Jeffrey Adam Kasten1, 2, Franois Lazeyras2, Dimitri Van de Ville1, 2
1Institute of Bioengineering, Ecole Polytechnique Fdrale de Lausanne, Lausanne, VD, Switzerland; 2Department of Radiology and Medical Informatics, Universit de Genve, Geneva, GE, Switzerland
Model-based MRSI reconstruction often relies upon structural MR images to characterize the sample by specifying spectrally-homogenous compartments. However, either spatio-spectral disparities between the two modalities or model mismatch will lead to additional artifacts. We therefore consider a more data-driven approach in which the raw MRSI data itself is used to estimate the generating signal model, employing a general framework predicated on principal component analysis and spatial regularization. Phantom experiments show that our method can yield highly resolved spatial and spectral components, while simultaneously surmounting a number of limitations associated with traditional Fourier reconstruction.