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KUL_NIS

imported

software/kul-nis

KUL/UZ NeuroImaging Suite. A set of tools for brain and spine MRI analysis.

Machine-generated from the listed sources and not yet reviewed by a human.

record
Category
Software & Systems
Subcategory
unknown
License
MPL-2.0(osi)
Status
active
Maturity
deployed
Organization
unknown
Country
unknown
Homepage
unknown
Documentation
unknown
Tags
dmri · fmri · image-processing · neuroimaging
Regulatory
unknown
built by · 2

Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.

similar by tags

Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.

  • fmriprepfmri · image-processing · neuroimaging

    fMRIPrep is a robust and easy-to-use pipeline for preprocessing of diverse fMRI data. The transparent workflow dispenses of manual intervention, thereby ensuring the reproducibility of the results.

  • Reconstruction of preprocessed q-space images (dMRI)

  • ActflowToolboxfmri · neuroimaging

    The Brain Activity Flow ("Actflow") Toolbox. Tools to quantify the relationship between connectivity and task activity through network simulations and machine learning prediction. Helps determine…

  • advanced_fMRI_coursefmri · neuroimaging

    List of ressources and practicals used for the fMRI data analysis course of UoB (UK) (2014-2017)

  • automaticanalysisfmri · neuroimaging

    Automatic Analysis (aa)

  • bids-toolsfmri · neuroimaging

    Tools for dealing with neuroimaging data in the BIDS structure

sources
  1. api.github.com/repos/treanus/KUL_NIS
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2026-08-05, 21 stars, license reported as MPL-2.0. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

machine-readable

/v1/entries/52.json→ .entries["kul-nis"]

Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.