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WOS Kategorileri : SCI SCI Eaxp SSCI AH ... ✕İlgili Araştırmacılar : Hatice Cansu KIŞ ✕
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Arş. Gör. Hatice Cansu KIŞDiş Hekimliği
Erişime Açık

Effect of internal derangements and degenerative bone changes on the minimum thickness of the roof of the glenoid fossa in temporomandibular joint

Hatice Cansu KIŞ

Objectives: The aim of this study is to investigate the effect of internal derangements and degenerative bone changes on the minimum thickness of the roof of the glenoid fossa (RGF). Methods: MRI and cone beam CT records of temporomandibular joints (TMJ) of 68 patients were evaluated retrospectively in this study. The joints were divided into three groups according to TMJ disc status which had been diagnosed in MRI: normal disc status, anterior disc displacement with reduction, and anterior disc displacement without reduction. Cone beam CT was used to evaluate the degenerative bone changes of ...Daha fazlası

Makale/Derleme 2019 Oral Radiology 8 Görüntülenme
Erişime Açık

The evaluation of the mandibular bone structure changes related to lactation with fractal analysis

Hatice Cansu KIŞ

Objectives Lactation-induced bone loss of lumbar spine, hip, femur and distal radius are well documented in the literature. The aim of this article is to investigate whether lactation afects the trabecular and cortical bone structure of human mandible. Methods 120 dental panoramic radiographs (DPR) of the lactating women who were breastfeeding for 3–6 months (study group) and 120 DPRs of the nulliparous women (control group) were evaluated. Regions of interest (ROI) were chosen from the geometric center of ramus, the geometric center of angulus and the cortical bone. ROIs were examined with fr ...Daha fazlası

Makale/Derleme 2019 Oral Radiology 7 Görüntülenme
Erişime Açık

Evaluation of styloid chain calcification related to temporomandibular joint disc displacement: a retrospective cohort study

KIŞ HATİCE CANSU

Objectives: The present study aimed to evaluate any relationship between elongated styloid process (ESP) and temporomandibular joint disc displacement (TMJD). Study design: A retrospective cohort study. Setting: Dentomaxillofacial Radiology division of Erciyes University Dental Hospital. Participants: Ninety-four temporomandibular joints (TMJs) of 47 patients were allocated in this study. Intervention-disease: Two experienced dentomaxillofacial radiologists have interpreted all CBCT and MR images. Patients who referred with TMJ disorders were classified according to temporomandibular joint's d ...Daha fazlası

Makale/Derleme 2020 Oral Radiol 4 Görüntülenme
Erişime Açık

Evaluation of the peri-implant bone trabecular microstructure changes in short implants with fractal analysis

Hatice Cansu KIŞ

Backgrounds: This study aimed to evaluate the microstructural changes in the peri-implant bone in patients with short implants in terms of implant survival status by using fractal analysis measurements. Results: Dental panoramic radiographs (DPRs) of 67 patients were examined and included in this study. Fractal analysis and measurement of the crown-implant ratio were performed with ImageJ. The fractal analysis measurement was performed on the DPRs obtained at preoperative (FD0) and in the follow-up periods (after 2 ± 2 weeks (FD1), 2 months ± 2 weeks (FD2), 6 months ± 2 weeks (FD3), and 12 mon ...Daha fazlası

Makale/Derleme 2020 International Journal of Implant Dentistry 6 Görüntülenme
Erişime Açık

A deep learning approach to dental restoration classification from bitewing and periapical radiographs

Özcan KARATAŞ | Nazire Nurdan ÇAKIR | Şaban Suat ÖZSARIYILDIZ | Cem Abdülkadir GÜRGAN

Objective: The aim of this study was to examine the success of deep learning-based convolutional neural networks (CNN) in the detection and differentiation of amalgam, composite resin, and metal-ceramic restorations from bitewing and periapical radiographs. Method and materials: Five hundred and fifty bitewing and periapical radiographs were used. Eighty percent of the images were used for training, and 20% were left for testing. Twenty percent of the images allocated for training were then used for validation during learning. The image classification model was based on the application of CNN. ...Daha fazlası

Makale/Derleme 2021 Quintessence International 12 Görüntülenme
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