Detailed Description
The following is a clear and complete description of the technical method of the present patent in conjunction with the accompanying drawings, and it is evident that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, are intended to fall within the scope of the present invention.
Furthermore, the drawings are merely schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus a repetitive description thereof will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. The functional entities may be implemented in software or in one or more hardware modules or integrated circuits or in different networks and/or processor methods and/or microcontroller methods.
It will be understood that, although the terms "first," "second," etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another element. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element, without departing from the scope of example embodiments. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
In order to achieve the above objective, referring to fig. 1 to 3, the present invention provides a method for constructing a three-dimensional model of an oral cavity and analyzing occlusion characteristics of teeth, the method comprising the steps of:
the method comprises the steps of S1, carrying out imaging scanning treatment on the oral cavity structure of a patient through an oral cavity scanner to obtain an oral cavity internal structure image set, and carrying out three-dimensional model construction on the oral cavity internal structure image set to generate an oral cavity internal structure three-dimensional space model;
Step S2, tooth segmentation and tooth characteristic analysis are carried out on the three-dimensional space model of the oral cavity internal structure so as to obtain three-dimensional geometrical shape characteristic data of oral cavity teeth and three-dimensional space position characteristic data of oral cavity teeth;
Step S3, carrying out tooth occlusal point positioning analysis on the three-dimensional space model of the oral cavity internal structure to obtain tooth occlusal point position data of the oral cavity;
And S4, carrying out dental occlusion characteristic analysis on the dental occlusion connecting surface to obtain the dental occlusion surface parallelism and the dental occlusion surface outline shape, and carrying out dental occlusion adjustment processing on the three-dimensional space model of the oral cavity internal structure based on the dental occlusion surface parallelism and the dental occlusion surface outline shape to generate an oral cavity dental occlusion surface adjustment scheme.
In the embodiment of the present invention, please refer to fig. 1, which is a schematic flow chart of steps of the method for constructing an oral cavity three-dimensional model and analyzing tooth occlusion characteristics, in this example, the method for constructing an oral cavity three-dimensional model and analyzing tooth occlusion characteristics comprises the following steps:
the method comprises the steps of S1, carrying out imaging scanning treatment on the oral cavity structure of a patient through an oral cavity scanner to obtain an oral cavity internal structure image set, and carrying out three-dimensional model construction on the oral cavity internal structure image set to generate an oral cavity internal structure three-dimensional space model;
According to the embodiment of the invention, the oral cavity structure of a patient is subjected to imaging scanning treatment by using the oral cavity scanning adjustment parameters obtained through real-time determination by the oral cavity scanner, so that the oral cavity scanner is placed at a proper position, and the image data of the oral cavity internal structure is obtained through the light source and the sensor of the oral cavity scanner, so that an image set of the oral cavity internal structure is obtained. Then, the image set of the oral cavity internal structure is analyzed by using a space feature analysis method to extract key features of the oral cavity structural space, such as the position, shape and size of teeth, the outline of gums and other structural features of oral cavity tissues, two-dimensional structural feature points are projected into a three-dimensional space, abnormal points or noise points in the two-dimensional structural feature points are removed to keep effective feature point data, meanwhile, three-dimensional model reconstruction of the oral cavity structure is carried out on the oral cavity structural feature point cloud data obtained after outlier removal processing by using a point cloud registration method, a curved surface reconstruction method and the like, so that point cloud data obtained from different visual angles or scanning are fused into a complete model, surface detail information and texture information in the two-dimensional image are mapped into an initially constructed space model to be optimized, and the sense of reality and the visual effect of the model are enhanced, and finally the three-dimensional model of the oral cavity internal structure is generated.
