A multiscale approach for analyzing in vivo magnetic resonance spectroscopic imaging (SI) data is described in this paper. With this method, fitting is performed at multiple spatial scales in a coarse-to-fine order. Results obtained at one scale are used as prior knowledge in fitting spectra at the next scale. The multiscale approach was validated with simulated data and demonstrated with proton SI datasets of the human brains. The results showed that this method improved the robustness and efficiency of the fitting and facilitated the automatic analysis of in vivo SI data.