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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:

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

Project details


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