论文标题

快速图书馆驱动的方法,用于实施体素扩散功能技术,以纠正磁场不均匀性伪像

Fast library-driven approach for implementation of the voxel spread function technique for correcting magnetic field inhomogeneity artifacts

论文作者

Wen, Jie, Zeng, Feiyan, Yablonskiy, Dmitriy, Sukstansky, Alexander, Liu, Ying, Cai, Bin, Zhang, Yong, Lv, Weifu

论文摘要

目的:先前开发的体素扩散功能(VSF)方法(Yablonskiy等,MRM,2013; 70:1283)提供了通过宏观磁场不均匀性引起的伪影的手段,这些图像在由多级级别捕获的eCho(mgre)技术获得的图像中。这项研究的目的是为快速VSF实施开发一种图书馆驱动的方法。方法:VSF方法描述了磁场不均匀性对MGRE信号衰变的贡献,该效果是根据MGRE相和幅度图像计算得出的F功能的。此处使用了由磁场不均匀性引起的各种背景场梯度的预定库来加快F功能的计算,并从两名健康志愿者收集的MGRE数据中生成定量R2*图。结果:与基于Voxel方法的直接计算F功能的直接计算相比,新型图书馆驱动的方法将计算时间从几个小时减少到几分钟,而同时提供了相似的R2*映射精度。结论:本研究中提出的新程序提供了一种快速的后处理算法,可以将其纳入MGRE数据的定量分析中,以说明背景领域的不均匀性工件,因此可以促进基于MGRE的基于MGRE的定量技术在临床实践中的应用。

Purpose: Previously-developed Voxel Spread Function (VSF) method (Yablonskiy, et al, MRM, 2013;70:1283) provides means to correct artifacts induced by macroscopic magnetic field inhomogeneities in the images obtained by multi-Gradient-Recalled-Echo (mGRE) techniques. The goal of this study is to develop a library-driven approach for fast VSF implementation. Methods: The VSF approach describes the contribution of the magnetic field inhomogeneity effects on the mGRE signal decay in terms of the F-function calculated from mGRE phase and magnitude images. A pre-calculated library accounting for a variety of background field gradients caused by magnetic field inhomogeneities was used herein to speed up calculation of the F-function and to generate quantitative R2* maps from the mGRE data collected from two healthy volunteers. Results: As compared with direct calculation of the F-function based on a voxel-wise approach, the new library-driven method substantially reduces computational time from several hours to few minutes, while, at the same time, providing similar accuracy of R2* mapping. Conclusion: The new procedure proposed in this study provides a fast post-processing algorithm that can be incorporated in the quantitative analysis of mGRE data to account for background field inhomogeneity artifacts, thus can facilitate the applications of mGRE-based quantitative techniques in clinical practices.

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