NiReports contains the two main components of the visual reporting system of NiPreps: 1) reportlets, visualizations for assessing the quality of a particular processing step within the neuroimaging pipeline, and 2) assemblers, end-user write out reportlets to a predetermined folder.

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.

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.

NeuroImaging Workflows provides processing tools for magnetic resonance images of the brain.

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

The Insight Toolkit (ITK) is a toolkit for N-dimensional scientific image processing, segmentation, and registration. Segmentation is the process of identifying and classifying data found in a digitally sampled representation. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning or developing correspondences between data. For example, in the medical environment, a CT scan may be aligned with a MRI scan in order to combine the information contained in both.

This package provides Python tools for working with the BIDS schema.

CiftiLib is a C++ library for CIFTI-2 file reading/writing. It additionally supports CIFTI-1 files, and supports both on-disk and in-memory access. It also provides C++ code for reading and writing generic NIfTI-1 and NIfTI-2 files.

CIFTI (Connectivity Informatics Technology Initiative) standardizes file formats for the storage of connectivity data. These formats are developed by the Human Connectome Project and other interested parties.

See http://www.nitrc.org/projects/cifti/ for more information.

This package provides programs to perform EM based segmentation of images in nifti or analyse format.

This package provides programs to perform rigid, affine and non-linear registration of 2D and 3D images stored as NIfTI or Analyze formats.

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 a Pydantic schema for BIDS Stats Models.

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

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.

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

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.

MRtrix3 provides a large suite of tools for image processing, analysis and visualisation, with a focus on the analysis of white matter using diffusion-weighted MRI.

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

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.

migas (mee-gahs) is a Python client to facilitate communication with a migas server.

Nitime contains a core of numerical algorithms for time-series analysis both in the time and spectral domains, a set of container objects to represent time-series, and auxiliary objects that expose a high level interface to the numerical machinery and make common analysis tasks easy to express with compact and semantically clear code.

The fsleyes-widgets package contains a collection of GUI widgets and utilities, based on wxPython, which are used by fsleyes-props and FSLeyes.

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.