Research On Simulation Of Tooth Root Based On Crown Characteristics

Three-dimensional digital tooth models are widely used in the field of orthodontics,especially the role of three-dimensional digital imaging in the diagnosis,treatment and curative effect prediction of orthodontics.The quality of teeth will affect a person’s temperament and image.Nowadays,people of different ages will have dental diseases or problems.Therefore,the use of computer technology to assist in the diagnosis of dental diseases and the development of computer-assisted simulation correction systems are of great significance to orthodontics.As the current 3D models of teeth are obtained from oral scans,only the crown and gingival surface are part of the tooth,and the root part of the data is lacking,which is not conducive to tooth simulation.In order to help doctors perform virtual orthodontics,this thesis studies the edge characteristics of the crown model,smoothes the crown model,removes edge noise,and can better perform 3D simulation of teeth.And research on how to build a complete tooth model based on the three-dimensional crown data model,the main research contents are as follows:(1)Aiming at the problem of noise points on the edges of 3D dental crown models,this thesis proposed a method for smoothing the edges of teeth based on noise points classification.Firstly,according to the characteristics of the edge of the tooth crown,this method proposed to divide the noise into two types:the noise in the boundary line and the noise in the fitting curve.Then,the Gaussian curvature was used for noise recognition.Finally,the improved Laplacian operator and the least square fitting method were used to remove these two noise points,and the denoised three-dimensional crown model is output.The experimental results show that the method is aimed at the smoothing effect of the crown edge in terms of noise removal rate,patch filling rate,and patch deletion rate.Compared with the traditional Laplacian,the noise removal rate is increased by 86.0%.,The probability of patch filling increases approximately twice,and the probability of deleting patches is basically the same.Compared with the least squares fitting method,the noise removal rate is increased by 75.9%,the patch filling rate is reduced by 22.61%,and the deleted patch is also reduced by 22.14%.(2)Because the three-dimensional dental model of the oral scan lacks root data,the complete three-dimensional tooth model is related to the results of the doctor’s tooth arrangement,implantation,orthodontics and biomechanical analysis.Therefore,this thesis proposed a simulation method of tooth root based on the characteristics of the crown.Firstly,this method simulated the two types of tooth roots as single root and multiple roots respectively,divided the single root and multiplerootteeth into segments,and designed different simulation schemes for each segment Then,for multi-root simulation,based on the spatial distribution of multi-root roots and the intersection characteristics of spatial curves,a method for multi-root root selection based on geometric features and a curve fusion method for improving fast intersection selection are proposed.The roots are selected according to the number of roots,and the root simulation is completed.Finally,the machine learning method was used to learn the characteristics of the surface of the real crown model and transfer the style of the root,so that the simulation effect of the tooth is closer to the real tooth.This method compared single root and multiple roots before and after simulation treatment in terms of crown-to-root ratio and roughness,and compares the effects before and after the style transfer.Experimental results showthat the tooth root model constructed in this thesis is very close to real teeth.