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首页> 外文期刊>IEEE Transactions on Medical Imaging >4D Flow MRI Pressure Estimation Using Velocity Measurement-Error-Based Weighted Least-Squares
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4D Flow MRI Pressure Estimation Using Velocity Measurement-Error-Based Weighted Least-Squares

机译:4D流动MRI压力估计使用速度测量误差的加权最小二乘

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This work introduces a 4D flow magnetic resonance imaging (MRI) pressure reconstruction method which employs weighted least-squares (WLS) for pressure integration. Pressure gradients are calculated from the velocity fields, and velocity errors are estimated from the velocity divergence for incompressible flow. Pressure gradient errors are estimated by propagating the velocity errors through Navier-Stokes momentum equation. A weight matrix is generated based on the pressure gradient errors, then employed for pressure reconstruction. The pressure reconstruction method was demonstrated and analyzed using synthetic velocity fields as well as Poiseuille flow measured using in vitro 4D flow MRI. Performance of the proposed WLS method was compared to the method of solving the pressure Poisson equation which has been the primary method used in the previous studies. Error analysis indicated that the proposed method is more robust to velocity measurement errors. Improvement on pressure results was found to be more significant for the cases with spatially-varying velocity error level, with reductions in error ranging from 50% to over 200%. Finally, the method was applied to flow in patient-specific cerebral aneurysms. Validation was performed with in vitro flow data collected using Particle Tracking Velocimetry (PTV) and in vivo flow measurement obtained using 4D flow MRI. Pressure calculated by WLS, as opposed to the Poisson equation, was more consistent with the flow structures and showed better agreement between the in vivo and in vitro data. These results suggest the utility of WLS method to obtain reliable pressure field from clinical flow measurement data.
机译:该工作引入了4D流动磁共振成像(MRI)压力重建方法,其采用加权最小二乘(WLS)进行压力集成。从速度场计算压力梯度,并且速度误差估计从不可压缩流的速度分歧。通过通过Navier-Stokes动量方程传播速度误差来估计压力梯度误差。基于压力梯度误差产生权重矩阵,然后用于压力重建。使用合成速度场以及使用体外4D流动MRI测量的Poiseuille流程来证明和分析压力重建方法。将所提出的WLS方法的性能与求解前一项研究中使用的主要方法的压力泊松方程的方法进行了比较。误差分析表明,该方法对速度测量误差更鲁棒。对具有空间不同速度误差水平的情况的情况下发现对压力结果的改进,误差减少了50%至超过200%。最后,将该方法应用于特异性脑动脉瘤的流动。使用使用颗粒跟踪速度(PTV)和使用4D流动MRI获得的体内流动测量来进行验证。由WLS计算的压力与泊松方程相反,与流动结构更加一致,并且在体内和体外数据之间显示出更好的一致性。这些结果表明WLS方法从临床流量测量数据获得可靠的压力场的效用。

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