brainlife.io's repositories
app-freesurfer
Freesurfer segments the t1w anatomical data into functionally different parts of the brain. Segmentation/parcellation can then be fed to many other subsequent analysis.
app-mrtrix3-preproc
Run the recommended preprocessing procedure provided by mrtrix3. The options available mostly reflect the optimal DESIGNER pipeline that was recently proposed. This App runs for >15 on topup if both PA and AP dwi files are provided. It detects bvecs flipping (dwigradcheck) and update the gradient table accordingly.
app-fmriprep
fMRIPrep is a functional magnetic resonance imaging (fMRI) data preprocessing pipeline that is designed to provide an easily accessible, state-of-the-art interface that is robust to variations in scan acquisition protocols and that requires minimal user input, while providing easily interpretable and comprehensive error and output reporting.
dockerfiles
repository to store various dockerfiles used to build docker containers that are used across multiple brainlife apps
app-tractanalysisprofiles
Create plots of diffusion metrics (i.e. FA, MD, RD, AD) for each of the segmented tracts from AFQ, known as Tract Profiles. Obtains streamline positions from segmented tracts and plots the metrics of interest along "nodes" of the tract, allowing for comparison of individual subject tracts. Requires the dt6 output from dtiinit and a white matter classification output from AFQ or WMA
pybrainlife
Library to access brainlife.io data objects and jupyter notebooks
app-detect-alpha-peak
Detect individual alpha peak in MEG/EEG signals
app-template-python
This is a template for a python-based brainlife.io/app
app-benson14-retinotopy
Brainlife.io app for Noah Benson's neuropythy library, retinotopy from T1 anatomy
app-cortex-tissue-mapping
This app will map volumated measure files (i.e. tensor, NODDI) to the cortical surface following Fukutomi et al (2018; 10.1016/j.neuroimage.2018.02.017) using Connectome Workbench.
app-predict-ppcs
App to predict Persisting Post Concussion Symptoms
app-tractDensityMasks
This app creates a streamline density mask (NIfTI format) for each structure labeled in a classification structure. This provides information about the volumetric density of streamline models of tracts.