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skm-tea

imported

data/skm-tea

Repository for the Stanford Knee MRI Multi-Task Evaluation (SKM-TEA) Dataset

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

skm-tea project image
GitHub preview card for StanfordMIMI/skm-tea. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Data & Standards
Subcategory
unknown
License
MIT(osi)
Status
dormant
Maturity
deployed
Organization
StanfordMIMI
Country
unknown
Homepage
unknown
Documentation
unknown
Tags
computer-vision · inverse-problems · machine-learning · mri
Regulatory
unknown
built by · 1

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.

  • cs-mri-ganinverse-problems · mri

    Structure preserving Compressive Sensing MRI Reconstruction using Generative Adversarial Networks (CVPRW 2020)

  • irim_fastMRIinverse-problems · mri

    i-RIM applied to the fastMRI challenge data.

  • meddlrinverse-problems · mri

    A flexible ML framework built to simplify medical image reconstruction and analysis experimentation.

  • MIRT.jlinverse-problems · mri

    MIRT: Michigan Image Reconstruction Toolbox (Julia version)

  • scope-mricomputer-vision · mri

    Resource for getting started with deep learning for MRIs/CTs. This codebase accompanies the release of the SCOPE-MRI dataset and paper (Sethi et al., NPJ AI 2025)

  • brainscannerinverse-problems

    Real-time EEG source localization based on Smarting mBrainTrain EEG headset and implemented in Matlab.

sources
  1. api.github.com/repos/StanfordMIMI/skm-tea
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2023-05-28, 104 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/33.json→ .entries["skm-tea"]

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