openmedical/registry
← registry

graynet

imported

software/graynet

Subject-wise networks from structural MRI, both vertex- and voxel-wise features (thickness, GM density, curvature, gyrification)

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

record
Category
Software & Systems
Subcategory
unknown
License
MIT(osi)
Status
active
Maturity
deployed
Organization
unknown
Country
unknown
Documentation
unknown
Tags
anatomical-mri · cortical-network · cortical-thickness · feature-extraction · freesurfer · graph · gray-matter · machine-learning
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.

  • visualqcanatomical-mri · freesurfer

    VisualQC : assistive tool to ease the quality control workflow of neuroimaging data.

  • brainstemx-fullfreesurfer

    Why should radiologists rely on eyesight alone, when computer vision and amazing open-source processing frameworks are already available. This respository hosts the full bash-based pipeline, whilst…

  • cat12cortical-thickness

    Computational Anatomy Toolbox for SPM

  • DL-DiReCTcortical-thickness

    DL+DiReCT - Direct Cortical Thickness Estimation using Deep Learning-based Anatomy Segmentation and Cortex Parcellation

  • autoflattenanatomical-mri

    automatically create cortical flatmaps from FreeSurfer surfaces

  • freesurferanatomical-mri

    BIDS app wrapping recon-all from FreeSurfer

sources
  1. api.github.com/repos/raamana/graynet
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2026-04-04, 38 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

machine-readable

/v1/entries/29.json→ .entries["graynet"]

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