CN117934885A - Coordinate automatic matching method and system based on CBCT data and three-dimensional facial scan data - Google Patents
Coordinate automatic matching method and system based on CBCT data and three-dimensional facial scan data Download PDFInfo
- Publication number
- CN117934885A CN117934885A CN202410325936.5A CN202410325936A CN117934885A CN 117934885 A CN117934885 A CN 117934885A CN 202410325936 A CN202410325936 A CN 202410325936A CN 117934885 A CN117934885 A CN 117934885A
- Authority
- CN
- China
- Prior art keywords
- data
- fitting
- dimensional
- coordinates
- cbct
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000007408 cone-beam computed tomography Methods 0.000 title claims abstract description 68
- 238000000034 method Methods 0.000 title claims abstract description 48
- 230000001815 facial effect Effects 0.000 title claims abstract description 39
- 210000004872 soft tissue Anatomy 0.000 claims abstract description 27
- 210000000988 bone and bone Anatomy 0.000 claims abstract description 19
- 238000005259 measurement Methods 0.000 claims abstract description 13
- 210000003625 skull Anatomy 0.000 claims abstract description 12
- 238000009826 distribution Methods 0.000 claims abstract description 8
- 239000003550 marker Substances 0.000 claims abstract description 7
- 238000004590 computer program Methods 0.000 claims description 14
- 230000008569 process Effects 0.000 claims description 12
- 238000003860 storage Methods 0.000 claims description 10
- 230000008859 change Effects 0.000 claims description 5
- 238000013499 data model Methods 0.000 claims description 4
- 238000010408 sweeping Methods 0.000 claims description 4
- 238000012937 correction Methods 0.000 claims description 3
- 238000013507 mapping Methods 0.000 claims description 3
- 230000000694 effects Effects 0.000 abstract description 6
- 238000013461 design Methods 0.000 abstract description 4
- 210000000214 mouth Anatomy 0.000 description 31
- 238000010586 diagram Methods 0.000 description 10
- 230000006870 function Effects 0.000 description 8
- 238000005516 engineering process Methods 0.000 description 4
- 238000012545 processing Methods 0.000 description 4
- 210000004513 dentition Anatomy 0.000 description 3
- 210000001519 tissue Anatomy 0.000 description 3
- 230000036346 tooth eruption Effects 0.000 description 3
- 238000004422 calculation algorithm Methods 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 210000003298 dental enamel Anatomy 0.000 description 2
- 238000002513 implantation Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000008439 repair process Effects 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000008921 facial expression Effects 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 239000007943 implant Substances 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 210000000944 nerve tissue Anatomy 0.000 description 1
- 230000011218 segmentation Effects 0.000 description 1
- 239000003826 tablet Substances 0.000 description 1
Landscapes
- Dental Tools And Instruments Or Auxiliary Dental Instruments (AREA)
- Image Processing (AREA)
Abstract
The invention provides a coordinate automatic matching method and system based on CBCT data and three-dimensional surface scanning data. The method comprises the steps of obtaining CBCT data, facial scanning data and upper and lower jaw three-dimensional mouth scanning data; fixing CBCT data, moving face scanning data, and carrying out coordinate automatic matching fitting on the CBCT data and the face scanning data to obtain first fitting data; drawing a gingival margin line based on the upper and lower jaw three-dimensional mouth scanning data, and dividing the teeth according to the gingival margin line to obtain coordinates of each tooth; fixing the upper and lower jaw three-dimensional mouth scan data, moving the first fitting data, and carrying out coordinate automatic matching fitting on the upper and lower jaw three-dimensional mouth scan data and the first fitting data to obtain second fitting data; based on the second fitting data, bone distribution of the skull, projection measurement marker points, and/or three-dimensional facial soft tissue identification points are identified. The invention solves the problem of low space coordinate precision of CBCT, mouth scanning and face scanning, and can realize product design in the fields of planting, orthodontic, activity and the like.
