• ITKArrayFire: ArrayFire-backed ITK pipelines
• Spiderclaw: OpenBCI 3D-printable EEG headset files
• dipy: 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.
• xnnppx: XNAT-NiPype-pyxnat
• incdb-poc: INcDb Proof of Conept
• LiviaNET: This repository contains the code of LiviaNET, a 3D fully convolutional neural network that was employed in our work: "3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study"
• bids2pype: from bids data structure and model extension to info ready for nipype
• 3D-F-CNN-BrainStruct: This repository contains materials employed in our work to segment subcortical brain structures by employing a 3D fully Convolutional Neural Network.
• life: Please use the new version of LiFE: www.github.com/brain-life/encode
• bids-examples: None
• C-PAC: Configurable Pipeline for the Analysis of Connectomes
• SnPM-devel: Statistical NonParametric Mapping, development version
• hcp2nipype-hack2015: The outcomes of the HCP to Nipype project at the OHBM Hackathon 2015.
• CoSMoMVPA: A lightweight multivariate pattern analysis (MVPA) toolbox in Matlab / Octave
• fmri-report: None
• 3D-brain-segmentation: This is a repository containing code to Paper "Optimized High Resolution 3D Dense-U-Net Network for Brain and Spine Segmentation" published at MDPI Applied sciences journal - https://www.mdpi.com/2076-3417/9/3/404 .
• BrainImagingPipelines: BIPs
• fastMRI: A large-scale dataset of both raw MRI measurements and clinical MRI images
• neuropower-core: This repository contains the core functions from neuropower in a python package.
• nilearn_tutorials: Nilearn tutorials for OHBM 2016 educational course
• FSL-scripts: Script-framework using FSL, Freesurfer and AFNI functionality for automatization and high-throughput processing of MRI data in clustered environments.
• eegtools: Collection of Python modules for EEG analysis. Includes EDF+ and BDF loaders, scalp plots and commonly used spatial filters.
• quickNAT_pytorch: PyTorch Implementation of QuickNAT and Bayesian QuickNAT, a fast brain MRI segmentation framework with segmentation Quality control using structure-wise uncertainty
• nsviewer: Neurosynth viewer
• r-xnat: XNAT library for R
• tvb-library: DEPRECATED: Use tvb-root. The science behind The Virtual Brain
• microdraw: Collaborative vectorial annotation tool for ultra high resolution data
• automaticanalysis: Automatic analysis
• bidsify: Tool to convert raw MRI datasets to BIDS-compatible datasets
• mindboggle: Automated anatomical brain label/shape analysis software (+ website)
• raiders_data: An fMRI dataset from rich naturalistic audio/video stimulation (movie "Raiders of the lost Ark"). Origin: http://datasets.datalad.org/?dir=/labs/haxby/raiders
• NeuroVault: Easy to use web database for statistical maps.
• RegNet: Deformable Cross-modality MRI Registration Using 3D CNN
• qa-athena: Quality assessment of Athena pipeline images
• dcmstack: DICOM to Nifti conversion with meta data preservation
• nidm-specs: Neuroimaging Data Model (NIDM): describing neuroimaging data and provenance
• neuropower-web: sample size calculations for fMRI
• quality-assessment-protocol: Scripts and documentation for the PCP's protocol for assessing data quality.
• BROCCOLI: BROCCOLI: Software for Fast fMRI Analysis on Many-Core CPUs and GPUs
• poldracklab-base: Repo for general-purpose code in the poldrack lab
• relion: Image-processing software for cryo-electron microscopy
• brain_segmentation: Implementation of VoxResNet for 3D brain segmentation
• lddmmMASGD: This executable file is used for 3D brain MRI registration
• nibabel: Python package to access a cacophony of neuro-imaging file formats
• django-dicom-review: None
• brainbrowser: Web-based visualization tools for neurological data.
• fmri: :exclamation: This is a read-only mirror of the CRAN R package repository. fmri — Analysis of fMRI Experiments. Homepage: http://www.wias-berlin.de/software/imaging/
• openBCI_BCI2k: a BCI2000 driver for the OpenBCI board
• HCPpipelines: Processing pipelines for the HCP
• cmp: Connectome Mapper
• deepmedic: Efficient Multi-Scale 3D Convolutional Neural Network for Segmentation of 3D Medical Scans
• pycortex: Pycortex is a python-based toolkit for surface visualization of fMRI data
• datman: scripts for managing xnat, QC, and data analysis
• pynetdicom: A pure Python DICOM network implementation
• ANTs: Advanced Normalization Tools (ANTs)
• _DEPRECATED_OpenBCI-V2hardware: This repository contains the core OpenBCI hardware and software frameworks.