Step S2, tooth segmentation and tooth characteristic analysis are carried out on the three-dimensional space model of the oral cavity internal structure so as to obtain three-dimensional geometrical shape characteristic data of oral cavity teeth and three-dimensional space position characteristic data of oral cavity teeth;
According to the embodiment of the invention, the tooth parts in the three-dimensional space model of the oral cavity internal structure are subjected to segmentation processing by using a computer tomography processing method, so that the tooth parts in the complex oral cavity structure are extracted independently, and each tooth structure in the segmented oral cavity tooth structure space model is subjected to dimension measurement processing by using a measuring tool or software, so that the length, width, height and the like of the tooth structure are measured, and the characteristics of the geometric shape, the contour and the like of the tooth are analyzed, so that the three-dimensional geometric shape characteristic data of the oral cavity tooth is obtained. Meanwhile, the position recognition analysis is carried out on the tooth structure in the three-dimensional space model of the oral cavity internal structure by using a space position analysis method, so that the position and the relative position of the tooth structure on the three-dimensional space model of the oral cavity internal structure are analyzed, and the specific position information of the tooth in the oral cavity is obtained, thereby obtaining the three-dimensional space position characteristic data of the tooth of the oral cavity. And then, carrying out evaluation analysis on the contact condition of the internal tooth structure in the three-dimensional space model of the oral cavity internal structure by using a contact mechanics theory and a simulation algorithm through combining the three-dimensional geometrical shape characteristic data of the oral cavity teeth and the three-dimensional space position characteristic data of the oral cavity teeth obtained through analysis so as to evaluate and analyze the contact condition between the teeth, the stability of the contact point and the like, and evaluating and analyzing the arrangement contact condition between the teeth in the oral cavity in the occlusion process from the contact condition, so as to finally obtain the arrangement contact condition data of the teeth in the oral cavity.
Step S3, carrying out tooth occlusal point positioning analysis on the three-dimensional space model of the oral cavity internal structure to obtain tooth occlusal point position data of the oral cavity;
According to the embodiment of the invention, interaction and relationship among teeth on the three-dimensional space model of the oral cavity internal structure are analyzed by using an occlusion relationship analysis method, so that the contact points among the teeth in the model, the occlusion mode and the like are checked to evaluate and analyze the malocclusion relationship among the teeth, and the occlusion points among the teeth on the three-dimensional space model of the oral cavity internal structure are identified and marked by using computer-aided analysis software or algorithm in combination with the dental occlusion relationship obtained by analysis, so that the occlusion points among the teeth in the three-dimensional space model of the oral cavity internal structure are obtained, and the three-dimensional coordinate specific position of each occlusion point is determined, so that the occlusion point data of the oral cavity teeth is obtained. Then, the connection relation between teeth on the three-dimensional space model of the oral cavity internal structure is excavated and analyzed by a connection relation excavation algorithm through combination analysis of the tooth arrangement contact condition data of the oral cavity teeth, so that the contact or occlusion relation between the teeth is analyzed and determined, the connection treatment of the tooth occlusion surfaces is carried out on the teeth corresponding to the three-dimensional space model of the oral cavity internal structure through combination of the tooth occlusion point data of the oral cavity, so that an occlusion surface is determined to be formed between the teeth, and the teeth are identified and connected, so that the occlusion connection surface of the oral cavity teeth is finally generated.
And S4, carrying out dental occlusion characteristic analysis on the dental occlusion connecting surface to obtain the dental occlusion surface parallelism and the dental occlusion surface outline shape, and carrying out dental occlusion adjustment processing on the three-dimensional space model of the oral cavity internal structure based on the dental occlusion surface parallelism and the dental occlusion surface outline shape to generate an oral cavity dental occlusion surface adjustment scheme.
According to the embodiment of the invention, the inclination angle of the dental occlusion connecting surfaces on the three-dimensional space model is measured by using an angle measuring instrument or a computer-aided measuring tool, so that the inclination angle of each occlusion connecting surface is accurately measured, the corresponding dental occlusion connecting surfaces are subjected to statistical calculation of inclination curvature by using a statistical method, so that the curvature degree of the occlusion connecting surfaces is quantitatively calculated, and meanwhile, the dental occlusion connecting surfaces are subjected to occlusion parallelism calculation by combining the measured inclination angle and the measured inclination curvature, so that the parallelism degree of the dental occlusion surfaces is quantitatively calculated, and the dental occlusion surface parallelism is obtained. And the contour shape of the dental occlusion connecting surface obtained by connection is identified and analyzed by using a computer vision algorithm so as to identify and acquire the contour shape of the dental occlusion surface and know the morphological characteristics of the dental occlusion surface, such as the degree of concavity and convexity, the irregularity and the like, thereby obtaining the contour shape of the dental occlusion surface. Then, the three-dimensional space model of the internal structure of the oral cavity is adjusted by combining the tooth occlusal characteristics such as the parallelism of the tooth occlusal surface and the outline shape of the tooth occlusal surface obtained by the previous analysis through a computer aided design tool or a three-dimensional simulation method, so that the internal structure of the oral cavity is adjusted according to the information of the parallelism and the outline shape of the internal structure of the oral cavity, the tooth occlusal surface is enabled to be parallel, the outline shape of the internal structure of the oral cavity meets the requirements of the anatomical structure and the function of the oral cavity, and a targeted tooth occlusal adjustment scheme is formulated, so that the misjaw of the tooth is corrected, the occlusion function is improved, and the like, and finally the oral tooth occlusal surface adjustment scheme is generated.
