Danish Research Centre for Magnetic Resonance, Hvidovre, Denmark.
Magn Reson Med. 2009 Nov;62(5):1147-54. doi: 10.1002/mrm.22129.
For single-voxel spectroscopy, the acquisition of the spectrum is typically repeated n times and then combined with a factor sqrt[n] in order to improve the signal-to-noise ratio. In practice, the acquisitions are not only affected by random noise but also by physiologic motion and subject movements. Since the influence of physiologic motion such as cardiac and respiratory motion on the data is limited, it can be compensated for without data loss. Individual acquisitions hampered by subject movements, on the other hand, need to be rejected if no correction or compensation is possible. If the individual acquisitions are stored, it is possible to identify and reject the motion-disturbed acquisitions before averaging. Several automatic algorithms were investigated using a dataset of spectra from nonanesthetized infants with a gestational age of 40 weeks. Median filtering removed most subject movement artifacts, but at the cost of increased sensitivity to random noise. Neither independent component analysis nor outlier identification with multiple comparisons has this problem. These two algorithms are novel in this context. The peak height values of the metabolites were increased compared to the mean of all acquisitions for both methods, although primarily for the ICA method.
对于单体光谱学，光谱的采集通常重复 n 次，然后与因子 sqrt[n] 组合，以提高信噪比。实际上，采集不仅受到随机噪声的影响，还受到生理运动和受试者运动的影响。由于像心脏和呼吸运动这样的生理运动对数据的影响是有限的，因此可以在不丢失数据的情况下进行补偿。另一方面，如果没有校正或补偿的可能性，则需要拒绝因受试者运动而受到干扰的个别采集。如果存储了个别采集，则可以在平均之前识别和拒绝受运动干扰的采集。使用来自胎龄为 40 周的非麻醉婴儿的光谱数据集研究了几种自动算法。中值滤波去除了大多数受试者运动伪影，但代价是增加了对随机噪声的敏感性。独立成分分析和多次比较的异常值识别都没有这个问题。这两种算法在这种情况下是新颖的。与两种方法的所有采集的平均值相比，代谢物的峰高值都增加了，尽管主要是 ICA 方法。
