CN112862974A - Tooth veneering model generation and thickness measurement method based on oral scanning point cloud - Google Patents
Tooth veneering model generation and thickness measurement method based on oral scanning point cloud Download PDFInfo
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Abstract
The invention discloses a tooth veneering model generation and thickness measurement method based on oral scanning point cloud, which comprises the following steps: 1) modifying a target tooth on a tooth to be treated by using a preoperative dentition scanning model of an oral cavity of a patient to obtain a target dentition model of the tooth, and converting the preoperative dentition scanning model and the modified target dentition model into point cloud; 2) after the two are converted into point clouds, point cloud registration is carried out according to the invariant parts of the two, and the target teeth are superposed on the corresponding tooth positions; 3) performing difference on the two point clouds, and finally obtaining the increment part of the tooth through bottom sealing; 4) reconstructing the incremental part of the tooth, and filling holes on the surface of the reconstructed model to obtain a veneering three-dimensional model with a smooth surface; 5) and (4) 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 oral scanning point cloud.
Background
Veneering restoration is a restoration method of fixing a restoration to the labial surface of a diseased tooth through an adhesive material to cover the defects of the labial surface of the anterior tooth. For veneered restorations, the traditional process of preparing teeth includes: firstly, the dental face treatment and the veneering treatment. Secondly, data acquisition and preoperative tooth morphology are carried out. Thirdly, a diagnosis wax pattern and an appearance guide plate are manufactured to carry out communication before doctors and patients. Fourth, the patient condition allowed advises that a diagnosis temporary crown is made by self-coagulation before preparing teeth, and the patient tries to wear the temporary crown for 1-2 weeks to see the effect of the patient. After the temporary crown is tried on and used for passing the adaptation period, the temporary crown is communicated with the patient, and a satisfactory, clear and effective manufacturing scheme for the patient is made. Fifthly, after tooth preparation, the appearance guide plate is used for inspection. Sixth, bonding requires that the veneers on the dentition be simultaneously positioned, and bonding each veneer with minimal adhesive is performed before bonding one by one.
With the development of oral three-dimensional scanning technology, the digital impression of the craniomaxillofacial part of the internal organs of a patient obtained by a portable oral scanner is gradually applied to the field of oral prosthetics. A repairing doctor obtains scanning data of the mouth and the face of a patient, and utilizes aesthetic design software such as digital smile design and the like to carry out predictive design on a repairing body according to an aesthetic repairing principle of the front teeth, so that morphological characteristics of the craniomaxillofacial part and the lips of the patient can be truly restored in a three-dimensional virtual form, and the aesthetic repairing effect of the front teeth which is easier for communication between doctors and patients is achieved. Compared with the traditional tooth preparation process, the digital design of the tooth veneering restoration is carried out through computer aided design, the tooth preparation efficiency can be greatly improved, and the communication difficulty and contradiction between doctors and patients are reduced.
On the basis that a doctor carries out aesthetic restoration design of anterior teeth through oral scanning point cloud, a digital model of tooth veneering is automatically generated through a point cloud processing algorithm and a model reconstruction algorithm, and the method is an important link for getting through from the aesthetic restoration design to the veneering manufacturing automation process. The generated veneering digital model can be further processed and then used for 3D printing, and finally the veneering material capable of being assembled is obtained. The overlay thickness measurement is helpful for providing prompts in the design process of doctors, so that wearing damage or wearing incapability caused by local over-thinness or over-thickness of the generated overlay model can be avoided.
Through papers and patent research, certain achievements exist in the aspects of hardware devices and control systems of oral cavity scanning equipment at present, but the achievements in the aspect of generation of a digital model of tooth veneering are not related. The Lizong has applied for the Chinese invention patent of "oral cavity scanner control method and oral cavity scanning device" (application number 201810144955.2), which has been granted patent. 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. Liuwei et al filed the Chinese patent of invention "oral cavity scanning results and face matching method" (application No. 202010894616.3), and accepted it. The invention discloses a method for matching an oral cavity scanning result and a facial scanning result, which does not relate to the problem of generation of a digital model of tooth veneering.
Disclosure of Invention
In order to solve the problems, the invention discloses a tooth veneering model generation and thickness measurement method based on oral scanning point cloud, which improves tooth restoration design and tooth preparation efficiency and reduces communication difficulty and contradiction between doctors and patients.
