CN112862974B - Tooth veneering model generation and thickness measurement method based on oral cavity scanning point cloud - Google Patents
Tooth veneering model generation and thickness measurement method based on oral cavity scanning point cloud Download PDFInfo
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- 230000036346 tooth eruption Effects 0.000 claims abstract description 34
- 238000013461 design Methods 0.000 claims abstract description 13
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Abstract
The invention discloses a tooth veneering model generation and thickness measurement method based on an oral scanning point cloud, which comprises the following steps of: 1) Modifying a target tooth on the tooth to be treated by using the preoperative dentition scanning model of the oral cavity of the patient to obtain a target dentition model of the patient, and then converting the preoperative dentition scanning model and the modified target dentition model into point clouds; 2) After converting the two points into point clouds, carrying out point cloud registration according to the unchanged parts of the two points, and superposing the target teeth on the corresponding tooth positions; 3) Making a difference between the two point clouds, and finally obtaining an increment part of the tooth through back cover; 4) Reconstructing the increment part of the tooth, filling holes on the reconstructed model surface, and obtaining a smooth-surface faced three-dimensional model; 5) And (5) performing thickness measurement on the veneering point cloud to remind a doctor to correct the veneering design. The invention can greatly improve the tooth preparation efficiency and reduce the communication difficulty and contradiction between doctors and patients.
Description
Technical Field
The invention belongs to the field of digital computer aided design of tooth veneering restoration, and particularly relates to a tooth veneering model generation and thickness measurement method based on an oral cavity scanning point cloud.
Background
Veneering repair is a repair method in which a prosthesis is fixed to the labial surface of a diseased tooth by an adhesive material so as to cover the labial surface defect of the anterior tooth. For veneering restoration, the traditional dental procedure includes: firstly, dental surface treatment and veneering treatment. And secondly, data acquisition is carried out, and the tooth morphology is carried out before operation. Thirdly, manufacturing a diagnosis wax type and shape guide plate to conduct doctor-patient preoperative communication. Fourth, patient condition permissive, propose to make the diagnosis temporary crown by self-coagulation before preparing teeth, let patient try on for 1-2 weeks, give patient's friendly to see effect. After the temporary crown is tried over the adaptation period, the temporary crown is communicated with the patient, and a satisfactory, clear and effective manufacturing scheme for the patient is formulated. Fifthly, after tooth preparation, checking by using the shape guide plate. Sixth, the upper veneers are required to be simultaneously positioned, and each veneer is bonded and retained by a very small adhesive before the veneers begin to be bonded one by one.
With the development of three-dimensional oral scanning technology, the acquisition of digital impressions of the craniomaxillofacial of an intraoral machine of a patient by a portable oral scanner has been gradually applied to the field of stomatology. The repairing doctor can truly restore the morphological characteristics of the craniomaxillofacial and the labia of the patient in a three-dimensional virtual form by acquiring the scanning data of the oral and facial of the patient and utilizing aesthetic design software such as digital smile design and the like to predictively design the repairing body according to the aesthetic repairing principle of the anterior teeth, thereby achieving the aesthetic repairing effect of the anterior teeth which is easier for both sides of the doctor and the patient to communicate. Compared with the traditional tooth preparation process, the digital design of tooth veneering restoration is performed through the computer-aided design, so that the tooth preparation efficiency can be greatly improved, and the communication difficulty and contradiction between doctors and patients are reduced.
On the basis that doctors carry out front tooth aesthetic restoration design through oral cavity scanning point cloud, automatic generation of a digital model of tooth veneers through a point cloud processing algorithm and a model reconstruction algorithm is an important link for opening an automatic process from aesthetic restoration design to veneering manufacture. The generated veneering digital model can be used for 3D printing after being further processed, and finally the assembled veneering material is obtained. The veneering thickness measurement is helpful to provide prompts in the design process of doctors, so that the situations of wearing damage or incapability caused by excessively thin or excessively thick local veneering models are avoided.
Through paper and patent research, certain achievements exist in the aspects of hardware devices and control systems of oral cavity scanning equipment at present, but no achievements in the aspect of tooth veneer digital model generation are involved. Li Zongxi the Chinese patent "oral scanner control method and oral scanning device" (application No. 201810144955.2) is issued. The invention discloses an oral cavity scanning device and a scanning device control method, which do not relate to the processing of scanning point clouds. Liu Weicai et al filed a Chinese patent application for "method for matching oral scan results to faces" (application number 202010894616.3), and accepted. The patent of the invention discloses a method for matching an oral scanning result and a facial scanning result, which does not relate to the problem of generating a digital model of tooth veneering.
Disclosure of Invention
In order to solve the problems, the invention discloses a method for generating a tooth veneering model and measuring the thickness based on an oral scanning point cloud, which improves the tooth restoration design and the tooth preparation efficiency and reduces the communication difficulty and contradiction between doctors and patients.
