[Advances in algorithms for three-dimensional craniomaxillofacial features construction based on point clouds].

In light of the increasing digitalization of dentistry, the automatic determination of three-dimensional (3D) craniomaxillofacial features has become a development trend. 3D craniomaxillofacial landmarks and symmetry reference plane determination algorithm based on point clouds has attracted a lot of attention, for point clouds are the basis for virtual surgery design and facial asymmetry analysis, which play a key role in craniomaxillofacial surgery and orthodontic treatment design. Based on the studies of our team and national and international literatures, this article presented the deep geometry learning algorithm to determine landmarks and symmetry reference plane based on 3D craniomaxillofacial point clouds. In order to provide reference for future clinical application, we describe the development and latest research in this field, and analyze and discuss the advantages and limitations of various methods.点云数据是口腔虚拟手术设计、颜面不对称分析等环节的基础，颅颌面三维特征在口腔颌面外科、正畸矫治设计中发挥关键作用。随着口腔数字化技术临床应用的普及，颅颌面三维特征的自动化构建成为研究发展趋势，因而基于颅颌面点云数据的三维解剖标志点定点和对称参考平面构建算法备受关注。本文结合笔者团队研究及国内外研究进展，论述基于颅颌面点云数据，构建解剖标志点和对称参考平面特征的数学算法和深度学习算法，阐述该领域的发展历程和最新研究进展，分析探讨各种方法的优势及局限，以期为口腔临床研究和应用提供参考。.