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生物医学磁共振波谱数据的频率选择性定量分析

Frequency-selective quantification of biomedical magnetic resonance spectroscopy data.

作者信息

Vanhamme L, Sundin T, Van Hecke P, Van Huffel S, Pintelon R

机构信息

Department of Electrical Engineering (ESAT), Katholieke Universiteit Leuven, Kard. Mercierlaan 94, Leuven, 3001, Belgium.

出版信息

J Magn Reson. 2000 Mar;143(1):1-16. doi: 10.1006/jmre.1999.1960.

Abstract

In this paper the possibility of obtaining accurate estimates of parameters of selected peaks in the presence of unknown or uninteresting spectral features in biomedical magnetic resonance spectroscopy (MRS) signals is investigated. This problem is denoted by frequency-selective parameter estimation. A new time-domain technique based on maximum-phase finite impulse response (FIR) filters is presented. The proposed method is compared to a number of existing approaches: the application of a weighting function in the time domain, frequency domain fitting using a polynomial baseline, and the time-domain HSVD filter method. The ease of use and low computational complexity of the FIR filter method make it an attractive approach for frequency-selective parameter estimation. The methods are validated using simulations of relevant (13)C and (31)P MRS examples.

摘要

本文研究了在生物医学磁共振波谱(MRS)信号中存在未知或不感兴趣的光谱特征时,获得所选峰参数准确估计值的可能性。这个问题被称为频率选择性参数估计。提出了一种基于最大相位有限脉冲响应(FIR)滤波器的新时域技术。将该方法与许多现有方法进行了比较:在时域中应用加权函数、使用多项式基线进行频域拟合以及时域HSVD滤波器方法。FIR滤波器方法的易用性和低计算复杂度使其成为频率选择性参数估计的一种有吸引力的方法。使用相关的(13)C和(31)P MRS示例的模拟对这些方法进行了验证。

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