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A Comprehensive Cardiac Motion Estimation Framework Using Both Untagged and 3-D Tagged MR Images Based on Nonrigid Registration

机译:基于非刚性配准的使用未标记和3D标记MR图像的综合心脏运动估计框架

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摘要

In this paper, we present a novel technique based on nonrigid image registration for myocardial motion estimation using both untagged and 3-D tagged MR images. The novel aspect of our technique is its simultaneous usage of complementary information from both untagged and 3-D tagged MR images. To estimate the motion within the myocardium, we register a sequence of tagged and untagged MR images during the cardiac cycle to a set of reference tagged and untagged MR images at end-diastole. The similarity measure is spatially weighted to maximize the utility of information from both images. In addition, the proposed approach integrates a valve plane tracker and adaptive incompressibility into the framework. We have evaluated the proposed approach on 12 subjects. Our results show a clear improvement in terms of accuracy compared to approaches that use either 3-D tagged or untagged MR image information alone. The relative error compared to manually tracked landmarks is less than 15% throughout the cardiac cycle. Finally, we demonstrate the automatic analysis of cardiac function from the myocardial deformation fields.
机译:在本文中,我们提出了一种基于非刚性图像配准的新颖技术,该技术使用未标记的和3-D标记的MR图像进行心肌运动估计。我们技术的新颖之处在于它同时使用了未标记和3D标记MR图像中的补充信息。为了估计心肌内的运动,我们将心脏周期中一系列标记和未标记的MR图像配准至舒张末期一组参考标记和未标记的MR图像。在空间上对相似性度量进行加权,以最大程度地利用两个图像中的信息。另外,所提出的方法将阀平面跟踪器和自适应不可压缩性集成到框架中。我们已经对12个主题评估了建议的方法。与仅使用3-D标签或未标签MR图像信息的方法相比,我们的结果显示出在准确性方面的明显改善。在整个心动周期中,与手动跟踪的路标相比,相对误差小于15%。最后,我们展示了心肌变形场对心功能的自动分析。

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