Radiograph Morphometry Agent

An LLM agent that drafts structured reports for musculoskeletal radiographs, grounded in automated morphometry and retrieved guideline text.

Project Page

Note

Work in progress. This is an ongoing research project and not a medical device. A reader study with radiologists is coming soon.

Overview

The agent connects three services:

• a language model (any OpenAI-compatible vision model) that runs the case and writes the report
• a morphometry service (RadiographLandmarkMatching) that places the landmarks and computes every measurement
• a guideline search (your own retrieval system or a folder of text files) that supplies every reference range

The language model never supplies a number or a threshold of its own. The radiologist can correct landmarks, and the report follows.

Getting started

You need Python 3.11+, Node.js 18+ and access to the three services above.

pip install -r requirements.txt
cp .env.example .env        # model, guideline search and morphometry service
python run.py               # open http://localhost:5173

Each service is configured in .env and can be replaced, see docs/configuration.md. The interface and the reports are in German.

Citation

A paper on the agent is in preparation. Until then, please cite the morphometry framework:

@article{eschweiler2026landmark,
  title   = {An Artificial Intelligence Framework for Universal Landmark Matching and Morphometry in Musculoskeletal Radiography},
  author  = {Eschweiler, Dennis and Cornejo Merodio, Eneko and Barajas Ordonez, Felix and Lichev, Aleksandar and Ignatova, Nikol and von der St{\"u}ck, Marc Sebastian and Kuhl, Christiane and Truhn, Daniel and Nebelung, Sven},
  journal = {European Radiology},
  year    = {2026},
  doi     = {10.1007/s00330-026-12555-y}
}