WO2023179699A1 - 基于面型参数生成颞下颌关节髁突运动包络面方法和装置 - Google Patents

基于面型参数生成颞下颌关节髁突运动包络面方法和装置 Download PDF

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WO2023179699A1
WO2023179699A1 PCT/CN2023/083266 CN2023083266W WO2023179699A1 WO 2023179699 A1 WO2023179699 A1 WO 2023179699A1 CN 2023083266 W CN2023083266 W CN 2023083266W WO 2023179699 A1 WO2023179699 A1 WO 2023179699A1
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target
craniofacial
parameters
cross
temporomandibular joint
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PCT/CN2023/083266
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English (en)
French (fr)
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许向亮
郭传瑸
陈克难
王晶
姜俊岐
王珺林
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北京大学口腔医学院
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Priority to US18/850,026 priority Critical patent/US20250218118A1/en
Publication of WO2023179699A1 publication Critical patent/WO2023179699A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
    • G06T17/20—Finite element generation, e.g. wire-frame surface description, tesselation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2200/00—Indexing scheme for image data processing or generation, in general
    • G06T2200/04—Indexing scheme for image data processing or generation, in general involving 3D image data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2210/00—Indexing scheme for image generation or computer graphics
    • G06T2210/41—Medical

Definitions

  • This application belongs to the field of digital medicine, and particularly relates to a method and device for generating the temporomandibular joint condylar motion envelope and its cross-sectional curve based on facial parameters.
  • the temporomandibular joint is the only movable joint in the craniofacial region and one of the most complex joints in the human body.
  • Figure 1 shows a schematic structural diagram of the temporomandibular joint.
  • the temporomandibular joint mainly includes an articular disc 001, an articular process 002 and a glenoid fossa 003.
  • the temporomandibular joint can perform both sliding and rotational movements to achieve important physiological functions, including opening and closing the mouth, swallowing, chewing, language, etc.
  • artificial total temporomandibular joint prosthesis replacement is one of the treatments that has developed rapidly in recent years.
  • artificial temporomandibular joint prostheses are generally designed with reference to large joints of the limbs such as the hip joint, and are mainly designed with a ball-and-socket relationship or an approximate ball-and-socket relationship.
  • the purpose is to increase the morphological constraints of the joint socket prosthesis on the articular process prosthesis and prevent Dislocation caused by loss of tissue around a joint.
  • the articular process of the temporomandibular joint is much smaller than the glenoid fossa. It relies on surrounding tissues such as articular discs, joint capsules, muscles, etc. to achieve more flexible movements than the large joints of the limbs.
  • the natural joint on the contralateral side of the joint prosthesis is subject to greater forces and changes in range of motion, resulting in potential damage to the natural joint on the contralateral side.
  • the condyle movement envelope of the temporomandibular joint is the boundary range within which the condyle can naturally move.
  • the shape of the condyle movement envelope of the temporomandibular joint can guide the movement of the artificial articular process along the functional surface of the glenoid fossa, thereby achieving physiological movement of the mandible. Way.
  • the applicant has conducted intensive research by measuring some facial parameters of healthy people with temporomandibular joints, and generated a matrix based on the facial parameters, and then used the matrix and the target facial shape.
  • the parameters generate the cross-sectional curve of a specific section of the target condylar motion envelope.
  • a target condylar motion envelope surface can be generated based on the plurality of cross-sectional curves.
  • this application provides a method for generating a temporomandibular joint condylar motion envelope based on facial parameters.
  • the method includes:
  • a temporomandibular joint condylar motion envelope is generated based on the plurality of temporomandibular joint condylar motion envelope curves.
  • the acquisition of multiple temporomandibular joint condylar motion envelope cross-sectional curve equations specifically includes:
  • a target cross-section curve equation is generated according to the matrix and the target surface shape parameters.
  • obtaining target craniofacial features includes:
  • Target craniofacial features are extracted based on the target craniofacial three-dimensional digital model.
  • obtaining the target surface parameters includes:
  • target craniofacial three-dimensional digital model Measure the target craniofacial three-dimensional digital model to obtain target facial parameters, which include SNA, SNB, mandibular angle distance, mandibular body length, mandibular plane angle, and the angle between the N-Me connection line and the FH plane .
  • obtaining the datum type parameters includes:
  • the reference craniofacial three-dimensional digital model is measured to obtain the reference profile parameters, and the reference profile parameters correspond to the same type as the reference profile parameters.
  • obtaining the reference craniofacial three-dimensional digital model includes:
  • a reference craniofacial three-dimensional digital model is generated based on the plurality of candidate craniofacial models according to preset rules.
  • obtaining the datum section fitting curve equation includes:
  • a reference section fitting curve equation is generated according to the coordinates of the plurality of characteristic points.
  • generating a target cross-section curve according to the matrix and the target surface parameters includes:
  • this application also provides a device for generating a temporomandibular joint condylar motion envelope surface based on facial parameters.
  • the device includes:
  • the cross-sectional curve generation unit is used to generate multiple temporomandibular joint condylar motion envelope cross-sectional curve equations
  • a surface equation generation unit is used to generate a plurality of temporomandibular joint condylar motion envelope cross-sectional curve equations. It forms multiple temporomandibular joint condylar motion envelope curves;
  • a curved surface generation unit is used to generate a temporomandibular joint condyle motion envelope surface based on the plurality of temporomandibular joint condyle motion envelope curves.
  • this application also provides a program for generating a temporomandibular joint condylar motion envelope based on facial parameters.
  • the program is used to generate the temporomandibular joint condylar motion envelope as described in the first aspect when executed. Method steps.
  • a fourth aspect is a computer-readable storage medium on which computer instructions are stored. When the instructions are executed by a processor, the steps of the method for generating a temporomandibular joint condylar motion envelope surface described in the first aspect are implemented.
  • a detection device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the one processor , the instructions are executed by the at least one processor, so that the at least one processor executes the method of generating a temporomandibular joint condylar motion envelope surface described in the first aspect.
  • this application also provides a method for generating a temporomandibular joint condylar motion envelope cross-sectional curve based on facial parameters.
  • the method includes:
  • a target cross-section curve is generated according to the matrix and the target surface shape parameters.
  • obtaining target craniofacial features includes:
  • Target craniofacial features are extracted based on the target craniofacial three-dimensional digital model.
  • obtaining the target surface parameters includes:
  • target craniofacial three-dimensional digital model Measure the target craniofacial three-dimensional digital model to obtain target facial parameters, which include SNA, SNB, mandibular angle distance, mandibular body length, mandibular plane angle, and the angle between the N-Me connection line and the FH plane .
  • obtaining the datum type parameters includes:
  • the reference craniofacial three-dimensional digital model is measured to obtain the reference profile parameters, and the reference profile parameters correspond to the same type as the reference profile parameters.
  • obtaining the reference craniofacial three-dimensional digital model includes:
  • a reference craniofacial three-dimensional digital model is generated based on the plurality of candidate craniofacial models according to preset rules.
  • obtaining the datum section fitting curve equation includes:
  • a reference section fitting curve equation is generated according to the coordinates of the plurality of characteristic points.
  • generating a target cross-section curve according to the matrix and the target surface parameters includes:
  • this application also provides a device for generating a temporomandibular joint condylar motion envelope cross-sectional curve based on facial parameters.
  • the device includes:
  • a parameter acquisition unit is used to acquire target craniofacial features and target facial parameters
  • a curve equation fitting unit used to obtain datum surface shape parameters and datum cross-section fitting curve equations in combination with the target craniofacial features
  • a matrix generation unit configured to generate a matrix according to the datum surface type parameters and the datum section fitting curve equation
  • the curve fitting unit is also used to generate a target cross-section curve according to the matrix and the target surface shape parameters.
  • this application also provides a program for generating a temporomandibular joint condylar motion envelope cross-sectional curve based on facial parameters.
  • the program used is used to implement the generation of the temporomandibular joint based on facial parameters in the sixth aspect when executed. Steps of the condylar motion envelope section curve method.
  • a computer-readable storage medium has computer instructions stored thereon. When the instructions are executed by a processor, the method of generating a temporomandibular joint condylar motion envelope cross-sectional curve based on facial parameters as described in the sixth aspect is implemented. A step of.
  • a detection device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the one processor , the instructions are executed by the at least one processor, so that the at least one processor executes the method of generating a temporomandibular joint condylar motion envelope cross-sectional curve based on facial parameters in the sixth aspect.
