We introduce MedMNIST v2, a large-scale MNIST-like dataset collection of standardized biomedical images, including 12 datasets for 2D and 6 datasets for 3D. All images are pre-processed into a small size of 28x28 (2D) or 28x28x28 (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 dataset 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. We benchmark several baseline methods on MedMNIST v2, including 2D / 3D neural networks and open-source / commercial AutoML tools. The data and code are publicly available at https://medmnist.com/.

介绍了一个类似于MNIST的大规模医学图像数据集MedMNIST v2，包括12个2D数据集和6个3D数据集，经过预处理的图像大小为28x28或28x28x28，支持多种数据集规模和任务，并提供了基准方法 （2D/3D神经网络和开源/商业AutoML工具）进行分类任务。可用于医学图像分析，计算机视觉和机器学习等领域的研究和教育目的。

MedMNIST v2 -- 二维和三维生物医学图像分类的大规模轻量级基准