3D segmentation of dental crown for volumetric age estimation with CBCT imaging

In adult dental age estimation, segmentation of dental volumetric information from different tooth parts using cone-beam computed tomography (CBCT) has proven beneficial in improving the regression model reliability. This segmentation method can be expanded in the crown part since the volumetric inf...

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Bibliographic Details
Published in:International journal of legal medicine 2023-01, Vol.137 (1), p.123-130
Main Authors: Merdietio Boedi, Rizky, Shepherd, Simon, Oscandar, Fahmi, Mânica, Scheila, Franco, Ademir
Format: Article
Language:English
Subjects:
Age
Age Determination by Teeth - methods
Chronology
Component reliability
Computed tomography
Cone-Beam Computed Tomography
Crowns
Cuspid - diagnostic imaging
Dental crowns
Forensic Dentistry - methods
Forensic Medicine
Forensic odontology
Image segmentation
Imaging, Three-Dimensional
Independent variables
Medical Law
Medicine
Medicine & Public Health
Original
Original Article
Regression models
Reproducibility of Results
Retrospective Studies
Spiral Cone-Beam Computed Tomography
Teeth
Three dimensional imaging
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Summary:In adult dental age estimation, segmentation of dental volumetric information from different tooth parts using cone-beam computed tomography (CBCT) has proven beneficial in improving the regression model reliability. This segmentation method can be expanded in the crown part since the volumetric information in the crown is affected by attrition in the enamel and secondary dentine in the dentine and pulp chamber. CBCT scans from 99 patients aged between 20 and 60 were collected retrospectively. A total of 80 eligible teeth for each tooth type were used in this study. The enamel to dentine volume ratio (EDVR), pulp to dentine volume ratio (PDVR) and sex were used as independent variables to predict chronological age (CA). The EDVR was not affected by PDVR. The highest R 2 was calculated from the maxillary canine ( R 2 = 0.6). The current approach in crown segmentation has proven to improve model performance in anterior maxillary teeth.
ISSN:0937-9827
1437-1596
DOI:10.1007/s00414-022-02898-8