Key Laboratory of Metallurgical Equipment and Control Technology, Ministry of Education, Wuhan University of Science and Technology, Wuhan, China; Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan, China.
School of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan, China.
Comput Methods Programs Biomed. 2022 Apr;216:106678. doi: 10.1016/j.cmpb.2022.106678. Epub 2022 Feb 2.
To present and validate a method for automated identification of the Lagrangian vortices and Eulerian vortices for analyzing flow within the right atrium (RA), from phase contrast magnetic resonance imaging (PC-MRI) data.
Our proposed algorithm characterizes the trajectory integral associated with vorticity deviation and the spatial mean of vortex rings, for the Lagrangian averaged vorticity deviation (LAVD) based identification and tracking of vortex rings within the heart chamber. For this purpose, the optical flow concept was adopted to interpolate the time frames between larger discrete frames, to minimize the error caused by constructing a continuous velocity field for the integral process of LAVD. Then the Hough transform was used to automatically extract the vortex regions of interest. The computed flow data within the RA of the participants' hearts was then used to validate the performance of our proposed method.
In the paper, illustrations are provided for derived evolution of Euler vortices and Lagrangian vortices of a healthy subject. The visualization results have shown that our proposed method can accurately identify the Euler vortices and Lagrangian vortices, in the context of measuring the vorticity and vortex volume of the vortices within the RA chamber. Then the employment of Hough transform-based automated vortex extraction has improved the robustness and scalability of the LAVD in identifying cardiac vortices. The analytical results have demonstrated that the introduction of the Horn-Schunck optical flow can more accurately synthesize the intermediate PC-MRI to construct a continuous velocity field, compared with other interpolation methods.
A novel analytical framework has been developed to accurately identify the flow vortices in the RA chamber based on Horn-Schunck optical flow and Hough transform. From the obtained analytical study results, the development and changes of dominant vortices within this cardiac chamber during the cardiac cycle can be acquired. This can provide to cardiologists a deeper understanding of the hemodynamics within the heart chambers.
提出并验证一种从对比磁共振成像（PC-MRI）数据中自动识别右心房（RA）内拉格朗日涡旋和欧拉涡旋的方法。
我们提出的算法基于轨迹积分特征，描述与涡度偏差和涡环空间平均值相关的特征，用于基于拉格朗日平均涡度偏差（LAVD）的识别和跟踪心脏室内的涡环。为此，采用光流概念对较大离散帧之间的时间帧进行插值，以最小化在 LAVD 积分过程中构建连续速度场引起的误差。然后使用霍夫变换自动提取感兴趣的涡旋区域。然后使用参与者心脏 RA 内计算出的血流数据来验证我们提出的方法的性能。
本文提供了健康受试者衍生的欧拉涡旋和拉格朗日涡旋演变的说明。可视化结果表明，我们提出的方法可以准确识别 RA 腔内心脏涡旋的欧拉涡旋和拉格朗日涡旋，同时测量 RA 腔内心脏涡旋的涡度和涡旋体积。然后，基于 Hough 变换的自动涡旋提取的应用提高了 LAVD 识别心脏涡旋的鲁棒性和可扩展性。分析结果表明，与其他插值方法相比，Horn-Schunck 光流的引入可以更准确地合成中间 PC-MRI 来构建连续速度场。
开发了一种新的分析框架，基于 Horn-Schunck 光流和 Hough 变换准确识别 RA 腔内心脏流涡旋。从获得的分析研究结果中，可以获得此心脏腔内心脏周期内主导涡旋的发展和变化。这可以为心脏病专家提供对心脏腔内心动血流动力学的更深入理解。
