multimodal-medical-imaging
Analyzes medical images (X-ray, MRI, CT) using multimodal LLMs to identify anomalies and generate reports.
npx skills add majiayu000/claude-skill-registry --skill multimodal-analysis --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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.
- When to Use This Skill
- Core Capabilities
- Workflow
- Example Usage
python3 Skills/Clinical/Medical_Imaging/Multimodal_Analysis/multimodal_agent.py \
What does the multimodal-medical-imaging skill do?
Analyzes medical images (X-ray, MRI, CT) using multimodal LLMs to identify anomalies and generate reports.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill multimodal-analysis --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.