Neuroimaging Python Packages

nibabel

Python package to access a cacophony of neuro-imaging file formats

mne

MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python

nilearn

Machine learning for NeuroImaging in Python

dipy

DIPY is the paragon 3D/4D+ medical imaging library in Python. 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.

bidsschematools

Brain Imaging Data Structure (BIDS) Specification

nipype

Workflows and interfaces for neuroimaging packages

braindecode

Deep learning software to decode EEG, ECG or MEG signals

mne-bids

MNE-BIDS is a Python package that allows you to read and write BIDS-compatible datasets with the help of MNE-Python.

neurocombat

Harmonization of multi-site imaging data with ComBat (Python)

antspyx

A fast medical imaging analysis library in Python with algorithms for registration, segmentation, and more.

pyprep

PyPREP: A Python implementation of the Preprocessing Pipeline (PREP) for EEG data

dcm2niix

dcm2nii DICOM to NIfTI converter: compiled versions available from NITRC

junifer

Forschungszentrum Jülich Neuroimaging Feature Extractor

bjdata

Binary JSON (BJData/UBJSON) Support for Python

neuroglancer-scripts

Conversion of neuroimaging data for display in Neuroglancer

fmriprep

fMRIPrep is a robust and easy-to-use pipeline for preprocessing of diverse fMRI data. The transparent workflow dispenses of manual intervention, thereby ensuring the reproducibility of the results.

hedtools

Python validation, summary, and analysis tools for HED (Hierarchical Event Descriptors).

nimare

Coordinate- and image-based meta-analysis in Python

nireports

The NiPreps' Reporting and Visualization system - report templates and "reportlets"

dcm2bids

Reorganising NIfTI files from dcm2niix into the Brain Imaging Data Structure

mne-lsl

A framework for real-time brain signal streaming with MNE-Python.

tedana

TE-dependent analysis of multi-echo fMRI

phys2cvr

python module to compute cerebrovascular reactivity mapping and other related maps

fmriprep-docker

fMRIPrep is a robust and easy-to-use pipeline for preprocessing of diverse fMRI data. The transparent workflow dispenses of manual intervention, thereby ensuring the reproducibility of the results.