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Spatial normalization of cardiac Diffusion Tensor Imaging for modeling the muscular structure of the myocardium

机译:心脏扩散张量成像的空间归一化,用于建模心肌的肌肉结构

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To build a model of the myocardium, a first step is the spatial normalization of data to a reference framework. Diffusion Tensor Imaging (DTI) provides information about tissue orientation, that is, fiber structures. Therefore, proper registration algorithms must be defined to deal with this image modality. In this paper, we propose a registration framework for cardiac DTI that takes into account the special features of DTI when applied to visualization of the myocardium. We propose a similarity measure adapted to the tensorial nature of the images, as well as an appropriate framework for averaging the DTI data sets. Results shown the advantages of the proposed methodology over other related approaches.
机译:要建立心肌模型,第一步是将数据相对于参考框架进行空间归一化。扩散张量成像(DTI)提供有关组织方向(即纤维结构)的信息。因此,必须定义适当的配准算法来处理该图像模态。在本文中,我们提出了心脏DTI的注册框架,该框架考虑了DTI在应用于心肌可视化时的特殊功能。我们提出了一种适合于图像张量性质的相似性度量,以及一种用于平均DTI数据集的适当框架。结果表明,与其他相关方法相比,该方法具有优势。

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