Zobrazeno 1 - 10 of 84 pro vyhledávání: '"Ibrahim Sevki, Bayrakdar"'
1
Akademický článek
YOLO-V5 based deep learning approach for tooth detection and segmentation on pediatric panoramic radiographs in mixed dentition
Autor: Busra Beser, Tugba Reis, Merve Nur Berber, Edanur Topaloglu, Esra Gungor, Münevver Coruh Kılıc, Sacide Duman, Özer Çelik, Alican Kuran, Ibrahim Sevki Bayrakdar
Publikováno v: BMC Medical Imaging, Vol 24, Iss 1, Pp 1-14 (2024)
Abstract Objectives In the interpretation of panoramic radiographs (PRs), the identification and numbering of teeth is an important part of the correct diagnosis. This study evaluates the effectiveness of YOLO-v5 in the automatic detection, segmentat
Externí odkaz: https://doaj.org/article/1dfb768d52924928ae40ea86d4878a4e
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2
Akademický článek
Evaluation of the relationship between periodontal bone destruction and mesial root concavity of the maxillary first premolar
Autor: Zehra Beycioglu, Buket Acar, Mert Ocak, Ibrahim Sevki Bayrakdar, Guliz N. Guncu, Abdullah C. Akman
Publikováno v: BMC Oral Health, Vol 24, Iss 1, Pp 1-10 (2024)
Abstract Background The purpose of this study was to investigate the morphology of maxillary first premolar mesial root concavity and to analyse its relation to periodontal bone loss (BL) using cone beam computed tomography (CBCT) and panoramic radio
Externí odkaz: https://doaj.org/article/170366514e0d4613b4c1564b9b35a332
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3
Akademický článek
Detecting white spot lesions on post-orthodontic oral photographs using deep learning based on the YOLOv5x algorithm: a pilot study
Autor: Pelin Senem Ozsunkar, Duygu Çelİk Özen, Ahmed Z Abdelkarim, Sacide Duman, Mehmet Uğurlu, Mehmet Rıdvan Demİr, Batuhan Kuleli, Özer Çelİk, Busra Seda Imamoglu, Ibrahim Sevki Bayrakdar, Suayip Burak Duman
Publikováno v: BMC Oral Health, Vol 24, Iss 1, Pp 1-11 (2024)
Abstract Background Deep learning model trained on a large image dataset, can be used to detect and discriminate targets with similar but not identical appearances. The aim of this study is to evaluate the post-training performance of the CNN-based Y
Externí odkaz: https://doaj.org/article/d81690ea29474ab9a5a5c20b9e4cbb55
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5
Akademický článek
A Deep Learning Approach to Automatic Tooth Caries Segmentation in Panoramic Radiographs of Children in Primary Dentition, Mixed Dentition, and Permanent Dentition
Autor: Esra Asci, Munevver Kilic, Ozer Celik, Kenan Cantekin, Hasan Basri Bircan, İbrahim Sevki Bayrakdar, Kaan Orhan
Publikováno v: Children, Vol 11, Iss 6, p 690 (2024)
Objectives: The purpose of this study was to evaluate the effectiveness of dental caries segmentation on the panoramic radiographs taken from children in primary dentition, mixed dentition, and permanent dentition with Artificial Intelligence (AI) mo
Externí odkaz: https://doaj.org/article/1e0f1157dc76451c88e309639aeb21ca
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6
Akademický článek
A deep learning approach for dental implant planning in cone-beam computed tomography images
Autor: Sevda Kurt Bayrakdar, Kaan Orhan, Ibrahim Sevki Bayrakdar, Elif Bilgir, Matvey Ezhov, Maxim Gusarev, Eugene Shumilov
Publikováno v: BMC Medical Imaging, Vol 21, Iss 1, Pp 1-9 (2021)
Abstract Background The aim of this study was to evaluate the success of the artificial intelligence (AI) system in implant planning using three-dimensional cone-beam computed tomography (CBCT) images. Methods Seventy-five CBCT images were included i
Externí odkaz: https://doaj.org/article/d2f5cd8264774c6a9bf7a13a104d0243
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7
Akademický článek
The Relationship between carotid artery calcification and pulp stone among hemodialysis patients: A retrospective study
Autor: Sevcihan Gunen Yilmaz, Fatih Yilmaz, Ibrahim Sevki Bayrakdar, Abubekir Harorli
Publikováno v: Saudi Journal of Kidney Diseases and Transplantation, Vol 30, Iss 4, Pp 755-763 (2019)
The aim of this study was to determine the relationship between the presence of carotid artery calcification (CAC) and pulp stone (PS). A total of 60 chronic hemodialysis (HD) patients (30 CAC positive, 30 CAC negative) participated in this study. Th
Externí odkaz: https://doaj.org/article/54fb9094833e459080469650a6773cbd
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8
Detecting the presence of taurodont teeth on panoramic radiographs using a deep learning-based convolutional neural network algorithm
Autor: Sacide Duman, Emir Faruk Yılmaz, Gözde Eşer, Özer Çelik, Ibrahim Sevki Bayrakdar, Elif Bilgir, Andre Luiz Ferreira Costa, Rohan Jagtap, Kaan Orhan
Publikováno v: Oral Radiology. 39:207-214
Artificial intelligence (AI) techniques like convolutional neural network (CNN) are a promising breakthrough that can help clinicians analyze medical imaging, diagnose taurodontism, and make therapeutic decisions. The purpose of the study is to devel
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8e41dd9800253b86bff9edba6def3e0f
https://doi.org/10.1007/s11282-022-00622-1
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9
A Deep Learning Model for Idiopathic Osteosclerosis Detection on Panoramic Radiographs
Autor: Selin Yesiltepe, Ibrahim Sevki Bayrakdar, Kaan Orhan, Özer Çelik, Elif Bilgir, Ahmet Faruk Aslan, Alper Odabaş, Andre Luiz Ferreira Costa, Rohan Jagtap
Publikováno v: Medical Principles and Practice. 31:555-561
Objective: The purpose of the study was to create an artificial intelligence (AI) system for detecting idiopathic osteosclerosis (IO) on panoramic radiographs for automatic, routine, and simple evaluations. Subject and Methods: In this study, a deep
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ad75c39e782a6220345534d8bc30d4b3
https://doi.org/10.1159/000527145
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