A Practical Acceleration Algorithm for Real-Time Imaging

Abstract

A practical acceleration algorithm for real-time magnetic resonance imaging (MRI) is presented. Neither separate training scans nor embedded training samples are used. The Kalman filter based algorithm provides a fast and causal reconstruction of dynamic MRI acquisitions with arbitrary readout trajectories. The algorithm is tested against abrupt changes in the imaging conditions and offline reconstructions of in vivo cardiac MRI experiments are presented.