/LabelFusion

Implementation of various label fusion approaches for medical imaging.

Primary LanguagePythonOtherNOASSERTION

LabelFusion

DOI

This repo contains implementation of various label fusion approaches that can be used to fuse multiple labels.

Installation

For Usage

conda create -n venv_labelFusion python=3.6.5 -y
conda activate venv_labelFusion
pip install LabelFusion

For Development

# fork to your own repo
git clone ${yourFork_labelFusion_repo_link}
cd LabelFusion
conda create -p ./venv python=3.6.5 -y
conda activate ./venv
pip install -e .
# develop, push
# initiate pull request

Available LabelFusion:

Usage

Command-Line interface

# 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' - not used for STAPLE or ITKVoting
  -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

Python interface

# assuming virtual environment containing LabelFusion is activated
import SimpleITK as sitk
from LabelFusion.wrapper import fuse_images

label_to_fuse_0 = '/path/to/image_0.nii.gz'
label_to_fuse_1 = '/path/to/image_1.nii.gz'

images_to_fuse = []
images_to_fuse.append(sitk.ReadImage(label_to_fuse_0, sitk.sitkUInt8))
images_to_fuse.append(sitk.ReadImage(label_to_fuse_1, sitk.sitkUInt8))
fused_staple = fuse_images(images_to_fuse, 'staple') # class_list is not needed for staple/itkvoting
sitk.WriteImage(fused_staple, '/path/to/output_staple.nii.gz')
fused_simple = fuse_images(images_to_fuse, 'simple', class_list=[0,1,2,4])
sitk.WriteImage(fused_simple, '/path/to/output_simple.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