Imaging data sets (artificial intelligence)

Last revised by Joshua Yap on 26 Aug 2022

The aggregation of an imaging data set is a critical step in building artificial intelligence (AI) for radiology. Imaging data sets are used in various ways including training and/or testing algorithms. Many data sets for building convolutional neural networks for image identification involve at least thousands of images but smaller data sets are useful for texture analysistransfer learning, and other programs. 

Many commercial AI products are built on proprietary data sets or specific hospital data sets not available due to concerns over patient privacy. There are however several imaging data sets of radiological images and/or reports publicly available at the following websites:

Additionally, The Cancer Imaging Archive contains links to many open radiology data sets including the following:

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