# Multimodal Medical Imaging

> Analyzes medical images (X-ray, MRI, CT) using multimodal LLMs to identify anomalies and generate reports.

- Skill: `fridrichmethod/multimodal-medical-imaging` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add fridrichmethod/multimodal-medical-imaging`
- Raw SKILL.md: https://api.skillmd.com/api/skills/fridrichmethod/multimodal-medical-imaging/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: FridrichMethod (https://skillmd.com/u/fridrichmethod)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/fridrichmethod/multimodal-medical-imaging

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# 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."
```



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