In order to achieve the above purpose, the technical scheme of the invention is as follows:
a tooth veneering model generation and thickness measurement method based on an oral cavity scanning point cloud comprises the following steps:
step 1, obtaining a preoperative dentition scanning model of the oral cavity of a patient through a portable oral scanner, modifying the model on one or more teeth to be treated by an oral doctor to obtain a target dentition model, and converting the preoperative dentition scanning model and the modified target dentition model into point clouds.
And 2, after converting the two points into point clouds, carrying out point cloud registration according to the unchanged parts of the two points, and superposing the target teeth on the corresponding tooth positions.
And 3, performing difference operation on the two point clouds through the phase difference operation between the point clouds, and finally obtaining the increment part of the tooth through back cover.
And 4, reconstructing the increment part of the tooth by using a surface reconstruction algorithm, filling holes on the surface of the increment part, and obtaining the veneering three-dimensional digital model with a smooth surface.
And 5, measuring the thickness of the point cloud corresponding to the veneering, and reminding a doctor to correct the veneering design. And calculating a 3D bounding box of the point cloud by adopting an AABB method, and obtaining the main direction of the veneering. And finding a projection plane orthogonal to the main direction, projecting the veneers onto the projection plane layer by layer from top to bottom, calculating the thickness of the veneers through the two-dimensional profile obtained after each layer of projection, rendering the points on the surface of the veneers with color scales, and enabling the color of each point to correspond to the thickness normalization value at the point.
Further, the registration method in step 2 adopts a two-step registration algorithm from coarse to fine. The coarse registration adopts a Super4PCS algorithm to estimate an initial registration matrix, reduces dislocation among point clouds to be registered, and the accurate registration adopts an ICP algorithm to finely adjust the registration matrix, so that alignment errors of the two point clouds are minimum.
Further, in the step 3, the phase difference operation between the dentition point cloud containing the target teeth and the preoperative dentition scanning point cloud is performed to obtain a non-closed point cloud formed by only enclosing the two origin cloud surfaces, so that the point cloud needs to be subjected to back cover to obtain the increment part corresponding to the veneering.
Further, the surface reconstruction algorithm adopted in the step 4 is a greedy triangle reconstruction algorithm, and the output is an STL model with small holes, so that the hole removal process of the next step is required.
Further, in step 5, the veneering thickness is calculated by the two-dimensional contour obtained after projection of each layer, which includes two calculation bases. And firstly, a horizontal distance method is adopted, namely, a horizontal line is found, an intersection point of the horizontal line and the left and right boundaries of the two-dimensional projection contour of the veneering is calculated, and the distance between the two points is calculated. And secondly, refining the shape of the two-dimensional projection contour of the veneering to obtain a framework, traversing sampling points on the framework, calculating a tangent line on each sampling point, and calculating the distance between the tangent line and the intersection point of the left boundary and the right boundary of the two-dimensional projection contour of the veneering.
Further, in step 5, the doctor is reminded to correct the veneering design, that is, the thickness threshold is set, and a specific color is rendered for the point cloud exceeding the over-thickness threshold or exceeding the over-thin threshold, so that the reminding effect is achieved.
Further, the dental row point cloud containing the target teeth in the step 3 includes both the modified dental point cloud and other dental point clouds without modification.
Further, the data formats of the preoperative dentition scanning model and the target dentition model in the steps 1, 2 and 3 are STL files, and the data formats of the preoperative dentition scanning point cloud and the target dentition point cloud are OBJ files.
The beneficial effects of the invention are as follows:
the invention discloses a tooth veneering model generation and thickness measurement method based on an oral scanning point cloud, which is characterized in that for a preoperative dentition scanning model and a modified target dentition model which are needed for generating tooth veneers, the two models are not needed to be registered manually, an algorithm automatic registration mode is adopted, so that the registration time is greatly saved, and the registration effect is more accurate than that of manual registration.
And reconstructing the surface of the partial point cloud of the dentition increment obtained by the difference to obtain an STL model for generating subsequent tooth veneers, and compared with the prior art, adding a hole filling function to ensure that the obtained model is smoother.
The automatically generated dental veneer can be fed back to the practitioner in areas of partial over-thinness or over-thickness, thereby assisting the practitioner in improving the dental veneer design. The physician can further process the veneering digital model and 3D print to finally obtain the fittable veneering material.
Drawings
FIG. 1 is an overall flow chart of an implementation of the present invention;
FIG. 2 is an effect diagram after point cloud registration;
FIG. 3 is an effect diagram of partial surface reconstruction of a point cloud delta;
FIG. 4 is a graph showing the effect of a dentition scanning model before veneering, after veneering registration;
FIG. 5 is a bounding box and principal axis of a faced point cloud;
FIG. 6 is a two-dimensional profile effect of a cloud of points in the overlay projected onto a projection surface;
fig. 7 is a veneering over-thin area cue.
