Recently, a robust principle component analysis (rPCA) method was implemented to myelin water fraction (MWF) mapping using mGRE data. Based on the intrinsic nature of T2* relaxation, hankelization and non-negative matrix factorization was implemented to enhance low rankness of each rank-1 component. In this study, the noise sensitivity of model-free rPCA was investigated. According to simulation and in vivo analysis, model-free rPCA technique is more robust at noise and other physiological artifacts than model-based fitting technique.
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