Adaptive data acquisition in MRI

We propose an adaptive data acquisition technique that depends on the object to be imaged in magnetic resonance (MR) imaging. In this paper, we employed a matching pursuit (MP) algorithm to achieve the adaptive data acquisition. Since the matching pursuit is a greedy algorithm to find RF and gradient waveforms which are the best match for an object-signal, the signal can be decomposed with a few iterations and thereby lead reduction of imaging time in MR. To adopt the matching pursuit algorithm to the adaptive data acquisition in MRI, we have designed a dictionary which contains a windowed Fourier basis set. Because the basis set is localized spatially, the image signal could be divided into segmented signals so that matching pursuit with the segmented signals could lead to effective and object-dependent data acquisition. To verify the proposed technique, computer simulations and experiments are performed with a 1.0 T whole body MRI system.