Datasets › MedMNIST v2

MedMNIST v2

Introduced by Jiancheng Yang et al. in MedMNIST v2 -- A large-scale lightweight benchmark for 2D and 3D biomedical image classification27 Oct 2021 archive 2025-07-28

MedMNIST v2 is a large-scale MNIST-like collection of standardized biomedical images, including 12 datasets for 2D and 6 datasets for 3D. All images are pre-processed into 28 x 28 (2D) or 28 x 28 x 28 (3D) with the corresponding classification labels, so that no background knowledge is required for users. Covering primary data modalities in biomedical images, MedMNIST v2 is designed to perform classification on lightweight 2D and 3D images with various data scales (from 100 to 100,000) and diverse tasks (binary/multi-class, ordinal regression and multi-label). The resulting dataset, consisting of 708,069 2D images and 10,214 3D images in total, could support numerous research / educational purposes in biomedical image analysis, computer vision and machine learning.

Description and image from: MedMNIST v2: A Large-Scale Lightweight Benchmark for 2D and 3D Biomedical Image Classification

Each subset keeps the same license as that of the source dataset. Please also cite the corresponding paper of source data if you use any subset of MedMNIST.

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 27 papers for it but never published that list.

Dataset loaders archive 2025-07-28

3 loaders as listed in the archive; links are outbound and not re-checked here.

Tasks archive 2025-07-28

No task tagged in the archive.

License archive 2025-07-28

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Modalities archive 2025-07-28

Languages archive 2025-07-28

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Variants archive 2025-07-28

  • MedMNIST v2

1 variant name, as the archive lists them.

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