• 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.
• NeuroVault: Easy to use web database for statistical maps.
• RegNet: Deformable Cross-modality MRI Registration Using 3D CNN
• qc_pipeline: None
• freshMRI: a collection of resources to set up a neuroimaging data analysis environment
• niak: GNU Octave library for connectivity analysis in large fMRI datasets
• fmri-analysis-vm: A VM setup for use in fMRI analysis and education
• 3DUnetCNN: Pytorch 3D U-Net Convolution Neural Network (CNN) designed for medical image segmentation
• 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"
• 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.
• BROCCOLI: BROCCOLI: Software for Fast fMRI Analysis on Many-Core CPUs and GPUs
• brainiak: Brain Imaging Analysis Kit
• csg_mri_pipelines: MRI preprocessing and analysis pipelines and tools for the study of disorders of consciousness
• 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.
• brain_segmentation: Implementation of VoxResNet for 3D brain segmentation
• lddmmMASGD: This executable file is used for 3D brain MRI registration
• biananes: Scalable fMRI Data Analysis
• 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"
• epitome: scriptit modules for fmri analysis
• 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/
• pipeline-scheduler: Flask server to schedule and process XNAT pipelines with OpenStack
• deepmedic: Efficient Multi-Scale 3D Convolutional Neural Network for Segmentation of 3D Medical Scans
• psacnn: 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 .
• fmri-report: None
• pycortex: Pycortex is a python-based toolkit for surface visualization of fMRI data
• pyhrf: PyHRF is a set of tools to analyze fMRI data and specifically study hemodynamics.
• fastMRI: A large-scale dataset of both raw MRI measurements and clinical MRI images
• BEaST: C implementation of Brain Extraction based on nonlocal Segmentation Technique
• quickNAT_pytorch: PyTorch Implementation of QuickNAT and Bayesian QuickNAT, a fast brain MRI segmentation framework with segmentation Quality control using structure-wise uncertainty
• heudiconv: A flexible DICOM converter for organizing brain imaging data into structured directory layouts
• ismrmrd: ISMRM Raw Data Format
• ICA-AROMA: ICA-AROMA Software Package: a data-driven method to identify and remove head motion-related artefacts from functional MRI data.
• nipy: Neuroimaging in Python FMRI analysis package
• PowerGrid: GPU accelerated non-Cartesian magnetic resonance imaging reconstruction toolkit
• studycentric: StudyCentric - research DICOM viewer
• bidsify: Tool to convert raw MRI datasets to BIDS-compatible datasets
• mindboggle: Automated anatomical brain label/shape analysis software (+ website)
• birthdaycard: Program to generate birthday cards from structural brain scans.