Abstract #3411

Independent Component Analysis for Noise Removal in MR Fingerprinting

Emma L Thomson^1,2, Claudia A M Gandini Wheeler-Kingshott^3,4,5, and Geoff J M Parker^1,6,7

¹Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom, ²UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, London, United Kingdom, ³NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, London, United Kingdom, ⁴Department of Brain & Behavioural Sciences, University of Pavia, Pavia, Italy, ⁵Brain Connectivity Centre Research Department, IRCCS Mondino Foundation, Pavia, Italy, ⁶NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, London, United Kingdom, ⁷Bioxydyn Limited, Manchester, United Kingdom

Synopsis

Keywords: Artifacts, MR FingerprintingWe 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 (ν_b) and inter-vascular water exchange (1/τ_b). We demonstrate that removal of coherent noise sources in this way can improve the precision of measurements of parameters.

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