OBJECTIVE: Normal interictal [ F]FDG-PET can be predicted from the corresponding T1w MRI with Generative Adversarial Networks (GANs). A technique we call SIPCOM (Subtraction Interictal PET Co-registered to MRI) can then be used to compare epilepsy pa...
Magnetoencephalography (MEG) is a powerful non-invasive diagnostic modality for presurgical epilepsy evaluation. However, the clinical utility of MEG mapping for localising epileptic foci is limited by its low efficiency, high labour requirements, an...
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Aug 9, 2023
OBJECTIVE: This study aimed to explore sensitive detection methods for pathological high-frequency oscillations (HFOs) to improve seizure outcomes in epilepsy surgery.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Jul 27, 2023
OBJECTIVE: Interictal epileptiform discharges (IED) are hallmark biomarkers of epilepsy which are typically detected through visual analysis. Deep learning has shown potential in automating IED detection, which could reduce the burden of visual analy...
In recent years, artificial intelligence, particularly deep learning (DL), has demonstrated utility in diverse areas of medicine. DL uses neural networks to automatically learn features from the raw data while this is not possible with conventional m...
BMC medical informatics and decision making
Jul 6, 2023
Deep learning models have been widely used in electroencephalogram (EEG) analysis and obtained excellent performance. But the adversarial attack and defense for them should be thoroughly studied before putting them into safety-sensitive use. This wor...
Constructing an efficient and accurate epilepsy detection system is an urgent research task. In this paper, we developed an EEG-based multi-frequency multilayer brain network (MMBN) and an attentional mechanism based convolutional neural network (AM-...
Physiological signal processing plays a key role in next-generation human-machine interfaces as physiological signals provide rich cognition- and health-related information. However, the explosion of physiological signal data presents challenges for ...
During surgery for foci-related epilepsy, neurosurgeons face significant difficulties in identifying and resecting MRI-negative or deep-seated epileptic foci. Here, we present a neuro-robotic navigation system that is specifically designed for resect...
BACKGROUND: This protocol describes the design of a multicenter randomized controlled trial of robot-assisted stereotactic lesioning versus epileptogenic foci resection. Typical causes of focal epilepsy include hippocampal sclerosis and focal cortica...
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