  • the method provided by this application is based on the matrix representation theory of linear transformation. It first generates the measurable facial parameters in the skull model expressed in matrix form and the cross-sectional curve coefficient of the condylar motion envelope of the temporomandibular joint. Mapping relationship, and then using the matrix to perform an inverse operation based on the measurable facial parameters in the target skull model to generate the temporomandibular joint condylar motion envelope cross-sectional curve, so that a more accurate motion envelope can be generated using only static parameters. Based on this, it is possible to more accurately generate parameters of the condylar motion envelope in healthy conditions that cannot be collected due to various reasons.
  • the method provided by this application is simple and easy to collect physical parameters, all parameters are collected non-invasively, and each parameter can be collected with the help of routine inspection results without the need for special parameter collection, and the overall calculation of the plan The amount is small, and the cross-section curve of the target envelope surface and the envelope surface can be quickly determined.
  • Figure 1 shows a schematic structural diagram of the temporomandibular joint
  • Figure 2-1 shows a schematic diagram of the three-dimensional structure of the condylar motion envelope of a healthy temporomandibular joint
  • Figure 2-2 shows the three-dimensional structural grid diagram of the articular process motion envelope shown in Figure 2-1;
  • Figure 3 shows a flow chart of the method provided by this application for generating the temporomandibular joint condylar motion envelope cross-sectional curve based on facial parameters
  • Figure 4-1 shows the front view of the sagittal cross-section of the envelope shown in Figure 2-1;
  • Figure 4-2 shows a schematic three-dimensional structural diagram of the structure shown in Figure 4-1;
  • Figure 5 shows the fitting curve obtained by fitting based on the cross-sectional curves shown in Figure 4-1 and Figure 4-2.
  • the temporomandibular joint mainly includes an articular disc 001, an articular process 002 and a glenoid fossa 003.
  • the articular process 002 can move under the traction and restriction of the articular disc 001.
  • the joint socket 003 slides or rotates to realize various physiological functions of the mandible, such as closing the mouth, swallowing, chewing, or speaking.
  • Figure 2-1 shows a schematic three-dimensional structural diagram of the condylar motion envelope of a healthy temporomandibular joint.
  • Figure 2-2 shows a three-dimensional structural grid diagram of the articular process motion envelope shown in Figure 2-1, as shown in Figure 2-1 As shown in Figure 2-1 and Figure 2-2, the movement trajectory of healthy articular processes in the glenoid fossa is difficult to express with simple mathematical expressions.
  • the movement envelope surface of the temporomandibular joint condylar process refers to the movement of the temporomandibular joint process during various movements of the temporomandibular joint. boundary. In fact, at its maximum opening, parts of the articular process extend beyond the corresponding glenoid fossa.
  • the envelope surface is an irregular and uneven surface, and, from a three-dimensional perspective, the envelope surface forms an irregular nest-like structure.
  • This socket-like structure is not the same as the structure of the bony glenoid fossa.
  • the envelope surface in a healthy state after removal of the disease is difficult to determine in advance. Since the shape of the envelope surface is a key parameter in designing an artificial temporomandibular joint prosthesis, it is particularly important in practice to determine a more accurate shape of the envelope surface in advance.
  • this application provides a method for generating a cross-sectional curve of the temporomandibular joint condylar motion envelope based on facial parameters.
  • the cross-sectional curve of the reference skull temporomandibular joint condylar motion envelope on a specific cross-section is provided.
  • Mathematical expression of the section curve on the corresponding section is provided.
  • the expression of the corresponding envelope surface can be generated, and the corresponding shape can be drawn.
  • Figure 3 shows a flow chart of the method for generating the temporomandibular joint condyle motion envelope based on facial parameters provided by this application. As shown in Figure 3, the method includes the following steps S001 to S003:
  • step S001 may specifically include the following steps S100 to S400:
  • the acquisition of target craniofacial features may specifically include the following steps S111 and S112:
  • Step S111 Obtain the target craniofacial three-dimensional digital model.
  • the target craniofacial three-dimensional digital model may be reconstructed using computer-aided means based on the two-dimensional digital information of the target head.
  • Step S112 Extract target craniofacial features based on the target craniofacial three-dimensional digital model.
  • the target craniofacial features refer to the craniofacial features extracted from the three-dimensional digital model of the target head, and the craniofacial features can be considered as the craniofacial features of the target object.
  • the craniofacial features can be specifically set according to specific needs.
  • the craniofacial features can include Facial length, width, and the front-to-back position relationship of the upper and lower jaws, etc.
  • the specific parameters used to determine the facial length, width, and front-to-back position relationship of the upper and lower jaws can be specifically set according to needs.
  • each of the aforementioned craniofacial features can be further decomposed into multiple sub-features.
  • the craniofacial features may also include other parameters.
  • the target surface parameters refer to surface parameters extracted from the target three-dimensional digital model.
  • the facial parameters are different from the craniofacial features, where the craniofacial features are the basis for qualitatively classifying craniofacial types, and the facial parameters are extracted from a craniofacial three-dimensional digital model and can reflect Quantitative data on the facial features of the collected object.
  • obtaining the target surface shape parameters may specifically include the following steps S121 and S122:
  • Step S121 Obtain the target craniofacial three-dimensional digital model.
  • this step can directly call the target craniofacial three-dimensional digital model generated in step S111 to avoid repeated calculations.
  • Step S122 Measure target facial parameters based on the target craniofacial three-dimensional digital model.
  • the target facial parameters include corresponding parameters of the temporomandibular joint and muscle-related parameters, such as SNA, SNB, mandibular angular distance, mandibular body, etc. length, mandibular plane angle, and the angle between the N-Me line and the FH plane.
  • target surface shape parameters may also include other parameters capable of predicting the envelope surface shape.
  • the facial parameters of the target can be measured using any method in the existing technology that can measure data based on a three-dimensional digital model.
  • PROPLAN CMF software can be used to perform cephalometric measurements on the three-dimensional digital model of the target skull to obtain the target. Surface parameters.
  • the reference facial parameters are facial parameters obtained based on a reference craniofacial three-dimensional digital model, where the reference three-dimensional cranial digital model is obtained based on a three-dimensional cranial digital model of a healthy population.
  • the three-dimensional digital skull model of healthy people is referred to as the alternative three-dimensional skull digital model.
  • the alternative three-dimensional digital skull model can be stored in the alternative model library.
  • the alternative model library include an effective number of alternative three-dimensional digital models of the skull, for example, there is at least one alternative three-dimensional digital model of the skull for each facial shape.
  • the reconstruction method of the candidate three-dimensional digital skull model is the same as the reconstruction method of the target three-dimensional digital skull model, which not only simplifies the processing operation method, but also makes the two data comparable.
  • the alternative three-dimensional digital model of the skull can be directly selected from the three-dimensional digital model of the skull of healthy people. It can also be further calibrated based on the digital physical model of the upper and lower jaws on the basis of the three-dimensional digital model of the skull of healthy people.
  • the obtained three-dimensional digital model, the digital physical model of the upper and lower jaws includes a plaster model scanned model, or a digital model obtained by oral scanning to collect the oral cavity of the subject.
  • correcting the candidate three-dimensional digital model of the head based on the upper and lower jaw digital solid models specifically includes the following steps S201 to step S202:
  • Step S201 Obtain the standard three-dimensional model of the maxillary and mandibular dentition and the mandibular movement trajectory.
  • a plaster model can be used to obtain a standard three-dimensional model of the maxillary and mandibular dentition, which may include the following steps:
  • using a scanner to scan the upper and lower jaw models specifically includes:
  • the upper jaw three-dimensional model and the lower jaw three-dimensional model are simulated to obtain a standard upper and lower jaw three-dimensional model.
  • oral scanning can be used to collect the subject's oral cavity to obtain a standard three-dimensional model of the maxillary and mandibular dentition, which may include the following steps:
  • the method of obtaining the mandibular movement trajectory can be any method of collecting the mandibular movement trajectory in the existing technology.
  • obtaining the mandibular movement trajectory can specifically include the following steps:
  • the upper dentition jaw pad and the lower dentition jaw pad of the collection object are produced, an upper target is provided at the front dentition of the upper dentition jaw pad, and a lower target is provided at the front dentition of the lower dentition jaw pad. target;
  • the collection subject is made to wear the upper dentition jaw pad and the lower dentition jaw pad, and a mandibular movement trajectory scanner is used to track the upper target and lower target to obtain the mandibular movement trajectory.
