Electromagnetic Source Imaging With a Combination of Sparse Bayesian Learning and Deep Neural Network
Author:
Affiliation:
1. Shien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, China
2. Pazhou Laboratory, Guangzhou, China
Funder
National Natural Science Foundation of China
Technology Innovation 2030
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Biomedical Engineering,General Neuroscience,Internal Medicine,Rehabilitation
Link
http://xplorestaging.ieee.org/ielx7/7333/10031624/10071956.pdf?arnumber=10071956
Reference40 articles.
1. sLORETA allows reliable distributed source reconstruction based on subdural strip and grid recordings
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3. Performance evaluation of the Champagne source reconstruction algorithm on simulated and real M/EEG data
4. ConvDip: A Convolutional Neural Network for Better EEG Source Imaging
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