Reverse Dependencies of nilearn

The following projects have a declared dependency on nilearn:

• afids-utils — Utility functions for working with AFIDs data / workflows
• ardent — A tool for nonlinear image registration.
• ascnii — View brain images in terminal using ASCII characters
• asldro — ASL Digital Reference Object
• atlaspy — Python library for working with brain atlases
• bbrc-validator — Systematic sanity checks on imaging datasets within an XNAT environment
• bcblib — no summary
• bidsonym — A BIDSapp for deidentification of neuroimaging data.
• bp-neurotools — General helper functions for working with neuroimaging data.
• brain-pred-toolbox — The Brain Predictability toolbox (BPt) is a Python based machine learning library designed to work with a range of neuroimaging data. Warning: Not actively maintained as of 11/30/22.
• brainiak — Brain Imaging Analysis Kit
• brainsprite — Python API for the brainsprite MRI brain viewer
• brainstat — A toolbox for statistical analysis of neuroimaging data
• branesta — Tool for computing brain network stability, a biomarker for brain aging.
• cbig-network-correspondence — A toolbox for exploring network correspondence across atlases
• clinica — Software platform for clinical neuroimaging studies
• clinicadl — Framework for the reproducible processing of neuroimaging data with deep learning methods
• comet-toolbox — Dynamic functional connectivity toolbox for multiverse analysis
• connPFM — no summary
• connsearch — Analysis of connectivity data by dividing the connectome and fitting independent models
• contarg — Python package implementing/wrapping connectivity based rTMS targeting methods.
• conwhat — python library for connectome-based white matter atlas analyses in neuroimaging
• crtoolbox — The Confidence Regions Toolbox
• cvrmap — CVRmap is an opensource software to compute maps of Cerebro-Vascular Reactivity
• dbspace — Library for data-congruent, model-centric DBS Research
• ddmra — A Python package for distance-dependent motion-related artifact (DDMRA) analysis.
• deepdefacer — Automatic Removal of Facial Features from MRI Images
• denoise-fmri — denoise_fmri - BIDS app for denoising fmriprep outputs
• difit — Diffusion weighted models fitting
• dsbundle — Streamline your data science setup with dsbundle in one effortless install.
• dyneusr — Dynamical Neural Spatiotemporal Representations.
• dypac — Dynamic parcel aggregation with clustering
• eddymotion — Pure python eddy-current and head-motion correction for dMRI, an extension of QSIprep's SHOREline algorithm (Cieslak, 2020) to multiple diffusion models.
• eeg-to-fmri — no summary
• eegsynth — Converting real-time EEG into sounds, music and visual effects
• eigenstrapping — For generating surrogate brain maps with spatial autocorrelation using geometric eigenmodes.
• eisen-core — Eisen is a collection of tools to train neural networks for medical image analysis
• falconz — FalconZ: A streamlined Python package for PET motion correction.
• fitlins — Fit Linear Models to BIDS Datasets
• fmralign — Functional alignment of fMRI data in Python
• fmridenoise — fMRIDenoise - automated denoising, denoising strategies comparison, and functional connectivity data quality control.
• fMRIpreprocessing — no summary
• frat-brain — Application for ROI fMRI data analysis.
• fugw — A collection of gpu-compatible solvers for fused unbalanced gromov-wasserstein optimization problems
• gawseed-tcorex — Correlation Explanation Methods
• glm-express — Automated linear models for functional neuroimaging data
• gradec — Meta-analytic gradient decoding
• gradiator — turn covariance matrices into brain gradients
• hidimstat — High-dimensional statistical inference tools for Python
• hippunfold_plot — Plotting functions for hippocampal surface maps from HippUnfold
• hippunfold-toolbox — A toolbox for viewing, manipulating, and additional actions on HippUnfold outputs
• hipsta — A python package for hippocampal shape and thickness analysis
• hypercoil — Differentiable programming for neuroimaging analysis
• Ingress2QSIRecon — Tool to ingress data from other pipelines for use in QSIRecon
• JALE — Package allowing users to run Activation Likelihood Estimation Meta-Analysis
• junifer — JUelich NeuroImaging FEature extractoR
• livingpark-utils — Utility functions to write LivingPark notebooks.
• load-confounds — load fMRIprep confounds in python
• m2g — Neuro Data MRI to Graphs Pipeline
• macapype — Pipeline for anatomic processing for macaque
• mapca — Moving Average Principal Component Analysis for fMRI data
• medimage-pkg — MEDimage is a Python package for processing and extracting features from medical images
• mia-processes — mia_processes
• mindstorm — Mindstorm: Advanced analysis of neuroimaging data
• MiTfAT — A Python-based Scikit-Learn-friendly fMRI Analysis Tool, Made in Tuebingen.
• mne-bids — MNE-BIDS: Organizing MEG, EEG, and iEEG data according to the BIDS specification and facilitating their analysis with MNE-Python
• mne-connectivity — mne-connectivity: A module for connectivity data analysis with MNE.
• mne-nirs — An MNE compatible package for processing near-infrared spectroscopy data
• mnisiscom — A simple command line tool and GUI for computing subtraction ictal SPECT coregistered to MRI (SISCOM). mnisiscom is exclusively intended for research use!
• mriqc — Automated Quality Control and visual reports for Quality Assessment of structural (T1w, T2w) and functional MRI of the brain.
• MVComp — Multivariate Comparisons using Whole-brain and ROI-derived Metrics from MRI
• nctpy — Python implementation of concepts from network control theory
• ndmg — Neuro Data MRI to Graphs Pipeline
• ndslib — Utility functions for Neuroimaging and Data Science
• netneurotools — A toolbox for network neuroscience
• netneurotools-scipyfix — Commonly used tools in the Network Neuroscience Lab
• neurocaps — Co-activation Patterns (CAPs) Python package
• NeuroConn — A BIDS toolbox for connectivity & gradient analyses.
• neuroginius — A repertoire of tools in python for high-level analyses of fMRI data.
• NeuroGraph — no summary
• neuroimager — A collection of utilities used for MRI data analysis
• neurolang — "NeuroLang: Probabilistic Logic Programming for NeuroScience Research"
• neuromaps — A toolbox for projecting, resampling, and comparing brain maps
• NeuroPrep — no summary
• NeuroPreprocessing — no summary
• neuroquery — Meta-analysis of neuroimaging studies.
• neuroquery-image-search — Search the NeuroQuery dataset for studies with activation patterns similar to an input image.
• NeuroRA — A Python Toolbox for Multimodal Neural Data Representation Analysis
• nibetaseries — BetaSeries Correlations implemented in Nipype
• nichord — Creates chord diagrams for connectivity/graph data
• nidmd — Dynamic Mode Decomposition of time-series fMRI
• nigsp — A python library (and toolbox!) to run Graph Signal Processing on multimodal MRI data.
• nilearn-extra — Drop-in extra functionalities for nilearn (statistics for neuroimaging in Python)
• NiMARE — NiMARE: Neuroimaging Meta-Analysis Research Environment
• nipype — Neuroimaging in Python: Pipelines and Interfaces
• nisnap — nisnap
• nistats — Modeling and Statistical analysis of fMRI data in Python
• niworkflows — NeuroImaging Workflows provides processing tools for magnetic resonance images of the brain.
• nixtract — A unified interface for timeseries extraction from different functional neuroimaging file types
• nltools — A Python package to analyze neuroimaging data