Label fusion strategies for multi-class labels.
Project description
LabelFusion
This repo contains implementation of various label fusion approaches that can be used to fuse multiple labels.
Installation
git clone ${labelFusion_repo_link}
cd LabelFusion
conda create -p ./venv python=3.6.5 -y
conda activate ./venv
pip install -e .
Available LabelFusion:
- Voting (ITK): DOI:10.1016/j.patrec.2005.03.017
- STAPLE (ITK): DOI:10.1109/TMI.2004.830803
- Majority Voting: DOI:10.1007/978-3-319-20801-5_11
- SIMPLE: DOI:10.1109/tmi.2010.2057442
Usage
# continue from previous shell
python fusion_run -h
-h, --help show this help message and exit
-inputs INPUTS The absolute, comma-separated paths of labels that need to be fused
-classes CLASSES The expected labels; for example, for BraTS, this should be '0,1,2,4'
-method METHOD The method to apply; currently available: STAPLE | ITKVoting | MajorityVoting | SIMPLE
-output OUTPUT The output file to write the results
Example:
# continue from previous shell
python fusion_run \
-inputs /path/to/seg_algo_1.nii.gz,/path/to/seg_algo_2.nii.gz,/path/to/seg_algo_3.nii.gz \
-classes 0,1,2,4 \
-method STAPLE \
-output /path/to/seg_fusion.nii.gz
Testing
This repo has continuous integration enbabled via Azure DevOps for the following operating systems:
- Windows
- Ubuntu
- macOS
And for the following python versions:
- 3.6
- 3.7
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