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To better retrieve task related discriminative source patches, we propose a novel EEG source imaging model based on spatial and temporal graph structures. In particular, graph fractional-order total variation (gFOTV) is used to enhance spatial smoothness, and the label information of brain state is enclosed in a temporal graph regularization term to guarantee intra-class consistency of estimated sources. Numerical experiments have shown that our method localizes source extents more effectively than the benchmark methods.
This presentation is part of Minisymposium “MS4 - Graph Techniques for Image Processing (2 parts)”
organized by: Yifei Lou (University of Texas at Dallas) , Jing Qin (Montana State University) .