Miller A J, Joseph P M
Department of Radiology, University of Pennsylvania, Philadelphia 19104.
Magn Reson Imaging. 1993;11(7):1051-6. doi: 10.1016/0730-725x(93)90225-3.
Zero-mean noise introduced into quadrature detected MRI signals is generally rectified by the reconstruction algorithm to give a nonzero background intensity in the displayed image. In low signal-to-noise ratio (SNR) images, this background will inflate region of interest (ROI) signal measurements, leading to improper T2 and diffusion fits. A method is described here which separates signal from noise by computing power images from traditional magnitude data. Parameters measured from such power images show closer agreement with true values that do those derived from magnitude images. Because the correction algorithm is the same for all pixel intensities, it can be used with regions of interest with heterogeneous values.
引入到正交检测磁共振成像(MRI)信号中的零均值噪声通常会被重建算法校正,从而在显示的图像中产生非零的背景强度。在低信噪比(SNR)图像中,这种背景会使感兴趣区域(ROI)的信号测量值膨胀,导致T2和扩散拟合不当。本文描述了一种通过从传统幅度数据计算功率图像来分离信号与噪声的方法。从此类功率图像测量得到的参数与从幅度图像得到的参数相比,与真实值的一致性更高。由于校正算法对所有像素强度都是相同的,因此它可用于具有异质值的感兴趣区域。