This work introduces a new framework for myelin water fraction (MWF) estimation. We use a novel scan design approach to construct a sequence a fast steady-state sequences and optimize corresponding flip angles and repetition times for precise MWF estimation. We quantify MWF and five other parameters per voxel using a novel method based on kernel ridge regression. We obtain MWF maps in vivo that are comparable to those reported in literature, with possibly shorter overall scan time.
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