In order to achieve the purpose, the technical scheme of the invention is as follows:
the tooth veneering model generation and thickness measurement method based on the oral scanning point cloud comprises the following steps:
step 1, obtaining a preoperative dentition scanning model of a patient oral cavity through a portable oral scanner, modifying target teeth on one or more teeth to be treated by using the model through an oral physician to obtain a target dentition model, and converting the preoperative dentition scanning model and the modified target dentition model into point cloud.
And 2, converting the two into point clouds, performing point cloud registration according to the invariant parts of the two, and superposing the target tooth on the corresponding tooth position.
And 3, performing difference operation on the two point clouds through the phase difference operation between the point clouds, and finally obtaining the incremental part of the tooth through bottom sealing.
And 4, reconstructing the incremental part of the tooth by using a surface reconstruction algorithm, and filling holes in the surface of the incremental part to obtain a 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 of correcting the veneering design. And calculating a 3D bounding box of the point cloud by adopting an AABB method to obtain the main direction of the veneering. Finding a projection plane orthogonal to the main direction, projecting the veneers to the projection plane layer by layer from top to bottom, calculating the thickness of the veneers through a two-dimensional contour obtained after each layer of projection, rendering points on the surfaces of the veneers into a color gradation, wherein the color of each point corresponds to the thickness normalization value of the point.
Further, the registration method in step 2 is to use a two-step registration algorithm from coarse to fine. The initial registration matrix is estimated by adopting a Super4PCS algorithm in the coarse registration, the dislocation between the point clouds to be registered is reduced, and the registration matrix is finely adjusted by adopting an ICP algorithm in the accurate registration, so that the alignment error of the two point clouds is minimum.
Further, in the step 3, a non-closed point cloud which is only formed by enclosing two origin cloud surfaces is obtained through phase difference operation between the dentition point cloud containing the target teeth and the preoperative dentition scanning point cloud, and therefore the point cloud needs to be bottomed to obtain the corresponding veneering increment part.
Further, the surface reconstruction algorithm adopted in the step 4 is a greedy triangle reconstruction algorithm, and an STL model with small holes is output, so that hole removal processing in the next step is required.
Further, the calculation of the thickness of the overlay by the two-dimensional profile obtained after the projection of each layer in step 5 includes two calculation bases. The first is a horizontal distance method, namely finding a horizontal line, calculating an intersection point of the horizontal line and the left and right boundaries of the veneering two-dimensional projection outline, and calculating the distance between the two points. Secondly, thinning the shape of the veneering two-dimensional projection outline to obtain a framework, traversing sampling points on the framework, calculating a tangent at each sampling point, and calculating the distance between the tangent and the intersection point of the left boundary and the right boundary of the veneering two-dimensional projection outline.
Furthermore, in the step 5, the physician is reminded to correct the veneering design by setting a thickness threshold value and rendering a specific color for the point cloud exceeding the over-thick threshold value or exceeding the over-thin threshold value, so that the reminding effect is achieved.
Further, the dentition point cloud containing the target tooth in the step 3 includes both the modified tooth point cloud and other tooth point clouds without modification.
Further, the data formats of the preoperative dentition scanning model and the target dental 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 dental point cloud are OBJ files.
The invention has the beneficial effects that:
the invention discloses a tooth overlay model generation and thickness measurement method based on oral scanning point cloud, and for a preoperative dentition scanning model and a modified target dentition model required for generating tooth overlay, the preoperative dentition scanning model and the modified target dentition model do not need to be manually registered, but an algorithm automatic registration mode is adopted, so that the registration time is greatly saved, and the registration effect is more accurate than manual registration.
And reconstructing the surface of the dentition increment part point cloud obtained by difference to obtain an STL model for generating subsequent tooth veneering, and compared with the prior art, increasing the hole filling function to ensure that the obtained model is smoother.
The automatically generated locally too thin or too thick areas of the dental overlay can be fed back to the practitioner, thereby assisting the practitioner in improving the dental overlay design. The medical practitioner can further process and 3D print the overlay digital model to obtain the final assembled overlay material.
Drawings
FIG. 1 is an overall flow chart of the practice of the present invention;
FIG. 2 is an effect diagram after point cloud registration;
FIG. 3 is a graph of the effect of point cloud incremental partial surface reconstruction;
FIG. 4 is a diagram of the effects of the dentition scan model before veneering, after veneering registration and after veneering;
FIG. 5 is a bounding box and principal axes of a veneered point cloud;
FIG. 6 is a two-dimensional contour effect obtained by projecting a point cloud of a certain layer of veneers to a projection plane;
fig. 7 is a close-up over-thinning area cue.