Description
Technical Field
The invention relates to the technical field of medical artificial intelligence, in particular to a coordinate automatic matching method and system based on CBCT data and three-dimensional facial scan data.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
At present, the matching mode of CBCT data and three-dimensional surface scan data is a manual fixed point matching mode, and the method is roughly divided into two steps:
The first step: the method comprises the steps that a patient acquires images of a skull through an oral cavity CT device, then performs intraoral scanning of the patient, acquires upper and lower jaw dentition data through a digital imaging technology, and acquires three-dimensional data of the face of the patient through facial scan data, wherein the facial expression of the patient at the moment is smiling, and the upper and lower jaw anterior teeth information of the patient needs to be displayed as much as possible;
And a second step of: three obvious characteristic points of the oral cavity are selected through professional dental design software, space coordinate matching is conducted, coordinate matching is conducted on three-dimensional upper and lower jaw dentition data of the oral cavity and CBCT data, a first group of same coordinate relation data is obtained, then three-dimensional data of the face of a patient is imported, three obvious identification points are still selected on the CBCT data and facial scanning data, and space coordinate matching is conducted.
The manual fixed-point matching mode can play a key role in aesthetic restoration of a patient, can show the change contrast of front and rear tooth areas before and after the restoration of the patient, and can compare the form, proportion and color of the restoration of the front tooth area at the same time, so that the most suitable restoration form of the patient is found. But also has the following drawbacks:
(1) The coordinate accuracy is poor, the space coordinate alignment in the prior art only needs to be matched by a three-point representation method, obvious errors exist, and the problem of low accuracy exists for a reference conclusion of data;
(2) The technology field involved is narrow, and the technology is only applied to the repair field in a large scale, and has almost no related technology and product application for planting, orthodontic and activities.
Disclosure of Invention
In order to solve the technical problems in the background art, the invention provides a coordinate automatic matching method and system based on CBCT data and three-dimensional surface scanning data.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
The first aspect of the invention provides a coordinate automatic matching method based on CBCT data and three-dimensional facial scan data, which comprises the following steps:
Step 1, CBCT data, facial scanning data and upper and lower jaw three-dimensional mouth scanning data are obtained;
Step 2, fixing CBCT data, moving face scanning data, and carrying out coordinate automatic matching fitting on the CBCT data and the face scanning data to obtain first fitting data;
step 3, drawing gingival margin lines based on the upper and lower jaw three-dimensional mouth sweeping data, and dividing the teeth according to the gingival margin lines to obtain coordinates of each tooth;
Fixing the upper and lower jaw three-dimensional mouth scan data, moving the first fitting data, and carrying out coordinate automatic matching fitting on the upper and lower jaw three-dimensional mouth scan data and the first fitting data to obtain second fitting data;
and 4, identifying skeleton distribution, projection measurement mark points and/or three-dimensional facial soft tissue mark points of the skull based on the second fitting data.
Further, the process of moving the face scan data before the fixed CBCT data in step 2 further includes:
Based on CBCT data, adjusting a surface critical value of the jawbone data to obtain a facial soft tissue image; identifying a face soft tissue image, marking the face soft tissue image by adopting a plurality of first marking points, and connecting the first marking points into a plurality of first planes; identifying coordinates of the first mark point and coordinates of the first plane;
Recognizing coordinates of the face scanning data, and marking the face scanning data by a plurality of second marking points to obtain a plurality of second marking points; the second mark points are connected into a plurality of second planes, and the coordinates of the second mark points and the coordinates of the second planes are identified.
Furthermore, the step 2 of fixing CBCT data and moving face scan data, and performing coordinate automatic matching fitting on the CBCT data and the face scan data to obtain first fitting data includes: and taking the CBCT data as a fixed grid, taking the face scanning data as a movable grid, and moving the face scanning data to enable the coordinates of the second mark point and the coordinates of the second plane to be aligned with the coordinates of the first mark point and the coordinates of the first plane in a capturing way, and obtaining first fitting data when the contact area between the first plane and the second plane is maximum.
Further, the process of drawing the gingival margin line based on the upper and lower jaw three-dimensional mouth scan data in the step 3 includes: marking a near midpoint of the tooth, a far midpoint of the tooth, a highest point of the tooth cusp and a lowest point of the gingival margin based on the upper and lower jaw three-dimensional mouth scan data; measuring the distance between the near midpoint of the tooth and the far midpoint of the tooth and the vertical distance between the highest point of the cusp and the lowest point of the gingival margin; the gingival margin line is drawn from the distance between the near midpoint of the tooth and the far midpoint of the tooth and the vertical distance.
