This repository includes a collection of scripts that were used to analyze the MRI data and generate figures for the article "Breheret et al. Impact of through-slice gradient optimization for dynamic slice-wise shimming in the cervico-thoracic spinal cord (in revision)".
Note
The bash scripts can only be run on Unix-based operating systems.
Citation:
Coming soon
Before using these scripts, you need to:
- Install dependencies
git clone -b v1.2 https://github.com/shimming-toolbox/shimming-toolbox/ ~/shimming-toolbox/
cd ~/shimming-toolbox/
make install
Note
If you already have Shimming Toolbox installed, please remove it from your directory before cloning the repository.
rm -rf ~/shimming-toolbox/
git clone -b 6.3 https://github.com/spinalcordtoolbox/spinalcordtoolbox/ ~/spinalcordtoolbox/
cd ~/spinalcordtoolbox/
./install_sct
- FSL (follow instructions on their website)
- Clone the GitHub repository
cd <path_to_where_you_want_the_repository>
git clone https://github.com/shimming-toolbox/spinalcord-signal-recovery.git
- Move to the repository
cd spinalcord-signal-recovery
- Create a conda environment using the env.yml file
conda env create -n <name_of_your_env> -f env.yml
- Activate the new environment
conda activate <name_of_your_env>
- Download the data available on OSF
- Place the unzipped data folder in this folder (spinalcord-signal-recovery)
- Note that the outputs are already provided in this folder.
Navigate to the different script folders for specific instructions on how to run the different scripts.
- experiment_script: These scripts are used at the scanner during the acquisition to obtain the shimming coefficients
- post_processing_scripts: Process the data to generatetSNR measurements
- figure_scripts: Generate figures for the paper