An inverse problem for reduced-encoding MRI velocimetry in potential flowAn inverse problem for reduced-encoding MRI velocimetry in potential flow Πλήρης Δημοσίευση σε Συνέδριο Conference Full Paper 2015-10-172004enWe propose a computational technique to reconstruct internal physiological flows described by sparse point-wise MRI velocity measurements. Assuming that the viscous forces in the flow are negligible, the incompressible flow field can be obtained from a velocity potential that satisfies Laplace's equation. A set of basis functions each satisfying Laplace's equation with appropriately defined boundary data is constructed using the finite-element method. An inverse problem is formulated where higher resolution boundary and internal velocity data are extracted from the point-wise MRI velocity measurements using a least-squares method. From the results we obtained with ∼100 internal measurement points, the proposed reconstruction method is shown to be effective in filtering out the experimental noise at levels as high as 30%, while matching the reference solution within 2%. This allows the reconstruction of a high-resolution velocity field with limited MRI encoding. http://creativecommons.org/licenses/by/4.0/1100-110326th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Rovas Dimitrios Ροβας Δημητριος Raguin L. Guy Georgiadis, John, 1938- Kodali Anil Institute of Electrical and Electronics Engineers Inverse problems MRI Magnetic resonance imaging Velocity measurement Laplace equations Finite element methods Data mining Noise measurement Reconstruction algorithms Matched filters Filtering