首页> 外文会议>Medical Imaging 1993: Physics of Medical Imaging >Use of noise and signal-source covariance matrices in reconstructing biocurrent distributions from biomagnetic measurements
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Use of noise and signal-source covariance matrices in reconstructing biocurrent distributions from biomagnetic measurements

机译:噪声和信号源协方差矩阵在根据生物磁测量重建生物电流分布中的用途

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Abstract: This paper proposes three methods for reconstructing magnetic- source biocurrent distribution. These methods are more effective than the conventional pseudo-inversion-based reconstruction when the signal-to-noise ratio of measured data is low. First, a method of estimating magnetic-source-current covariance matrix using the measured-data covariance matrix is presented, and an averaged current squared-intensity distribution is reconstructed using the diagonal terms of the covariance matrix. The use of its off-diagonal terms leads to the second method that can separate magnetic-source activities correlated to each other from the uncorrelated activities. The third method is the Wiener reconstruction of current distributions based on the estimated source covariance matrix. Results of computer simulation demonstrate the effectiveness of those three methods.!19
机译:摘要:本文提出了三种重建磁源生物电流分布的方法。当测量数据的信噪比较低时,这些方法比常规的基于伪反转的重构更有效。首先,提出了一种使用测量数据协方差矩阵估计磁源-电流协方差矩阵的方法,并使用协方差矩阵的对角项重建平均电流平方强度分布。使用其非对角线项导致了第二种方法,该方法可以将彼此相关的磁源活动与不相关的活动分开。第三种方法是基于估计的源协方差矩阵的电流分布的维纳重构。计算机仿真结果证明了这三种方法的有效性。!19

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