Advanced reconstruction methods for fast MRI

Image reconstruction has been a field of active research since the dawn of MRI, and the quest for faster patient exams has triggered substantial innovations during this time. This chapter provides a chronologically ordered overview of image reconstruction methods for accelerated MR imaging, from phase-constrained partial Fourier imaging over parallel imaging to compressed sensing and recent developments in machine learning. Didactic numerical experiments are presented with a data set that is representative for a clinical neuroimaging exam.