The dataset includes more than 1.5 million anonymous MR images of the knee, taken from 10,000 scans, in addition to raw measurement data from nearly 1,600 scans.
The release is the latest phase of a collaboration between the school's Center for Advanced Imaging Innovation and Research and FAIR. The goal is to share open-source tools and spur the development of AI systems to make MRI scans 10 times faster.
The collaboration will promote research reproducibility and provide evaluation methods, according to the university. The joint team will also provide a suite of tools, including baseline metrics to compare results and also a leaderboard to keep track of progress as part of an organized challenge to be announced in the near future.