spinalcord-signal-recovery

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 starting

Before using these scripts, you need to:

1. Install dependencies

• Anaconda or Miniconda
• Shimming Toolbox's v1.1

git clone -b 1.1 https://github.com/shimming-toolbox/shimming-toolbox/ ~/shimming-toolbox/
cd ~/shimming-toolbox/
make install

• SCT v6.3

git clone -b 6.3 https://github.com/spinalcordtoolbox/spinalcordtoolbox/ ~/spinalcordtoolbox/
cd ~/spinalcordtoolbox/
./install_sct

• FSL (follow instructions on their website)

2. Clone the GitHub repository

cd <path_to_where_you_want_the_repository>
git clone https://github.com/shimming-toolbox/spinalcord-signal-recovery.git

3. Move to the repository

cd spinalcord-signal-recovery

4. Create a conda environment using the env.yml file

conda env create -n <name_of_your_env> -f env.yml

5. Activate the new environment

conda activate <name_of_your_env>

3. Download the data available on OSF
4. Place the unzipped data folder in this folder (spinalcord-signal-recovery)

• Note that the outputs are already provided in this folder.

How to use

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