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利用傅里叶域分析对低 SNR 的相位图像进行解包裹。

The use of Fourier-domain analyses for unwrapping phase images of low SNR.

机构信息

Department of Biomedical Engineering, University of Arizona, Tucson, Arizona.

The BIO5 Institute, University of Arizona, Tucson, Arizona.

出版信息

Magn Reson Med. 2019 Jul;82(1):356-366. doi: 10.1002/mrm.27719. Epub 2019 Mar 12.

DOI:10.1002/mrm.27719
PMID:30859614
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6491212/
Abstract

PURPOSE

We report a new postprocessing procedure that uses Fourier-domain data analyses to improve the accuracy and reliability of phase unwrapping for MRI data of low SNR.

METHODS

The developed method first identifies the Fourier-domain energy peak locations corresponding to different image-domain areas from which a robust measurement of image-domain phase gradients can be obtained even for MRI data of low SNR. The phase-gradient information measured from critical brain regions using the above-mentioned Fourier-domain analysis is then combined with the conventional temporal-domain or spatial-domain phase-unwrapping procedure to remove phase wraps. The developed method was tested with MRI data obtained from 30 healthy adult volunteers, and its performance was quantitatively evaluated.

RESULTS

The developed Fourier-domain analysis could robustly quantify image-domain phase gradients even for MRI data with low SNR (e.g., SNR 2). Experimental results show that the Fourier-domain analyses could further reduce phase wrap artifact in data produced by the conventional temporal-domain or spatial-domain phase-unwrapping procedures.

CONCLUSION

Our results demonstrate that the developed phase-unwrapping method can reduce residual phase wraps resulting from conventional procedures in critical brain regions (e.g., near the air-tissue interfaces) and should prove valuable for studies that require accurate measurements of MRI phase values, such as QSM, B field mapping, and temperature mapping.

摘要

目的

我们报告了一种新的后处理程序,该程序使用傅里叶域数据分析来提高低 SNR MRI 数据相位解缠的准确性和可靠性。

方法

该方法首先从傅里叶域中识别出与不同图像域区域相对应的能量峰位置,即使对于低 SNR 的 MRI 数据,也可以从这些区域中获得稳健的图像域相位梯度测量值。然后,使用上述傅里叶域分析从关键脑区测量的相位梯度信息与传统的时域或空域相位解缠过程相结合,以去除相位缠绕。该方法使用从 30 名健康成年志愿者获得的 MRI 数据进行了测试,并对其性能进行了定量评估。

结果

即使对于低 SNR(例如 SNR 2)的 MRI 数据,开发的傅里叶域分析也可以稳健地量化图像域相位梯度。实验结果表明,傅里叶域分析可以进一步减少传统时域或空域相位解缠过程产生的数据中的相位缠绕伪影。

结论

我们的结果表明,所开发的相位解缠方法可以减少关键脑区(例如,在空气-组织界面附近)中常规方法产生的残余相位缠绕,对于需要准确测量 MRI 相位值的研究(例如,QSM、B 场映射和温度映射)应该非常有价值。

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一种在超高场下对高度包裹的多回波相位图像进行解包裹的方法:UMPIRE。
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