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nf-neuro

Welcome to the nf-neuro documentation

Build efficient neuroimaging pipelines

Section titled “Build efficient neuroimaging pipelines”

nf-neuro is an open-source initiative originally developed by the Sherbrooke Connectivity Imaging Lab (SCIL)

Our mission is to provide researchers with scalable, reproducible, and efficient pipelines for neuroimaging applications.

Valcourt Caron A, Boré A, Edde M, Gagnon, A, Thoumyre S, Royer A, Rheault F, Descoteaux M. nf-neuro: Developing Maintainable Pipelines for Seamless Processing of Diffusion MRI. Proceedings of the ISMRM Workshop on 40 Years of Diffusion: Past, Present and Future Perspectives. 2025.

Why Choose nf-neuro?

Section titled “Why Choose nf-neuro?”

Reproducibility

nf-neuro contains thoroughly tested and validated modules to built efficient neuroimaging pipeline ensuring reproducible results.

Development guidelines

nf-neuro is built against the nf-core guidelines, which promotes high coding standards and good practice.

State-of-the-art neuroimaging tools

nf-neuro regroups multiple modules using state-of-the-art tools from popular libraries (e.g., FSL, ANTs, scilpy, etc.).

Portability

Each components from nf-neuro have their own container (Docker or Singularity). Enabling an easy use on all architectures.

Get started

Section titled “Get started”

Create Your Pipeline from A to Z: Leverage our modules to build customized neuroimaging workflows.

Contribute to nf-neuro: Join our community and help advance the project.

API Documentation: Access detailed information on our modules and subworkflows and their functionalities.

Advanced tutorials: Go beyond and give superpowers to your pipeline (Add BIDS input, setup BIDS output or automatic QC)

Join the Community

Section titled “Join the Community”

nf-neuro is an evolving project that thrives on contributions from the community. Whether you are a researcher, developer, or enthusiast, there are multiple ways to get involved:

  1. Report issues or suggest new features.

  2. Contribute code, documentation, or new modules.

  3. Engage in discussions through forums and working groups such as neurostars

By working together, we can push the boundaries of computational neuroscience and make powerful tools more accessible to all.