Abstract
To quickly and robustly separate fat/water components of 7T MR images in the presence of field inhomogeneity for the study of metabolic disorders in small animals. Starting with a Markov random field (MRF) based formulation for the 3-point Dixon separation problem, we incorporated new implementation strategies, including stability tracking, multiresolution image pyramid, and improved initial value generation. We term the new method FLAWLESS (Fast Lipid And Water Levels by Extraction with Spatial Smoothing). Compared with non-MRF techniques, FLAWLESS decreased the fat-water swapping mistakes in all of the three-dimensional (3D) animal volumes that we tested. FLAWLESS converged in approximately 1/60th of the computation time of other MRF approaches. The initial value generation of FLAWLESS further improved robustness to field inhomogeneity in 3D volume data. We have developed a novel 3-point Dixon technique found to be useful for high field small animal imaging. It is being used to assess lipid depots and metabolic disorders as a function of genes, diet, age, and therapy.
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