MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
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Updated
Jun 13, 2024 - Python
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
Workflows and interfaces for neuroimaging packages
Deep learning software to decode EEG, ECG or MEG signals
DIPY is the paragon 3D/4D+ 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.
Pycortex is a python-based toolkit for surface visualization of fMRI data
Neuroimaging analysis and visualization suite
Brain Imaging Analysis Kit
Brainchop: In-browser 3D MRI rendering and segmentation
normalize the intensities of various MR image modalities
Automated Quality Control and visual reports for Quality Assessment of structural (T1w, T2w) and functional MRI of the brain
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