Further, the fixed upper and lower jaw three-dimensional mouth scan data in the step 3, before moving the first fitting data, further includes:
Based on the upper and lower jaw three-dimensional mouth scan data, recognizing the upper and lower jaw three-dimensional mouth scan data surface, marking the upper and lower jaw three-dimensional mouth scan data by adopting a plurality of third marking points, and connecting the third marking points into a plurality of third planes; identifying coordinates of the third mark point and coordinates of the third plane;
Acquiring first fitting data, adjusting a surface critical value of jaw data to acquire a bone tissue image, identifying bone tissue image data, marking the bone tissue image data by adopting a plurality of fourth marking points, and connecting the fourth marking points into a plurality of fourth planes; the coordinates of the fourth mark point and the coordinates of the fourth plane are identified.
Further, the step 3 of fixing the three-dimensional mouth scan data of the upper and lower jaws, moving the first fitting data, and performing coordinate automatic matching fitting on the three-dimensional mouth scan data of the upper and lower jaws and the first fitting data, so as to obtain second fitting data, wherein the process of obtaining the second fitting data comprises the following steps:
And taking the upper and lower jaw three-dimensional mouth scan data as a fixed grid, taking the first fitting data as a movable grid, and moving the first fitting data so as to capture and align the coordinates of the fourth mark point and the coordinates of the fourth plane with the coordinates of the third mark point and the coordinates of the third plane, and obtaining second fitting data when the contact area between the third plane and the fourth plane is maximum.
Further, the process of identifying the bone distribution, the projection measurement marker points and/or the three-dimensional facial soft tissue marker points of the skull in the step 4 based on the second fitting data comprises the following steps:
Based on the coordinates of the second fitting data, analyzing the change of the jaw position according to the correction step, virtually modeling the analyzed jaw position, replacing an original data model, acquiring CBCT data, adjusting surface critical values, respectively identifying the surfaces of bone tissues and soft tissues, marking orthodontic mark points according to the identified information, and mapping lines and planes according to the mark points.
The second aspect of the invention provides an automatic coordinate matching system based on CBCT data and three-dimensional surface scanning data, which is used for executing the automatic coordinate matching method based on CBCT data and three-dimensional surface scanning data.
A third aspect of the present invention provides a computer-readable storage medium.
A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps in the method of coordinate auto-matching based on CBCT data and three-dimensional facial sweep data as described in the first aspect above.
A fourth aspect of the invention provides a computer device.
A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps in the method of coordinate auto-matching based on CBCT data and three-dimensional facial scan data as described in the first aspect above when the program is executed.
Compared with the prior art, the invention has the beneficial effects that:
According to the invention, based on CBCT data, the surface critical value of the jawbone data is adjusted to obtain a facial soft tissue image, large-area and multi-tissue face matching is carried out with the obtained facial scanning data, the matching precision is maximized, a more accurate matching effect is realized, meanwhile, the CBCT enamel area and shape are identified, and the face-to-face matching is carried out on the mouth scanning data, so that the problem of low space coordinate precision of CBCT, mouth scanning and face scanning is solved.
According to the invention, by utilizing an intelligent AI algorithm of software, CBCT tooth root tissues, nerve tissues and skull mass tissues are respectively identified for side position identification point calibration and 3D skull projection measurement, and patient surface scanning soft tissue identification points are identified for soft tissue projection measurement in the same way, so that product designs in the fields of implantation, orthodontics, activity and the like are realized.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention.
Fig. 1 is a flowchart of the coordinate automatic matching method based on CBCT data and three-dimensional facial scan data according to the present invention.
Detailed Description
The invention will be further described with reference to the drawings and examples.
It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the invention. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present invention. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.
It is noted that the flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of methods and systems according to various embodiments of the present disclosure. It should be noted that each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the logical functions specified in the various embodiments. It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by special purpose hardware-based systems which perform the specified functions or operations, or combinations of special purpose hardware and computer instructions.
