首页> 外文会议>International Workshop on Functional Imaging and Modeling of the Heart(FIMH 2007); 20070607-09; Salt Lake City,UT(US) >Automated Tag Tracking Using Gabor Filter Bank, Robust Point Matching, and Deformable Models
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Automated Tag Tracking Using Gabor Filter Bank, Robust Point Matching, and Deformable Models

机译:使用Gabor滤波器组,鲁棒点匹配和可变形模型进行自动标签跟踪

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Tagged Magnetic Resonance Imaging (tagged MRI or tMRI) provides a means of directly and noninvasively displaying the motion of the myocardium. Reconstruction of the motion field is needed for quantitative analysis of important clinical information, e.g., the myocardial strain. In this paper, we present a two-step method for this task. First, we use a Gabor filter bank to generate a corresponding phase map of tMRI images. Second, deformable models are initialized at the discontinuities in the wrapped phase map, and are deformed under the influence of the image gradient to track the motion of tags. Unlike previous approaches, a Robust Point Matching (RPM) module has been integrated into the model evolution to avoid false tracking results caused by 1) through-plane motion, and 2) small tag spacing. The method has been tested on a numeric phantom, as well as in vivo heart data. The experimental results show that the new method has a good performance on both synthetic and real data, and has the potential to be used in clinical applications.
机译:标记磁共振成像(标记MRI或tMRI)提供了一种直接且无创地显示心肌运动的方法。需要对运动场进行重建,以对重要的临床信息(例如心肌张力)进行定量分析。在本文中,我们针对此任务提出了一种两步方法。首先,我们使用Gabor滤波器组来生成tMRI图像的相应相位图。其次,可变形模型在包裹的相位图中的不连续点处初始化,并在图像梯度的影响下变形以跟踪标签的运动。与以前的方法不同,稳健点匹配(RPM)模块已集成到模型演化中,以避免1)平面运动和2)小标签间距引起的错误跟踪结果。该方法已经在数字体模以及体内心脏数据上进行了测试。实验结果表明,该新方法在合成数据和真实数据上均具有良好的性能,具有在临床应用中的潜力。

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