  • Step S202 using the mesial incisal angle of the incisors and the mesial cusps of the left and right first molars as reference points, match the standard maxillary and mandibular dentition three-dimensional model with the alternative craniofacial three-dimensional digital model to obtain a corrected craniofacial model. 3D digital model.
  • the corrected craniofacial three-dimensional digital model is used to replace the corresponding candidate craniofacial three-dimensional digital model in the candidate model library, so that Update the information in the alternative model library.
  • the software that performs this step can use any software in the existing technology that can perform the above operations, for example, Geomagic Studio software.
  • obtaining the datum surface type parameters may specifically include the following steps S211 to S212:
  • Step S211 Obtain a reference craniofacial three-dimensional digital model.
  • the reference cranial three-dimensional digital model can be obtained by at least the following two methods:
  • the first solution is to directly select the reference craniofacial three-dimensional digital model from multiple candidate craniofacial three-dimensional digital models
  • the second solution is to fuse multiple candidate craniofacial three-dimensional digital models to generate the reference craniofacial three-dimensional digital model.
  • this step S211 may specifically include the following steps S2111 and S2112:
  • Step S2111 Obtain multiple candidate craniofacial models.
  • the candidate craniofacial model is selected from alternative craniofacial models, and the candidate craniofacial model and the target craniofacial model satisfy the first screening rule, thereby achieving preliminary screening of alternative craniofacial models.
  • the first screening rule can be specifically formulated according to specific needs.
  • candidate craniofacial models are divided into 8 categories based on facial length, width, and the front-to-back position relationship of the upper and lower jaws.
  • the first screening rule is: a category of candidate craniofacial models that have the same characteristics as the target craniofacial model. .
  • the first screening rule can also be other rules that can screen out corresponding candidate craniofacial models from the candidate craniofacial models according to specific needs, so that the similarity between the candidate craniofacial model and the target craniofacial model is higher.
  • Step S2112 Generate a reference cranial three-dimensional digital model based on the candidate craniofacial model according to the first conversion rule.
  • the first conversion rule is to select a candidate craniofacial model with the highest similarity to the target craniofacial model from the candidate craniofacial models as the base craniofacial three-dimensional digital model, without doing anything to the candidate craniofacial model. data deal with.
  • the first conversion rule is the candidate craniofacial model with the highest similarity to the target craniofacial three-dimensional digital model.
  • sampling points used to calculate the similarity between two three-dimensional digital models can be specifically set according to specific needs.
  • this step S211 may specifically include the following steps S2113 and S2114:
  • Step S2113 Obtain multiple candidate craniofacial models.
  • the candidate craniofacial model is selected from alternative craniofacial models, and the candidate craniofacial model and the target craniofacial model satisfy the second screening rule, thereby achieving preliminary screening of alternative craniofacial models.
  • the second filtering rule may be the same as the first filtering rule, or may be different from the first filtering rule, so as to meet the requirements of selecting the candidates that can be more accurately fused into the base craniofacial system in the second solution.
  • the second filtering rule may satisfy a preset condition for the corresponding parameter, wherein the corresponding parameter is included in the line distance and angle representing the surface shape, and the preset condition is the same, or Meet the preset threshold range.
  • Step S2114 Generate a reference craniofacial three-dimensional digital model based on the candidate craniofacial model according to the second conversion rule.
  • the second conversion rule may include the following steps:
  • the modules to be fused are fused to generate a reference craniofacial three-dimensional digital model.
  • each module to be fused is fused with each other to obtain a complete craniofacial three-dimensional digital model.
  • Step S212 Measure the reference craniofacial three-dimensional digital model to obtain reference facial profile parameters, which correspond to the target facial profile parameters.
  • the reference craniofacial three-dimensional digital model is measured to obtain the reference facial shape parameters.
  • the method used to measure the reference craniofacial three-dimensional digital model is the same as the method used to measure the target craniofacial three-dimensional digital model.
  • PROPLAN CMF software is used for cephalometric measurement.
  • sampling points of the two also correspond to the same, so that the initial data collected are comparable.
  • they can be traditional cephalometric parameters and temporomandibular joint parameters.
  • the reference section fitting curve equation may specifically include the following steps S221 to S224:
  • Step S221 Obtain the reference envelope model.
  • the reference envelope model is the envelope surface formed by the movement of the condyle of the temporomandibular joint in the reference craniofacial three-dimensional digital model.
  • the reference envelope model can be calculated based on the reference craniofacial three-dimensional digital model and the mandibular movement trajectory. Specifically, the following steps S2211 to S2212 can be included:
  • Step S2211 Match the mandibular movement trajectory with the corresponding candidate craniofacial three-dimensional digital model.
  • the matching refers to combining the mandibular movement data through the standard three-dimensional model of the maxillary and mandibular dentition and The process of matching the three-dimensional digital model of the target head and unifying the mandibular movement trajectory with the three-dimensional digital model of the target head in the same coordinate system.
  • This application does not specifically limit the software used to perform this step. Any software in the existing technology that can perform the above steps can be used, for example, Geomagic Studio software.
  • Step S2212 Calculate and generate a reference envelope surface model based on the mandibular movement trajectory and the condylar movement functional surface preset on the candidate craniofacial three-dimensional digital model.
  • the mandibular condyle motion envelope surface is obtained through computer simulation. Specifically, the mandible can be moved in a preset sequence, and the mandibular motion trajectory can be set at each The positions at each moment are saved, and the positions are superimposed, and the result is the condylar motion envelope surface.
  • the specific implementation manner of this step can be any method in the prior art that can implement this step.
  • Step S222 Use the reference section to intercept the reference envelope model to form an actual curve of the reference section of the envelope surface.
  • any method in the existing technology that can perform planar interception of a three-dimensional digital model can be used.
  • Geomagic software can be used to implement the above solution.
  • the reference section is taken as the sagittal plane.
  • step S221 import the datum envelope model obtained in step S221 into the Geomagic software, adjust the direction of the datum envelope surface in the software, and then use the horizontal plane section function to perform a sagittal cross-section of the datum envelope surface. , further, extract the cross-sectional curve of the reference envelope model on the sagittal cross-section based on the sagittal cross-section, and save the cross-sectional curve in Obj. format.
  • Figure 4-1 shows the sagittal cross-sectional front view of the envelope surface shown in Figure 2-1
  • Figure 4-2 shows the three-dimensional structural diagram of the structure shown in Figure 4-1, as shown in Figure 4-1 and Figure 4-2
  • the cross-sectional curve obtained in this step is approximately a bimodal curve.
  • Step S223 Obtain the coordinates of multiple feature points on the actual curve of the reference section of the envelope surface.
  • the cross-sectional curve extracted in step S222 is opened in txt. format, and the coordinates of multiple feature points are extracted on the cross-sectional curve.
  • the coordinates of the characteristic points can be imported into the MATLAB software, the spatial coordinates of the characteristic points can be converted into two-dimensional plane point coordinates, and then the cross-sectional curve can be aligned using the orbital plane as the reference horizontal plane. Rotate clockwise or counterclockwise to obtain the coordinates of the cross-sectional curve point in the xy plane when the orbital auricular plane is parallel to the x-axis.
  • the coordinates used in subsequent steps are the coordinates of the cross-section curve points.
  • Characteristic point coordinates are selected on the processed cross-sectional curve.
  • the number of characteristic points and the selected five categories can be specifically set according to the specific shape of the cross-sectional curve.
  • Feature point (1) is the highest point of the first bulge from the left, and determine this point as the proposed new two-dimensional coordinate
  • the origin of the system the characteristic point (2) is the lowest point in the depression of the two peaks
  • the characteristic point (3) is the highest point of the second bulge from the left
  • characteristic point (5) and characteristic point (6) are the cross-sectional curve at characteristic point (1) and the two points between the characteristic point (2)
  • the characteristic point (7) and the characteristic point (8) are the two points of the cross-sectional curve between the characteristic point (2) and the characteristic point (3)
  • the characteristic point (9) and characteristic point (10) are the two points of the cross-sectional curve in the positive x direction of the characteristic point (3) in the proposed two-dimensional coordinate system.
  • Step S224 Generate a reference section fitting curve equation based on the coordinates of the plurality of feature points.
  • Figure 5 shows the fitting curve obtained by fitting based on the cross-sectional curves shown in Figure 4-1 and Figure 4-2.
  • MATLAB is used to fit the feature point coordinates obtained in step S223, as shown in Figure 5 , generate a datum section fitting curve and the datum section fitting curve equation.
