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Reliability Testing of in vivo H-MRS-signals and Elimination of Signal Artifacts by Median Filtering

机译:体内H-MRS信号的可靠性测试和中值过滤消除信号伪影

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In order to make SV-MRS clinically viable, assessment of spectral quality and reliability of the data should preferably be handled by the MR-scanner system rather than by medical staff. The reliability of the data is most affected by patient motion during acquisition. In this paper, we devise, apply, and test two statistical methods that can be used for automated data reliability- and quality-assessment. Next, we establish that, in order to assess the reliability of SV-MR-data, it is essential to store the data of each acquisition separately, rather than averaging the data of all acquisitions irreversibly prior to storage. We propose a) statistical tests on these separately stored acquisitions that can reveal artifacts, b) application of a special type of order-statistics filtering, namely median filtering, once artifacts have been detected. Furthermore, we develop computer algorithms that provide automated, fully user-independent information on spectral quality and reliability of the acquired spectra. Finally, we conclude that combination of statistical tests with median filtering can provide user-free quality and reliability assessment and improvement of SV-MR-spectra.
机译:为了使SV-MRS临床上可行,可以优选地由MR-Scanner系统而不是医务人员来处理数据的谱质量和可靠性的评估。在采集期间,数据的可靠性受到患者运动的影响最大。在本文中,我们设计,应用和测试了两个可用于自动数据可靠性和质量评估的统计方法。接下来,我们确定,为了评估SV-MR-DATA的可靠性,必须分别存储每个获取的数据,而不是在存储之前不可逆转地平均所有采集的数据。我们提出了关于这些单独存储的采集的统计测试,该获取可以揭示文物,b)一种特殊类型的秩序统计滤波的应用,即中值滤波,一旦已经检测到伪像。此外,我们开发计算机算法,其提供有关所获取的光谱质量和可靠性的自动化,完全用户独立的信息。最后,我们得出结论,具有中值滤波的统计测试的组合可以提供无用户的质量和可靠性评估和SV-MR光谱的改进。

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