What is the best similarity measure for motion correction in fMRI time series?
What is the best similarity measure for motion correction in fMRI time series?
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DOI：
10.1109/tmi.2002.1009383
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发表时间：
2002-05-01
影响因子：
10.6
通讯作者：
Mangin, JF
中科院分区：
文献类型：
--
作者：
Freire, L;Roche, A;Mangin, JF
已经表明，标准重新对准包（SENT 和 AIR）使用的平方成本函数的差异可能导致检测到虚假激活，因为运动参数估计受到激活区域的偏差。因此，本文描述了旨在选择更好的相似性度量来驱动功能磁共振图像配准的几个实验。使用模拟时间序列和源自 3T 磁体的实际数据研究了 Geman-McClure (GM) 估计器、相关比和相对于激活区域的互信息 (MI) 的行为。结果表明，这些方法比通常的平方差测量更稳健。结果还表明，根据 GM 估计器等稳健指标构建的度量可能是最佳选择，而 MI 也是一个有趣的解决方案。然而，还需要做更多的工作来比较文献中提出的各种稳健指标。
It has been shown that the difference of squares cost function used by standard realignment packages (SENT and AIR) can lead to the detection of spurious activations, because the motion parameter estimations are biased by the activated areas. Therefore, this paper describes several experiments aiming at selecting a better similarity measure to drive functional magnetic resonance image registration. The behaviors of the Geman-McClure (GM) estimator, of the correlation ratio, and of the mutual information (MI) relative to activated areas are studied using simulated time series and actual data stemming from a 3T magnet. It is shown that these methods are more robust than the usual difference of squares measure. The results suggest also that the measures built from robust metrics like the GM estimator may be the best choice, while MI is also an interesting solution. Some more work, however, is required to compare the various robust metrics proposed in the literature.