  • this step can use a Fourier transform to generate a datum section fitting curve.
  • the reference section fitting curve can be pre-stored in the database, and during subsequent use, the reference section fitting curve corresponding to the target head model type can be directly retrieved according to the type of the target head.
  • the matrix can also be pre-stored in the database, and during subsequent use, the matrix corresponding to the target head model type can be directly retrieved according to the type of the target head.
  • reference section fitting curve and matrix pre-stored in the database can be updated at any time as needed.
  • this step can be specifically implemented by using any method in the prior art that generates a corresponding matrix based on parameters and corresponding fitting curves.
  • the parameters in the datum section fitting curve equation are extracted, and the datum surface type parameters and the parameters of the datum section fitting curve equation are input into MATLAB, and then the matrices of the two are calculated.
  • S400 Generate a target cross-section curve according to the matrix and the target surface shape parameters.
  • this step may specifically include the following steps S401 and S402:
  • Step S401 Use the target surface shape parameters and the matrix to perform an inverse operation to generate a target cross-section curve equation.
  • this step may be the inverse operation of step S300.
  • the target surface shape parameters are input into MATLAB, the matrix is used to calculate the parameters to generate the target cross-section curve equation, and the parameters are then used to generate the target cross-section curve equation.
  • Step S402 Draw a target cross-section curve according to the target cross-section curve equation.
  • data processing software is used to generate a target section curve equation according to the parameters, that is, the target section curve is predicted.
  • the method provided by this application simplifies the expression of the three-dimensional shape of the envelope surface into the two-dimensional shape of the sagittal cross-section curve of the envelope surface.
  • This curve has regularity, and its mathematical expression and prediction have extremely high application value, and can realize individual analysis. Envelope surface morphology prediction.
  • step S002 is not particularly limited, and any method in the prior art that generates a curved surface including multiple curves based on the multiple curves can be used.
  • step S003 is not particularly limited, and any existing method that can generate a corresponding curved surface based on a curved surface equation can be used. It can be understood that the above solution can be implemented with the help of any software in the existing technology.
  • the generation of the temporomandibular joint condylar motion envelope can be understood as drawing the temporomandibular joint condylar motion envelope.
  • this application also provides a device for generating the temporomandibular joint condylar motion envelope cross-sectional curve based on facial parameters.
  • the device includes:
  • a cross-sectional curve generation unit is used to generate multiple temporomandibular joint condylar motion envelope cross-sectional curve equations according to the aforementioned method
  • a curve generation unit configured to generate multiple temporomandibular joint condyle motion envelope curves based on the multiple temporomandibular joint condylar motion envelope cross-sectional curve equations
  • a curved surface generation unit is used to generate a temporomandibular joint condyle motion envelope surface based on the plurality of temporomandibular joint condyle motion envelope curves.
  • This application also provides a method for generating a temporomandibular joint condylar motion envelope cross-sectional curve based on facial parameters.
  • the method includes:
  • a target cross-section curve is generated according to the matrix and the target surface shape parameters.