Detailed Description
The present invention is further illustrated in the following drawings and detailed description, which are to be understood as being merely illustrative of the invention and not limiting the scope of the invention.
As shown in fig. 1, the invention discloses a tooth veneering model generation and thickness measurement method based on an oral scanning point cloud, which mainly comprises five steps:
and step 1, converting the preoperative dentition scanning model and the target dentition model into point clouds.
The method comprises the steps of obtaining a preoperative dentition scanning model of a patient oral cavity through a portable oral cavity scanner, modifying the model on one or more teeth to be treated by an oral cavity doctor to obtain a target dentition model, and converting the preoperative dentition scanning model and the modified target dentition model into point clouds.
And 2, registering the point clouds.
After the two are converted into point clouds, point cloud registration is carried out according to the unchanged parts of the two, and target teeth are overlapped on the corresponding tooth positions. Because the accurate point cloud registration algorithm has higher requirements on the initial position of the point cloud to be registered, the point cloud splicing is generally completed by adopting a method of initial registration and then accurate registration. The coarse registration adopts Super4PCS algorithm to estimate initial registration matrix, and reduces dislocation between point clouds to be registered. The Super4PCS algorithm reduces the generation of invalid pairs when the traditional algorithm searches for matching through an optimization algorithm on the basis of the traditional 4PCS algorithm, so that the algorithm execution speed is increased. The accurate registration adopts ICP algorithm to fine tune the registration matrix, so that the alignment error of two point clouds is minimum. For a target point cloud P and a source point cloud Q of a point pair to be matched, an ICP algorithm finds the nearest neighbor point (P) through iteration under a certain constraint condition i ，q i ) Then, optimal matching parameters R and t are calculated so that the error function is minimized. The error function is E (R, t) is:
where n is the number of nearest neighbor point pairs, p i Q is a point in the target point cloud P i For the AND p in the source point cloud Q i The corresponding nearest point, R is the rotation matrix and t is the translation vector.
And step 3, obtaining an increment part by the point cloud difference.
The point cloud difference comprises a phase difference operation and a back cover operation. The phase difference operation of the two point clouds obtains a non-closed point cloud formed by enclosing the two original point cloud surfaces, and then the point cloud is subjected to back cover to obtain an increment part of the corresponding veneering, namely an incisor virtual shadow part indicated by an arrow in fig. 2 is an increment part of the corresponding veneering.
And 4, reconstructing the increment part of the tooth by using a surface reconstruction algorithm.
The veneering incremental reconstruction is a greedy triangular algorithm reconstruction algorithm, a sample triangular plate is selected as an initial curved surface, the boundary of the curved surface is continuously expanded, a complete triangular mesh curved surface is finally formed, topological connection among original three-dimensional points is finally determined according to the connection relation of projection point clouds, the obtained triangular mesh is the curved surface model obtained through reconstruction, and the triangular mesh curved surface model is shown in figure 3.
And filling holes on the surface of the model obtained after reconstruction to obtain a faced three-dimensional model with a smooth surface. Fig. 4 shows a smooth veneered three-dimensional model and an effect map of the registration of the veneered model on a dentition model.
And 5, measuring the thickness of the point cloud corresponding to the veneering, and reminding a doctor to correct the veneering design.
And calculating a 3D bounding box of the point cloud by adopting an AABB method, and obtaining the main direction of the veneering. And then, the veneers are rotationally corrected according to the main direction, so that the main direction is parallel to the z axis, and the thickness direction is parallel to the y axis, thereby facilitating thickness measurement. A projection plane is found orthogonal to the main direction, onto which the overlay is projected layer by layer from top to bottom, as shown in fig. 5.
The overlay thickness was calculated from the two-dimensional profile obtained after projection of each layer, including two calculation bases, as shown in fig. 6. And firstly, a horizontal distance method is used for calculating an intersection point of the horizontal line and the left and right boundaries of the two-dimensional projection contour of the veneering by taking the thickness direction obtained by the AABB method as the horizontal line and calculating the distance between the two points. And secondly, refining the shape of the two-dimensional projection contour of the veneering to obtain a framework, traversing sampling points on the framework, calculating a tangent line on each sampling point, and calculating the distance between the tangent line and the intersection point of the left boundary and the right boundary of the two-dimensional projection contour of the veneering. And rendering the points of the surface of the veneer into color scales, wherein the color of each point corresponds to the thickness normalized value at the point. And finally, setting a thickness threshold, and rendering a specific color or circling an excessively thin area for the point cloud exceeding the excessively thick threshold so as to achieve the reminding effect, as shown in fig. 7.
