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首页> 外文会议>Physics of Medical Imaging pt.3; Progress in Biomedical Optics and Imaging; vol.8 no.29; Proceedings of SPIE-The International Society for Optical Engineering; vol.6510 pt.3 >Statistics of MR Signals - Revisited
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Statistics of MR Signals - Revisited

机译：MR信号统计-再探

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A common view in MRI research is that the object variability of MR signals is negligible. With this recognition, the signal components of MR signals are treated as constant and the noise components are studied as random processes. Because signal components of MR signals represent a collective behavior of a huge mount of spins, a statistical investigation may provide a better understanding of MR signals. The work reported in this paper first investigates statistics of the thermal equilibrium macroscopic magnetization (TEMM) which is the quantity to be imaged - one that can be measured and actually observed in MRI. Then it investigates statistics of the transverse precessing macroscopic magnetization (TPMM) which introduce an electromagnetic force in the receiver coil of MRI. Finally this study investigates statistics of signal components of three MR signals at the different stages of MR signal detection module: Free Induction Decay (FID), Phase Sensitive Detection (PSD), and Analog-to-Digital Conversion (ADC), sequentially, k-space sample is a reformatted ADC signal. The study derives and proves stochastic models for TEMM, TPMM, FID, PSD, and ADC signals, also proposes and justifies stochastic models for homogeneous and inhomogeneous samples. The study shows that under the normal conditions and the ordinary settings, magnetizations can be characterized as spatially deterministic processes with Probability one, and MR signals - signal component plus noise component - can be characterized as temporal Gaussian random processes with the means of signal components and the variances of noise components. These means are expressed in closed forms in terms of parameters of MR imaging system and the samples. The derived statistical properties of MR signals will serve as the basis for evaluating performances of imaging system and studying statistics of the MR image.
机译：MRI研究的一个普遍观点是，MR信号的对象变异性可以忽略不计。通过这种识别，MR信号的信号分量被视为常数，而噪声分量则被视为随机过程。由于MR信号的信号成分代表了巨大自旋量的集体行为，因此统计调查可能会更好地理解MR信号。本文报道的工作首先研究了热平衡宏观磁化强度（TEMM）的统计数据，即要成像的数量-可以在MRI中测量和实际观察到的数量。然后，研究横向进动宏观磁化（TPMM）的统计数据，该统计数据在MRI的接收线圈中引入了电磁力。最后，本研究调查了三个MR信号在MR信号检测模块不同阶段的信号成分统计：自由感应衰减（FID），相敏检测（PSD）和模数转换（ADC），依次为k空间样本是重新格式化的ADC信号。该研究推导并证明了TEMM，TPMM，FID，PSD和ADC信号的随机模型，还提出并证明了均质和非均质样品的随机模型。研究表明，在正常条件下和普通设置下，磁化强度可以表征为概率为1的空间确定性过程，而MR信号-信号分量加噪声分量-可以表征为时间高斯随机过程，其信号强度为噪声分量的方差。这些手段根据MR成像系统和样本的参数以封闭形式表示。得出的MR信号统计特性将作为评估成像系统性能和研究MR图像统计信息的基础。

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