Temporally diffeomorphic cardiac motion estimation from three-dimensional echocardiography by minimization of intensity consistency error.
Temporally diffeomorphic cardiac motion estimation from three-dimensional echocardiography by minimization of intensity consistency error.
复制标题
通过强度一致性误差最小化从三维超声心动图进行时间微分同态心脏运动估计。
DOI：
10.1118/1.4867864
复制
发表时间：
2014
期刊：
影响因子：
3.8
通讯作者：
Song,Xubo
中科院分区：
文献类型：
--
作者：
Zhang,Zhijun;Ashraf,Muhammad;Sahn,DavidJ;Song,Xubo
目的：定量分析心脏运动对评价心功能有重要意义。三维（3D）超声心动图是运动估计中最常用的成像方式之一，因为它方便、真实的、低成本和非电离。然而，从三维超声心动图序列的运动估计仍然是一个具有挑战性的问题，由于低图像质量和图像腐败的噪声和artifacts.Methods：作者已经开发了一种时间上的运动估计方法，其中速度场，而不是位移场进行了优化。最优速度场优化了一个新的相似性函数，我们称之为强度一致性误差，定义为多个连续帧演变到每个时间点。结果：采用模拟数据集、活体兔体模图像、活体开胸猪心图像和健康人体图像进行实验，验证了本文方法的有效性。模拟和真实的心脏序列测试表明，作者的方法比其他竞争的时间同态方法的结果更准确。声显微测量的测试表明，跟踪的晶体位置与地面实况有很好的一致性，作者的方法比时间双态自由变形（TDFFD）方法具有更高的精度。利用开放获取的人类心脏数据集进行验证表明，作者的方法比TDFFD和帧到帧方法具有更小的特征跟踪误差。结论：作者提出了一种通过约束速度场在多个连续帧内具有最大局部强度一致性来实现时间平滑的同构运动估计方法。该方法估计的运动具有良好的时间一致性，比其他时间同构运动估计方法更精确。
Purpose:Quantitative analysis of cardiac motion is important for evaluation of heart function. Three dimensional (3D) echocardiography is among the most frequently used imaging modalities for motion estimation because it is convenient, real‐time, low‐cost, and nonionizing. However, motion estimation from 3D echocardiographic sequences is still a challenging problem due to low image quality and image corruption by noise and artifacts.Methods:The authors have developed a temporally diffeomorphic motion estimation approach in which the velocity field instead of the displacement field was optimized. The optimal velocity field optimizes a novel similarity function, which we call the intensity consistency error, defined as multiple consecutive frames evolving to each time point. The optimization problem is solved by using the steepest descent method.Results:Experiments with simulated datasets, images of anex vivorabbit phantom, images ofin vivoopen‐chest pig hearts, and healthy human images were used to validate the authors’ method. Simulated and real cardiac sequences tests showed that results in the authors’ method are more accurate than other competing temporal diffeomorphic methods. Tests with sonomicrometry showed that the tracked crystal positions have good agreement with ground truth and the authors’ method has higher accuracy than the temporal diffeomorphic free‐form deformation (TDFFD) method. Validation with an open‐access human cardiac dataset showed that the authors’ method has smaller feature tracking errors than both TDFFD and frame‐to‐frame methods.Conclusions:The authors proposed a diffeomorphic motion estimation method with temporal smoothness by constraining the velocity field to have maximum local intensity consistency within multiple consecutive frames. The estimated motion using the authors’ method has good temporal consistency and is more accurate than other temporally diffeomorphic motion estimation methods.