The invention firstly uses the oral scanner to carry out imaging scanning treatment on the oral structure of the patient, thereby scanning to obtain an image set of the oral internal structure, the image data is truly reflected on the oral internal structure of the patient, and a necessary basis is provided for subsequent treatment and analysis. Meanwhile, by constructing a three-dimensional model of the image set of the internal structure of the oral cavity, a three-dimensional space model of the internal structure of the oral cavity can be accurately constructed, the model not only can intuitively display the structural characteristics of the oral cavity of a patient, but also can provide important references for the subsequent dental occlusion characteristic analysis process, and provides important support for further research and practice in the field of stomatology. Secondly, the tooth part in the complex oral cavity structure can be extracted independently by carrying out tooth segmentation treatment on the three-dimensional space model of the oral cavity internal structure, so that the three-dimensional space model of the oral cavity tooth structure area is obtained, and the key point of the step is that a foundation can be provided for subsequent tooth correlation analysis, so that the fine analysis on the characteristics of the shape, the position and the like of the tooth is possible. By analyzing the tooth characteristics of the three-dimensional space model of the segmented oral cavity teeth, geometrical shape characteristics of the teeth, such as the appearance, curvature and the like of the teeth, can be revealed, and specific position information of the teeth in the oral cavity can be obtained, so that basis is provided for evaluating the problems of tooth arrangement, occlusion and the like. The contact condition between teeth, including the number of contact points, the contact area and the like, can be evaluated by carrying out interdental contact evaluation analysis on the three-dimensional space model of the internal structure of the oral cavity based on the three-dimensional geometrical shape feature data of the oral cavity teeth and the three-dimensional space position feature data of the oral cavity teeth, and the key point of the step is to help evaluate the arrangement condition and the occlusion function of the teeth, and provide data support for the subsequent occlusion feature analysis process, so that the accuracy and individuation of oral cavity health management are promoted. Then, tooth bite points are determined by carrying out positioning analysis on the three-dimensional space model of the oral cavity internal structure, and specific position data of the tooth bite points of the oral cavity are obtained by positioning analysis, and the data provides data support for the subsequent processing process. The tooth occlusal surface connection division is carried out on the three-dimensional space model of the internal structure of the oral cavity based on the tooth arrangement contact condition data of the oral cavity and the tooth occlusal point position data of the oral cavity, and the purpose of the step is to generate the tooth occlusal surface connection of the oral cavity, so that finer and accurate information is provided for further analysis of the oral cavity structure. By dividing the occlusion connecting surface, the overall shape and functional characteristics of the oral cavity structure can be better understood, and more scientific and effective support is provided for subsequent occlusion characteristic analysis, so that the occlusion characteristics and occlusion relation of teeth can be accurately reflected. Finally, through carrying out tooth occlusion feature analysis on the dental occlusion connecting surface, the method aims at evaluating and analyzing the parallelism degree of the dental occlusion surface and the outline shape of the dental occlusion surface so as to know the morphological characteristics of the dental occlusion surface, and the analysis is helpful for revealing the occlusion relation and the morphological characteristics among teeth, provides more comprehensive information for evaluating the oral cavity structure, and further improves the accuracy and the precision of the occlusion feature analysis. In addition, the three-dimensional space model of the internal structure of the oral cavity is subjected to tooth occlusion adjustment based on the parallelism of the tooth occlusion surface and the outline shape of the tooth occlusion surface, and the step aims at making a targeted tooth occlusion adjustment scheme according to the analysis result, providing guidance for the adjustment and repair of the occlusion process of the oral cavity structure, and correcting the misjaw of the teeth and improving the occlusion function by adjusting the tooth occlusion surface, so that the health level and the quality of life of the oral cavity are improved.
Preferably, step S1 comprises the steps of:
S11, analyzing the oral cavity condition and the scanning requirement of the oral cavity structure of the patient to obtain the oral cavity structure condition data of the patient and the oral cavity scanning requirement data of the patient;
Step S12, carrying out self-adaptive adjustment processing on scanning parameters of an oral scanner according to the oral structure condition data of a patient and the oral scanning requirement data of the patient so as to generate an oral scanning self-adaptive adjustment parameter set;
S13, carrying out imaging scanning treatment on the oral cavity structure of a patient through an oral cavity scanner based on the oral cavity scanning self-adaptive adjustment parameter set to obtain an oral cavity internal structure image set;
Step S14, performing image denoising treatment on the oral cavity internal structure image set to obtain an oral cavity structure denoising image set;
And S15, constructing a three-dimensional model of the standard image set of the oral cavity structure to generate a three-dimensional space model of the oral cavity internal structure.
