• ANTs (tested with version 2.3.3.dev168-g29bdf)
• Python 3.7
• Clone this repository and install its requirements:

  git clone https://github.com/rrsg2020/analysis.git rrsg2020/analysis
  cd rrsg2020/analysis
  pip install -r requirements.txt

Run the commands:

python make_pooled_datasets.py configs/3T_NIST_T1maps.json 3T_NIST_T1maps
python make_pooled_datasets.py configs/3T_NIST.json 3T_NIST

Note: Labels and a phantom mask are already included in the T1 map OSF dataset

Run the registration script:

python register_t1maps_nist.py -j configs/3T_NIST.json -p 3T_NIST_pooled/ 3T_NIST_T1maps_pooled/

Note: the registration script will download the reference mask (e.g. for the NIST phantom) and will create labels for the initial affine transformation.

• Requirement: Miniforge for OSX arm64

conda env create -f environment_ARM.yml
conda activate analysis_arm 
python setup_ARM.py install
python -m ipykernel install --user --name=analysis_arm
pytest