Echocardiographic particle imaging velocimetry data assimilation with least square finite element methods

被引:5
|
作者
Rajaraman, Prathish K. [1 ]
Manteuffel, T. A. [2 ]
Belohlavek, M. [3 ]
McMahon, E. [3 ]
Heys, Jeffrey J. [1 ]
机构
[1] Montana State Univ, Dept Chem & Biol Engn, Bozeman, MT 59717 USA
[2] Univ Colorado, Dept Appl Math, Boulder, CO 80309 USA
[3] Mayo Clin Arizona, Scottsdale, AZ 85259 USA
基金
美国国家科学基金会;
关键词
Least-square; Finite element; Data assimilation; Particle imaging velocimetry; NAVIER-STOKES EQUATIONS; FLOW; REFINEMENT; SIMULATION; SCIENCE; SCHEME; FOSLS;
D O I
10.1016/j.camwa.2014.07.026
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Recent developments in the field of echocardiography have introduced various noninvasive methods to image blood flow within the heart chambers. FDA-approved microbubbles can be used for intracardiac blood flow imaging and determining the velocity of the blood based on the displacement of the bubbles and the frame rate of the ultrasound scan. A limitation of this approach is that the velocity field information is only two-dimensional and inevitably contains noise. A weighted least square finite element method (WLSFEM) was developed to assimilate noisy, two-dimensional data from echocardiographic particle imaging velocimetry (echo-Ply) into a three-dimensional Navier Stokes numerical model so that additional flow properties such as the stress and pressure gradient can be determined from the full velocity and pressure fields. The flexibility of the WLSFEM framework allows for matching the noisy echo-P1V data weakly and using the weighted least square functional as an indicator of how well the echo-Ply data are satisfying the numerical model. Results from the current framework demonstrate the ability of the approach to more closely match the more accurate echo-PIV data and less closely match the noisy data. The positive impact of assimilating the echo-Ply data is demonstrated: compared to a conventional computational fluid dynamic approach, echo-Ply data assimilation potentially enables a more accurate flow model. (C) 2014 Elsevier Ltd, All rights reserved.
引用
收藏
页码:1569 / 1580
页数:12
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