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Pressure mapping from flow imaging: Enhancing computation of the viscous term through velocity reconstruction in near-wall regions

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

Original languageEnglish
Title of host publication36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2014)
Number of pages4
ISBN (Print)9781424479276
PublishedAug 2014

King's Authors


Although being small compared to inertial acceleration, viscous component of the pressure gradient has recently emerged as a potential biomarker for aortic disease conditions including aortic valve stenosis. However, as it involves the computation of second order derivatives and viscous dissipation is locally higher in the near-wall region of the larger vessels, where the lowest local signal-to-noise ratios are encountered, the estimation process from medical image velocity data through mathematical models is highly challenging. We propose a fully automatic framework to recover the laminar viscous pressure gradient through reconstruction of the velocity vector field in the aortic boundary region. An in-silico study is conducted and the pressure drop is computed solving a Poisson problem on pressure using both a reconstructed and non-reconstructed velocity profile near the vessel walls, showing a global improvement of performance with the enhanced method.

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