MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
The MATLAB toolbox for MEG, EEG and iEEG analysis
Multi-platform, free open source software for visualization and image computing.
Machine learning for NeuroImaging in Python
Workflows and interfaces for neuroimaging packages
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.
Deep Learning Toolkit for Medical Image Analysis
Advanced Normalization Tools (ANTs)
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.
Train AI models efficiently on medical images using any framework
Neuroimaging analysis and visualization suite
Slicer extensions index
Python package to access a cacophony of neuro-imaging file formats
dcm2nii DICOM to NIfTI converter: compiled versions available from NITRC
Deep learning software to decode EEG, ECG or MEG signals
Brain Imaging Data Structure (BIDS) Specification
LORIS is a web-accessible database solution for longitudinal multi-site studies.
A fast medical imaging analysis library in Python with algorithms for registration, segmentation, and more.
Website of the BrainHack School
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