Detailed Description
The present invention will be further illustrated with reference to the accompanying drawings and specific embodiments, which are to be understood as merely illustrative of the invention and not as limiting the scope of the invention.
As shown in figure 1, the invention discloses a tooth veneering model generation and thickness measurement method based on oral scanning point cloud, which mainly comprises five steps:
step 1, converting a preoperative dentition scanning model and a target dentition model into point cloud.
Obtaining a preoperative dentition scanning model of the oral cavity of a patient through a portable oral scanner, modifying target teeth on one or more teeth to be treated by using the model through an oral physician to obtain a target dentition model, and converting the preoperative dentition scanning model and the modified target dentition model into point cloud.
And 2, point cloud registration.
And after the two are converted into point clouds, point cloud registration is carried out according to the invariant parts of the two, and the target teeth are superposed on the corresponding tooth positions. Because the requirement of the point cloud accurate registration algorithm on the initial position of the point cloud to be registered is high, the point cloud registration is generally completed by adopting a method of initial registration and then accurate registration. And the initial registration matrix is estimated by adopting a Super4PCS algorithm in the coarse registration, and the dislocation among the point clouds to be registered is reduced. The Super4PCS algorithm reduces the generation of invalid pairs when the traditional algorithm searches for matching pairs through an optimization algorithm on the basis of the traditional 4PCS algorithm, thereby accelerating the execution speed of the algorithm. The accurate registration adopts an ICP algorithm to fine tune a registration matrix, so that the alignment error of the 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 (inductively coupled plasma) algorithm finds out the nearest neighbor point (P) through iteration under certain constraint conditionsi，qi) Then, thenAnd calculating optimal matching parameters R and t to minimize an error function. The error function is E (R, t) is:
where n is the number of nearest neighbor point pairs, piFor a point in the target point cloud P, qiIs the source point in cloud Q and piAnd R is a rotation matrix and t is a translation vector.
And 3, carrying out point cloud subtraction to obtain an increment part.
The point cloud difference making comprises phase difference operation and bottom sealing operation. And performing phase difference operation on the two point clouds to obtain a non-closed point cloud surrounded by the two original point cloud surfaces, and then performing bottom sealing on the point cloud to obtain an incremental part corresponding to the veneering, wherein the door tooth ghost part indicated by an arrow in fig. 2 is the incremental part corresponding to the veneering.
And 4, reconstructing the incremental part of the tooth by using a surface reconstruction algorithm.
The veneering incremental reconstruction is a reconstruction algorithm by utilizing a greedy triangle algorithm, the method comprises the steps of selecting a sample triangular plate as an initial curved surface, continuously expanding the boundary of the curved surface, finally forming a complete triangular mesh curved surface, finally determining topological connection among original three-dimensional points according to the connection relation of projection point clouds, obtaining a triangular mesh which is a reconstructed curved surface model, and obtaining the triangular mesh curved surface model as shown in figure 3.
And filling holes in the surface of the model obtained after reconstruction to obtain a veneering three-dimensional model with a smooth surface. Fig. 4 shows the smooth veneered three-dimensional model and the effect graph of the veneered model registered on the dentition model.
And 5, measuring the thickness of the point cloud corresponding to the veneering, and reminding a doctor of correcting the veneering design.
And calculating a 3D bounding box of the point cloud by adopting an AABB method to obtain the main direction of the veneering. Then, the veneers are corrected in a rotating mode according to the main direction, so that the main direction is parallel to the z axis, the thickness direction is parallel to the y axis, and thickness measurement is facilitated. A projection plane is found which is orthogonal to the main direction and the veneers are projected layer by layer from top to bottom onto this projection plane as shown in fig. 5.
The thickness of the overlay is calculated by the two-dimensional profile obtained after the projection of each layer, and two calculation bases are included, as shown in fig. 6. The first is a horizontal distance method, in which the thickness direction obtained by the AABB method is used as a horizontal line, the intersection point where the horizontal line intersects with the left and right borders of the two-dimensional projection outline of the overlay is calculated, and the distance between the two points is calculated. Secondly, thinning the shape of the veneering two-dimensional projection outline to obtain a framework, traversing sampling points on the framework, calculating a tangent on each sampling point, and calculating the distance between intersection points of the tangent and the left and right boundaries of the veneering two-dimensional projection outline. And rendering points of the veneering surface into color scales, wherein the color of each point corresponds to the thickness normalization value at the point. Finally, a thickness threshold is set, and a specific color is rendered for the point cloud exceeding the over-thick threshold or an over-thin area is circled, so that the reminding effect is achieved, as shown in fig. 7.
