深度学习在上颌窦建模中的应用

doi:10.13701/j.cnki.kqyxyj.2026.03.006

口腔医学研究 ›› 2026, Vol. 42 ›› Issue (3): 206-212.DOI: 10.13701/j.cnki.kqyxyj.2026.03.006

深度学习在上颌窦建模中的应用

李放^1*, 潘研¹, 韩爽¹, 庄硕²

1.合肥市口腔医院正畸三科早矫中心安徽医科大学合肥口腔临床学院安徽合肥 230061;
2.合肥工业大学计算机与信息学院安徽合肥 230601

收稿日期:2025-10-09 发布日期:2026-03-26
通讯作者: * 李放,E-mail:lf000210@163.com
作者简介:李放(1983~ ),女,合肥人,硕士,副主任医师,研究方向:口腔正畸。
基金资助:
2024年安徽省卫生健康科研项目(编号:AHWJ2024Aa20222);2024年蚌埠医科大学自然科学重点项目(编号:2024byzd342)

Application of Deep Learning in Maxillary Sinus Modeling

LI Fang^1*, PAN Yan¹, HAN Shuang¹, ZHUANG Shuo²

1. Department of Orthodontics Ⅲ & Early Correvolion, Hefei Stomatological Hospital, Hefei Stomatological Clinical College, Anhui Medical University, Hefei 230061, China;
2. School of Computer Science and Information, Hefei University of Technology, Hefei 230601, China

Received:2025-10-09 Published:2026-03-26

摘要/Abstract

摘要： 目的:探索SegFormer深度学习模型在上颌窦建模中的作用。方法:应用SegFormer对纳入的33例患者锥形束CT影像资料进行上颌窦自动提取重建并测量上颌窦体积,与手动测量结果进行比较并进行统计分析。结果:利用SegFormer进行上颌窦图像的自动提取重建并进行体积测量仅需约30 s,比手动测量效率高,两者测量的上颌窦体积比较无显著性差异(P＞0.05)。结论:SegFormer深度学习模型可以更快速准确地重建上颌窦,体现了人工智能在口腔医学领域的辅助诊断价值。

关键词: 人工智能, 上颌窦体积, 锥形束CT, 三维重建

Abstract: Objective: To explore the effect of SegFormer deep learning model in maxillary sinus modeling. Methods: SegFormer was applied to automatically segment and reconstruct the maxillary sinus from cone-beam CT images of 33 included patients, and the maxillary sinus volume was measured and compared with manual measurements for statistical analysis. Results: Using SegFormer for automated segmentation, reconstruction, and measurement of the maxillary sinus volume takes only about 30 seconds, and is substantially faster than manual measurement, while showing no statistically significant difference in maxillary sinus volume (P>0.05). Conclusion: The SegFormer deep learning model can reconstruct the maxillary sinus more quickly and accurately, reflecting the auxiliary diagnostic value of artificial intelligence in the field of dentistry

Key words: artificial intelligence, maxillary sinus volume, cone-beam computer tomography, three-dimensional reconstruction

李放, 潘研, 韩爽, 庄硕. 深度学习在上颌窦建模中的应用[J]. 口腔医学研究, 2026, 42(3): 206-212.

LI Fang, PAN Yan, HAN Shuang, ZHUANG Shuo. Application of Deep Learning in Maxillary Sinus Modeling[J]. Journal of Oral Science Research, 2026, 42(3): 206-212.

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深度学习在上颌窦建模中的应用

Application of Deep Learning in Maxillary Sinus Modeling

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