Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA.
IEEE Trans Biomed Eng. 2010 Jun;57(6):1437-45. doi: 10.1109/TBME.2009.2038229. Epub 2010 Feb 17.
This paper presents a new method for improved flow analysis and quantification using MRI. The method incorporates fluid dynamics to regularize the flow quantification from tagged MR images. Specifically, the flow quantification is formulated as a minimization problem based on the following: 1) the Navier-Stokes equation governing the fluid dynamics; 2) the flow continuity equation and boundary conditions; and 3) the data consistency constraint. The minimization is carried out using a genetic algorithm. This method is tested using both computer simulations and MR flow experiments. The results are evaluated using flow vector fields from the computational fluid dynamics software package as a reference, which show that the new method can achieve more realistic and accurate flow quantifications than the conventional method.
本文提出了一种使用 MRI 进行改进的流动分析和量化的新方法。该方法将流体动力学纳入到标记磁共振图像的流量量化中进行正则化。具体来说，流量量化被公式化为基于以下内容的最小化问题：1）控制流体动力学的纳维-斯托克斯方程；2）流量连续方程和边界条件；3）数据一致性约束。最小化是使用遗传算法进行的。该方法使用计算机模拟和磁共振流动实验进行了测试。结果使用计算流体动力学软件包的流矢量场作为参考进行评估，结果表明新方法可以比传统方法实现更真实和准确的流量量化。
