Hansen Michael S, Inati Souheil J, Kellman Peter
National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA.
Magn Reson Med. 2015 Mar;73(3):1300-8. doi: 10.1002/mrm.25194. Epub 2014 Mar 13.
The purpose of this work was to develop and validate a technique for predicting the standard deviation (SD) associated with thermal noise propagation in region of interest measurements.
Standard methods for error propagation estimation were used to derive equations for the SDs of linear combinations of complex, magnitude, or phase pixel values. The equations were applied to common imaging scenarios in which the image pixels were correlated due to anisotropic pixel resolutions and parallel imaging. All SD estimates were evaluated efficiently using only vector-vector multiplications and Fourier transforms. The estimated SDs were compared to those obtained using repeated experiments and pseudo replica reconstructions.
The proposed method was able to predict region of interest SDs in all the tested analysis scenarios. Positive and negative noise correlations caused by different parallel-imaging aliasing point spread functions were accurately predicted, and the method predicted the confidence intervals (CI) of time-intensity curves for in vivo cardiac perfusion measurements.
An intuitive technique for region of interest CIs was developed and validated using phantom experiments and in vivo data.
本研究旨在开发并验证一种技术，用于预测感兴趣区域测量中与热噪声传播相关的标准差（SD）。
采用误差传播估计的标准方法，推导复数、幅度或相位像素值线性组合的标准差方程。这些方程应用于常见的成像场景，其中由于各向异性像素分辨率和平行成像，图像像素存在相关性。所有标准差估计仅通过向量-向量乘法和傅里叶变换进行有效评估。将估计的标准差与通过重复实验和伪复制重建获得的标准差进行比较。
所提出的方法能够在所有测试分析场景中预测感兴趣区域的标准差。由不同平行成像混叠点扩散函数引起的正负噪声相关性得到了准确预测，并且该方法预测了体内心脏灌注测量时间-强度曲线的置信区间（CI）。
通过体模实验和体内数据，开发并验证了一种用于感兴趣区域置信区间的直观技术。
