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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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