MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
Train AI models efficiently on medical images using any framework
Multi-platform, free open source software for visualization and image computing.
Deep Learning Toolkit for Medical Image Analysis
Advanced Normalization Tools (ANTs)
Machine learning for NeuroImaging in Python
dcm2nii DICOM to NIfTI converter: compiled versions available from NITRC
The MATLAB toolbox for MEG, EEG and iEEG analysis
Deep learning software to decode EEG, ECG or MEG signals
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.
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.
Neuroimaging analysis and visualization suite
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
Brain Imaging Analysis Kit
normalize the intensities of various MR image modalities
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