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Abstract #1335

Sparse Representations for Compressed Sensing Acceleration of Fourier Velocity Encoded MRI

Gabriel L. S. L. Oliveira1, Joao L. A. Carvalho1

1Department of Electrical Engineering, University of Braslia, Braslia, DF, Brazil

Fourier velocity encoding (FVE) is useful in the assessment of vascular and valvular stenosis and intravascular wall shear stress, as it eliminates partial volume effects that may cause loss of diagnostic information in more conventional phase-contrast MRI. FVE shows great potential for compressed sensing acceleration, due to its high dimensionality and intrinsic sparseness in image domain. In this work, we investigate other sparse representantions for FVE data, using a five-dimensional (x,y,z,v,t) FVE dataset of the neck (focusing on carotid flow). Several combinations of separable transforms were evaluated. Two promising combinations of transforms are proposed.