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一种用于确定磁共振成像信噪比的新型单次采集、双图像差分方法。

A new single acquisition, two-image difference method for determining MR image SNR.

作者信息

Steckner Michael C, Liu Bo, Ying Leslie

机构信息

Toshiba Medical Research Institute USA, Inc., Mayfield Village, Ohio 44143, USA.

出版信息

Med Phys. 2009 Feb;36(2):662-71. doi: 10.1118/1.3036118.

Abstract

A new method for computing the signal-to-noise ratio (SNR) of magnetic resonance images is presented. The proposed method is a "difference of images" based technique where two images are produced from one acquisition in which the readout direction field of view (FOV) and matrix size are doubled compared to the phase encode direction. Two "normal" unaliased FOV images are produced by splitting (undersampling) the even versus odd data points in the read direction into two separate raw data sets. After image reconstruction, conventional difference of images SNR computations are applied. [Signal defined as mean within signal producing region of interest (ROI) in one image, noise defined as standard deviation of the difference between the two images using the same signal ROI position and size, divided by sqrt(2) to account for the subtraction process.] This method combines the desirable minimal acquisition time of a single image acquisition technique and the superior noise quantification characteristics of the difference of images methodology. The proposed method is more robust against system drift than existing SNR difference of images methods because the two images are effectively acquired nearly simultaneously in time. This method is compatible with phased array coils and is useful for parallel image reconstruction analysis because it is very stable. This method produces results that can be made equivalent to, and compared with, other existing SNR methods with simple known scale factors, assuming the image noise follows theoretical expectations.

摘要

提出了一种计算磁共振图像信噪比(SNR)的新方法。所提出的方法是一种基于“图像差值”的技术,其中从一次采集中生成两幅图像,在该采集中,读出方向视野(FOV)和矩阵大小相对于相位编码方向加倍。通过将读取方向上的偶数与奇数数据点分割成两个单独的原始数据集,生成两幅“正常”的无混叠FOV图像。图像重建后,应用传统的图像差值SNR计算方法。[信号定义为一幅图像中感兴趣的信号产生区域(ROI)内的均值,噪声定义为使用相同信号ROI位置和大小的两幅图像之间差值的标准差,除以sqrt(2)以考虑减法过程。]该方法结合了单图像采集技术所需的最短采集时间和图像差值方法卓越的噪声量化特性。与现有的图像差值SNR方法相比,所提出的方法对系统漂移更具鲁棒性,因为这两幅图像实际上是在几乎同时采集的。该方法与相控阵线圈兼容,并且由于其非常稳定,因此对于并行图像重建分析很有用。假设图像噪声符合理论预期,该方法产生的结果可以通过简单的已知比例因子与其他现有SNR方法等效并进行比较。

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