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.

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.

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

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

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.

DIPY is the paragon 3D/4D+ medical imaging library in Python. It contains generic methods for spatial normalization, signal processing, machine learning, statistical analysis and visualization of medical images. Additionally, it contains specialized methods for computational anatomy including diffusion, perfusion and structural imaging.

dcm2niix is designed to convert neuroimaging data from the DICOM format to the NIfTI format. dcm2niix is also able to generate a BIDS JSON format sidecar which includes relevant information for brain scientists in a vendor agnostic and human readable form.

This package provides the version schemes used for packaging software from the NiPreps organization.

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

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.

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

Convert3d is a command-line tool for converting 3D images between common file formats. The tool also includes a growing list of commands for image manipulation, such as thresholding and resampling. The tool can also be used to obtain information about image files.

FSL is a comprehensive library of analysis tools for FMRI, MRI and diffusion brain imaging data. FSLeyes is a GUI for visualizing and editing brain images, from different sources and platforms.

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

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.

The BIDS Validator is a web application, command-line utility, and Javascript/Typescript library for assessing compliance with the BIDS standard.

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

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

The indexed_gzip project is a Python extension which aims to provide a drop-in replacement for the built-in Python gzip.GzipFile class, the IndexedGzipFile. indexed_gzip was written to allow fast random access of compressed NIFTI image files (for which GZIP is the de-facto compression standard), but will work with any GZIP file.

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.

The etelemetry Python client facilitates communication with the etelemetry server, providing version information and checking for critical bugs in projects. The client allows you to retrieve project details and compare versions to identify and warn about problematic versions.

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.

{dcmstack