---
name: 'multimodal-medical-imaging'
description: 'Analyzes medical images (X-ray, MRI, CT) using multimodal LLMs to identify anomalies and generate reports.'
measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes.
allowed-tools:
- read_file
- run_shell_command
---
# Multimodal Medical Imaging Analysis
The **Multimodal Medical Imaging Analysis Skill** leverages state-of-the-art Vision-Language Models (VLMs) like Gemini 1.5 Pro and GPT-4o to interpret medical imagery alongside clinical text.
## When to Use This Skill
* When you need a preliminary screening of medical images.
* When correlating visual findings with textual clinical notes.
* To generate structured reports (DICOM-SR-like) from raw images.
## Core Capabilities
1. **Anomaly Detection**: Identify potential pathologies in X-rays, CTs, etc.
2. **Report Generation**: Draft radiology reports in standard formats.
3. **VQA (Visual Question Answering)**: Answer specific questions about an image (e.g., "Is there a fracture in the left femur?").
## Workflow
1. **Input**: Provide an image file path (JPG, PNG) and a specific clinical question or "generate report" instruction.
2. **Analyze**: The agent sends the image and prompt to the VLM.
3. **Output**: Returns a JSON object with findings, confidence scores, and reasoning.
## Example Usage
**User**: "Analyze this chest X-ray for pneumonia."
**Agent Action**:
```bash
python3 Skills/Clinical/Medical_Imaging/Multimodal_Analysis/multimodal_agent.py \
--image "/path/to/cxr.jpg" \
--prompt "Check for signs of pneumonia and consolidation."
```