Abstract

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.

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