Example 1
As shown in fig. 1, this embodiment provides a method for automatically matching coordinates based on CBCT data and three-dimensional surface scanning data, and this embodiment is illustrated by applying the method to a server, and it can be understood that the method may also be applied to a terminal, and may also be applied to a system and a terminal, and implemented through interaction between the terminal and the server. The server can be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, and can also be a cloud server for providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network servers, cloud communication, middleware services, domain name services, security services CDNs, basic cloud computing services such as big data and artificial intelligent platforms and the like. The terminal may be, but is not limited to, a smart phone, a tablet computer, a notebook computer, a desktop computer, a smart speaker, a smart watch, etc. The terminal and the server may be directly or indirectly connected through wired or wireless communication, and the present invention is not limited herein.
In this embodiment, a coordinate automatic matching method based on CBCT data and three-dimensional surface scanning data includes the following steps:
Step 1, CBCT data, facial scanning data and upper and lower jaw three-dimensional mouth scanning data are obtained;
Step 2, fixing CBCT data, moving face scanning data, and carrying out coordinate automatic matching fitting on the CBCT data and the face scanning data to obtain first fitting data;
the process of moving face scan data prior to the fixed CBCT data further comprises:
Based on CBCT data, adjusting a surface critical value of the jawbone data to obtain a facial soft tissue image; identifying a face soft tissue image, marking the face soft tissue image by adopting a plurality of first marking points, and connecting the first marking points into a plurality of first planes; identifying coordinates of the first mark point and coordinates of the first plane;
Recognizing coordinates of the face scanning data, and marking the face scanning data by a plurality of second marking points to obtain a plurality of second marking points; the second mark points are connected into a plurality of second planes, and the coordinates of the second mark points and the coordinates of the second planes are identified.
The process of automatically matching and fitting the coordinates of the CBCT data and the face scanning data to obtain first fitting data comprises the following steps: and taking the CBCT data as a fixed grid, taking the face scanning data as a movable grid, and moving the face scanning data to enable the coordinates of the second mark point and the coordinates of the second plane to be aligned with the coordinates of the first mark point and the coordinates of the first plane in a capturing way, and obtaining first fitting data when the contact area between the first plane and the second plane is maximum.
According to the invention, step 2 is realized by intelligently identifying CBCT skull data and CBCT soft tissue outline data through software AI, and matching three-dimensional coordinates through CBCT soft tissue outline and multi-dimensional tissue surface and surface scanning integral data, so that accurate coordinate superposition is realized, and bone tissue and soft tissue are matched with actual coordinates.
And automatically running the step setting program to realize AI automation in the software.
Step 3, drawing gingival margin lines based on the upper and lower jaw three-dimensional mouth sweeping data, and dividing the teeth according to the gingival margin lines to obtain coordinates of each tooth;
Fixing the upper and lower jaw three-dimensional mouth scan data, moving the first fitting data, and carrying out coordinate automatic matching fitting on the upper and lower jaw three-dimensional mouth scan data and the first fitting data to obtain second fitting data;
The process for drawing the gingival margin line based on the upper and lower jaw three-dimensional mouth sweeping data comprises the following steps: marking a near midpoint of the tooth, a far midpoint of the tooth, a highest point of the tooth cusp and a lowest point of the gingival margin based on the upper and lower jaw three-dimensional mouth scan data; measuring the distance between the near midpoint of the tooth and the far midpoint of the tooth and the vertical distance between the highest point of the tooth cusp and the lowest point of the gingival margin; the gingival margin line is drawn from the distance between the near midpoint of the tooth and the far midpoint of the tooth and the vertical distance.
The method further comprises the following steps of:
Based on the upper and lower jaw three-dimensional mouth scan data, recognizing the upper and lower jaw three-dimensional mouth scan data surface, marking the upper and lower jaw three-dimensional mouth scan data by adopting a plurality of third marking points, and connecting the third marking points into a plurality of third planes; identifying coordinates of the third mark point and coordinates of the third plane;
Acquiring first fitting data, adjusting a surface critical value of jaw data to acquire a bone tissue image, identifying bone tissue image data, marking the bone tissue image data by adopting a plurality of fourth marking points, and connecting the fourth marking points into a plurality of fourth planes; the coordinates of the fourth mark point and the coordinates of the fourth plane are identified.
