Reverse Dependencies of nibabel

The following projects have a declared dependency on nibabel:

• mne-bids-pipeline — A full-flegded processing pipeline for your MEG and EEG data
• mne-connectivity — mne-connectivity: A module for connectivity data analysis with MNE.
• mne-gui-addons — MNE-Python GUI addons.
• mne-pipeline-hd — A Pipeline-GUI for MNE-Python from MEG-Lab Heidelberg
• mni-to-atlas — A simple Python-based tool for finding brain atlas regions based on MNI coordinates.
• mnisiscom — A simple command line tool and GUI for computing subtraction ictal SPECT coregistered to MRI (SISCOM). mnisiscom is exclusively intended for research use!
• monai — AI Toolkit for Healthcare Imaging
• monai-weekly — AI Toolkit for Healthcare Imaging
• moosez — An AI-inference engine for 3D clinical and preclinical whole-body segmentation tasks
• morphometry — FreeSurfer E2E pipeline
• morphonet — Python API to interact with MorphoNet
• mosamaticdesktop — Desktop tool for analyzing medical images
• moval — Model evaluation without manual labels
• mpunet — Multi-Planar UNet for autonomous segmentation of 3D medical images
• MR-OCTOPUS — Off-resonance correction of MR images
• mrainet — MR acquisition-invariant network.
• mrdataset — MRdataset
• mrftools — Tools for Magnetic Resonance Fingerprinting
• mri_tools — Various tools for MRI related work.
• mri2mesh — Tool for converting labeled MRI data to a mesh
• mriqc — Automated Quality Control and visual reports for Quality Assessment of structural (T1w, T2w) and functional MRI of the brain.
• mrirage — MRI visualization
• MRISeg — A deep learnign based method to segment deep brain structures from T1w MRI
• mrisnapshot — QC tool for verification of datasets with MRI images and derived maps
• mrivis — Intuitive high-level classes for visualization of medical imaging data
• mrQA — mrQA suite of tools offering automatic evaluation of protocol compliance
• mrs-denoising-tools — Package for low-rank denoising of magnetic resonance spectroscopic imaging
• msiimport — Access analyze75 formatted mass spec images
• mssfp — mSSFP is library for image reconstuction for multi-acqusition SSFP
• multi_med_image_ml — Deep learning library to encode multiple brain images and other electronic health record data in disease detection.
• multiecho — Combine multi-echoes from a multi-echo fMRI acquisition.
• muscle-bids — Library for standardized data input/output for muscle MR imaging, based on BIDS
• MVComp — Multivariate Comparisons using Whole-brain and ROI-derived Metrics from MRI
• nanslice — Scripts to slice and display neuroimages (probably stored in nifti format)
• napari-mri — A simple plugin to use with napari for 3D-viewing of Magnetic Resonance Imaging file formats
• napari-nibabel — Read access to some common neuroimaging file formats
• navinibs — Software for neuronavigated non-invasive brain stimulation
• nctpy — Python implementation of concepts from network control theory
• ndagen — Command Line Tool to Generate Metadata Spreadsheet for NDA Upload
• ndexchange — Python 3 program to download data from NeuroData
• ndmg — Neuro Data MRI to Graphs Pipeline
• ndslib — Utility functions for Neuroimaging and Data Science
• nekton — A python package for DICOM to NifTi and NifTi to DICOM-SEG and GSPS conversion
• netneurotools — A toolbox for network neuroscience
• netneurotools-scipyfix — Commonly used tools in the Network Neuroscience Lab
• netplotbrain — Package to plot networks on brains
• neurite — Neural Networks Toolbox for Medical Imaging
• neuroboros — Neuroimaging analysis in Python
• neurocaps — Co-activation Patterns (CAPs) Python package
• NeuroConn — A BIDS toolbox for connectivity & gradient analyses.
• neurofeatures — Generic feature extraction package for neuroimaging features (examples include: connectivity from rs-fmri, regional mean fractional anisotropy, structural covariance etc)
• neuroglancer-scripts — Conversion of images to the Neuroglancer pre-computed format
• NeuroGraph — no summary
• neurohab — Voxelwise brain habituation
• neurolang — "NeuroLang: Probabilistic Logic Programming for NeuroScience Research"
• neuromaps — A toolbox for projecting, resampling, and comparing brain maps
• neuropredict — easy and standardized predictive analysis for biomarkers, neuroimaging, and beyond
• NeuroRA — A Python Toolbox for Multimodal Neural Data Representation Analysis
• ngtools — Tracts visualization and annotation in neuroglancer
• nib-save-wrapper — no summary
• nibabies — Processing workflows for magnetic resonance images of the brain in infants
• nibetaseries — BetaSeries Correlations implemented in Nipype
• NiChart-DLMUSE — Run NiChart_DLMUSE on your data (currently only structural pipeline is supported).
• NiChart-Viewer — Viewer to visualize neuroimaging chart (NiChart) image descriptors and biomarkers
• NiChartHarmonize — Harmonization tools for multi-center neuroimaging studies.
• nidb-to-bids — Our lab's code to convert data dumped from NiDB to BIDS
• nidmresults — Export of neuroimaging statistical results using NIDM as specified at http://nidm.nidash.org/specs/nidm-results.html.
• nifti-converter — Convert NIfTI files to usual image formats
• nifti-mrs — Software tools for the NIfTI-MRS data format
• nifti2dicom — A package to convert NIfTI images to DICOM format using a reference DICOM series.
• niftithings — A Python library for working with Nifti images.
• NiftyNet — An open-source convolutional neural networks platform for research in medical image analysis and image-guided therapy
• niftypad — Neuroimaging for the Prevention of Alzheimer's Disease
• niftytorch — Deep Learning Library for NeuroImaging
• nigsp — A python library (and toolbox!) to run Graph Signal Processing on multimodal MRI data.
• nii-info — Display NIfTI image information in a tabular format
• nii-plot — Plot mean NIfTI timeseries
• nii2dcm — nii2dcm: NIfTI to DICOM creation with Python
• nii2png — A lightweight neuroimaging .nii to .png converter
• niicat — Preview nifti images on the terminal
• nilabels — Toolkit to manipulate and measure image segmentations in nifti format.
• nilearn — Statistical learning for neuroimaging in Python
• NiMARE — NiMARE: Neuroimaging Meta-Analysis Research Environment
• nimesh — A Python package to manipulate neuroimaging triangular meshes.
• nipreps-synthstrip — NiPreps implementation of FreeSurfer's SynthStrip
• nipy — A python package for analysis of neuroimaging data
• nipy-gradunwarp — HCP version of Gradient Unwarping Package for Python/Numpy
• nipype — Neuroimaging in Python: Pipelines and Interfaces
• nipype-fsl-anat — Nipype interface(s) wrapping the `fsl_anat` command line tool
• nipype-generate-fieldmaps — Nipype workflow to generate fieldmaps from EPI acquisitions with differing phase-encoding directions
• nireports — NiReports - The Visual Report System (VRS) of NiPreps
• nisnap — nisnap
• nistats — Modeling and Statistical analysis of fMRI data in Python
• nitime — Nitime: timeseries analysis for neuroscience data
• nitransforms — NiTransforms -- Neuroimaging spatial transforms in Python.
• niutils — Various utilities to fast-track some boring python coding.
• 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
• nlsam — Implementation of "Non Local Spatial and Angular Matching : Enabling higher spatial resolution diffusion MRI datasets through adaptive denoising"
• nltools — A Python package to analyze neuroimaging data