Filtreler

2022 - 20253
Filtreleri Sıfırla

Ayarlar

Yazar: Demirer, Rüştü Murat ×

Arama Sonuçları

Listeleniyor 1 - 3 / 3
  • Küçük Resim
    Yayın
    A new novel synchronization index of brain networks in hyperbolic EEG dynamics
    (Sakarya Üniversitesi Fen Bilimleri Enstitüsü, 2022-06) Demirer, Rüştü Murat
    The functional connectivity ofbrain connectivity changes its pattern over time i.e. dynamics, even in the resting state with an infinite number of degrees of freedom with local couplings. Recently, quantifying the level of synchrony has received considerable attention. We hypothesized that time-varying instantaneous phase synchronization over local couplings are defined in hyperbolic space and different brain regions can identify failures, flexibility, and stability in network dynamics.Our goal is to understand the phase synchronization changes of the beta-gamma band, and in addition, to investigate Shannon entropy based on phase synchronization stability. Whole EEG dynamics from local phase synchronizations was used to detect treatment resistance from both hemispheres in OCD patients. Temporal filtering and Hilbert transforms were performed to infer beta-gamma band phase difference activity from the EEG brain dynamics.Then, the response beta-gamma band phase stability was quantified using a new phase synchronization index (PSI). Results indicated significantly changed phase synchronization of the response and non-response to treatment, patients in OCD patients in F7 electrode. Greater phase fluctuations of beta-gamma synchronizations in treatment resistance OCD is claiming phase deficiencies within neural populations.This study first provides experimental and theoretical support for characterizing cycle structure depends on the non-Euclidian dynamics of neural phase synchrony caused by disturbances of underlying neurotransmitter systems, as reflected in different normal and disease states.
  • Küçük Resim
    Yayın
    Deri lezyonlarının evrişimsel yapay sinir ağları ile sınıflandırılması
    (Pamukkale Univ, 2022-07-10) Bilginer, Onur; Tunga, Burcu; Demirer, Rüştü Murat
    Bu çalışmada Uluslararası Deri Görüntüleme Birliği tarafından 2019 yılında yayınlanan ve 25000’den fazla dermoskopik deri görüntüsü içeren ISIC 2019 veri seti kullanılarak 4 çeşit (Melanom, Melanositik Nevüs, Bazal Hücreli Karsinom, İyi Huylu Keratoz) deri pigmentasyonu Evrişimsel Sinir Ağları yöntemi yardımıyla sınıflandırılmıştır. Sınıflandırma yapılırken InceptionV3 yapay sinir ağı mimarisi kullanılmıştır. Deri görüntülerine önişlem olarak Hilbert Dönüşümü ve Yüksek Boyutlu Model Gösterilimi uygulanmıştır. Elde edilen sonuçlara göre test verisi üzerinde Hilbert Dönüşümü uygulanmış görüntülerde Bazal Hücreli Karsinom hastalığının sınıflandırılmasında %89 başarı oranı elde edilmiştir. Yüksek Boyutlu Model Gösterilimi ile Kontrast Artırımı uygulanan görsellerde ise Melanomun sınıflandırılmasında %78 başarı oranı elde edilmiştir.
  • Küçük Resim
    Yayın
    Boundary element method for EEG single-dipole localization: a study in patients with OCD
    (Institute of Electrical and Electronics Engineers Inc., 2025-08-15) Abdullahi, Fatima I.; Demirer, Rüştü Murat
    This study investigates EEG dipole localization in patients diagnosed with obsessive-compulsive disorder (OCD) using the Boundary Element Method (BEM) implemented via Brainstorm and OpenMEEG. EEG signals from 33 OCD patients were analyzed using a realistic, multi-layer head model consisting of scalp, skull, and brain tissues with respective conductivity values. Dipoles were accurately localized for each discrete time instant within the gamma frequency range (20-50 Hz) using a single dipole assumption per time point. EEG potentials measured from 19 standard electrodes were numerically computed by solving the forward EEG problem with the boundary element approach provided by OpenMEEG. Spectral clustering analysis identified distinct neural patterns corresponding to clinically recognized OCD subtypes, facilitating better diagnostic interpretations. Our results address previous methodological limitations by combining realistic head geometry modeling and precise temporal and spatial dipole estimation, offering promising directions for enhanced EEG-based diagnostic tools in psychiatry.