The process for fixing the upper and lower jaw three-dimensional mouth sweep data, moving the first fitting data, and carrying out coordinate automatic matching fitting on the upper and lower jaw three-dimensional mouth sweep data and the first fitting data to obtain second fitting data comprises the following steps:
And taking the upper and lower jaw three-dimensional mouth scan data as a fixed grid, taking the first fitting data as a movable grid, and moving the first fitting data so as to capture and align the coordinates of the fourth mark point and the coordinates of the fourth plane with the coordinates of the third mark point and the coordinates of the third plane, and obtaining second fitting data when the contact area between the third plane and the fourth plane is maximum.
And automatically running the step setting program to realize AI automation in the software.
The step 3 of the invention realizes the combination of CBCT bone tissue and three-dimensional facial sweep, then carries out space coordinate matching on the three-dimensional mouth sweep data of the upper jaw and the lower jaw, the software AI intelligently identifies the tooth enamel of the CBCT tooth, automatically separates each tooth position, restores the tooth shape, realizes the automatic segmentation of the dental crowns, at the moment, leads in the three-dimensional upper jaw and lower jaw dentition data, identifies the dental crown data, the software AI intelligently calculates the corresponding tooth position and the tissue surface with obvious characteristics, carries out a plurality of surface matching, thereby realizing the best matching effect.
And 4, identifying skeleton distribution, projection measurement mark points and/or three-dimensional facial soft tissue mark points of the skull based on the second fitting data.
The process of identifying the bone distribution, the projection measurement marker points and/or the three-dimensional facial soft tissue marker points of the skull based on the second fitting data comprises the following steps: based on the coordinates of the second fitting data, analyzing the change of the jaw position according to the correction step, virtually modeling the analyzed jaw position, replacing an original data model, acquiring CBCT data, adjusting surface critical values, respectively identifying the surfaces of bone tissues and soft tissues, marking orthodontic mark points according to the identified information, and mapping lines and planes according to the mark points.
Wherein, according to the step of correcting analyzes the change of jaw position, carries out virtual modeling and replaces original data model's process with the jaw position that analyzes includes: according to the expansion size of the expander and the distance of 1/4 circle of expansion, determining the coordinate moving distance of the local jaw mesh according to the coordinate of the jaw data, generating a virtual jaw mesh according to the coordinate moving distance of the local jaw mesh after moving, integrating the whole jaw data and the virtual generated local jaw mesh by means of big data, and thus obtaining virtual jaw mesh data after expanding the expander.
And automatically running the step setting program to realize AI automation in the software.
In the step 4 of the invention, after three-dimensional coordinates of CBCT, facial scanning and upper and lower teeth data are matched, software AI intelligently identifies skeleton distribution of the skull, effectively identifies projection measurement mark points, simultaneously identifies three-dimensional facial soft tissue mark points, and traditional projection measurement carries out measurement analysis through a two-dimensional plane.
The coordinate automatic matching method based on the CBCT data and the three-dimensional facial scan data realizes the establishment of a 4D design scheme in the fields of implantation, orthodontics, repair, activities and the like through a software intelligent AI algorithm, effectively meets the individual requirements of patients, and realizes the influence of products such as implants, brackets and the like on soft tissues and bone tissues of the patients through intelligent measurement and calculation of the software, thereby establishing more accurate product design sites.
Example two
The embodiment provides a coordinate automatic matching system based on CBCT data and three-dimensional surface scanning data, which is used for executing the coordinate automatic matching method based on CBCT data and three-dimensional surface scanning data.
Example III
The present embodiment provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps in the coordinate automatic matching method based on CBCT data and three-dimensional surface scan data as described in the above embodiment.
