This web page is a result of a collaboration between the research groups of Prof. Michael Lustig at UC Berkeley and Dr. Shreyas Vasanawala at Stanford's Lucille Packard Children's Hospital.  The goal is to bring compressed sensing technology to magnetic resonance imaging (MRI).  Compressed sensing techniques sample the MRI signal below the standard Nyquist rate and then use novel algorithms to reconstruct the resulting medical images. With undersampling, MRI scan times can be reduced, which is especially beneficial for small children who cannot stay still in an MRI scanner for long periods.  Compressed sensing has recently become an active area of research in the MRI development community.  This web site aims to provide standard data sets, both undersampled and fully sampled, so that developers can test algorithms and contribute to a community of reproducible research. Our hope is that these datasets will help the MRI research community to accelerate their improvements in medical image processing.