Robust Reconstruction of MRSI Data Using a Sparse Spectral Model and High Resolution MRI Priors

We introduce a novel algorithm to address the challenges in magnetic resonance (MR) spectroscopic imaging. In contrast to classical sequential data processing schemes, the proposed method combines the reconstruction and post processing steps into a unified algorithm. This integrated approach enables us to inject a range of prior information into the data processing scheme, thus constraining the reconstructions. We use high resolution, 3-D estimate of the magnetic field inhomogeneity map to generate an accurate forward model, while a high resolution estimate of the fat/water boundary is used to minimize spectral leakage artifacts. We parameterize the spectrum at each voxel as a sparse linear combination of spikes and polynomials to capture the metabolite and baseline components, respectively. The constrained model makes the problem better conditioned in regions with significant field inhomogeneity, thus enabling the recovery even in regions with high field map variations. To exploit the...

• Type: Journal
• Year: 2010
• Where: TMI
• Authors: Ramin Eslami, Mathews Jacob
• Keywords: Data Processing Scheme, Field Inhomogeneity, Leakage Artifacts, Management, TMI 2010