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images/nipype_architecture_overview2.png

Current neuroimaging software offer users an incredible opportunity to analyze data using a variety of different algorithms. However, this has resulted in a heterogeneous collection of specialized applications without transparent interoperability or a uniform operating interface.

Nipype, an open-source, community-developed initiative under the umbrella of NiPy_, is a Python project that provides a uniform interface to existing neuroimaging software and facilitates interaction between these packages within a single workflow. Nipype provides an environment that encourages interactive exploration of algorithms from different packages (e.g., SPM_, FSL_, FreeSurfer_, Camino_, MRtrix_, MNE_, AFNI_, Slicer_), eases the design of workflows within and between packages, and reduces the learning curve necessary to use different packages. Nipype is creating a collaborative platform for neuroimaging software development in a high-level language and addressing limitations of existing pipeline systems.

Nipype allows you to:

  • easily interact with tools from different software packages
  • combine processing steps from different software packages
  • develop new workflows faster by reusing common steps from old ones
  • process data faster by running it in parallel on many cores/machines
  • make your research easily reproducible
  • share your processing workflows with the community

Reference

Gorgolewski K, Burns CD, Madison C, Clark D, Halchenko YO, Waskom ML, Ghosh SS. (2011). Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in Python. Front. Neuroinform. 5:13. `Download`__

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