# LabelFusion
<p align="center">
<a href="https://dev.azure.com/FETS-AI/LabelFusion/_build?definitionId=2&_a=summary" alt="Windows_3.6"><img src="https://dev.azure.com/FETS-AI/LabelFusion/_apis/build/status/FETS-AI.LabelFusion" /></a>
<a href="https://doi.org/10.5281/zenodo.4534123"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.4534123.svg" alt="DOI"></a>
<a href="https://anaconda.org/conda-forge/labelfusion" alt="Install"><img src="https://img.shields.io/conda/vn/conda-forge/labelfusion" /></a>
<a href="https://pypi.org/project/LabelFusion/"><img src="https://img.shields.io/pypi/v/labelfusion"/></a>
</p>
This repo contains implementation of various label fusion approaches that can be used to fuse multiple labels.
## Installation
### For Usage
```powershell
conda create -n venv_labelFusion python=3.6.5 -y
conda activate venv_labelFusion
pip install LabelFusion
```
### For Development
```powershell
# 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:
- [Voting (ITK)](https://simpleitk.org/doxygen/latest/html/classitk_1_1simple_1_1LabelVotingImageFilter.html): [DOI:10.1016/j.patrec.2005.03.017](https://doi.org/10.1016/j.patrec.2005.03.017)
- [STAPLE (ITK)](https://simpleitk.org/doxygen/latest/html/classitk_1_1simple_1_1MultiLabelSTAPLEImageFilter.html): [DOI:10.1109/TMI.2004.830803](https://doi.org/10.1109/TMI.2004.830803)
- Majority Voting: [DOI:10.1007/978-3-319-20801-5_11](https://doi.org/10.1007/978-3-319-20801-5_11)
- SIMPLE: [DOI:10.1109/tmi.2010.2057442](https://doi.org/10.1109/TMI.2010.2057442)
## Usage
### Command-Line interface
```powershell
# 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:
```powershell
# 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
```python
# 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](https://dev.azure.com/FETS-AI/LabelFusion/_build?definitionId=2&_a=summary) for the following [operating systems](https://github.com/FETS-AI/LabelFusion/blob/a51b82ad9880d466ed1d42441dd46de37e931df4/azure-pipelines.yml#L9):
- Windows
- Ubuntu
- macOS
And for the following python versions:
- 3.6
- 3.7
- 3.8
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"description": "# LabelFusion\n\n<p align=\"center\">\n <a href=\"https://dev.azure.com/FETS-AI/LabelFusion/_build?definitionId=2&_a=summary\" alt=\"Windows_3.6\"><img src=\"https://dev.azure.com/FETS-AI/LabelFusion/_apis/build/status/FETS-AI.LabelFusion\" /></a>\n <a href=\"https://doi.org/10.5281/zenodo.4534123\"><img src=\"https://zenodo.org/badge/DOI/10.5281/zenodo.4534123.svg\" alt=\"DOI\"></a>\n <a href=\"https://anaconda.org/conda-forge/labelfusion\" alt=\"Install\"><img src=\"https://img.shields.io/conda/vn/conda-forge/labelfusion\" /></a>\n <a href=\"https://pypi.org/project/LabelFusion/\"><img src=\"https://img.shields.io/pypi/v/labelfusion\"/></a>\n</p>\n\n\nThis repo contains implementation of various label fusion approaches that can be used to fuse multiple labels.\n\n## Installation\n\n### For Usage\n```powershell\nconda create -n venv_labelFusion python=3.6.5 -y\nconda activate venv_labelFusion\npip install LabelFusion\n```\n\n### For Development\n```powershell\n# fork to your own repo\ngit clone ${yourFork_labelFusion_repo_link}\ncd LabelFusion\nconda create -p ./venv python=3.6.5 -y\nconda activate ./venv\npip install -e .\n# develop, push\n# initiate pull request\n```\n\n## Available LabelFusion:\n\n- [Voting (ITK)](https://simpleitk.org/doxygen/latest/html/classitk_1_1simple_1_1LabelVotingImageFilter.html): [DOI:10.1016/j.patrec.2005.03.017](https://doi.org/10.1016/j.patrec.2005.03.017)\n- [STAPLE (ITK)](https://simpleitk.org/doxygen/latest/html/classitk_1_1simple_1_1MultiLabelSTAPLEImageFilter.html): [DOI:10.1109/TMI.2004.830803](https://doi.org/10.1109/TMI.2004.830803)\n- Majority Voting: [DOI:10.1007/978-3-319-20801-5_11](https://doi.org/10.1007/978-3-319-20801-5_11)\n- SIMPLE: [DOI:10.1109/tmi.2010.2057442](https://doi.org/10.1109/TMI.2010.2057442)\n\n## Usage\n\n### Command-Line interface\n\n```powershell\n# continue from previous shell\npython fusion_run -h\n -h, --help show this help message and exit\n -inputs INPUTS The absolute, comma-separated paths of labels that need to be fused\n -classes CLASSES The expected labels; for example, for BraTS, this should be '0,1,2,4' - not used for STAPLE or ITKVoting\n -method METHOD The method to apply; currently available: STAPLE | ITKVoting | MajorityVoting | SIMPLE\n -output OUTPUT The output file to write the results\n```\n\nExample:\n```powershell\n# continue from previous shell\npython fusion_run \\\n-inputs /path/to/seg_algo_1.nii.gz,/path/to/seg_algo_2.nii.gz,/path/to/seg_algo_3.nii.gz \\\n-classes 0,1,2,4 \\\n-method STAPLE \\\n-output /path/to/seg_fusion.nii.gz\n```\n\n### Python interface\n\n```python\n# assuming virtual environment containing LabelFusion is activated\nimport SimpleITK as sitk\nfrom LabelFusion.wrapper import fuse_images\n\nlabel_to_fuse_0 = '/path/to/image_0.nii.gz'\nlabel_to_fuse_1 = '/path/to/image_1.nii.gz'\n\nimages_to_fuse = []\nimages_to_fuse.append(sitk.ReadImage(label_to_fuse_0, sitk.sitkUInt8))\nimages_to_fuse.append(sitk.ReadImage(label_to_fuse_1, sitk.sitkUInt8))\nfused_staple = fuse_images(images_to_fuse, 'staple') # class_list is not needed for staple/itkvoting\nsitk.WriteImage(fused_staple, '/path/to/output_staple.nii.gz')\nfused_simple = fuse_images(images_to_fuse, 'simple', class_list=[0,1,2,4])\nsitk.WriteImage(fused_simple, '/path/to/output_simple.nii.gz')\n```\n\n## Testing\n\nThis repo has continuous integration enbabled via [Azure DevOps](https://dev.azure.com/FETS-AI/LabelFusion/_build?definitionId=2&_a=summary) for the following [operating systems](https://github.com/FETS-AI/LabelFusion/blob/a51b82ad9880d466ed1d42441dd46de37e931df4/azure-pipelines.yml#L9):\n\n- Windows\n- Ubuntu\n- macOS\n\nAnd for the following python versions:\n\n- 3.6\n- 3.7\n- 3.8\n",
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