  • each step in the method of generating the temporomandibular joint condylar motion envelope cross-sectional curve based on facial parameters corresponds to the specific implementation manner of the aforementioned steps S100 to S400, and will not be described again here.
  • This application also provides a device for generating a temporomandibular joint condylar motion envelope cross-sectional curve based on facial parameters.
  • the device includes:
  • a parameter acquisition unit is used to acquire target craniofacial features and target facial parameters
  • a curve equation fitting unit used to obtain datum surface shape parameters and datum cross-section fitting curve equations in combination with the target craniofacial features
  • a matrix generation unit configured to generate a matrix according to the datum surface type parameters and the datum section fitting curve equation
  • the curve fitting unit is also used to generate a target cross-section curve according to the matrix and the target surface shape parameters.
  • each unit is specifically used to implement the solution of each corresponding step.
  • the method provided by this application uses the datum surface shape parameters and the datum cross-section curve to generate a matrix, and uses the matrix as a conversion intermediary to generate the cross-sectional curve of the target condyle motion envelope.
  • the target cross-sectional curve is obtained by using the matrix reversible operation.
  • multiple target cross-sectional curves are obtained according to the facial parameters of the same target head.
  • the multiple target cross-sectional curves can constitute the target condylar motion envelope surface.
  • the method provided by this application simplifies the expression of the temporomandibular joint condylar motion envelope surface and covers its main morphological characteristics. Furthermore, a mathematical expression method for the simplified form of the temporomandibular joint condylar motion envelope surface is proposed. This enables the morphological information of the condylar motion envelope of the temporomandibular joint to be quantitatively studied.
  • the method provided by this application can generate a cross-sectional curve on any cross-section of the target condylar motion envelope, for example, the cross-sectional curve of the target condylar motion envelope on the sagittal cross-section of the target skull, and can also be The cross-sectional curve of the target condylar motion envelope surface on other representative cross-sections of the target head.

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Abstract

本申请公开了一种基于面型参数生成颞下颌关节髁突运动包络面及其截面曲线的方法和装置，所述方法通过测量颞下颌关节健康人的基准面型参数，并基于所述基准面型参数以及基准髁突运动包络面截面曲线方程生成矩阵，再利用所述矩阵以及目标面型参数生成目标髁突运动包络面特定截面的目标截面曲线，进一步地，基于多条所述目标截面曲线可生成目标髁突运动包络面。

Description

基于面型参数生成颞下颌关节髁突运动包络面方法和装置 技术领域
本申请属于数字化医学领域，特别涉及一种基于面型参数生成颞下颌关节髁突运动包络面及其截面曲线的方法和装置。
背景技术
颞下颌关节是颅颌面唯一可活动的关节，也是人体最复杂的关节之一。图1示出颞下颌关节的结构示意图，如图1所示，颞下颌关节主要包括关节盘001、关节突002和关节窝003。所述颞下颌关节既可进行滑动运动，也可进行转动运动，从而实现重要的生理功能，主要包括开闭口、吞咽、咀嚼、语言等。对于因肿瘤、创伤、感染、关节强直等疾病造成的颞下颌关节缺损，而不能正常行使功能者，人工颞下颌全关节假体置换术是近年来发展迅速的治疗手段之一。
目前，人工颞下颌关节假体一般参照髋关节等四肢大关节进行设计，以球窝关系或近似球窝关系的设计为主，目的是增加关节窝假体对关节突假体的形态约束，防止因关节周围组织的缺失而导致的脱位。但是在生理状态下，颞下颌关节的关节突远小于关节窝，借助周围组织如关节盘、关节囊、肌肉等实现比四肢大关节更为灵活的运动，因而参照大关节设计的人工颞下颌关节，在植入相应位置后，颞下颌关节的运动情况与健康关节相差较大，现有临床病例长期随访结果显示患者术后开口度常无法达到正常值，也无法良好实现侧方运动及前伸运动。
现有技术除参照大关节设计的球窝关节外，也有参照正常颞下颌关节骨性结构设计的全关节假体。但是与天然关节相比，全关节假体无法模拟关节盘功能，因此仅参照骨性结构设计的人工关节假体仍然无法充分恢复关节运动功能，因而难以获得满意的临床效果。随访结果显示术后患者在开口度、前伸、侧方运动等方面仍与生理状态存在较大差别。
进一步地，对于单侧全关节置换者，由于双侧关节运动不一致，导致关节假体对侧的天然关节受力较大、运动范围改变较大，因而导致对侧天然关节发生潜在病损。
颞下颌关节髁突运动包络面是髁突自然运动可达的边界范围，颞下颌关节髁突运动包络面的形态能够引导人工关节突沿关节窝功能面运动，从而实现下颌骨的生理运动方式。
然而，需要全关节置换者多因肿瘤、创伤、感染、关节强直等疾病无法实现下颌骨的运动，无法直接获得其颞下颌关节髁突运动包络面数据。因此，亟需获得一种生成颞下颌关节髁突运动包络面的方法。
发明内容
为解决现有技术所存在的技术问题，本申请人经过锐意研究，通过测量颞下颌关节健康人的部分面型参数，并基于所述面型参数生成矩阵，再利用所述矩阵以及目标面型参数生成目标髁突运动包络面特定截面的截面曲线。进一步地，基于多条所述截面曲线可生成目标髁突运动包络面。
本申请的目的在于提供以下几个方面：
第一方面，本申请提供一种基于面型参数生成颞下颌关节髁突运动包络面方法，所述方法包括：
获取多条颞下颌关节髁突运动包络面截面曲线方程；
根据多条所述颞下颌关节髁突运动包络面截面曲线方程生成多条颞下颌关节髁突运动包络面曲线；
根据所述多条颞下颌关节髁突运动包络面曲线生成颞下颌关节髁突运动包络面。
在一种可实现的方式中，所述获取多条颞下颌关节髁突运动包络面截面曲线方程具体包括：
获取目标颅面特征以及目标面型参数；
结合所述目标颅面特征获取基准面型参数以及基准截面拟合曲线方程；
根据所述基准面型参数以及所述基准截面拟合曲线方程生成矩阵；
根据所述矩阵以及所述目标面型参数生成目标截面曲线方程。
在一种可实现的方式中，所述获取目标颅面特征包括：
获取目标颅面三维数字模型；
基于所述目标颅面三维数字模型提取目标颅面特征。
