Spatio-temporal modeling and minimum redundancy adaptive acquisition in dynamic MRI

We propose two models for dynamic cardiac imaging, based on the spatial and temporal-spectral support of the object. The models explicitly account for the aperiodicity of cardiac motion. The models are used for both adaptive minimum redundancy data acquisition optimized for the object being imaged and to reconstruct a high temporal resolution movie of the dynamic object. Schemes for (a) estimating the model parameters, (b) designing the minimum redundancy acquisition sequence, and (c) reconstructing the image sequence from acquired data, are presented. Simulated cardiac MRI experiments show high quality cine reconstructions with 20-fold reduction in acquisition rates.