neuroimaging

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

Multi-platform, free open source software for visualization and image computing.

Train AI models efficiently on medical images using any framework

Advanced Normalization Tools (ANTs)

Machine learning for NeuroImaging in Python

Deep learning software to decode EEG, ECG or MEG signals

dcm2nii DICOM to NIfTI converter: compiled versions available from NITRC

The MATLAB toolbox for MEG, EEG and iEEG analysis

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

Neuroimaging analysis and visualization suite

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.

Workflows and interfaces for neuroimaging packages

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

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.

Pycortex is a python-based toolkit for surface visualization of fMRI data

Learn about the Neumorphic engineering process of creating large-scale integration (VLSI) systems containing electronic analog circuits to mimic neuro-biological architectures.

Brainchop: In-browser 3D MRI rendering and segmentation