OCMR—Open-Access Multi-Coil k-Space Dataset for Cardiovascular Magnetic Resonance Imaging

Cardiovascular MRI (CMR) is a non-invasive imaging modality that provides excellent soft-tissue contrast without the use of ionizing radiation. Physiological motions and limited speed of MRI data acquisition necessitate development of accelerated methods, which typically rely on undersampling. Recovering diagnostic quality CMR images from highly undersampled data has been an active area of research. Recently, several data acquisition and processing methods have been proposed to accelerate CMR. The availability of data to objectively evaluate and compare different reconstruction methods could expedite innovation and promote clinical translation of these methods. In this work, we introduce an open-access dataset, called OCMR, that provides multi-coil k-space data from 74 fully sampled and 212 prospectively undersampled cardiac cine series, comprising of 183 and 842 slices, respectively.

October 08, 2020 (added more fully sampled data)

sampling number of files number of slices
fully sampled 74 183
prospectively undersampled 212 842

August 10, 2020 (original launch)

sampling number of files number of slices
fully sampled 53 81
prospectively undersampled 212 842