国际口腔医学杂志2026，Vol.53Issue(5)：615-623,9.DOI:10.7518/gjkq.2026628
三维颅颌面软硬组织智能头影测量分析的研究进展
Research progress in the intelligent cephalometric analysis of three-dimensional craniomaxillofacial soft and hard tissues
摘要
Abstract
In recent years,deep learning has achieved remarkable advances in medical image analysis.Automated land-mark identification and cephalometric analysis of craniofacial hard and soft tissues are key components of three-dimen-sional(3D)craniofacial assessment.These techniques have shown great potential for improving measurement efficiency,reducing interobserver variability,and supporting personalized diagnosis and treatment planning.This article reviews the development of two-dimensional automated cephalometric analysis and summarizes recent progress in deep learning-based methods for 3D automated landmark identification and cephalometric analysis of craniofacial hard and soft tissues.Major challenges are discussed,including the lack of standardized measurement protocols,dependence on large annotated datasets,limited model generalizability,and insufficient clinical interpretability.Future perspectives are also presented,with a focus on the establishment of large-scale clinical databases,the development of standardized measure-ment systems,and the application of multimodal and multitask models for clinical decision support.This re-view aims to provide a reference for future research and clinical translation of 3D automated craniofacial land-mark identification and cephalometric analysis.关键词
三维头影测量/颅颌面结构/自动定点/深度学习/口腔正畸学Key words
three-dimensional cephalometry/craniomaxillofacial structure/automatic landmark detection/deep learning/orthodontics分类
医药卫生引用本文复制引用
刘璐玮,严斌..三维颅颌面软硬组织智能头影测量分析的研究进展[J].国际口腔医学杂志,2026,53(5):615-623,9.基金项目
National Key Research and Development Program of China(2023YFC2413605) （2023YFC2413605）
International Coopera-tion Project of Jiangsu Science and Technology Key R&D Plan(BZ2023042) （BZ2023042）
National Online Course Research Project for Graduate Students in Medicine and Pharmacy(2024-28) 国家重点研发计划课题(2023YFC2413605) （2024-28）
江苏省科技重点研发计划国际合作项目(BZ2023042) （BZ2023042）
全国医药学研究生在线课程建设与教学研究课题(2024-28) （2024-28）
