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dc.contributor.authorComu, S
dc.contributor.authorDemiralp, Tamer
dc.contributor.authorBaykan, BETÜL
dc.contributor.authorAdemoglu, A
dc.contributor.authorIstefanopulos, Y
dc.date.accessioned2021-03-04T07:55:10Z
dc.date.available2021-03-04T07:55:10Z
dc.identifier.citationAdemoglu A., Demiralp T., Istefanopulos Y., Comu S., Baykan B., "Epileptic source localization using wavelet prefiltering and MUSIC scanning", 25th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society, Cancun, Meksika, 17 - 21 Eylül 2003, cilt.25, ss.2366-2369
dc.identifier.othervv_1032021
dc.identifier.otherav_6099f395-3fd2-4039-9727-2d442a1e7f45
dc.identifier.urihttp://hdl.handle.net/20.500.12627/67397
dc.identifier.urihttps://doi.org/10.1109/iembs.2003.1280391
dc.description.abstractThe epileptic focus localization in the 3-D brain structure is performed using integer spline wavelet prefiltering and source localization. The forward and inverse problems are solved by Boundary Element Method (BEM) and MUSIC (Multiple Signal Classification) Scanning algorithm, respectively. The realistic head model is obtained by using an average human MRI data released by the Montreal Neurological Institute (MNI). 19 Channel EEG data from three different patients are collected. The technique is tested on these three clinical cases with secondary epileptic seizures based on morphological lesions that could be depicted in the anatomical MRI examinations of the patients. The estimated locations of the generators of interictal epileptiform signals correspond well to the surrounding neural tissue of the lesions. Especially, the disappearance of the seizures in two operated patients after the removal of the astrocytomas verifies the results. The wavelet prefiltering facilitates the visual inspection and detection of the interictal epileptic spikes and the BEM based on a realistic head model gives a more accurate anatomical localization for the focus. A focal source model is widely accepted in many cases of epilepsy and the MUSIC scanning seems to be very suitable for localizing these type of sources.
dc.language.isoeng
dc.subjectSinirbilim ve Davranış
dc.subjectCARDIAC ve CARDIOVASCULAR SİSTEMLER
dc.subjectYaşam Bilimleri (LIFE)
dc.subjectRADYOLOJİ, NÜKLEER TIP ve MEDİKAL GÖRÜNTÜLEME
dc.subjectTıp
dc.subjectSağlık Bilimleri
dc.subjectDahili Tıp Bilimleri
dc.subjectKardiyoloji
dc.subjectNükleer Tıp
dc.subjectTıbbi Ekoloji ve Hidroklimatoloji
dc.subjectBilgisayar Bilimleri
dc.subjectBilgisayar Grafiği
dc.subjectBiyomedikal Mühendisliği
dc.subjectYaşam Bilimleri
dc.subjectTemel Bilimler
dc.subjectMühendislik ve Teknoloji
dc.subjectMühendislik, Bilişim ve Teknoloji (ENG)
dc.subjectMÜHENDİSLİK, BİYOMEDİKSEL
dc.subjectMühendislik
dc.subjectTIP, ARAŞTIRMA VE DENEYSEL
dc.subjectNEUROSCIENCES
dc.subjectKlinik Tıp
dc.subjectKlinik Tıp (MED)
dc.subjectBİLGİSAYAR BİLİMİ, İNTERDİSİPLİNER UYGULAMALAR
dc.subjectBilgisayar Bilimi
dc.titleEpileptic source localization using wavelet prefiltering and MUSIC scanning
dc.typeBildiri
dc.contributor.department, ,
dc.identifier.volume25
dc.contributor.firstauthorID718806


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