An extensible fMRI Preprocessing Pipeline in nipype based on a 2015 Jonathan Power Pipeline

A Dockerfile to create a Ubuntu docker for neuroimaging

Reusable neuroimaging pipelines using nipype

Portable, modular, reusable, and reproducible processing pipeline software for fetal brain MRI super-resolution

A graphical pipeline builder for p3 in electron

Some pipelines implemented with nipype.

Preprocessing Pipelines for EEG (MNE-python), fMRI (nipype), MEG (MNE-python/autoreject) data

Nipype interface(s) wrapping the fsl_anat command line tool

Nipype workflow to generate fieldmaps from EPI acquisitions with differing phase-encoding directions

Nipype and tractography!

The basic structural and diffusion MRI registration with pre-processing pipeline in Python.

build a container from which EH's analysis code (and others) can be run, without relying on windows/mac compatibility

Pypelines Utilizing a Modular Inventory

Beginner's guide for Nipype

Neuropycon package of functions for electrophysiology analysis, can be used from graphpype and nipype

A repository for creating Docker and Singularity files using Neurodocker

An innovative and collaborative solution for setting up and executing Jupyter Notebooks on High-Performance Computing (HPC) clusters, tailored for neuroscience data processing workflows.

The Medical Image Analysis Laboratory Super-Resolution ToolKit (MIALSRTK) consists of a set of C++ and Python processing and workflow tools necessary to perform motion-robust super-resolution fetal MRI reconstruction in the BIDS Apps framework.