Self-Calibrated Subspace Reconstruction using Temporally Local Matrix Completion for Multidimensional MR Fingerprinting

We propose a new reconstruction method, named self-calibrated subspace reconstruction, for multidimensional MR fingerprinting (mdMRF), in order to correct the artifacts due to inter-shot (segment) magnitude and phase variations, without the need for extra navigator or calibration data. Different options for utilizing the low-rank property and the signal structure of mdMRF data are investigated and the optimal scheme is determined. Such that aliasing-free high-resolution image reconstruction and high-quality quantification, can be achieved.