一种用于重建扩展皮质电流源的新型稀疏源成像方法。
A novel sparse source imaging in reconstructing extended cortical current sources.
作者信息
Ding Lei
机构信息
University of Oklahoma, Norman, USA.
出版信息
Annu Int Conf IEEE Eng Med Biol Soc. 2008;2008:4555-8. doi: 10.1109/IEMBS.2008.4650226.
We have developed a new sparse source imaging (SSI) method with the use of the L1-norm in EEG inverse problems to reconstruct extended cortical current sources. The new SSI method explores the sparseness in cortical current density variation maps (the transform domain) other than in the cortical current density maps (the original domain) from previously reported SSI methods. The new SSI is assessed by a series of computer simulations. The performance of SSI is compared with the well-known L2-norm MNE using the AUC metric. Our present simulation data indicate that the new SSI has significantly improved performance in reconstructing extended cortical current sources and estimating their cortical extents. The L2-norm MNE shows relatively poor performance in the same source imaging tasks. The new SSI method is also applicable to MEG source imaging.
我们开发了一种新的稀疏源成像（SSI）方法，该方法在脑电图逆问题中使用L1范数来重建扩展的皮质电流源。新的SSI方法探索的是皮质电流密度变化图（变换域）中的稀疏性，而非先前报道的SSI方法所关注的皮质电流密度图（原始域）中的稀疏性。通过一系列计算机模拟对新的SSI进行了评估。使用AUC指标将SSI的性能与著名的L2范数最小范数估计（MNE）方法进行了比较。我们目前的模拟数据表明，新的SSI在重建扩展的皮质电流源及其皮质范围估计方面具有显著提高的性能。L2范数MNE在相同的源成像任务中表现相对较差。新的SSI方法也适用于脑磁图源成像。
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