A Stacked Sparse Autoencoder-Based Detector for Automatic Identification of Neuromagnetic High Frequency Oscillations in Epilepsy

High-frequency oscillations (HFOs) are spontaneous magnetoencephalography (MEG) patterns that have been acknowledged as a putative biomarker to identify epileptic foci. Correct detection of HFOs in the MEG signals is crucial for the accurate and timely clinical evaluation. Since the visual examinati...

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Veröffentlicht in:	IEEE transactions on medical imaging Jg. 37; H. 11; S. 2474 - 2482
Hauptverfasser:	Guo, Jiayang, Yang, Kun, Liu, Hongyi, Yin, Chunli, Xiang, Jing, Li, Hailong, Ji, Rongrong, Gao, Yue
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.11.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Adolescent Adult Algorithms Background noise Biomarkers brain Brain - diagnostic imaging Child Deep Learning deep learning model detector Detectors Epilepsy Epilepsy - diagnostic imaging Error detection Feature extraction Female Hafnium oxide Head High-frequency oscillations Humans Image Interpretation, Computer-Assisted - methods Machine learning Magnetoencephalography Magnetoencephalography - methods Male MEG Middle Aged Optimization Oscillations Performance measurement Sensitivity and Specificity Sensors Signal Processing, Computer-Assisted SSAE Surgery Young Adult
ISSN:	0278-0062, 1558-254X, 1558-254X
Online-Zugang:	Volltext
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