Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/10391
Title: Localization of Epileptic Focus by Gray Matter Reduction Analysis From Brain Mr Images for Temporal Lobe Epilepsy Patients
Authors: Ficici, C.
Telatar, Z.
Eroğul, O.
Keywords: Epileptic focus
MRI
Temporal lobe epilepsy
Voxel based morphometry
Diagnosis
Image analysis
Magnetic resonance
Neurology
% reductions
Brain MR images
Epilepsy surgery
Epileptic foci
Gray matter
Localisation
MR-images
Temporal lobe epilepsy
Temporal lobe epilepsy patients
Voxel-based morphometry
Magnetic resonance imaging
adult
anterior cingulate
Article
brain atrophy
cingulate gyrus
clinical article
controlled study
detection algorithm
electroencephalogram
epileptic focus
epileptic patient
expectation-maximization algorithm
gray matter
hippocampal sclerosis
human
image registration
left hippocampus
Levenberg Marquardt algorithm
limbic cortex
middle temporal gyrus
neuroimaging
nuclear magnetic resonance imaging
parahippocampal gyrus
retrospective study
right hippocampus
segmentation algorithm
sensitivity and specificity
superior temporal gyrus
T1 weighted imaging
temporal lobe
temporal lobe epilepsy
voxel based morphometry
Publisher: Elsevier Ltd
Abstract: Localization of epileptic focus is crucial for resective epilepsy surgery and treatment planning. The purpose of this study is to develop a method analyzing gray matter reduction in brain magnetic resonance images in order to identify epileptogenic focus of temporal lobe epilepsy (TLE) patients. So, a new voxel based morphometry analysis based epileptogenic brain side detection approach was proposed. Gray matter abnormalities were detected from T1-weighted MR images by using Statistical Parametric Mapping based voxel based morphometry analysis. The dataset of the introduced retrospective analysis consists of MR images of 15 TLE patients including patients with hippocampal sclerosis, mesial temporal sclerosis, and MRI negative diagnoses. In addition, MRI of 14 healthy subjects were used as the control group. TLE focus detection performed by the proposed method and seizure lateralization from EEG recordings realized by the expert overlapped at a rate of 91.7 %. In addition, sensitivity of 100 % and 80 % were obtained for right TLE and left TLE detection, respectively. Experimental results showed that the proposed algorithm can reveal subtle Gray matter reduction in the temporal lobe and limbic lobe areas, thus providing an automated medical support system for the expert in identifying the epileptic focus of TLE patients. © 2023 Elsevier Ltd
URI: https://doi.org/10.1016/j.bspc.2023.104716
https://hdl.handle.net/20.500.11851/10391
ISSN: 1746-8094
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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