Machine learning for NeuroImaging in Python

Workflows and interfaces for neuroimaging packages

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.

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

TE-dependent analysis of multi-echo fMRI

Easy to use web database for statistical maps.

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

A toolbox for comparing brain maps

Framework for the reproducible processing of neuroimaging data with deep learning methods

Automated anatomical brain label/shape analysis software (+ website)

Graph theory analysis of brain MRI data

PyTorch Implementation of QuickNAT and Bayesian QuickNAT, a fast brain MRI segmentation framework with segmentation Quality control using structure-wise uncertainty

BIDScoin converts your source-level neuroimaging data to BIDS

Useful tools from the Network Neuroscience Lab

A NIfTI (nii.gz) 3D Visualizer using VTK and Qt5

C++ library for simulation of multiscale neural field dynamics

Public release of The Cole-Anticevic Brain-wide Network Partition (CAB-NP)

Python API for Mentalab biosignal aquisition devices

Brain tumor segmentation using fully-convolutional deep neural networks.

A python package which aligns histology to the Allen Brain Atlas and Waxholm rat atlas using deep learning.