Claims (8)
1. A tooth veneering model generation and thickness measurement method based on oral scanning point cloud is characterized in that: the method comprises the following steps:
step 1, obtaining a preoperative dentition scanning model of a patient oral cavity through a portable oral scanner, modifying target teeth on one or more teeth to be treated by using the model through an oral physician to obtain a target dentition model, and converting the preoperative dentition scanning model and the modified target dentition model into point cloud;
step 2, after the two are converted into point clouds, point cloud registration is carried out according to the invariant parts of the two, and the target teeth are superposed 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 the incremental part of the tooth through bottom sealing;
step 4, reconstructing the incremental part of the tooth by using a surface reconstruction algorithm, and filling holes in the surface of the incremental 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 the veneering; finding a projection plane orthogonal to the main direction, projecting the veneers to the projection plane layer by layer from top to bottom, calculating the thickness of the veneers through a two-dimensional contour obtained after each layer of projection, rendering points on the surfaces of the veneers into a color gradation, wherein the color of each point corresponds to the thickness normalization value of the point.
2. The method for generating a tooth overlay model and measuring thickness based on oral scanning point cloud according to claim 1, wherein the registration algorithm of step 2 is a two-step registration algorithm from coarse to fine:
the initial registration matrix is estimated by the coarse registration by adopting a Super4PCS algorithm, the dislocation among the point clouds to be registered is reduced,
the accurate registration adopts an ICP algorithm to fine tune a registration matrix, so that the alignment error of the two point clouds is minimum.
3. The method for generating a tooth overlay model and measuring the thickness of a tooth according to claim 1, wherein the step 3 comprises a phase difference operation between the dentition point cloud of the target tooth and the preoperative dentition scanning point cloud, only a non-closed point cloud enclosed by two origin cloud surfaces can be obtained, and the point cloud needs to be sealed to obtain an increment part corresponding to the overlay.
4. The method for generating a tooth veneering model and measuring the thickness based on the oral scanning point cloud as claimed in claim 1, wherein the veneering incremental reconstruction in the step 4 is to use a greedy trigonometric algorithm reconstruction algorithm to establish a triangular mesh of the closed veneering, namely the reconstructed curved surface model.
5. The method for generating a tooth overlay model and measuring thickness based on oral scanning point cloud as claimed in claim 1, wherein said step 5 of calculating overlay thickness by using two-dimensional contour obtained after each layer projection comprises two calculation bases: the method comprises the steps of firstly, finding a horizontal line, calculating an intersection point of the horizontal line and the left and right boundaries of the veneering two-dimensional projection outline, and calculating the distance between the two points; secondly, thinning the shape of the veneering two-dimensional projection outline to obtain a framework, traversing sampling points on the framework, calculating a tangent at each sampling point, and calculating the distance between the tangent and the intersection point of the left boundary and the right boundary of the veneering two-dimensional projection outline.
6. The method for generating a tooth overlay model and measuring thickness based on oral scanning point cloud according to claim 1, wherein the step 5 of reminding a doctor to modify the overlay design is to set an overlay thickness threshold value and render a specific color for the point cloud exceeding the over-thick threshold value or exceeding the over-thin threshold value, so as to achieve the reminding effect.
7. The method for generating a tooth overlay model and measuring thickness based on oral scanning point cloud of claim 3, wherein the point cloud of dentition containing target teeth comprises both the modified point cloud of teeth and other point clouds of teeth without modification.
8. The method for generating a tooth overlay model and measuring thickness based on oral scanning point cloud according to claim 1, wherein the data format of the preoperative dentition scanning model and the target dentition model is STL file, and the data format of the preoperative dentition scanning point cloud and the target dentition point cloud is 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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| Publication number | Priority date | Publication date | Assignee | Title |
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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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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113223063A (en) * | 2021-07-09 | 2021-08-06 | 四川大学 | Tooth registration method based on ICP algorithm and point cloud elimination algorithm |
| CN113223063B (en) * | 2021-07-09 | 2021-09-21 | 四川大学 | Tooth registration method based on ICP algorithm and point cloud elimination algorithm |
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