A joint reconstruction framework is proposed to reconstruct a series of T1-weighted, T2-weighted, and T2*-weighted images and corresponding parameter maps simultaneously from undersampled cartesian k-space data. Joint Total Variation (JTV) and model-based constraints were employed to resolve the ambiguity introduced due to undersampling. T1 and T2 maps were used to identify fluid, adipose, muscle and tumor tissue types. T2*w images reconstructed from undersampled data were analyzed to produce maps of Proton Density Fat Fraction (PDFF), Proton Density Water Fraction (PDwF), and the relaxation rates of water ($$$R^*_{2w}$$$) and fat ($$$R^*_{2f}$$$) in each tissue type [1].
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