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rf-shimming-7t

DOI Badge Open In Colab launch binder

Reproducible Notebook for the paper "RF shimming in the cervical spinal cord at 7T"

Run with Google Colab

Click on the badge "Open in Colab" ☝️. The notebook takes about 2 hours to run on Google Colab (without a paid subscription that gives access to more powerful resource).

Run in a Docker container (NeuroLibre, MyBinder, repo2ocker)

repo2docker

To run locally on your computer, you must first have Docker installed, running, and have created an account. Follow the instructions here.

Then, you need to install repo2docker. Install via pip: pip install jupyter-repo2docker

To launch a Docker session from this repo, run repo2docker --ref main https://www.github.com/shimming-toolbox/rf-shimming-7t. After it's completed, it will provie you with a weblink, copy and open this link in a browser to open the Jupyter Notebook session.

NeuroLibre

Note

This repo isn't on NeuroLibre's whitelist yet, to cannot access it's binderhub until reviewed/published there.

MyBinder

Note

MyBinder sometimes crashes during Docker build. NeuroLibre servers are preferred.

Click on the badge "launch binder" ☝️. This environment setup downloads the data and the output of notebook previously run on Google Colab, and by default the notebook will only run the analysis cells (i.e. not the SCT-related commands).

If you'd like to re-run the processing from scratch, change the notebook = 'neurolibre-figures' line in the first cell to notebook = 'neurolibre-clean'. This will delete the processed files and then re-run the entire processing pipeline. Note that some cells take a lot of RAM, and may fail on certain systems.

Run locally with Jupyter Notebook

Install Spinal Cord Toolbox

Clone this repository

git clone https://github.com/shimming-toolbox/rf-shimming-7t.git
git checkout r20240528
cd rf-shimming-7t

Install Python dependencies (assuming Python is already installed)

pip install -r binder/requirements.txt

Download data

cd content
repo2data -r ../binder/data_requirement.json

Run notebook

jupyter notebook index.ipynb