Brain Focal Activation Detection with MEG Signals Using Combination Method

Mehdi Rajabioun
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Abstract

Magnetoencephalography(MEG) is one of newest methods for detecting brain activations. But because of illposedness of this problem many papers are proposed to solving this problem and acquiring accurate unique solution. In this paper we propose a method whose solution is less sensitive to noise, is spatially unbiased, focal and has low computational complexity. We combine the ideas of weighting, regularization to provide a combination method. Simulation studies on focal activation detection in different location and signal to noise ratio (SNR) reveal that the proposed method provides accurate and focal solution in the presence of noise. This method has superior performance compared to non-iterative methods. Its performance is similar to the iterative methods (like FOCUSS) but with lower computational load.
结合脑磁图信号的脑局灶激活检测
脑磁图(MEG)是检测大脑活动的最新方法之一。但由于该问题的病态性,许多论文都提出要解决该问题并获得精确的唯一解。本文提出了一种求解对噪声不敏感、空间无偏、集中、计算复杂度低的方法。我们将加权、正则化的思想结合起来,提供了一种组合方法。对不同位置和信噪比下的病灶激活检测进行了仿真研究,结果表明,该方法在存在噪声的情况下仍能提供准确的病灶解。与非迭代方法相比,该方法具有优越的性能。它的性能与迭代方法(如focus)相似,但计算负荷更低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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