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Determining the Navier slip parameter in the descending aorta using 4D PC-MRI data

Publication at Faculty of Mathematics and Physics |
2022

Abstract

We investigate a computational model which is able to use variational data assimilation to reconstruct blood flow in patient-specific geometries from 4D PC-MRI images. The model uses the Navier slip boundary condition, which is able fit the MRI data more accurately.

One of the goals of the study is to develop a computational tool that could estimate the slip parameter on the aortic wall from the real patient MRI data.