A doubly adaptive approach to dynamic MRI sequence estimation

Dynamic magnetic resonance imaging (MRI) refers to the acquisition of a sequence of MRI images to monitor temporal changes in tissue structure. We present a method for the estimation of dynamic MRI sequences based on two complimentary strategies: an adaptive framework for the estimation of the MRI images themselves, and an adaptive method to tailor the MRI system excitations for each data acquisition. We refer to this method as the doubly adaptive temporal update method (DATUM) for dynamic MRI. Analysis of the adaptive image estimate framework shows that calculating the optimal system excitations for each new image requires complete knowledge of the next image in the sequence. Since this is not realizable, we introduce a linear predictor to aid in determining appropriate excitations. Simulated examples using real MRI data are included to illustrate that the doubly adaptive strategy can provide estimates with lower steady state error than previously proposed methods and also the ability to recover from dramatic changes in the image sequence.