As an embodiment of the present invention, referring to fig. 2, a detailed step flow chart of step S1 in fig. 1 is shown, in which step S1 includes the following steps:
S11, analyzing the oral cavity condition and the scanning requirement of the oral cavity structure of the patient to obtain the oral cavity structure condition data of the patient and the oral cavity scanning requirement data of the patient;
The embodiment of the invention obtains the data of the oral cavity structure of the patient by carrying out detailed analysis on the oral cavity structure of the patient, including checking the arrangement, the size, the shape and the health condition of the gums of the patient and any existing oral diseases or abnormal conditions. Meanwhile, the oral cavity structure of the patient is analyzed by using a demand analysis method according to the specific condition of the patient so as to analyze and determine the range, the precision and the parameters of oral cavity scanning, and finally, the oral cavity scanning demand data of the patient is obtained.
Step S12, carrying out self-adaptive adjustment processing on scanning parameters of an oral scanner according to the oral structure condition data of a patient and the oral scanning requirement data of the patient so as to generate an oral scanning self-adaptive adjustment parameter set;
according to the embodiment of the invention, the parameters of the oral cavity scanner are adaptively adjusted by combining the patient oral cavity structure condition data and the patient oral cavity scanning requirement data obtained through analysis, so that the parameters such as the resolution, the scanning speed, the exposure time, the focal length, the scanning angle and the scanning mode of the scanner are adjusted according to the oral cavity condition of the patient, the detailed information of the oral cavity structure is ensured to be comprehensively and accurately captured, and finally, an oral cavity scanning adaptive adjustment parameter set is generated.
S13, carrying out imaging scanning treatment on the oral cavity structure of a patient through an oral cavity scanner based on the oral cavity scanning self-adaptive adjustment parameter set to obtain an oral cavity internal structure image set;
according to the embodiment of the invention, the oral cavity scanner performs imaging scanning treatment on the oral cavity structure of a patient by applying the oral cavity scanning self-adaptive adjustment parameter set which is determined in real time previously, so that the oral cavity scanner is placed at a proper position, and the image data of the oral cavity internal structure is obtained through the light source and the sensor of the oral cavity scanner, and finally the oral cavity internal structure image set is obtained.
Step S14, performing image denoising treatment on the oral cavity internal structure image set to obtain an oral cavity structure denoising image set;
According to the embodiment of the invention, various image processing algorithms (such as median filtering, gaussian filtering and the like) are used for denoising the image set of the oral cavity internal structure, so that noise and interference in the image are reduced, the quality and definition of the image are improved, and the denoising image set of the oral cavity structure is obtained. Meanwhile, the image normalization method is used for processing the denoising image set of the oral structure so as to adjust parameters such as brightness, contrast, color balance and the like of the image, so that the image of the oral structure has a uniform visual effect, consistency and comparability among different images are ensured, and finally the standard image set of the oral structure is obtained.
And S15, constructing a three-dimensional model of the standard image set of the oral cavity structure to generate a three-dimensional space model of the oral cavity internal structure.
According to the embodiment of the invention, the standard image set of the oral cavity structure is analyzed by using a space feature analysis method, so that key features of the oral cavity structure space, such as the position, the shape and the size of teeth, the outline of gums and other structural features of oral cavity tissues, are extracted from the two-dimensional image set, two-dimensional structural feature points are projected into a three-dimensional space, abnormal points or noise points in the two-dimensional structural feature points are removed to keep effective feature point data, meanwhile, three-dimensional model reconstruction of the oral cavity structure is carried out on the oral cavity structure space feature point cloud data obtained after outlier removal processing by using methods such as point cloud registration and curved surface reconstruction, so that point cloud data obtained from different visual angles or scanning are fused into a complete model, and surface detail information and texture information in the two-dimensional image are mapped into an initially constructed space model to be optimized, so that the sense and the visual effect of the model are enhanced, and finally the three-dimensional model of the oral cavity internal structure is generated.
