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Deep learning for forensic age estimation using orthopantomograms in children, adolescents, and young adults.
Eur Radiol
January 2025
Department of Radiology, Jena University Hospital-Friedrich Schiller University, Am Klinikum 1, 07747, Jena, Germany.
Objectives: Forensic age estimation from orthopantomograms (OPGs) can be performed more quickly and accurately using convolutional neural networks (CNNs), making them an ideal extension to standard forensic age estimation methods. This study evaluates improvements in forensic age prediction for children, adolescents, and young adults by training a custom CNN from a previous study, using a larger, diverse dataset with a focus on dental growth features.
Methods: 21,814 OPGs from 13,766 individuals aged 1 to under 25 years were utilized.
Artificial Intelligence-Based Detection and Numbering of Dental Implants on Panoramic Radiographs.
Clin Implant Dent Relat Res
February 2025
SEMRUK Technology Inc., Cumhuriyet Teknokent, Sivas, Turkiye.
Objectives: This study aimed to develop an artificial intelligence (AI)-based deep learning model for the detection and numbering of dental implants in panoramic radiographs. The novelty of this model lies in its ability to both detect and number implants, offering improvements in clinical decision support for dental implantology.
Materials And Methods: A retrospective dataset of 32 585 panoramic radiographs, collected from patients at Sivas Cumhuriyet University between 2014 and 2024, was utilized.
Investigation of the Effect of Periodontitis on Trabecular Bone Structure by Fractal Analysis.
Cureus
January 2025
Oral and Maxillofacial Radiology, Biruni University, İstanbul, TUR.
Objective: This study aimed to evaluate the trabecular microarchitecture in the interdental region of panoramic radiographs from periodontally healthy individuals and those with stage III/IV periodontitis using fractal analysis (FA), while also assessing the relationship between clinical periodontal parameters and FA outcomes.
Study Design: Clinical and radiographic records of 20 periodontally healthy individuals and 19 individuals with stage III/IV periodontitis were included. Clinical measurements including the plaque score, bleeding on probing, probing pocket depth, and clinical attachment level were recorded.
Classification and prognostic evaluation of ameloblastoma using multiplanar CT imaging: a retrospective analysis.
BMC Oral Health
January 2025
Department of Oral and Maxillofacial Radiology and Dental Research Institute, School of Dentistry, Seoul National University, Seoul, Republic of Korea.
Background: Ameloblastoma is the most prevalent odontogenic tumor of the jaw, with a significant recurrence rate. It was conventionally classified radiographically as unilocular or multilocular. As 3D images become more common, there is a need to reassess this classification.
View Article and Find Full Text PDFClinical study on deciduous fused teeth and inherited permanent teeth.
Hua Xi Kou Qiang Yi Xue Za Zhi
February 2025
Dept. of Preventive Oral Health, Suzhou Stomatological Hospital, Suzhou 215000, China.
Objectives: This study aimed to investigate the clinical characteristics of deciduous fused teeth and their inherited permanent-tooth performance type by using panoramic radiographs.
Methods: A total of 14 404 panoramic radiographs of 3- to 6-year-old children with deciduous dentition were collected from January 2023 to July 2024. The incidence of deciduous fused teeth was observed, and the abnormality of permanent teeth was recorded.
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