There are 1 repository under nipype topic.
Generate custom Docker and Singularity images, and minimize existing containers
The project is used to do preprocessing on brain MR images by using Nipype.
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.
Neuropycon package of functions for electrophysiology analysis, can be used from graphpype and nipype
Preprocessing Pipelines for EEG (MNE-python), fMRI (nipype), MEG (MNE-python/autoreject) data
Open-source eddy-current and head-motion correction for dMRI.
A Dockerfile to create a Ubuntu docker for neuroimaging
Portable, modular, reusable, and reproducible processing pipeline software for fetal brain MRI super-resolution
Nipype workflow to generate fieldmaps from EPI acquisitions with differing phase-encoding directions
A repository for creating Docker and Singularity files using Neurodocker
The basic structural and diffusion MRI registration with pre-processing pipeline in Python.
A summary of topics covered by the Nipype workshop and hackweek
An extensible fMRI Preprocessing Pipeline in nipype based on a 2015 Jonathan Power Pipeline
A graphical pipeline builder for p3 in electron
Nipype interface(s) wrapping the fsl_anat command line tool
build a container from which EH's analysis code (and others) can be run, without relying on windows/mac compatibility
An innovative and collaborative solution for setting up and executing Jupyter Notebooks on High-Performance Computing (HPC) clusters, tailored for neuroscience data processing workflows.