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Conference Papers Year : 2015

MEM-diffusion MRI framework to solve MEEG inverse problem


In this paper, we present a framework to fuse information coming from diffusion magnetic resonance imaging (dMRI) with Magnetoencephalography (MEG)/ Electroencephalography (EEG) measurements to reconstruct the activation on the cortical surface. The MEG/EEG inverse-problem is solved by the Maximum Entropy on the Mean (MEM) principle and by assuming that the sources inside each cortical region follow Normal distribution. These regions are obtained using dMRI and assumed to be functionally independent. The source reconstruction framework presented in this work is tested using synthetic and real data. The activated regions for the real data is consistent with the literature about the face recognition and processing network.
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hal-01207165 , version 1 (28-04-2016)




  • HAL Id : hal-01207165 , version 1


Brahim Belaoucha, Jean-Marc Lina, Maureen Clerc, Théodore Papadopoulo. MEM-diffusion MRI framework to solve MEEG inverse problem. 2015 23rd European Signal Processing Conference (EUSIPCO), Aug 2015, Nice, France. ⟨hal-01207165⟩
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