to fork this Space to customize the system prompts or integrate it into your own clinical AI research workflows!