Example IV
The present embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor, where the processor implements the steps in the coordinate automatic matching method based on CBCT data and three-dimensional surface scanning data according to the above embodiment when executing the program.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, magnetic disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Those skilled in the art will appreciate that implementing all or part of the above-described methods in accordance with the embodiments may be accomplished by way of a computer program stored on a computer readable storage medium, which when executed may comprise the steps of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disc, a Read-Only Memory (ROM), a Random access Memory (Random AccessMemory, RAM), or the like.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. The coordinate automatic matching method based on CBCT data and three-dimensional facial scan data is characterized by comprising the following steps:
Step 1, CBCT data, facial scanning data and upper and lower jaw three-dimensional mouth scanning data are obtained;
step 2, based on CBCT data, adjusting a surface critical value of the jawbone data to obtain a facial soft tissue image; identifying a face soft tissue image, marking the face soft tissue image by adopting a plurality of first marking points, and connecting the first marking points into a plurality of first planes; identifying coordinates of the first mark point and coordinates of the first plane;
recognizing coordinates of the face scanning data, and marking the face scanning data by a plurality of second marking points to obtain a plurality of second marking points; connecting the second mark points into a plurality of second planes, and identifying the coordinates of the second mark points and the coordinates of the second planes;
fixing CBCT data, moving face scanning data, and carrying out coordinate automatic matching fitting on the CBCT data and the face scanning data to obtain first fitting data;
step 3, drawing gingival margin lines based on the upper and lower jaw three-dimensional mouth sweeping data, and dividing the teeth according to the gingival margin lines to obtain coordinates of each tooth;
Based on the upper and lower jaw three-dimensional mouth scan data, recognizing the upper and lower jaw three-dimensional mouth scan data surface, marking the upper and lower jaw three-dimensional mouth scan data by adopting a plurality of third marking points, and connecting the third marking points into a plurality of third planes; identifying coordinates of the third mark point and coordinates of the third plane;
acquiring first fitting data, adjusting a surface critical value of jaw data to acquire a bone tissue image, identifying bone tissue image data, marking the bone tissue image data by adopting a plurality of fourth marking points, and connecting the fourth marking points into a plurality of fourth planes; identifying coordinates of the fourth mark point and coordinates of the fourth plane;
Fixing the upper and lower jaw three-dimensional mouth scan data, moving the first fitting data, and carrying out coordinate automatic matching fitting on the upper and lower jaw three-dimensional mouth scan data and the first fitting data to obtain second fitting data;
and 4, identifying skeleton distribution, projection measurement mark points and/or three-dimensional facial soft tissue mark points of the skull based on the second fitting data.
2. The method for automatically matching coordinates based on CBCT data and three-dimensional facial scan data according to claim 1, wherein the steps of fixing CBCT data in step 2, moving facial scan data, and automatically matching and fitting the CBCT data and the facial scan data to obtain first fitting data comprise: and taking the CBCT data as a fixed grid, taking the face scanning data as a movable grid, and moving the face scanning data to enable the coordinates of the second mark point and the coordinates of the second plane to be aligned with the coordinates of the first mark point and the coordinates of the first plane in a capturing way, and obtaining first fitting data when the contact area between the first plane and the second plane is maximum.
3. The automatic coordinate matching method based on CBCT data and three-dimensional facial scan data according to claim 1, wherein the process of drawing the gingival margin line based on the upper and lower jaw three-dimensional oral scan data in the step 3 comprises: marking a near midpoint of the tooth, a far midpoint of the tooth, a highest point of the tooth cusp and a lowest point of the gingival margin based on the upper and lower jaw three-dimensional mouth scan data; measuring the distance between the near midpoint of the tooth and the far midpoint of the tooth, and the vertical distance between the highest point of the tooth cusp and the lowest point of the gingival margin; the gingival margin line is drawn from the distance between the near midpoint of the tooth and the far midpoint of the tooth and the vertical distance.
4. The automatic coordinate matching method based on CBCT data and three-dimensional facial scan data according to claim 1, wherein the step 3 of fixing the three-dimensional facial scan data of the upper and lower jaws, moving the first fitting data, and performing automatic coordinate matching fitting on the three-dimensional facial scan data of the upper and lower jaws and the first fitting data, and the step of obtaining the second fitting data comprises:
And taking the upper and lower jaw three-dimensional mouth scan data as a fixed grid, taking the first fitting data as a movable grid, and moving the first fitting data so as to capture and align the coordinates of the fourth mark point and the coordinates of the fourth plane with the coordinates of the third mark point and the coordinates of the third plane, and obtaining second fitting data when the contact area between the third plane and the fourth plane is maximum.
