Minimal annotation muscle segmentation (MuSeg)

Minimal annotation muscle segmentation (MuSeg) based on artificial intelligence (AI), short MuSegAI. If you use this work, please consider citing it.

The repository provides a command line interface (CLI) based on a Docker image for segmentation. Prerequisites for the segmentation are two Dixon MRI volumes at echo times 1.95 and 2.75 ms (in- and out-of-phase volumes). Currently, a segmentation model for the thigh muscles is available, which segments 13 muscles (see ./docker/labels_thigh.txt). The volumes can either contain both thighs or left and right only.

Installation

Install the MuSeg-AI package by (tested on Ubuntu 22.04 with Python 3.10)

git clone https://github.com/fabianbalsiger/minimal-annotation-muscle-segmentation.git
cd minimal-annotation-muscle-segmentation
pip install .[cli]

You can also directly work with the Docker image available on DockerHub, pull it by

docker pull fabianbalsiger/museg:thigh-model3

Follow the docker/README.md instructions on how to execute a Docker container for segmentation.

CLI usage

Let's assume having volumes saved in a directory in as volume195.mha and volume275.mha (the names can be arbritary). Segment them by

museg-ai in/volume195.mha in/volume275.mha

The files volume195.mha, the segmentation, and labels.txt, an ITK-SNAP labels file, will be saved at the location where the script has been executed.

NOTE: If the Docker image for segmentation has not yet been pulled, it will be done automatically, which might take a while.

Print all available options by

museg-ai --help

Citation

The scientific article is currently under review. Please open an issue if you want to cite it before acceptance.

Development

A little project cheatsheet for development:

• pre-commit: pre-commit run --all-files --hook-stage=manual
• pytest: pytest or pytest -s
• coverage: coverage run -m pytest followed by coverage html or coverage report
• create towncrier entry: towncrier create 123.added --edit

Follow these steps for the initial project setup as well as setting up a new development environment:

1. See docs/getting_started.md or docs/quickstart.md for how to get up & running.
2. Check docs/project_specific_setup.md for project specific setup.
3. See docs/detect_secrets.md for more on creating a .secrets.baseline file using detect-secrets.
4. See docs/using_towncrier.md for how to update the CHANGELOG.md using towncrier.