README.md

DDMR: Deep Deformation Map Registration

Cross-modal transfer learning and adaptive multi-task learning for improved abdominal CT registration

DDMR was developed by SINTEF Health Research. A paper is submitted to X and the preprint is openly available at arXiv.

💻 Getting started

1. Setup virtual environment:

virtualenv -ppython3 venv --clear
source venv/bin/activate

2. Install requirements:

pip install -r requirements.txt

🏋️‍♂️ Training

Use the "MultiTrain" scripts to launch the trainings, providing the neccesary parameters. Those in the COMET folder accepts a .ini configuration file (see COMET/train_config_files for example configurations).

For instance:

python TrainingScripts/Train_3d.py

🔍 Evaluate

Use Evaluate_network to test the trained models. On the Brain folder, use "Evaluate_network__test_fixed.py" instead.

For instance:

python EvaluationScripts/evaluation.py

🏆 Acknowledgements

✨ How to cite

Please, consider citing our paper, if you find the work useful:

  @misc{frutos2022ddmr,
  author={Pérez de Frutos, Javier and Pedersen, André and Pelanis, Egidijus and Bouget, David and Survarachakan, Shanmugapriya and Langø, Thomas and Lindseth, Frank and Elle, Ole-Jakob},
  publisher = {arXiv},
  title={Cross-modal transfer learning and adaptive multi-task learning for improved abdominal CT registration}, 
  year={2022},
  doi = {10.48550/ARXIV.2011.06033},
  url = {https://arxiv.org/abs/2011.06033}}