Independent Component Analysis for Noise Removal in MR Fingerprinting

Abstract

We propose the use of independent component analysis for the removal of coherent noise sources prior to matching for magnetic resonance fingerprinting (MRF). We tested this technique for the removal of reconstruction artefacts on images acquired with a spiral k-space acquisition to quantify intravascular T1, extravascular T1, B1+, cerebral blood volume (νb) and inter-vascular water exchange (1/τb). We demonstrate that removal of coherent noise sources in this way can improve the precision of measurements of parameters.