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On the Choice of Coil Combination Weights for Phase-Sensitive GRAPPA Reconstruction in Multichannel SWI

机译:关于多通道SWI中相敏法重建的线圈组合权重的选择

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The feasibility of applying Generalized Auto-calibrating Partially Parallel Acquisition (GRAPPA) techniques has been established, with a two-fold or more reduction in scan time without compromising vascular contrast in Susceptibility Weighted Imaging (SWI) by choosing an optimal sensitivity map for combining the coil images. The overall SNR performance in GRAPPA is also dependent on the weights used for combining the GRAPPA reconstructed coil images. In this article, different methods for estimating the optimal coil combination weights are qualitatively and quantitatively analysed for maximizing the structural information in the tissue phase. The performance of various methods is visually evaluated using minimum Intensity Projection (mIP), Among the three methods, sensitivity estimated using the dominant eigenvector mentioned as ESPIRiT-based sensitivity in this article shows superior performance over the other two methods including estimating the sensitivity from the centre k-space line and from reconstructed channel images. Combining channel images using ESPIRiT sensitivity shows its ability to preserve the local phase variation and reduction in noise amplification.
机译:已经建立了应用广义自动校准部分平行采集(GRAPPA)技术的可行性,通过选择用于组合的最佳敏感性图,在不损害易感性加权成像(SWI)中的扫描时间的两倍或更多的扫描时间。卷图像。 Grappa中的整体SNR性能也取决于用于组合Grappa重建圈图像的权重。在本文中,定性地分析了用于估计最佳线圈组合权重的不同方法,以最大化组织阶段中的结构信息。各种方法的性能,使用最小强度投影(MIP),在这三种方法中目视评价,灵敏度使用在本文中显示出优异的性能比其它两种方法包括估计从所述灵敏度提及作为基于ESPIRIT灵敏度的主要特征向量估计中心k空间线和重建的频道图像。使用espirit敏感性的相互组合频道图像显示其保留局部相位变化和降低噪声放大的能力。

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