Official implementation of Stochastic Cortical Self-Reconstruction (SCSR).
- Check out repository
- Create environment:
conda env create --file environment.yml
- Activate environment:
conda activate SCSR
- Download model https://drive.google.com/file/d/1qmD5m3wR1F_sqVmBTyZgWWxi_VCpEbKz/view?usp=sharing and copy to directory
checkpoints
We used data from Alzheimer's Disease Neuroimaging Initiative (ADNI).
- The package uses PyTorch
- As input data, an input table with columns ['DX', 'AGE', 'PTGENDER', per-vertex values] is expected as a .feather file
- To train SCSR, set the path to the input table
table_path
in the training file and callpython SCSR_train.py config_files/training_configs/config.yaml
. - For testing, again set the path to the input table
table_path
in the testing file and callpython SCSR_test.py
@article{wachinger2024stochastic,
title={Stochastic Cortical Self-Reconstruction},
author={Wachinger, Christian and Hedderich, Dennis and Bongratz, Fabian},
journal={arXiv preprint arXiv:2403.06837},
year={2024}
}