The American College of Radiology® (ACR®) Data Science Institute® (DSI) and the Cancer Imaging Archive (TCIA), funded by the National Cancer Institute (NCI) at the National Institutes of Health (NIH), have teamed to connect use cases and datasets to speed medical imaging artificial intelligence (AI) development. TCIA datasets have been matched to ACR DSI cancer and non-cancer use cases based upon attributes such as body area, modality, and presence of secondary comorbidities. TCIA data are available under Creative Commons Attribution Licenses, and most are freely available for commercial use for machine learning purposes.
“Finding a good source of data and adequate data for model testing and validation is an ongoing challenge for those developing AI. We’ve now made it easier for those developing AI for medical imaging to get good data, and we’re sharing it along with the guidelines provided by our use cases to be sure the algorithms developed have value for us as radiologists,” said Bibb Allen Jr., MD, FACR, ACR DSI Chief Medical Officer and Diagnostic Radiologist at Grandview Medical Center.
Connecting Define-AI use cases with TCIA datasets may advance research and development by providing AI developers with another set of resources for building AI tools to benefit radiology.