MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python
Train AI models efficiently on medical images using any framework
Deep Learning Toolkit for Medical Image Analysis
Machine learning for NeuroImaging in Python
Deep learning software to decode EEG, ECG or MEG signals
Workflows and interfaces for neuroimaging packages
A fast medical imaging analysis library in Python with algorithms for registration, segmentation, and more.
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
Learn about the Neumorphic engineering process of creating large-scale integration (VLSI) systems containing electronic analog circuits to mimic neuro-biological architectures.
Brain Imaging Analysis Kit
Automated Quality Control and visual reports for Quality Assessment of structural (T1w, T2w) and functional MRI of the brain
Normalize MR image intensities in Python
Brain Imaging Data Structure (BIDS) Specification
A toolbox for comparing brain maps
Software platform for clinical neuroimaging studies
Coordinate- and image-based meta-analysis in Python
Reorganising NIfTI files from dcm2niix into the Brain Imaging Data Structure
TE-dependent analysis of multi-echo fMRI
Framework for the reproducible processing of neuroimaging data with deep learning methods
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