Araştırmacılar Mehmet Özgür Özemre
Mehmet Özgür ÖzemreDİŞ HEKİMLİĞİ FAKÜLTESİ KLİNİK BİLİMLER BÖLÜMÜ AĞIZ, DİŞ VE ÇENE RADYOLOJİSİ ANABİLİM DALI
169855

Comparison of the First Period of the COVID-19 Pandemic and the Current Situation in Ankara and İstanbul in Terms of Dentistry: Descriptive Research

özemre,mehmet özgür

Objective: The purpose of this study is to examine the effect of the pandemic and the control measures implemented to contain it on the dentistry. The study also aims to identify the changes that have occurred in the field of dentistry and to compare the initial period of the coronavirus disease-2019 (COVID-19) pandemic in Türkiye with the present situation. Material and Methods: The study assessed a total of 424 patients, with the first group being evaluated in May 2020 and the second group being evaluated in November 2022. A record was taken of the patients, detailing when they were admitted, the reason for admission, their history of systemic disease, the number of people accompanying them, and whether they had any symptoms such as cough, respiratory distress, or nasal discharg...

169849

Enhanced diagnostic pipeline for maxillary sinus-maxillary molars relationships: a novel implementation of Detectron2 with faster R-CNN R50 FPN 3x on CBCT images

özemre,mehmet özgür | Bektaş, Jale | yanık,hüseyin | baysal,lütfiye

Background The anatomical relationship between the maxillary sinus and maxillary molars is critical for planning dental procedures such as tooth extraction, implant placement and periodontal surgery. Methods This study presents a novel artificial intelligence-based approach for the detection and classification of these anatomical relationships in cone beam computed tomography (CBCT) images. The model, developed using advanced image recognition technology, can automatically detect the relationship between the maxillary sinus and adjacent molars with high accuracy. Results The artificial intelligence algorithm used in our study provided faster and more consistent results compared to traditional manual evaluations, reaching 89% accuracy in the classification of anatomical structures....

169853

KONİK IŞINLI BİLGİSAYARLI TOMOGRAFİ GÖRÜNTÜLERİNDE RASTLANTISAL BULGULAR: BİR KESİTSEL ARAŞTIRMA

ÖZEMRE,MEHMET ÖZGÜR | TOPBAŞ KOÇAK, NAZAN

Amaç: Maksillofasiyal konik ışınlı bilgisayarlı tomografi görüntülerinde karşılaşılan rastlantısal bulguların yerini, tipini ve sıklığını geriye dönük olarak incelemektir. Gereç ve yöntem: Çalışmada, 2018-2021 yılları arasında sadece implant planlaması amacıyla alınmış konik ışınlı bilgisayarlı tomografi görüntüleri geriye dönük olarak rastlantısal bulgu varlığı açısından değerlendirilmiştir. Görüntüler, iki deneyimli dentomaksillofasiyal radyolog tarafından geriye dönük olarak incelenmiştir. Rastlantısal bulgular bulundukları bölgeye göre; hava yolu bulguları, gömülü diş-kök varlığı, temporomandibular eklem bulguları, endodontik lezyonlar, osteoskleroz ve yumuşak doku kalsifikasyonları olarak sınıflandırılmıştır. Bulgular: Çalışmada 109’u erkek 91’i kadın olan toplam 200 hastanın (yaş o...