A novel quantitative framework for detection of different tissue compartments based on bSSFP signal profile asymmetries (SPARCQ) is reported. SPARCQ uses a dictionary-based weight optimization algorithm to estimate voxel-wise off-resonance frequency and relaxation time ratio spectra from acquired bSSFP signal profiles. From the obtained spectra, quantitative parameters (i.e. fractions of the components of interest, thermal equilibrium magnetization) can be extracted. Validation and proof-of-concept are provided for voxel-wise water-fat separation and fat fraction mapping. Accuracy and repeatability of SPARCQ are demonstrated with phantom and in vivo experiments.