在一种可实现的方式中，所述获取目标面型参数包括：
获取目标颅面三维数字模型；
测量所述目标颅面三维数字模型获取目标面型参数，所述目标面型参数包括SNA、SNB、下颌角间距、下颌体长、下颌平面角度、N-Me连线与FH平面之间的角度。
在一种可实现的方式中，所述获取基准面型参数包括：
获取基准颅面三维数字化模型；
测量所述基准颅面三维数字化模型获取基准面型参数，所述基准面型参数与所述基准面型参数的类型对应相同。
可选地，获取基准颅面三维数字化模型包括：
获取多个候选颅面模型；
基于所述多个候选颅面模型根据预设规则生成基准颅面三维数字模型。
在一种可实现的方式中，所述获取基准截面拟合曲线方程包括：
获取基准包络面模型；
利用基准截面对所述基准包络面模型进行截取，形成包络面基准截面实际曲线；
获取所述包络面基准截面实际曲线上多个特征点的坐标；
根据多个所述特征点的坐标生成基准截面拟合曲线方程。
在一种可实现的方式中，根据所述矩阵以及所述目标面型参数生成目标截面曲线包括：
利用所述目标面型参数以及所述矩阵进行逆运算生成目标截面曲线方程；
根据所述目标截面曲线方程绘制目标截面曲线。
第二方面，本申请还提供一种基于面型参数生成颞下颌关节髁突运动包络面装置，所述装置包括：
截面曲线生成单元，用于生成多条颞下颌关节髁突运动包络面截面曲线方程；
曲面方程生成单元，用于根据多条所述颞下颌关节髁突运动包络面截面曲线方程生 成多条颞下颌关节髁突运动包络面曲线；
曲面生成单元，用于根据所述多条颞下颌关节髁突运动包络面曲线生成颞下颌关节髁突运动包络面。
第三方面，本申请还提供一种基于面型参数生成颞下颌关节髁突运动包络面的程序，所用程序用于执行时实现上述第一方面所述生成颞下颌关节髁突运动包络面方法的步骤。
第四方面，一种计算机可读存储介质，其上存储有计算机指令，该指令被处理器执行时实现上述第一方面所述生成颞下颌关节髁突运动包络面方法的步骤。
第五方面，一种检测设备，所述检测设备包括：至少一个处理器；以及与所述至少一个处理器通信连接的存储器；其中，所述存储器存储有可被所述一个处理器执行的指令，所述指令被所述至少一个处理器执行，以使所述至少一个处理器执行上述第一方面所述生成颞下颌关节髁突运动包络面方法。
第六方面，本申请还提供一种基于面型参数生成颞下颌关节髁突运动包络面截面曲线方法，所述方法包括：
获取目标颅面特征以及目标面型参数；
结合所述目标颅面特征获取基准面型参数以及基准截面拟合曲线方程；
根据所述基准面型参数以及所述基准截面拟合曲线方程生成矩阵；
根据所述矩阵以及所述目标面型参数生成目标截面曲线。
在一种可实现的方式中，所述获取目标颅面特征包括：
获取目标颅面三维数字模型；
基于所述目标颅面三维数字模型提取目标颅面特征。
在一种可实现的方式中，所述获取目标面型参数包括：
获取目标颅面三维数字模型；
测量所述目标颅面三维数字模型获取目标面型参数，所述目标面型参数包括SNA、SNB、下颌角间距、下颌体长、下颌平面角度、N-Me连线与FH平面之间的角度。
在一种可实现的方式中，所述获取基准面型参数包括：
获取基准颅面三维数字化模型；
测量所述基准颅面三维数字化模型获取基准面型参数，所述基准面型参数与所述基准面型参数的类型对应相同。
可选地，获取基准颅面三维数字化模型包括：
获取多个候选颅面模型；
基于所述多个候选颅面模型根据预设规则生成基准颅面三维数字模型。
在一种可实现的方式中，所述获取基准截面拟合曲线方程包括：
获取基准包络面模型；
利用基准截面对所述基准包络面模型进行截取，形成包络面基准截面实际曲线；
获取所述包络面基准截面实际曲线上多个特征点的坐标；
根据多个所述特征点的坐标生成基准截面拟合曲线方程。
在一种可实现的方式中，根据所述矩阵以及所述目标面型参数生成目标截面曲线包括：
利用所述目标面型参数以及所述矩阵进行逆运算生成目标截面曲线方程；
根据所述目标截面曲线方程绘制目标截面曲线。
第七方面，本申请还提供一种基于面型参数生成颞下颌关节髁突运动包络面截面曲线装置，所述装置包括：
参数获取单元，用于获取目标颅面特征以及目标面型参数；
曲线方程拟合单元，用于结合所述目标颅面特征获取基准面型参数以及基准截面拟合曲线方程；
矩阵生成单元，用于根据所述基准面型参数以及所述基准截面拟合曲线方程生成矩阵；
所述曲线拟合单元还用于，根据所述矩阵以及所述目标面型参数生成目标截面曲线。
第八方面，本申请还提供一种基于面型参数生成颞下颌关节髁突运动包络面截面曲线的程序，所用程序用于执行时实现上述第六方面所述基于面型参数生成颞下颌关节髁突运动包络面截面曲线方法的步骤。
第九方面，一种计算机可读存储介质，其上存储有计算机指令，该指令被处理器执行时实现上述第六方面所述基于面型参数生成颞下颌关节髁突运动包络面截面曲线方法的步骤。
第十方面，一种检测设备，所述检测设备包括：至少一个处理器；以及与所述至少一个处理器通信连接的存储器；其中，所述存储器存储有可被所述一个处理器执行的指令，所述指令被所述至少一个处理器执行，以使所述至少一个处理器执行上述第六方面所述基于面型参数生成颞下颌关节髁突运动包络面截面曲线方法。
与现有技术相比，本申请提供的方法根据线性变换的矩阵表示理论，首先生成以矩阵形式表示的头颅模型中可测的面型参数与颞下颌关节髁突运动包络面截面曲线系数的映射关系，再基于在目标头颅模型中可测的面型参数利用所述矩阵进行逆运算生成颞下颌关节髁突运动包络面截面曲线，从而实现仅利用静态参数即可生成较为准确的运动包络面截面曲线，基于此，能够较为准确地生成由于种种原因而无法采集的健康状态下髁突运动包络面各参数。
进一步地，本申请提供的方法，物理参数的采集方法简便易行，所有参数均为无创采集，并且，各参数的采集可借助常规检查结果，而无需进行特别的参数采集，并且，方案整体计算量较小，能够实现目标包络面截面曲线以及包络面的快速确定。
附图说明
图1示出颞下颌关节的结构示意图；
图2-1示出一种健康颞下颌关节髁突运动包络面的立体结构示意图；
图2-2示出图2-1所示关节突运动包络面的立体结构网格图；
图3示出本申请提供的基于面型参数生成颞下颌关节髁突运动包络面截面曲线方法的流程图；
图4-1示出图2-1所示包络面的矢状截面主视图；
图4-2示出图4-1所示结构的立体结构示意图；
图5示出根据图4-1以及图4-2所示截面曲线进行拟合所得拟合曲线。
具体实施方式
首先，对本方案的使用场景作简要介绍。
如图1所示，对于健康人而言，颞下颌关节主要包括关节盘001、关节突002和关节窝003，其中，所述关节突002在所述关节盘001的牵引和限制下，可在所述关节窝003中滑动或者转动，从而实现下颌的各种生理功能，例如，闭口、吞咽、咀嚼或者语言等。
在本申请中，术语“颞下颌关节髁突”与术语“关节突”指代相同，即，二者表示相同的生理位置及结构。
图2-1示出一种健康颞下颌关节髁突运动包络面的立体结构示意图，图2-2示出图2-1所示关节突运动包络面的立体结构网格图，如图2-1和图2-2所示，健康关节突在关节窝中的运动轨迹难以用简单的数学表达式表达。
在本申请中，所述颞下颌关节髁突运动包络面(为方便表述，下文简称为“包络面”)是指颞下颌关节做各种运动过程中，所述颞下颌关节突的运动边界。实际上，在最大开口时，关节突的部分结构超出对应的关节窝。
由图2-1以及图2-2可见，所述包络面为一个不规则并且不平整的面，并且，从立体角度看，所述包络面形成一个不规则的窝状结构，但是，该窝状结构与骨性关节窝的结构并不相同。
可以理解的是，对于需要进行颞下颌全关节置换的患者，在去除病患后健康状态下的包络面难以预先确定。由于所述包络面的形态是设计人工颞下颌关节假体的关键参数，因此，预先确定较为准确的包络面形态在实践中尤为重要。
基于此，本申请提供一种基于面型参数生成颞下颌关节髁突运动包络面截面曲线的方法，具体地，首先对基准头颅颞下颌关节髁突运动包络面在特定截面上的截面曲线进行数学表达，再以矩阵的方法生成面型参数-包络面矢状截面的矩阵，再根据目标头颅的对应面型参数利用所述矩阵计算所述目标头颅颞下颌关节髁突运动包络面在相应截面上的截面曲线的数学表达式。
进一步地，基于所述颞下颌关节髁突运动包络面截面曲线可生成相应包络面的表达式，并绘制出相应形态。
具体地，图3示出本申请提供的基于面型参数生成颞下颌关节髁突运动包络面方法的流程图，如图3所示，所述方法包括以下步骤S001至步骤S003：
S001，获取多条颞下颌关节髁突运动包络面截面曲线方程；
S002，根据多条所述颞下颌关节髁突运动包络面截面曲线方程生成颞下颌关节髁突运动包络面曲线；
S003，根据所述颞下颌关节髁突运动包络面曲线生成颞下颌关节髁突运动包络面。
在本实例中，步骤S001具体可以包括以下步骤S100至步骤S400：
S100，获取目标颅面特征以及目标面型参数。
在本实例中，所述获取目标颅面特征具体可以包括以下步骤S111和步骤S112：
步骤S111，获取目标颅面三维数字模型。
在本实例中，所述目标颅面三维数字模型可以是根据目标头颅的二维数字信息利用计算机辅助的手段重建而得的。
步骤S112，基于所述目标颅面三维数字模型提取目标颅面特征。
在本实例中，所述目标颅面特征是指提取自目标头颅三维数字化模型的颅面特征，该颅面特征可以被认为是目标对象的颅面特征。
进一步地，所述颅面特征可以根据具体需要而具体设定，例如，颅面特征可以包括 面型长短、宽窄以及上下颌的前后位置关系等，其中，用于判定面型长短、宽窄、上下颌的前后位置关系等特征的具体参数可以根据需要而具体设定。
更进一步地，前述各颅面特征还可以进一步拆解为多个子特征。
可以理解的是，根据具体的需求，所述颅面特征还可以包括其它参数。
在本实例中，所述目标面型参数是指提取自目标三维数字化模型的面型参数。
在本实例中，所述面型参数不同于所述颅面特征，其中，所述颅面特征为定性划分颅面类型的依据，而所述面型参数提取于颅面三维数字模型，能够反映被采集对象面型特征的定量数据。
