PNH segmentation pipelines based on nipype

Open-source eddy-current and head-motion correction for dMRI.

Generate custom Docker and Singularity images, and minimize existing containers

Initial work on a complex-valued fMRI preprocessing workflow. Dropped in favor of fMRIPost-phase.

The project is used to do preprocessing on brain MR images by using Nipype.

PUMI: neuroimaging Pipelines Using Modular workflow Integration

A Reproducible Workflow for Structural and Functional Connectome Ensemble Learning

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.

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

A repository for creating Docker and Singularity files using Neurodocker

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

Beginner's guide for Nipype

Pypelines Utilizing a Modular Inventory

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

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

Nipype and tractography!

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

Nipype interface(s) wrapping the fsl_anat command line tool

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

Some pipelines implemented with nipype.