Time-domain model function fitting techniques were applied to improve the reconstruction of metabolite maps from the data sets obtained from in vivo 1H spectroscopic imaging (SI) experiments. First, residual water-related signals were removed from the SI data sets by using SVD-based linear time-domain fitting based upon the HSVD (State Space) approach. Second, peak integrals of the metabolites of interest were obtained by quantifying the proton spin-echoes of the voxels by means of non-linear time-domain fitting based upon the maximum likelihood principle. Third, in order to save computational time, interpolation of the metabolite images (from size 32 x 32 to 128 x 128) was performed in the image-domain by applying one-dimensional cubic splines. It was found that the residual water signals can be almost completely removed from the SI data sets by applying the linear HSVD fitting method. Furthermore, it was found that voxel dependency of certain NMR parameters (e.g., variations of the spin-echo offset frequencies and/or phase factors) can be accounted for automatically by applying the nonlinear time-domain fitting technique. For that purpose it appeared to be essential to employ prior knowledge of the NMR spectral parameters.