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Reconstruction of Scattered Data in Fetal Diffusion MRI

机译:胎儿扩散MRI中分散数据的重建

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In this paper we present a method for reconstructing D-MRI data on regular grids from sparse data without assuming specific diffusion models. This is particularly important when studying the fetal brain in utero, since registration methods applied for movement and distortion correction produce scattered data in spatial and angular (gradient) domains. We propose the use of a groupwise registration method, and a dual spatio-angular interpolation by using radial basis functions (RBF). Experiments performed on adult data showed a high accuracy of the method when estimating diffusion images in unavailable directions. The application to fetal data showed an improvement in the quality of the sequences according to criteria based on fractional anisotropy (FA) maps, and differences in the tractography results.
机译:在本文中,我们提出了一种在不假设特定扩散模型的情况下,根据稀疏数据在规则网格上重建D-MRI数据的方法。当在子宫内研究胎儿大脑时,这一点尤其重要,因为应用于运动和畸变校正的配准方法会在空间和角度(梯度)域中产生分散的数据。我们建议使用逐组配准方法,并通过使用径向基函数(RBF)进行双时空角度插值。对成人数据进行的实验表明,当估计沿不可用方向的扩散图像时,该方法具有很高的准确性。胎儿数据的应用显示,根据基于分数各向异性(FA)图的标准以及序列学结果的差异,序列质量得到了改善。

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