Neuroimaging Discovery
We build methods that help researchers study brain structure, function, and dynamics across clinical and nonclinical populations.
TReNDS
open source software
TReNDS develops, applies, and shares advanced analytic approaches and neuroinformatics tools that turn brain imaging, omics, and large-scale data into discoveries for brain health and disease.
Data Fusion
We connect multimodal brain imaging, omics, and machine learning to reveal patterns that single datasets cannot show alone.
Open Collaboration
We share software, data practices, and neuroinformatics tools through a collaborative center across GSU, Georgia Tech, and Emory.
We publish the results of our research as open-source software and research platforms. Below is a selection of tools from TReNDS for neuroimaging analysis, multimodal data fusion, simulation, machine learning, and brain connectivity research.
NeuroFLAME
Neuroimaging Federated Learning Analysis for Multi-site Environments, a GUI-based standalone application
View4D FFT Toolbox
Computes spatio-spectral temporal profiles for 4D imaging data.
ViewAverage Sliding Window
Simulation code and examples for average sliding window correlation in dynamic functional connectivity.
Viewbrainbow
Visualizes ICA components and ROI brain parcellations from NIfTI maps.
ViewBrainchop
Browser-based brain image segmentation for working with imaging models and segmentation workflows directly on the web.
Viewbrainchop
A separate Python package for running Brainchop workflows from the command line.
ViewCatalyst Neuro
PyTorch framework for deep learning research and development.
ViewCortex
A framework for training and evaluating neural networks using Theano.
ViewfMRI Simulation Toolbox (SimTB)
Generates flexible fMRI datasets under a model of spatiotemporal separability for testing analysis methods.
ViewFunctional Network Connectivity (FNC)
Finds and displays temporal relationships among components to help study causal relations in the brain.
ViewFusion ICA Toolbox (FIT)
Supports joint ICA, parallel ICA, and CCA with joint ICA for examining shared information across imaging, EEG, and genetic features.
ViewGroup ICA Toolbox (GIFT and EEGIFT)
Implements multiple algorithms for independent component analysis and blind source separation of group and single-subject fMRI and EEG data.
ViewGroup Inter-participant Correlation (GIPC)
Compares spatial activation similarities among subjects and across study groups.
ViewIRVI
Implements iterative refinement of the approximate posterior for directed belief networks.
ViewLaterality User Interface (LUI)
Generates lateral difference maps from brain images for laterality-focused analysis.
ViewMANCOVAN
Tools for multivariate analysis in neuroimaging research workflows.
ViewMeshNet
Torch implementation of the MeshNet architecture and trained weights for white and gray matter segmentation.
Viewmindfultensors
Builds dataloaders for MRI tensors and segmentation labels stored across MongoDB records.
ViewMISA-pytorch
PyTorch implementation for Multidataset Independent Subspace Analysis.
ViewPl2mind
Extends Pylearn2 for neuroimaging and brain data applications, including datasets for incorporating 3D brain data into deep models.
Viewpolyssifier
Runs many classifiers on a dataset and produces AUC reports for comparing model performance.
ViewSIMEEG
EEG simulation scripts for generating and testing EEG analysis workflows.
ViewsMRI Simulator
Simulates structural MRI data and includes an example simulation notebook.
ViewSquare-root Cubature Kalman Filter (SCKS)
Contains implementations of the square-root Cubature Kalman Filter and square-root Rauch-Tang-Striebel smoother.
ViewWavelet Denoising Toolbox (WaveIDioT)
Provides improved 3D denoising of fMRI datasets using a wavelet-based hierarchical approach.
Viewwirehead
Caches and serves synthetic data generator output through MongoDB-backed datasets.
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