Versatile frequency domain fitting using time domain models and prior knowledge
Versatile frequency domain fitting using time domain models and prior knowledge
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DOI：
10.1002/mrm.1910390607
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发表时间：
1998-06-01
影响因子：
3.3
通讯作者：
Kreis, R
中科院分区：
文献类型：
--
作者：
Slotboom, J;Boesch, C;Kreis, R
提出了一种基于时域模型的频域迭代非线性最小二乘拟合算法，用于复频域磁流变谱的量化。该算法允许结合先验知识，并且在处理缺失数据点和截断数据集问题方面具有时域拟合的优势，并且在处理多频率选择拟合方面具有频域拟合的优势。所描述的算法除了可以处理洛伦兹线形和高斯线形外，还可以处理Voigt线形和非解析线形。该程序允许用户设计自己的拟合策略，以优化达到全局最小二乘最小值的概率。通过体内H-1-， P-31-和C-13-MR光谱的例子说明了拟合程序的应用。
An iterative nonlinear least-squares fitting algorithm in the frequency domain using time domain models for quantification of complex frequency domain MR spectra is presented. The algorithm allows incorporation of prior knowledge and has both the advantage of time-domain fitting with respect to handling the problem of missing data points and truncated data sets and of frequency-domain fitting with respect to multiple frequency-selective fitting. The described algorithm can handle, in addition to Lorentzian and Gaussian lineshapes, Voigt and nonanalytic lineshapes. The program allows the user the design of his own fitting strategy to optimize the probability of reaching the global least-squares minimum. The application of the fitting program is illustrated with examples from in vivo H-1-, P-31-, and C-13-MR spectroscopy.