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

This package provides DICOM to NIfTI conversion with the added ability to extract and summarize meta data from the source DICOM files. The meta data can be injected it into a NIfTI header extension or written out as a JSON formatted text file.

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.

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

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

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).

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.

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 the version schemes used for packaging software from the NiPreps organization.

This package provides processing pipelines for structural MRI.

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.

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

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.

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.

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

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.

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

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 Python tools for working with the BIDS schema.

This package provides a Pydantic schema for BIDS Stats Models.

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.

SDCFlows (Susceptibility Distortion Correction workFlows) is a Python library of NiPype-based workflows to preprocess B0 mapping data, estimate the corresponding fieldmap and finally correct for susceptibility distortions. Susceptibility-derived distortions are typically displayed by images acquired with EPI MR schemes.

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.