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mriqc

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software/mriqc

Automated Quality Control and visual reports for Quality Assessment of structural (T1w, T2w) and functional MRI of the brain

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

mriqc project image
GitHub preview card for nipreps/mriqc. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Software & Systems
Subcategory
unknown
License
Apache-2.0(osi)
Status
active
Maturity
deployed
Organization
nipreps
Country
unknown
Documentation
unknown
Tags
machine-learning · mri · neuroimaging · quality-control · quality-reporter
Regulatory
unknown
built by · 6

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.

  • brainanamri · neuroimaging · quality-control

    End-to-end preprocessing framework for macaque brain MRI — anatomical & fMRI processing, image registration, surface reconstruction & HTML QC reports.

  • mrivismri · neuroimaging · quality-control

    medical image visualization library and development toolkit

  • mrQAmri · neuroimaging · quality-control

    mrQA: tools for quality assurance in medical imaging datasets, including protocol compliance

  • MultiQC_neuroimagingneuroimaging · quality-control

    MultiQC plugin dedicated to interact and analyze neuroimaging outputs.

  • nireportsneuroimaging · quality-control

    The NiPreps' Reporting and Visualization system - report templates and "reportlets"

  • nisnapneuroimaging · quality-control

    Display segmentation results over MRI scans in Jupyter notebooks.

sources
  1. api.github.com/repos/nipreps/mriqc
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2026-07-20, 369 stars, license reported as Apache-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/61.json→ .entries["mriqc"]

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