在本实例中，所述获取目标面型参数具体可以包括以下步骤S121和步骤S122：
步骤S121，获取目标颅面三维数字模型。
在本实例中，本步骤可以直接调用步骤S111生成的目标颅面三维数字模型，以避免重复性计算。
步骤S122，基于所述目标颅面三维数字模型测量目标面型参数，所述目标面型参数包括颞下颌关节的相应参数和肌肉相关的参数等，例如，SNA、SNB、下颌角间距、下颌体长、下颌平面角度、N-Me连线与FH平面之间的角度。
可以理解的是，目标面型参数还可以包括其它能够进行包络面形态预测的其他参数。
在本实例中，测量目标面型参数可以使用现有技术中任意一种可基于三维数字化模型测量数据的方法，例如，可以使用PROPLAN CMF软件对目标颅三维数字模型进行头影测量，从而获得目标面型参数。
S200，获取基准面型参数以及基准截面拟合曲线方程。
在本申请中，所述基准面型参数为基于基准颅面三维数字化模型而获取的面型参数，其中，所述基准头颅三维数字化模型为基于健康人群的头颅三维数字化模型获取。
在本申请中，为方便表述，将健康人群的头颅三维数字化模型简称为备选头颅三维数字化模型，所述备选头颅三维数字化模型可以被存储于备选模型库中，所述备选模型库包括有效数量的备选头颅三维数字化模型，例如，每种面型的备选头颅三维数字化模型至少有一种。
可选地，备选头颅三维数字化模型的重建方式与目标头颅三维数字化模型的重建方式相同，既简化处理操作方式，也使得二者的数据具有可对比性。
在本实例中，所述备选头颅三维数字化模型可以直接选自健康人群的头颅三维数字化模型，还可以在所述健康人群的头颅三维数字化模型的基础上，进一步根据上下颌数字化实体模型进行校正而得的三维数字化模型，所述上下颌数字化实体模型包括石膏模型扫描模型，或者，口扫采集对象口腔所得数字化模型。
具体地，根据上下颌数字化实体模型对备选头颅三维数字化模型进行校正具体包括以下步骤S201至步骤S202：
步骤S201，获取标准上下颌牙列三维模型和下颌运动轨迹。
在一种可实现的方式中，可使用石膏模型获取标准上下颌牙列三维模型，具体可以包括以下步骤：
制作采集对象的可拆分的上下颌实体模型，其中，所述上下颌实体模型可拆分为相互独立的上颌实体模型以及下颌实体模型；
使用扫描仪对所述上下颌实体模型进行扫描，得到标准上下颌牙列三维模型。
其中，对使用扫描仪对所述上下颌模型进行扫描具体包括：
将咬合状态的上下颌实体模型进行扫描，得到咬合上下颌三维模型；
将上颌模型与下颌模型分别进行扫描，分别得到上颌三维模型和下颌三维模型；
根据所述咬合上下颌三维模型的咬合关系，将上颌三维模型与下颌三维模型进行咬合模拟，得到标准上下颌三维模型。
在另一种可实现的方式中，可使用口扫采集对象口腔获取标准上下颌牙列三维模型，具体可以包括以下步骤：
使用口腔扫描仪对采集对象的口腔内部进行扫描，得到标准上下颌牙列三维模型。
在本实例中，获取下颌运动轨迹的方法可以采用现有技术中任意一种采集下颌运动轨迹的方法，例如，获取下颌运动轨迹可以具体包括以下步骤：
制作采集对象的上牙列颌垫以及下牙列颌垫，在所述上牙列颌垫的前牙列处设置有上靶标，在所述下牙列颌垫的前牙列处设置有下靶标；
令采集对象佩戴所述上牙列颌垫和所述下牙列颌垫，利用下颌运动轨迹扫描仪跟踪所述上靶标和下靶标，获得下颌运动轨迹。
步骤S202，以切牙近中切角、左右第一磨牙近中牙尖作为基准点，将所述标准上下颌牙列三维模型与所述备选颅面三维数字化模型进行匹配，得到校正颅面三维数字模型。
在本实例中，如果对备选颅面三维数字模型进行校正获得校正颅面三维数字模型，则在备选模型库中，使用校正颅面三维数字模型替换对应备选颅面三维数字模型，从而更新备选模型库中的信息。
在本实例中，执行本步骤的软件可以使用现有技术中任意一种可执行上述操作的软件，例如，Geomagic Studio软件。
在本实例中，所述获取基准面型参数可以具体包括以下步骤S211至步骤S212：
步骤S211，获取基准颅面三维数字化模型。
在本实例中，所述基准颅三维数字化模型可以由至少以下两种方案获取：
第一种方案为：由多个候选颅面三维数字化模型中直接选取所述基准颅面三维数字化模型；
第二种方案为：由多个候选颅面三维数字化模型进行融合，生成所述基准颅面三维数字化模型。
在第一种方案中，本步骤S211可以具体包括以下步骤S2111和步骤S2112：
步骤S2111，获取多个候选颅面模型。
在本方案中，所述候选颅面模型选自备选颅面模型，所述候选颅面模型与目标颅面模型满足第一筛选规则，从而实现对备选颅面模型进行初步筛选。
在本方案中，所述第一筛选规则可根据具体需要而具体制定。例如，根据面型的长短、宽窄、上下颌的前后位置关系等特征将备选颅面模型划分为8类，第一筛选规则为：与目标头颅面型特征相同的一类备选颅面模型。
可以理解的是，第一筛选规则还可以为根据具体需求能够从备选颅面模型中筛选出相应候选颅面模型的其它规则，使得候选颅面模型与目标颅面模型的相似度更高。
步骤S2112，基于所述候选颅面模型根据第一转换规则生成基准颅三维数字模型。
在本方案中，所述第一转换规则为从所述候选颅面模型中选择一个与目标颅面模型相似度最高的候选颅模型作为基准颅面三维数字模型，而不对候选颅面模型做任何数据 处理。
在本方案中，所述第一转换规则为与所述目标颅面三维数字模型相似度最高的候选颅面模型。
进一步地，本方案对计算所述目标颅面三维数字模型与候选颅模型相似度的方法不做任何限定，可以使用现有技术中任意一种可用于计算两个三维数字模型相似度的方法，例如，中国专利申请CN109767841A公开的颅面三维形态数据库相似模型的检索方法。
在本实例中，用于计算两个三维数字模型相似度的采样点可以根据具体需要而具体设定。
在第二种方案中，本步骤S211可以具体包括以下步骤S2113和步骤S2114：
步骤S2113，获取多个候选颅面模型。
在本方案中，所述候选颅面模型选自备选颅面模型，所述候选颅面模型与目标颅面模型满足第二筛选规则，从而实现对备选颅面模型进行初步筛选。
在本实例中，所述第二筛选规则可以与所述第一筛选规则相同，也可以与所述第一筛选规则不同，以满足在第二种方案中筛选出能够更准确融合成基准颅面三维数字模型的候选颅面模型。
在一种可实现的方式中，所述第二筛选规则可以为相应参数满足预设条件，其中，所述相应参数包括于表示面型的线距以及角度，所述预设条件为相同，或者符合预设阈值范围。
步骤S2114，基于所述候选颅面模型根据第二转换规则生成基准颅面三维数字模型。
在本方案中，所述第二转换规则可以包括以下步骤：
分别将每个所述候选颅面模型与所述目标颅面三维数字模型进行比对；
将各候选颅面模型中与目标颅面模型相似度最大的区域进行截取，获得多个待融合模块；
将各待融合模块进行融合生成基准颅面三维数字模型。
在本方案中，各待融合模块相互融合成能够获得一个完成的颅面三维数字模型。
步骤S212，测量所述基准颅面三维数字化模型获取基准面型参数，所述基准面型参数与所述目标面型参数对应相同。
在本实例中，对所述基准颅面三维数字化模型进行测量从而获取基准面型参数，优选地，测量基准颅面三维数字化模型所用的方法与测量所述目标颅面三维数字化模型所用的方法相同，例如，在本实例中，均使用PROPLAN CMF软件进行头影测量。
进一步地，二者的采样点也对应相同，使得采集所得初始数据具有可比性，例如，在本实例中，可以为传统头影测量参数和颞下颌关节参数等。
在本实例中，所述基准截面拟合曲线方程具体可以包括以下步骤S221至步骤S224：
步骤S221，获取基准包络面模型。
在本实例中，所述基准包络面模型为基准颅面三维数字化模型中颞下颌关节髁突运动形成的包络面。
在本实例中，所述基准包络面模型可根据所述基准颅面三维数字化模型以及下颌运动轨迹计算而得，具体地，可以包括以下步骤S2211至步骤S2212：
步骤S2211，将所述下颌运动轨迹与对应的备选颅面三维数字模型进行匹配。
在本实例中，所述匹配是指将下颌运动的数据通过所述标准上下颌牙列三维模型与 目标头颅三维数字化模型进行匹配，将下颌运动轨迹与所述目标头颅三维数字化模型统一坐标系的过程。
本申请对执行本步骤所使用的软件不做特别限定，可以使用现有技术中任意一种可执行上述步骤的软件，例如，Geomagic Studio软件。
步骤S2212，根据所述下颌运动轨迹以及预设于所述备选颅面三维数字模型上的髁突运动功能面，计算生成基准包络面模型。
在本实例中，所述髁突运动功能面配准之后，通过计算机仿真获得下颌骨髁突运动包络面，具体地，可使下颌骨按预设顺序运动，并将下颌骨运动轨迹在每个时刻的位置均进行保存，将所述位置进行叠加，所得结果即为髁突运动包络面。
在本实例中，本步骤的具体实现方式可以采用现有技术中任意一种可实现本步骤的方式。
步骤S222，利用基准截面对所述基准包络面模型进行截取，形成包络面基准截面实际曲线。
在本实例中，可以采用现有技术中任意一种可对三维数字模型进行平面截取的方法，例如，可以使用Geomagic软件实现上述方案。
为便于说明，在本实例中，基准截面以矢状面为例进行说明。
本申请人发现，使用矢状面作为基准截面对于目标包络面截面曲线以及目标包络面模型的完成有重要作用，同时，也为目标关节窝功能面的确立提供重要参考。
可以理解的是，在本方案中，还可以使用其它截面对所述基准包络面模型进行截取，其它截面不仅可以为冠状截面，还可以为其它角度的平面。
具体地，将步骤S221获得的基准包络面模型导入到Geomagic软件，并在该软件内调整所述基准包络面的方向，再使用水平面截面功能对所述基准包络面进行矢状向截面，进一步地，基于所述矢状向截面提取所述基准包络面模型在所述矢状向截面上的截面曲线，并将所述截面曲线保存为Obj.格式。
图4-1示出图2-1所示包络面的矢状截面主视图，图4-2示出图4-1所示结构的立体结构示意图，如图4-1和图4-2所示，在本实例中，本步骤所得截面曲线近似为双峰曲线。
