Automatic maxillary sinus segmentation and age estimation model for the northwestern Chinese Han population

Automatic maxillary sinus segmentation and age estimation model for the northwestern Chinese Han population

Abstract Background Age estimation is vital in forensic science, with maxillary sinus development serving as a reliable indicator. This study developed an automatic segmentation model for maxillary sinus identification and parameter measurement, combined with regression and machine learning models f...

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Main Authors: Yu-Xin Guo, Jun-Long Lan, Wen-Qing Bu, Yu Tang, Di Wu, Hui Yang, Jia-Chen Ren, Yu-Xuan Song, Hong-Ying Yue, Yu-Cheng Guo, Hao-Tian Meng
Format: Article
Language:English
Published: BMC 2025-02-01
Series:BMC Oral Health
Subjects:
Age estimation
Forensic anthropology
Maxillary sinus
Automatic segmentation
Machine learning
Online Access:https://doi.org/10.1186/s12903-025-05618-x
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Summary:Abstract Background Age estimation is vital in forensic science, with maxillary sinus development serving as a reliable indicator. This study developed an automatic segmentation model for maxillary sinus identification and parameter measurement, combined with regression and machine learning models for age estimation. Methods Cone Beam Computed Tomography (CBCT) images from 292 Han individuals (ranging from 5 to 53 years) were used to train and validate the segmentation model. Measurements included sinus dimensions (length, width, height), inter-sinus distance, and volume. Age estimation models using multiple linear regression and random forest algorithms were built based on these variables. Results The automatic segmentation model achieved high accuracy, which yielded a Dice similarity coefficient (DSC) of 0.873, an Intersection over Union (IoU) of 0.7753, a Hausdorff Distance 95% (HD95) of 9.8337, and an Average Surface Distance (ASD) of 2.4507. The regression model performed best, with mean absolute errors (MAE) of 1.45 years (under 18) and 3.51 years (aged 18 and above), providing relatively precise age predictions. Conclusion The maxillary sinus-based model is a promising tool for age estimation, particularly in adults, and could be enhanced by incorporating additional variables like dental dimensions.
ISSN:1472-6831

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