4 papers
FAIR-ESI: Feature Adaptive Importance Refinement for Electrophysiological Source Imaging
Linyong Zou, Liang Zhang, Xiongfei Wang +9
An essential technique for diagnosing brain disorders is electrophysiological source imaging (ESI). While model-based optimization and deep learning methods have achieved promising…
IEFS-GMB: Gradient Memory Bank-Guided Feature Selection Based on Information Entropy for EEG Classification of Neurological Disorders
Liang Zhang, Hanyang Dong, Jia-Hong Gao +5
Deep learning-based EEG classification is crucial for the automated detection of neurological disorders, improving diagnostic accuracy and enabling early intervention. However, the…
LV-CadeNet: A Long-View Feature Convolution-Attention Fusion Encoder-Decoder Network for EEG/MEG Spike Analysis
Kuntao Xiao, Xiongfei Wang, Pengfei Teng +8
The analysis of interictal epileptiform discharges (IEDs) in magnetoencephalography (MEG) or electroencephalogram (EEG) recordings represents a critical component in the diagnosis…
Automated Detection of Epileptic Spikes and Seizures Incorporating a Novel Spatial Clustering Prior
Hanyang Dong, Shurong Sheng, Xiongfei Wang +7
A Magnetoencephalography (MEG) time-series recording consists of multi-channel signals collected by superconducting sensors, with each signal's intensity reflecting magnetic field…