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.

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

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

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.

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

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

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.

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.

{dcmstack

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.

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

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.

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.

Surfa is a collection of Python utilities for medical image analysis and mesh-based surface processing. It provides tools that operate on 3D image arrays and triangular meshes with consideration of their representation in a world (or scanner) coordinate system. While broad in scope, surfa is developed with particular emphasis on neuroimaging applications.

AFNI, Analysis of Functional NeuroImages is a suite of programs for looking at and analyzing MRI brain images at all stages of analysis (planning, setting up acquisition, preprocessing, analysis, quality control and statistical analysis).

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

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

NiFreeze is a flexible framework for volume-to-volume motion estimation and correction in d/fMRI and PET, and eddy-current-derived distortion estimation in dMRI.

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

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.

The PETPVC toolbox comprises a suite of methods, both classic and more recent approaches, for the purposes of applying PVC to PET data. Eight core PVC techniques are available, and those core methods can be combined to create a total of 22 different PVC techniques.

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

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