临床口腔医学杂志2026，Vol.42Issue(6)：337-341,5.DOI:10.3969/j.issn.1003-1634.2026.06.005
基于深度学习与CBCT的上颌骨三维解剖标志点自动识别及不同年龄与骨性Ⅰ/Ⅱ类形态学差异分析
Automatic identification of three-dimensional maxillary anatomical landmarks and morphological analysis based on deep learning using CBCT
摘要
Abstract
Objective:To develop a deep learning method for automatic 3D maxillary landmark identification on CBCT and analyze differences across age groups and skeletal Class Ⅰ and Ⅱ.Methods:Totally 1321 CBCT datasets(2019～2024)were used.A PoseNet-3D based model identified 18 landmarks and 5 midfacial points.Performance was assessed by comparing time and error with manual annotation.Patients were grouped by age and skeletal class.Results:Maxillary land-mark identification took 10～15 s,that faster than manual.Mean error was 0.82 mm with good consistency.The errors were all within the clinically acceptable range(<2 mm).Significant differences existed in some landmark distances among age groups and skeletal classes.Conclusion:The method is accurate and efficient,enabling reliable 3D maxillary analysis and supporting digital orthodontic diagnosis and treatment.关键词
深度学习/CBCT/上颌骨/标志点自动识别/三维形态分析Key words
Deep learning/CBCT/Maxilla/Automatic landmark identification/Three-dimensional morphological a-nalysis分类
医药卫生引用本文复制引用
尹楠,孙梦媛,宋千卉,温泽惠,徐建光..基于深度学习与CBCT的上颌骨三维解剖标志点自动识别及不同年龄与骨性Ⅰ/Ⅱ类形态学差异分析[J].临床口腔医学杂志,2026,42(6):337-341,5.基金项目
安徽省自然科学基金面上基金项目(2408085MH221) （2408085MH221）