Claims (8)
1. The method for generating and measuring the thickness of the tooth veneering model based on the oral cavity scanning point cloud is characterized by comprising the following steps of: comprising the following steps:
step 1, obtaining a preoperative dentition scanning model of a patient oral cavity through a portable oral cavity scanner, modifying the model on one or more teeth to be treated by an oral cavity doctor to obtain a target dentition model, and converting the preoperative dentition scanning model and the modified target dentition model into point clouds;
step 2, after converting the two points into point clouds, carrying out point cloud registration according to the unchanged parts of the two points, and superposing the target teeth on the corresponding tooth positions;
step 3, performing difference operation on the two point clouds through phase difference operation between the point clouds, and finally obtaining an increment part of the tooth through back cover;
step 4, reconstructing the increment part of the tooth by using a surface reconstruction algorithm, filling holes on the surface of the increment part to obtain a veneering three-dimensional digital model with a smooth surface;
step 5, measuring the thickness of the point cloud corresponding to the veneering, and reminding a doctor to correct the veneering design; calculating a 3D bounding box of the point cloud by adopting an AABB method to obtain a main direction of veneering; and finding a projection plane orthogonal to the main direction, projecting the veneers onto the projection plane layer by layer from top to bottom, calculating the thickness of the veneers through the two-dimensional profile obtained after each layer of projection, rendering the points on the surface of the veneers with color scales, and enabling the color of each point to correspond to the thickness normalization value at the point.
2. The method for generating and measuring thickness of dental veneering model based on cloud of oral scan points according to claim 1, wherein the registration algorithm in step 2 is a two-step registration algorithm from coarse to fine:
the coarse registration adopts Super4PCS algorithm to estimate initial registration matrix, reduces dislocation between point clouds to be registered,
the accurate registration adopts ICP algorithm to fine tune the registration matrix, so that the alignment error of two point clouds is minimum.
3. The method for generating and measuring the thickness of a dental veneer model based on an oral scanning point cloud according to claim 1, wherein in the step 3, the phase difference operation between the dental line point cloud containing the target tooth and the preoperative dental line scanning point cloud can only obtain a non-closed point cloud surrounded by two origin cloud surfaces, and the incremental part of the corresponding veneer can be obtained only by sealing the point cloud.
4. The method for generating and measuring thickness of a dental veneering model based on an oral scanning point cloud according to claim 1, wherein the veneering incremental reconstruction in step 4 is a reconstruction algorithm using a greedy trigonometric algorithm, and the closed veneers are built with triangular meshes, namely the curved surface model is obtained by reconstruction.
5. The method for generating and measuring the thickness of a dental veneer model based on an oral scanning point cloud according to claim 1, wherein the step 5 of calculating the veneer thickness from the two-dimensional contour obtained after each layer of projection comprises two calculation bases: firstly, a horizontal distance method is adopted, namely a horizontal line is found, an intersection point of the horizontal line and the left and right boundaries of the veneering two-dimensional projection profile is calculated, and the distance between the two points is calculated; and secondly, refining the shape of the two-dimensional projection contour of the veneering to obtain a framework, traversing sampling points on the framework, calculating a tangent line on each sampling point, and calculating the distance between the tangent line and the intersection point of the left boundary and the right boundary of the two-dimensional projection contour of the veneering.
6. The method for generating and measuring tooth veneering model based on oral scanning point cloud as in claim 1, wherein in step 5, the step of reminding the doctor to correct the veneering design is to set a veneering thickness threshold, and to render a specific color for the point cloud exceeding the excessive thickness threshold or exceeding the excessive thickness threshold, thereby achieving the reminding effect.
7. The method for generating and measuring thickness of dental veneer model based on oral scanning point cloud as claimed in claim 3, wherein said target tooth-containing dentition point cloud comprises both modified tooth point cloud and other tooth point cloud without modification.
8. The dental veneering model generating and thickness measuring method based on the oral scanning point cloud according to claim 1, wherein the data format of the preoperative dentition scanning model and the target dentition model is an STL file, and the data format of the preoperative dentition scanning point cloud and the target dentition point cloud is an OBJ file.
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| CN105447908A (en) * | 2015-12-04 | 2016-03-30 | 山东山大华天软件有限公司 | Dentition model generation method based on oral cavity scanning data and CBCT (Cone Beam Computed Tomography) data |
| CN112200843A (en) * | 2020-10-09 | 2021-01-08 | 福州大学 | CBCT and laser scanning point cloud data tooth registration method based on hyper-voxels |
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| CN105447908A (en) * | 2015-12-04 | 2016-03-30 | 山东山大华天软件有限公司 | Dentition model generation method based on oral cavity scanning data and CBCT (Cone Beam Computed Tomography) data |
| CN112200843A (en) * | 2020-10-09 | 2021-01-08 | 福州大学 | CBCT and laser scanning point cloud data tooth registration method based on hyper-voxels |
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