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amid

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data/amid

Awesome Medical Imaging Datasets

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

amid project image
GitHub preview card for neuro-ml/amid. 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
maintained
Maturity
deployed
Organization
neuro-ml
Country
unknown
Homepage
neuro-ml.github.io/amid/
Repository
github.com/neuro-ml/amid
Documentation
unknown
Tags
datasets · medical-imaging · python
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.

  • dataset-uta4-dicomdatasets · medical-imaging

    [AVI 2020] UTA4: Medical Imaging DICOM files dataset.

  • dataset-uta7-dicomdatasets · medical-imaging

    [IJHCS] UTA7: a dataset with DICOM files of medical imaging provided by radiologists. The work was published in the International Journal of Human-Computer Studies.

  • picai_prepdatasets · medical-imaging

    Preprocessing 3D medical images and image archives —geared towards prostate cancer detection in MRI.

  • accessibility-atlas-datasetdatasets

    Disability demographics, web accessibility compliance, assistive technology usage, and related data

  • biosetsdatasets

    A bioinformatics extension of 🤗 Datasets library, built for ML applications on biological and omics data, offering easy integration of metadata and low-code data management tools.

  • Corrected-Skin-Image-Datasetsdatasets

    Data quality analysis of DermaMNIST (MedMNIST), HAM10000, and Fitzpatrick17k datasets

sources
  1. api.github.com/repos/neuro-ml/amid
    retrieved 2026-08-25 · via github-api

    Machine-imported from GitHub search. Last push 2025-12-01, 49 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/30.json→ .entries["amid"]

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