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A non-rigid registration approach for quantifying myocardial contraction in tagged MRI using generalized information measures.

机译:一种非严格的配准方法,用于使用广义信息量度来量化标记MRI中的心肌收缩。

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摘要

We address the problem of quantitatively assessing myocardial function from tagged MRI sequences. We develop a two-step method comprising (i) a motion estimation step using a novel variational non-rigid registration technique based on generalized information measures, and (ii) a measurement step, yielding local and segmental deformation parameters over the whole myocardium. Experiments on healthy and pathological data demonstrate that this method delivers, within a reasonable computation time and in a fully unsupervised way, reliable measurements for normal subjects and quantitative pathology-specific information. Beyond cardiac MRI, this work redefines the foundations of variational non-rigid registration for information-theoretic similarity criteria with potential interest in multimodal medical imaging.
机译:我们解决了从标记的MRI序列定量评估心肌功能的问题。我们开发了一种两步方法,其中包括(i)使用基于广义信息量度的新型变分非刚性配准技术的运动估计步骤,以及(ii)测量步骤,在整个心肌上产生局部和分段变形参数。对健康和病理数据的实验表明,该方法可在合理的计算时间内且以完全不受监督的方式提供对正常受试者的可靠测量结果和定量病理特定信息。除了心脏MRI之外,这项工作还为信息理论相似性标准重新定义了变分非刚性配准的基础,对多模式医学成像具有潜在的兴趣。

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