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Robust estimation of noise for electromagnetic brain imaging with the champagne algorithm

Chang Cai1, Ali Hashemi2, Mithun Diwakar3

  • 1National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, China; Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143-0628, United States.

Neuroimage
|October 11, 2020
PubMed
Summary

This study introduces noise learning for the Champagne algorithm, improving electromagnetic brain imaging. It enables robust source reconstruction from M/EEG data even without baseline measurements, using fewer trials.

Keywords:
Bayesian inferenceElectromagnetic brain mappingInverse problemMagnetoencephalographyRobust noise estimation

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