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基于双线性模型和运动补偿的标记 MRI 序列中分析信号相位的心肌运动估计。

Analytic signal phase-based myocardial motion estimation in tagged MRI sequences by a bilinear model and motion compensation.

机构信息

Université de Lyon, CREATIS; CNRS UMR 5220; Inserm U1044; INSA-Lyon; Université Lyon 1. Bât. Blaise Pascal, 7 avenue Jean Capelle, Villeurbanne F-69621, France.

Université de Toulouse, IRIT; CNRS UMR 5505; 118 Route de Narbonne, F-31062 Toulouse cedex 9, France.

出版信息

Med Image Anal. 2015 Aug;24(1):149-162. doi: 10.1016/j.media.2015.06.005. Epub 2015 Jun 24.

Abstract

Different mathematical tools, such as multidimensional analytic signals, allow for the calculation of 2D spatial phases of real-value images. The motion estimation method proposed in this paper is based on two spatial phases of the 2D analytic signal applied to cardiac sequences. By combining the information of these phases issued from analytic signals of two successive frames, we propose an analytical estimator for 2D local displacements. To improve the accuracy of the motion estimation, a local bilinear deformation model is used within an iterative estimation scheme. The main advantages of our method are: (1) The phase-based method allows the displacement to be estimated with subpixel accuracy and is robust to image intensity variation in time; (2) Preliminary filtering is not required due to the bilinear model. The proposed algorithm, integrating phase-based optical flow motion estimation and the combination of global motion compensation with local bilinear transform, allows spatio-temporal cardiac motion analysis, e.g. strain and dense trajectory estimation over the cardiac cycle. Results from 7 realistic simulated tagged magnetic resonance imaging (MRI) sequences show that our method is more accurate compared with state-of-the-art method for cardiac motion analysis and with another differential approach from the literature. The motion estimation errors (end point error) of the proposed method are reduced by about 33% compared with that of the two methods. In our work, the frame-to-frame displacements are further accumulated in time, to allow for the calculation of myocardial Lagrangian cardiac strains and point trajectories. Indeed, from the estimated trajectories in time on 11 in vivo data sets (9 patients and 2 healthy volunteers), the shape of myocardial point trajectories belonging to pathological regions are clearly reduced in magnitude compared with the ones from normal regions. Myocardial point trajectories, estimated from our phase-based analytic signal approach, seem therefore a good indicator of the local cardiac dynamics. Moreover, they are shown to be coherent with the estimated deformation of the myocardium.

摘要

不同的数学工具,如多维解析信号,可以计算实值图像的 2D 空间相位。本文提出的运动估计方法基于应用于心脏序列的二维解析信号的两个空间相位。通过结合来自两个连续帧的解析信号的相位信息,我们提出了一种用于二维局部位移的解析估计器。为了提高运动估计的准确性,在迭代估计方案中使用了局部双线性变形模型。我们的方法的主要优点是:(1)基于相位的方法允许以亚像素精度估计位移,并且对时间内的图像强度变化具有鲁棒性;(2)由于双线性模型,不需要进行初步滤波。所提出的算法集成了基于相位的光流运动估计和全局运动补偿与局部双线性变换的组合,允许进行时空心脏运动分析,例如在心脏周期上进行应变和密集轨迹估计。来自 7 个真实模拟标记磁共振成像 (MRI) 序列的结果表明,与心脏运动分析的最先进方法相比,与文献中的另一种差分方法相比,我们的方法更准确。与两种方法相比,所提出的方法的运动估计误差(端点误差)降低了约 33%。在我们的工作中,帧到帧的位移进一步在时间上积累,以允许计算心肌拉格朗日心脏应变和点轨迹。实际上,从 11 个体内数据集(9 名患者和 2 名健康志愿者)上随时间估计的轨迹,属于病理区域的心肌点轨迹的形状与正常区域的轨迹相比明显减小。从我们基于相位的解析信号方法估计的心肌点轨迹,因此似乎是局部心脏动力学的良好指标。此外,它们被证明与心肌的估计变形一致。

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