步骤S223，获取所述包络面基准截面实际曲线上多个特征点的坐标。
在本实例中，将步骤S222提取所得截面曲线以txt.格式打开，并在所述截面曲线上提取多个特征点的坐标。
具体地，在本实例中，可将特征点坐标导入MATLAB软件，并将所述特征点的空间坐标转换为二维平面点坐标，再以眶耳平面为基准水平面对所述截面曲线进行顺时针或逆时针旋转，获得眶耳平面与x轴平行时的xy平面内的所述截面曲线点坐标。后续步骤所使用的坐标为所述截面曲线点坐标。
在处理后的截面曲线上选取特征性点坐标，在本实例中，所述特征点的数量和选取五分类可根据所述截面曲线的具体形态而具体设定。
例如，如图4-2所示的截面曲线，则至少提取以下10个特征点：特征点(1)为左起第一个凸起的最高点，并将该点确定为拟新建二维坐标系的原点，特征点(2)为两峰凹陷处的最低点，特征点(3)为左起第二个凸起的最高点，特征点(4)为所述拟新建二维坐标系在x＝-2附近的点，特征点(5)和特征点(6)为所述截面曲线在特征点(1) 和特征点(2)之间的两个点，特征点(7)和特征点(8)为所述截面曲线在特征点(2)和特征点(3)之间的两个点，特征点(9)和特征点(10)为所述截面曲线在所述拟新建二维坐标系在特征点(3)的x正方向上的两个点。
步骤S224，根据多个所述特征点的坐标生成基准截面拟合曲线方程。
图5示出根据图4-1以及图4-2所示截面曲线进行拟合所得拟合曲线，在本实例中，使用MATLAB将步骤S223获得的特征点坐标进行拟合，如图5所示，生成基准截面拟合曲线以及所述基准截面拟合曲线方程。
在本实例中，本步骤可以使用傅立叶转换来生成基准截面拟合曲线。
在本实例中，可将所述基准截面拟合曲线预存于数据库中，在后续使用过程中，可根据目标头颅的类型直接调取与目标头颅模型类型对应的基准截面拟合曲线。
相应地，在本实例中，所述矩阵也可以预存于所述数据库中，在后续使用过程中，可根据目标头颅的类型直接调取与目标头颅模型类型对应的矩阵。
可以理解的是，预存于数据库中的基准截面拟合曲线以及矩阵均可根据需要而随时更新。
S300，根据所述基准面型参数以及所述基准截面拟合曲线方程生成矩阵。
在本实例中，本步骤的具体实现方式可以采用现有技术中任意一种根据参数与对应的拟合曲线生成相应矩阵的方法。
例如，提取所述基准截面拟合曲线方程中的参数，并将基准面型参数以及所述基准截面拟合曲线方程的参数输入MATLAB中，进而计算得到二者的矩阵。
S400，根据所述矩阵以及所述目标面型参数生成目标截面曲线。
在本实例中，本步骤具体可以包括以下步骤S401和步骤S402：
步骤S401，利用所述目标面型参数以及所述矩阵进行逆运算生成目标截面曲线方程。
在本实例中，本步骤的具体实现方式可以为步骤S300的逆运算。
例如，将该目标面型参数输入到MATLAB中，使用所述矩阵计算生成目标截面曲线方程的参数，再利用所述参数生成目标截面曲线方程。
步骤S402，根据所述目标截面曲线方程绘制目标截面曲线。
在本实例中，利用数据处理软件根据所述参数生成目标截面曲线方程生成目标截面曲线，即，预测出目标截面曲线。
本申请提供的方法将包络面三维形态简化表达为包络面的矢状截面曲线的二维形态，该曲线具有规律，实现其数学表达及预测具有极高的应用价值，可实现对个体的包络面形态预测。
在本申请中，步骤S002的具体实现方式不做特别限制，可以采用现有技术中任意一种根据多条曲线生成包括所述多条曲线的曲面的方法。
在本申请中，步骤S003的具体实现方式不做特别限制，可使用现有技术任意一种可根据曲面方程生成相应曲面的方法。可以理解的是，可以借助现有技术中任意一种软件实现上述方案。
进一步地，所述生成颞下颌关节髁突运动包络面可以理解为绘制颞下颌关节髁突运动包络面。
相应地，本申请还提供一种基于面型参数生成颞下颌关节髁突运动包络面截面曲线的装置，所述装置包括：
截面曲线生成单元，用于根据前述方法生成多条颞下颌关节髁突运动包络面截面曲线方程；
曲线生成单元，用于根据多条所述颞下颌关节髁突运动包络面截面曲线方程生成多条颞下颌关节髁突运动包络面曲线；
曲面生成单元，用于根据所述多条颞下颌关节髁突运动包络面曲线生成颞下颌关节髁突运动包络面。
本申请还提供一种基于面型参数生成颞下颌关节髁突运动包络面截面曲线方法，所述方法包括：
获取目标颅面特征以及目标面型参数；
结合所述目标颅面特征获取基准面型参数以及基准截面拟合曲线方程；
根据所述基准面型参数以及所述基准截面拟合曲线方程生成矩阵；
根据所述矩阵以及所述目标面型参数生成目标截面曲线。
在本实例中，所述基于面型参数生成颞下颌关节髁突运动包络面截面曲线方法中各步骤与前述步骤S100至步骤S400的具体实现方式对应相同，在此不再赘述。
本申请还提供一种基于面型参数生成颞下颌关节髁突运动包络面截面曲线的装置，所述装置包括：
参数获取单元，用于获取目标颅面特征以及目标面型参数；
曲线方程拟合单元，用于结合所述目标颅面特征获取基准面型参数以及基准截面拟合曲线方程；
矩阵生成单元，用于根据所述基准面型参数以及所述基准截面拟合曲线方程生成矩阵；
所述曲线拟合单元还用于，根据所述矩阵以及所述目标面型参数生成目标截面曲线。
在本申请中，各单元具体用于实现各对应步骤的方案。
本申请提供的方法使用基准面型参数以及基准截面曲线生成矩阵，并将所述矩阵作为生成目标髁突运动包络面截面曲线的转换中介，在确定所述目标头颅的面型参数后，再利用所述矩阵可逆运算获得目标截面曲线，进一步地，根据同一目标头颅的面型参数获得多条目标截面曲线，所述多条目标截面曲线可构成目标髁突运动包络面。
本申请提供的方法对颞下颌关节髁突运动包络面的形态进行简化表达，并涵盖其主要形态特征，进一步地，提出上述简化形态的颞下颌关节髁突运动包络面的数学表达方法，使得所述颞下颌关节髁突运动包络面的形态信息能够被定量研究。
可以理解的是，本申请提供的方法能够生成目标髁突运动包络面的任意截面上的截面曲线，例如，目标髁突运动包络面在目标头颅矢状截面上的截面曲线，还可为所述目标髁突运动包络面在目标头颅其它具代表性截面上的截面曲线。

Claims (10)

  1. 一种基于面型参数生成颞下颌关节髁突运动包络面方法，其特征在于，所述方法包括：
    获取多条颞下颌关节髁突运动包络面截面曲线方程；
    根据多条所述颞下颌关节髁突运动包络面截面曲线方程生成颞下颌关节髁突运动包络面曲线；
    根据所述多条颞下颌关节髁突运动包络面曲线生成颞下颌关节髁突运动包络面。
  2. 根据权利要求1所述的方法，其特征在于，所述获取多条颞下颌关节髁突运动包络面截面曲线方程具体包括：
    获取目标颅面特征以及目标面型参数；
    结合所述目标颅面特征获取基准面型参数以及基准截面拟合曲线方程；
    根据所述基准面型参数以及所述基准截面拟合曲线方程生成矩阵；
    根据所述矩阵以及所述目标面型参数生成目标截面曲线方程。
  3. 根据权利要求2所述的方法，其特征在于，所述获取目标颅面特征包括：
    获取目标颅面三维数字模型；
    基于所述目标颅面三维数字模型提取目标颅面特征。
  4. 根据权利要求2所述的方法，其特征在于，所述获取目标面型参数包括：
    获取目标颅面三维数字模型；
    测量所述目标颅面三维数字模型获取目标面型参数，所述目标面型参数包括SNA、SNB、下颌角间距、下颌体长、下颌平面角度、N-Me连线与FH平面之间的角度。
  5. 根据权利要求2所述的方法，其特征在于，所述获取基准面型参数包括：
    获取基准颅面三维数字化模型；
    测量所述基准颅面三维数字化模型，获取基准面型参数，所述基准面型参数与所述基准面型参数的类型对应相同。
  6. 根据权利要求2所述的方法，其特征在于，获取基准颅面三维数字化模型包括：
    获取多个候选颅面模型；
    基于所述多个候选颅面模型根据预设规则生成基准颅面三维数字模型。
  7. 根据权利要求2所述的方法，其特征在于，所述获取基准截面拟合曲线方程包括：
    获取基准包络面模型；
    利用基准截面对所述基准包络面模型进行截取，形成包络面基准截面实际曲线；
    获取所述包络面基准截面实际曲线上多个特征点的坐标；
    根据多个所述特征点的坐标生成基准截面拟合曲线方程。
  8. 一种基于面型参数生成颞下颌关节髁突运动包络面的装置，其特征在于，
    截面曲线生成单元，用于生成多条颞下颌关节髁突运动包络面截面曲线方程；
    曲面方程生成单元，用于根据多条所述颞下颌关节髁突运动包络面截面曲线方程生成多条颞下颌关节髁突运动包络面曲线；
    曲面生成单元，用于根据所述多条颞下颌关节髁突运动包络面曲线生成颞下颌关节髁突运动包络面。
  9. 一种基于面型参数生成颞下颌关节髁突运动包络面截面曲线方法，其特征在于， 所述方法包括：
    获取目标颅面特征以及目标面型参数；
    结合所述目标颅面特征获取基准面型参数以及基准截面拟合曲线方程；
    根据所述基准面型参数以及所述基准截面拟合曲线方程生成矩阵；
    根据所述矩阵以及所述目标面型参数生成目标截面曲线。
  10. 一种基于面型参数生成颞下颌关节髁突运动包络面截面曲线的装置，其特征在于，
    参数获取单元，用于获取目标颅面特征以及目标面型参数；
    曲线方程拟合单元，用于结合所述目标颅面特征获取基准面型参数以及基准截面拟合曲线方程；
    矩阵生成单元，用于根据所述基准面型参数以及所述基准截面拟合曲线方程生成矩阵；
    所述曲线拟合单元还用于，根据所述矩阵以及所述目标面型参数生成目标截面曲线。
PCT/CN2023/083266 2022-03-23 2023-03-23 基于面型参数生成颞下颌关节髁突运动包络面方法和装置 WO2023179699A1 (zh)

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