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Matching Sparse Sets of Cardiac Image Cross-Sections Using Large Deformation Diffeomorphic Metric Mapping Algorithm

机译:使用大变形微变形度量映射算法匹配心脏图像横截面的稀疏集

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The purpose of this study is to illustrate the application of large deformation diffeomorphic metric mapping to perform registration among sparsely sampled cardiac magnetic resonance imaging (MRI) data. To evaluate the performance of this method, we use two sets of data: 1) contours that are generated from sparsely sampled left ventricular sections and extracted from short axis cardiac MRI of patients with hypertrophic cardiomyopathy and 2) left ventricular surface mesh that is generated from higher resolution cardiac computed tomography image. We present two different discrepancy criteria, one based on a measure that is embedded in the dual of a reproducing kernel Hilbert space of functions for curves and the other is based on a geometric soft matching distance between a surface and a curve.
机译:这项研究的目的是说明大变形微晶度量映射在稀疏采样心脏磁共振成像(MRI)数据之间进行配准的应用。为了评估该方法的性能,我们使用了两组数据:1)从肥厚型心肌病患者的稀疏采样的左心室切片生成并从短轴心脏MRI中提取的轮廓,以及2)从更高分辨率的心脏计算机断层扫描图像。我们提出了两种不同的差异标准,一种基于嵌入在曲线函数的再生内核希尔伯特空间对偶中的量度,另一种基于曲面和曲线之间的几何软匹配距离。

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