AIMC Topic: Epilepsy, Temporal Lobe
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Deep-learning predicted PET can be subtracted from the true clinical fluorodeoxyglucose PET co-registered to MRI to identify the epileptogenic zone in focal epilepsy.
Epilepsia open
Aug 29, 2023
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...
Robot-assisted stereoencephalography vs subdural electrodes in the evaluation of temporal lobe epilepsy.
Epilepsia open
May 14, 2023
OBJECTIVE: Invasive video-electroencephalography (iVEEG) is the gold standard for evaluation of refractory temporal lobe epilepsy before second stage resective surgery (SSRS). Traditionally, the presumed seizure onset zone (SOZ) has been covered with...
Deep learning for the diagnosis of mesial temporal lobe epilepsy.
PloS one
Feb 23, 2023
OBJECTIVE: This study aimed to enable the automatic detection of the hippocampus and diagnose mesial temporal lobe epilepsy (MTLE) with the hippocampus as the epileptogenic area using artificial intelligence (AI). We compared the diagnostic accuracie...
Novel 3D video action recognition deep learning approach for near real time epileptic seizure classification.
Scientific reports
Nov 15, 2022
Seizure semiology is a well-established method to classify epileptic seizure types, but requires a significant amount of resources as long-term Video-EEG monitoring needs to be visually analyzed. Therefore, computer vision based diagnosis support too...
Localizing seizure onset zones in surgical epilepsy with neurostimulation deep learning.
Journal of neurosurgery
Sep 23, 2022
OBJECTIVE: In drug-resistant temporal lobe epilepsy, automated tools for seizure onset zone (SOZ) localization that use brief interictal recordings could supplement presurgical evaluations and improve care. Thus, the authors sought to localize SOZs b...
Deep learning resting state functional magnetic resonance imaging lateralization of temporal lobe epilepsy.
Epilepsia
Apr 1, 2022
OBJECTIVE: Localization of focal epilepsy is critical for surgical treatment of refractory seizures. There remains a great need for noninvasive techniques to localize seizures for surgical decision-making. We investigate the use of deep learning usin...
Abnormal Degree Centrality as a Potential Imaging Biomarker for Right Temporal Lobe Epilepsy: A Resting-state Functional Magnetic Resonance Imaging Study and Support Vector Machine Analysis.
Neuroscience
Feb 11, 2022
Previous studies have reported altered neuroimaging features in right temporal lobe epilepsy (rTLE). However, the alterations in degree centrality (DC) as a diagnostic method for rTLE have not been reported. Therefore, we aimed to explore abnormaliti...
Deep learning and radiomics based automatic diagnosis of hippocampal sclerosis.
The International journal of neuroscience
Dec 28, 2021
Accurate and rapid segmentation of the hippocampus can help doctors perform intractable temporal lobe epilepsy (TLE) preoperative evaluations to identify good surgical candidates. This study aims to establish a radiomics system for the automatic diag...
Deep learning-based diagnosis of temporal lobe epilepsy associated with hippocampal sclerosis: An MRI study.
Epilepsy research
Nov 21, 2021
PURPOSE: The currently available indicators-sensitivity and specificity of expert radiological evaluation of MRIs-to identify mesial temporal lobe epilepsy (MTLE) associated with hippocampal sclerosis (HS) are deficient, as they cannot be easily asse...
MRI-Based Machine Learning Prediction Framework to Lateralize Hippocampal Sclerosis in Patients With Temporal Lobe Epilepsy.
Neurology
Sep 2, 2021
BACKGROUND AND OBJECTIVES: MRI fails to reveal hippocampal pathology in 30% to 50% of temporal lobe epilepsy (TLE) surgical candidates. To address this clinical challenge, we developed an automated MRI-based classifier that lateralizes the side of co...
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