Nipype — Neuroimaging Workflow Engine

Nipype — Neuroimaging Workflow Engine

Nipype is a neuroimaging workflow framework that provides uniform Python interfaces to dozens of tools — FSL, SPM, FreeSurfer, ANTs, AFNI, MRtrix, Camino — and chains them into reproducible dataflow pipelines with parallel execution and smart caching.

Key features

• 500+ interface wrappers covering every major neuroimaging toolbox
• DAG-based workflow with conditional re-execution (only re-runs changed nodes)
• MultiProc, SGE, SLURM, PBS, and AWS Batch execution plugins
• Generates provenance records and dot-graph visualizations
• Underlies fMRIPrep, dMRIPrep, and HALFpipe

Quick start

pip install nipype

from nipype import Workflow, Node
from nipype.interfaces.fsl import BET, MCFLIRT

skull_strip = Node(BET(in_file="bold.nii"), name="skull_strip")
mc = Node(MCFLIRT(), name="motion_correct")

wf = Workflow(name="preproc", base_dir="/tmp")
wf.connect(skull_strip, "out_file", mc, "in_file")
wf.run()

npx ai-supply add nipype-neuroimaging-workflows

Curated mirror of the open-source Nipype (Apache-2.0). Get it from the source.