Agent skill

multimodal-medical-imaging

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Install this agent skill to your Project

npx add-skill https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/multimodal-medical-imaging

SKILL.md


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."

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