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MedMNIST

Lightweight Benchmark for Medical Image Analysis

MedMNIST

We present MedMNIST, a collection of 10 pre-processed medical open datasets. MedMNIST is standardized to perform classification tasks on lightweight 28 * 28 images, which requires no background knowledge. Covering the primary data modalities in medical image analysis, it is diverse on data scale (from 100 to 100,000) and tasks (binary/multi-class, ordinal regression and multi-label). MedMNIST could be used for educational purpose, rapid prototyping, multi-modal machine learning or AutoML in medical image analysis. Moreover, MedMNIST Classification Decathlon is designed to benchmark AutoML algorithms on all 10 datasets; We have compared several baseline methods, including open-source or commercial AutoML tools.

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Shanghai Jiao Tong University, Shanghai, China
https://en.sjtu.edu.cn
Task
Image Classification
Annotation Types
Classification Tags
720000
Items
18
Classes
720000
Labels
Models using this dataset
Last updated on 
January 20, 2022
Licensed under 
MIT
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