AIMC Topic: Epilepsy, Temporal Lobe

Clear Filters Showing 41 to 47 of 47 articles

Detection of temporal lobe epilepsy using support vector machines in multi-parametric quantitative MR imaging.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
The detection of MRI abnormalities that can be associated to seizures in the study of temporal lobe epilepsy (TLE) is a challenging task. In many cases, patients with a record of epileptic activity do not present any discernible MRI findings. In this...

Redefining diagnostic lesional status in temporal lobe epilepsy with artificial intelligence.

Brain : a journal of neurology
Despite decades of advancements in diagnostic MRI, 30%-50% of temporal lobe epilepsy (TLE) patients remain categorized as 'non-lesional' (i.e. MRI negative) based on visual assessment by human experts. MRI-negative patients face diagnostic uncertaint...

Improving Diagnostic Performance of MRI for Temporal Lobe Epilepsy With Deep Learning-Based Image Reconstruction in Patients With Suspected Focal Epilepsy.

Korean journal of radiology
OBJECTIVE: To evaluate the diagnostic performance and image quality of 1.5-mm slice thickness MRI with deep learning-based image reconstruction (1.5-mm MRI + DLR) compared to routine 3-mm slice thickness MRI (routine MRI) and 1.5-mm slice thickness M...

Voxel-based morphometry analysis and machine learning based classification in pediatric mesial temporal lobe epilepsy with hippocampal sclerosis.

Brain imaging and behavior
Mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS) is a common type of pediatric epilepsy. We sought to evaluate whether the combination of voxel-based morphometry (VBM) and support vector machine (SVM), a machine learning method, was...

Convergent Cross Mapping: Basic concept, influence of estimation parameters and practical application.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In neuroscience, data are typically generated from neural network activity. Complex interactions between measured time series are involved, and nothing or only little is known about the underlying dynamic system. Convergent Cross Mapping (CCM) provid...