5. The method according to claim 1, wherein the step 4 of identifying the bone distribution, the projection measurement marker points and/or the three-dimensional facial soft tissue marker points of the skull based on the second fitting data comprises:
Based on the coordinates of the second fitting data, analyzing the change of the jaw position according to the correction step, virtually modeling the analyzed jaw position, replacing an original data model, acquiring CBCT data, adjusting surface critical values, respectively identifying the surfaces of bone tissues and soft tissues, marking orthodontic mark points according to the identified information, and mapping lines and planes according to the mark points.
6. A coordinate automatic matching system based on CBCT data and three-dimensional surface scan data, which is used for executing the coordinate automatic matching method based on CBCT data and three-dimensional surface scan data according to any one of claims 1 to 5.
7. A computer readable storage medium having stored thereon a computer program, which when executed by a processor, implements the steps of the method for coordinate automatic matching based on CBCT data and three-dimensional facial scan data as claimed in any one of claims 1 to 5.
8. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor performs the steps in the method of coordinate auto-matching based on CBCT data and three-dimensional facial scan data as claimed in any one of claims 1 to 5 when the program is executed.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410325936.5A CN117934885A (en) | 2024-03-21 | 2024-03-21 | Coordinate automatic matching method and system based on CBCT data and three-dimensional facial scan data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410325936.5A CN117934885A (en) | 2024-03-21 | 2024-03-21 | Coordinate automatic matching method and system based on CBCT data and three-dimensional facial scan data |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117934885A true CN117934885A (en) | 2024-04-26 |
Family
ID=90761196
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202410325936.5A Pending CN117934885A (en) | 2024-03-21 | 2024-03-21 | Coordinate automatic matching method and system based on CBCT data and three-dimensional facial scan data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117934885A (en) |
-
2024
- 2024-03-21 CN CN202410325936.5A patent/CN117934885A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10980621B2 (en) | Dental design transfer | |
| US11735306B2 (en) | Method, system and computer readable storage media for creating three-dimensional dental restorations from two dimensional sketches | |
| US11517272B2 (en) | Simulated orthodontic treatment via augmented visualization in real-time | |
| KR101799878B1 (en) | 2d image arrangement | |
| JP5671734B2 (en) | Computer-aided creation of custom tooth setup using facial analysis | |
| US20060127854A1 (en) | Image based dentition record digitization | |
| EP3349680B1 (en) | Method for creating flexible arch model of teeth for use in restorative dentistry | |
| CN111784754B (en) | Tooth orthodontic method, device, equipment and storage medium based on computer vision | |
| AU4076999A (en) | Method and apparatus for generating 3d models from medical images | |
| WO2021218724A1 (en) | Intelligent design method for digital model for oral digital impression instrument | |
| KR20130044934A (en) | An image matching data creation method for orthodontics and remote mock treatment method and providing the information for orthodontics device using the same | |
| CN112120815A (en) | Digital oral smile repairing method | |
| EP3629336A1 (en) | Dental design transfer | |
| CN112419476A (en) | Method and system for creating three-dimensional virtual image of dental patient | |
| US11654002B2 (en) | Method for determining and visualizing tooth movements and planned instances of tooth repositioning | |
| CN111275808A (en) | Method and device for establishing orthodontic model | |
| CN117934885A (en) | Coordinate automatic matching method and system based on CBCT data and three-dimensional facial scan data | |
| CN114399551A (en) | Method and system for positioning tooth root canal orifice based on mixed reality technology | |
| CN108992193B (en) | Tooth restoration aided design method | |
| CN113397585B (en) | Tooth body model generation method and system based on oral CBCT and oral scan data | |
| CN115798728B (en) | Tooth preparation digital model design method based on computer assistance | |
| CN114343906B (en) | Method and device for acquiring occlusion vertical distance, medium and electronic equipment | |
| US20230113425A1 (en) | Oral Digital Impression Instrument, Digital Model for the Same, and Intelligent Method of Making and/or Using the Same | |
| US20240024076A1 (en) | Combined face scanning and intraoral scanning | |
| CN115547462A (en) | Construction method of tooth type database and related device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination |