Iterative adaptive sparse sampling method for magnetic resonance imaging

Magnetic Resonance Imaging (MRI) represents a major imaging modality for its low invasiveness and for its property to be used in real-time and functional applications. The acquisition of radial directions is often used but a complete examination always requires long acquisition times. The only way to reduce acquisition time is undersampling. We present an iterative adaptive acquisition method (AAM) for radial sampling/reconstruction MRI that uses the information collected during the sequential acquisition process on the inherent structure of the underlying image for calculating the following most informative directions. A full description of AAM is furnished and some experimental results are reported; a comparison between AAM and weighted compressed sensing (CS) strategy is performed on numerical data. The results demonstrate that AAM converges faster than CS and that it has a good termination criterion for the acquisition process.