• neurokernel: Neurokernel Project
• cet_toolbox: None
• open-brain-consent: Making neuroimaging open from the grounds (consent form) and up (tools)
• pyconto: Python Connectome Toolbox
• OctaveMVPA: An All-in-One Princeton MVPA, AFNI-for-MATLAB, and SPM Distro: All Converted for Use in Octave
• Suite2P: Tools for processing 2P recordings
• qc_pipeline: None
• SPM_connectome: Analysis of the data from the human connectome with SPM
• freshMRI: a collection of resources to set up a neuroimaging data analysis environment
• pybids: Python tools for querying and manipulating BIDS datasets.
• csg_mri_pipelines: MRI preprocessing and analysis pipelines and tools for the study of disorders of consciousness
• pyxnat: XNAT in Python
• image-registration-cnn: [Incomplete] A PyTorch implementation of CNN based MRI image registration based on MICCAI 2018 paper "Linear and Deformable Image Registration with 3D Convolutional Neural Networks"
• awesome-bci: Curated Collection of BCI resources
• nidb: NeuroInformatics Database
• repro-case-studies: Reproducibility case study contributions
• Scalable-Brain-Atlas: Source code of the Scalable Brain Atlas website (scalablebrainatlas.incf.org)
• fslr: FSL-R Interface package
• psacnn: None
• neurospinqc: None
• pyhrf: PyHRF is a set of tools to analyze fMRI data and specifically study hemodynamics.
• nipype: Workflows and interfaces for neuroimaging packages
• bctpy: brain connectivity toolbox for python
• BEaST: C implementation of Brain Extraction based on nonlocal Segmentation Technique
• visbrain: A multi-purpose GPU-accelerated open-source suite for brain data visualization
• brainx: Tools for analysis of brain imaging-derived networks, based on NetworkX
• brain-age-prediction: Notes on developmental trajectories, predicting brain maturation, effects of head motion on sMRI, and qMRI and brain development
• clij: CLIJ is deprecated. Visit CLIJ2
• heudiconv: A flexible DICOM converter for organizing brain imaging data into structured directory layouts
• myconnectome: Code for the myconnectome project
• ICA-AROMA: ICA-AROMA Software Package: a data-driven method to identify and remove head motion-related artefacts from functional MRI data.
• PowerGrid: GPU accelerated non-Cartesian magnetic resonance imaging reconstruction toolkit
• real-life: None
• fmriprep: 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.
• neurosynth-data: None
• 3DUnetCNN: Pytorch 3D U-Net Convolution Neural Network (CNN) designed for medical image segmentation
• projectMatlab: Interface R, Matlab, SPM
• fishexplorer: https://zebrafishatlas.zib.de/
• afni: Official AFNI source and documentation
• workbench: Connectome Workbench
• dcm2niix: dcm2nii DICOM to NIfTI converter: compiled versions available from NITRC
• Z-Brain: Z-Brain Viewer and Analysis Scripts for MAP-Mapping
• fieldtrip: The MATLAB toolbox for MEG, EEG and iEEG analysis
• niak: GNU Octave library for connectivity analysis in large fMRI datasets
• fmri-analysis-vm: A VM setup for use in fMRI analysis and education
• fs-cwl: Common workflow language wrappers and workflow for FreeSurfer
• CiftiLib: C++ Library for reading and writing CIFTI-2 and CIFTI-1 files
• Papaya: A pure JavaScript medical research image viewer.
• QUIT: A set of tools for processing Quantitative MR Images
• spm12w: Spm12w is a set of tools and scripts to automate various aspects of fMRI preprocessing and GLM analysis in SPM12.
• biananes: Scalable fMRI Data Analysis
• epitome: scriptit modules for fmri analysis
• grabbit: get grabby with file trees
• pipeline-scheduler: Flask server to schedule and process XNAT pipelines with OpenStack
• spm12: SPM12
• zindex: libznz with zindex
• ACE: Tools for automatic extraction of activation coordinates from published neuroimaging articles.
• nipy: Neuroimaging in Python FMRI analysis package
• Naplib: None
• studycentric: StudyCentric - research DICOM viewer
• nidata: Set of tools for downloading and accessing open-license neuroimaging data in a consistent format.
• GPU-DFC: None
• pipedream: PipeDream - open source neuroimaging pipelines