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一种用于扩散传播算子重建的高效交错多壳采样方案。

An efficient interlaced multi-shell sampling scheme for reconstruction of diffusion propagators.

机构信息

Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL 32611, USA.

出版信息

IEEE Trans Med Imaging. 2012 May;31(5):1043-50. doi: 10.1109/TMI.2012.2184551. Epub 2012 Jan 16.

Abstract

In this paper, we propose an interlaced multi-shell sampling scheme for the reconstruction of the diffusion propagator from diffusion weighted magnetic resonance imaging (DW-MRI). In standard multi-shell sampling schemes, sample points are uniformly distributed on several spherical shells in q-space. The distribution of sample points is the same for all shells, and is determined by the vertices of a selected polyhedron. We propose a more efficient interlaced scheme where sample points are different on alternating shells and are determined by the vertices of a pair of dual polyhedra. Since it samples more directions than the standard scheme, this method offers increased angular discrimination. Another contribution of this work is the application of optimal sampling lattices to q-space data acquisition and the proposal of a model-free reconstruction algorithm, which uses the lattice dependent sinc interpolation function. It is shown that under this reconstruction framework, the body centered cubic (BCC) lattice provides increased accuracy. The sampling scheme and the reconstruction algorithms were evaluated on simulated data as well as rat brain data collected on a 600 MHz (14.1T) Bruker imaging spectrometer.

摘要

在本文中,我们提出了一种用于从扩散加权磁共振成像(DW-MRI)重建扩散传播子的交错多壳采样方案。在标准的多壳采样方案中,采样点在 q 空间中的几个球壳上均匀分布。所有壳层的采样点分布相同,由所选多面体的顶点确定。我们提出了一种更有效的交错方案,其中交替壳层上的采样点不同,由一对对偶多面体的顶点确定。由于它比标准方案采样更多的方向,因此该方法提供了更高的角度分辨力。这项工作的另一个贡献是将最优采样格子应用于 q 空间数据采集,并提出了一种无模型重建算法,该算法使用格子相关的 sinc 插值函数。结果表明,在该重建框架下,体心立方(BCC)格子提供了更高的精度。该采样方案和重建算法在模拟数据以及在 600MHz(14.1T)布鲁克成像光谱仪上采集的大鼠脑数据上进行了评估。

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