Method for automatically extracting gingiva curves of three-dimensional digital dentition model

Abstract

The invention discloses a method for automatically extracting gingiva curves on a three-dimensional digital dentition model. The method comprises the steps of model positioning, gingival feature line search, gingival feature line partitioning and inter-tooth space gingival line interference analysis. The method is high in automatic degree, enclosed gingival curves around each tooth on the dentition model can be constructed rapidly and accurately, the problems of low efficiency, poor accuracy and the like existing in the conventional manual design are solved effectively, and the efficiency and attractiveness of oral rehabilitation are improved.

Description

technical field [0001] The invention belongs to the field of digital design, and relates to technical fields such as computer graphics and biomedical engineering. Background technique [0002] How to accurately obtain the gingival curve shape of each tooth on the patient's dentition model is an important prerequisite for successful oral restoration. Traditional restoration methods need to manually carve wax or plaster models to simulate the gingival curves in harmony with adjacent teeth according to aesthetic requirements and expert experience. However, this method has problems in efficiency and accuracy, especially when the patient has multiple This problem is particularly acute in the case of teeth. [0003] With the rapid development of computers, a large number of dental prosthetic CAD / CAM systems have emerged abroad. However, due to factors such as limited measurement accuracy and mesh reconstruction, on the surface of the 3D digital dentition model obtained by optica...

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Problems solved by technology

Kondo et al. (Kondo T, Ong SH, Foong KW.Tooth Segmentation of Dental Study Models Using Range Images.IEEE Transactions on Medical Imaging, 2004,23(3):350-362) proposed a gingival line extraction method based on depth images. The method first uses the detected tooth feature points in the plane depth image of the triangular mesh model to fit the dental arch line, and expands the dental arch line to calculate the panoramic depth image, then detects the position of the gum line in the plan view and the panoramic view respectively, and finally The results of the two images are combined to determine the segmentation boundary of each tooth; however, since the depth image cannot accurately reflect the three-dimensional information of the tooth, this method may have a large segmentation deviation for the model of severe deformity and interdental interference

Yuan Tianran et al. (YuanT, LiaoW, Dal N, Cheng X, Yu Q. Single-toothmodeling for 3D dental model. Journal of Biomedical Imaging, 2010) from Nanjing University of Aeronautics and Astronautics used morphology and hole repair techniques to extract gingival skeleton lines, and Restores the first-order continuous anatomical shape of each tooth; but the process requires a lot of interactive operations

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