CBCT and laser scanning point cloud data tooth registration method based on supervoxels

Abstract

The invention provides a CBCT and laser scanning point cloud data tooth registration method based on supervoxels. The method comprises the following steps: firstly, extracting a tooth model from oralcavity CBCT scanning data according to a region growing method; secondly, processing the tooth model by using a laser scanner, and separating a dental crown in the tooth model from abutment teeth according to the characteristics of the teeth; converting the tooth models from different sources into tooth point cloud data, adding color information to the tooth point cloud data to assist initial geometric alignment of the tooth point cloud, and realizing down-sampling of the point cloud based on a super voxel method; and finally, constructing an alignment metric, and proposing a mutual corresponding matching condition based on the mixed characteristics; two pieces of tooth point cloud data with color information are registered from different angles; according to the method, tooth registrationof different resolutions can be achieved, tooth color information is manually added, the registration precision is improved, the registration time is saved, and a complete tooth model capable of being used for implantation and orthognathic surgery is constructed.

Description

Technical field[0001]The invention relates to the technical field of medical image processing, in particular to a tooth registration method based on supervoxel-based CBCT and laser scanning point cloud data.Background technique[0002]A complete and accurate three-dimensional dental model is a necessary prerequisite for dental implant or orthognathic surgery planning. The doctor can have a deeper understanding of the three-dimensional spatial position of the patient's lesion through the three-dimensional model. The intraoral images taken by CBCT data include the anatomical structures of three visual planes (sagittal, coronal and lateral). It is a commonly used dental model visualization method in digital orthodontic software, but due to its accuracy, slice thickness, and metal artifacts During the filming process, the patient’s teeth are in occlusal state, and the upper and lower crowns are difficult to separate, resulting in low crown surface accuracy. Surface optical scanners have b...

AI Technical Summary

Problems solved by technology

[0004] At present, most of the improved ICP algorithms have some common defects: 1. Focus on pure geometric features, ignoring important color features

; 2. For manual extraction of feature points, human interference factors are large, while for automatic feature point selection, the algorithm is more complicated and the time utilization rate is not high; 3. Only for rigid body transformation, no scale transformation parameters are introduced, and the size and resolution cannot be solved Registration of 2 similar objects with discrepancies; color-based methods have received a lot of attention in recent years

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