Fully-Automated Spike Detection and Dipole Analysis of Epileptic MEG Using Deep Learning

Magnetoencephalography (MEG) is a useful tool for clinically evaluating the localization of interictal spikes. Neurophysiologists visually identify spikes from the MEG waveforms and estimate the equivalent current dipoles (ECD). However, presently, these analyses are manually performed by neurophysi...

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Veröffentlicht in:	IEEE transactions on medical imaging 2022-10, Vol.41 (10), p.2879-2890
Hauptverfasser:	Hirano, Ryoji, Emura, Takuto, Nakata, Otoichi, Nakashima, Toshiharu, Asai, Miyako, Kagitani-Shimono, Kuriko, Kishima, Haruhiko, Hirata, Masayuki
Format:	Artikel
Sprache:	eng
Schlagworte:	Automation Classification Data acquisition Deep learning dipole analysis Dipoles Epilepsy Estimation Firing pattern Image processing Image segmentation Localization Machine learning Magnetoencephalography Magnetoencephalography (MEG) Patients Semantics Sensors spike detection Training data Waveforms
Online-Zugang:	Volltext
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