ANTs is a C++ library available through the command line that computes high-dimensional mappings to capture the statistics of brain structure and function. It allows one to organize, visualize and statistically explore large biomedical image sets.

Nifti_clib is a set of I/O libraries for reading and writing files in the nifti-1, nifti-2, and (to some degree) cifti file formats. These are binary file formats for storing medical image data, e.g. MRI and fMRI brain images.

NiBabies is an open-source software pipeline designed to process anatomical and functional magnetic resonance imaging data, designed and optimized for human infants between 0-2 years old.

Connectome Workbench is a visualization and discovery tool used to map neuroimaging data, especially data generated by the Human Connectome Project. It allows exploration of data and activity on the surface, as well as in the volume of the brain.

It helps developers working in continuous integration (CI) environments by providing essential information about the CI server. It can determine if the code is running on a CI server,identify the specific server,and detect if a pull request is being tested.

This package provides processing pipelines for structural MRI.

pybids provides a set of tools for working with BIDS datasets. The BIDS standard aims at organizing and describing neuroimaging data in a uniform way in order to facilitate data sharing within the scientific community.

Nilearn enables approachable and versatile analyses of brain volumes and surfaces. It provides statistical and machine-learning tools, with instructive documentation & open community.

fsleyes_props is a framework for event-driven programming using Python descriptors, similar in functionality to, and influenced by Enthought Traits.

This package provides utilities for feature analysis, preprocessing and visualization of image quality metrics generated by MRIQC.

MRIQC extracts no-reference image quality metrics from structural (T1w and T2w), functional and diffusion MRI data.

Nipype 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.

niworkflows is capable of converting between formats and resampling images to apply transforms generated by the most popular neuroimaging packages and libraries (AFNI, FSL, FreeSurfer, ITK, and SPM).

This package provides the Python Client code for accessing neuroimaging templates hosted using TemplateFlow.

NIPY provides a platform-independent Python environment for the analysis of functional brain imaging data.

Convert data from DICOM and organise the resulting NIfTI files into BIDS.

Gifticlib is a a library for reading and writing files in GIfTI format. GIfTI is a standard for Geometry Data Format for Exchange of Surface-Based Brain Mapping Data.

fMRIPrep is a fMRI data preprocessing pipeline that is designed to provide an easily accessible, state-of-the-art interface that is robust to variations in scan acquisition protocols and that requires minimal user input, while providing easily interpretable and comprehensive error and output reporting. It performs basic processing steps (coregistration, normalization, unwarping, noise component extraction, segmentation, skull-stripping, etc.) providing outputs that can be easily submitted to a variety of group level analyses, including task-based or resting-state fMRI, graph theory measures, and surface or volume-based statistics.

elastix is an image registration toolbox based on ITK. The software consists of a collection of algorithms that are commonly used to perform (medical) image registration: the task of finding a spatial transformation, mapping one image (the fixed image) to another (the moving image), by optimizing relevant image similarity metrics. The modular design of elastix allows the user to quickly configure, test, and compare different registration methods for a specific application. A command-line interface enables automated processing of large numbers of data sets, by means of scripting.

The nipype1-workflows repository contains legacy workflows from Nipype 1.x, showcasing nearly a decade of development in neuroimaging data processing and analysis.

This module provides simple, consistent access to package resources.

A Python implementation of the moving average principal components analysis methods for functional MRI data translated from the MATLAB-based GIFT package.

This package provides an implementation of TRX, a tractography file format designed to facilitate dataset exchange, interoperability, and state-of-the-art analyses, acting as a community-driven replacement for the myriad existing file formats.

heudiconv is a flexible DICOM converter for organizing brain imaging data into structured directory layouts.