Published June 2, 2023 | Version v1
Software Open

A reproducible benchmark of resting-state fMRI denoising strategies using fMRIPrep and Nilearn

  • 1. Centre de recherche de l'Institut universitaire de gériatrie de Montréal (CRIUGM), Montréal, Québec, Canada
  • 2. Harvard University, MA, USA
  • 3. Computer Science and Operations Research Department, Université de Montréal, Montréal, Québec, Canada
  • 4. Inria, CEA, Université Paris-Saclay, Paris, France
  • 5. Department of Psychology, Stanford University, Stanford, United States

Contributors

Contact person:

  • 1. NeuroLibre

Description

Docker image built from the reference repository/commit by roboneuro, based on the latest change by the author, using repo2docker (through BinderHub).
To run locally:

  1. docker load < DockerImage_10.55458_NeuroLibre_00012_b56875.tar.gz
     
  2. docker run -it --rm -p 8888:8888 DOCKER_IMAGE_ID jupyter lab --ip 0.0.0.0
    by replacing DOCKER_IMAGE_ID above with the respective ID of the Docker image loaded from the tar.gz. file.

For details, please visit the corresponding NeuroLibre technical screening.

https://neurolibre.org

Files

Files (1.3 GB)

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md5:1899fc3a71b7cfaf9a47133fbc5003b5
1.3 GB Download

Additional details

Related works

Is supplement to
Preprint: 10.55458/neurolibre.00012 (DOI)