According to the invention, firstly, the oral cavity condition and the scanning requirement analysis are carried out on the oral cavity structure of a patient, the step is a key step in the whole oral cavity scanning process, the oral cavity structure condition of the patient including the conditions of the teeth, the gums, the tongue and other parts can be comprehensively known through careful analysis, meanwhile, the scanning requirement data of the patient such as the conditions of the scanning range, the precision requirement and the like can be obtained, the analysis process is helpful for determining the concrete scheme of the follow-up scanning and processing, and a solid foundation is laid for the oral cavity scanning process. Secondly, through carrying out scanning parameter self-adaptation adjustment processing to the oral scanner according to patient's oral cavity structure condition data and patient's oral cavity scanning demand data, can realize the personalized customization to scanning process parameter, this step can also improve the accuracy and the efficiency of scanning to the furthest through the parameter of adjustment scanner according to patient's specific condition to ensure to acquire high-quality oral cavity inner structure image data. Then, imaging scanning treatment is carried out on the oral cavity structure of the patient through an oral cavity scanner based on the oral cavity scanning self-adaptive adjustment parameter set, so that an image set of the oral cavity internal structure is obtained through scanning, and the image data truly reflect the oral cavity internal structure of the patient, thereby providing a necessary foundation for subsequent treatment and analysis. Then, through carrying out image denoising processing and standardization processing on the image set of the oral cavity internal structure, further optimization on image data can be realized, so that noise and interference in images are removed, and standardization processing on the denoising images is realized, so that follow-up processing is more accurate and reliable, and the quality and usability of the oral cavity structural images are improved. Finally, by constructing a three-dimensional model of the standard image set of the oral cavity structure, a three-dimensional space model of the internal structure of the oral cavity is constructed and obtained, and the model not only can intuitively display the structural characteristics of the oral cavity of a patient, but also can provide important references for the subsequent dental occlusion characteristic analysis process and provide important support for further research and practice in the field of stomatology.
Preferably, step S15 comprises the steps of:
Step S151, carrying out oral cavity structure space feature analysis on the oral cavity structure standard image set to obtain oral cavity structure space feature data;
Step S152, carrying out characteristic point cloud conversion processing on the oral structure space characteristic data to obtain three-dimensional space characteristic point cloud data of the oral structure;
Step 153, outlier elimination processing is carried out on the three-dimensional spatial characteristic point cloud data of the oral cavity structure, so as to obtain outlier elimination point cloud data of the spatial characteristic of the oral cavity structure;
step S154, reconstructing an oral structure three-dimensional model by eliminating point cloud data of outliers of spatial features of the oral structure, so as to obtain an initial spatial model of the oral structure three-dimensional reconstruction;
Step S155, performing texture mapping rendering processing on the initial spatial model of the three-dimensional reconstruction of the oral cavity structure based on the oral cavity structure standard image set so as to generate a three-dimensional spatial model of the oral cavity internal structure.
As an embodiment of the present invention, referring to fig. 3, a detailed step flow chart of step S15 in fig. 2 is shown, in which step S15 includes the following steps:
Step S151, carrying out oral cavity structure space feature analysis on the oral cavity structure standard image set to obtain oral cavity structure space feature data;
According to the embodiment of the invention, the standard image set of the oral cavity structure is analyzed by using a spatial feature analysis method, so that key features of the oral cavity structure space, such as the position, the shape and the size of teeth, the outline of gums and other structural space features of oral cavity tissues, are extracted from the two-dimensional image set, and finally the oral cavity structure space feature data is obtained.
Step S152, carrying out characteristic point cloud conversion processing on the oral structure space characteristic data to obtain three-dimensional space characteristic point cloud data of the oral structure;
According to the embodiment of the invention, the three-dimensional characteristic point cloud data of the oral structure is finally obtained by converting characteristic point clouds of the spatial characteristic data of the oral structure by using methods such as stereo matching, structured light scanning and the like, projecting two-dimensional characteristic points into a three-dimensional space, carrying out coordinate conversion according to camera parameters, and determining the spatial position of each spatial characteristic point according to depth information.
Step 153, outlier elimination processing is carried out on the three-dimensional spatial characteristic point cloud data of the oral cavity structure, so as to obtain outlier elimination point cloud data of the spatial characteristic of the oral cavity structure;
According to the embodiment of the invention, the outlier points in the three-dimensional spatial characteristic point cloud data of the oral structure are removed by using a clustering method based on density and setting a proper threshold or parameter, so that abnormal points or noise points in the point cloud data are removed, effective characteristic point data are reserved, and finally the outlier removed point cloud data of the spatial characteristic of the oral structure is obtained.
Step S154, reconstructing an oral structure three-dimensional model by eliminating point cloud data of outliers of spatial features of the oral structure, so as to obtain an initial spatial model of the oral structure three-dimensional reconstruction;
According to the embodiment of the invention, the three-dimensional model reconstruction of the oral structure is carried out on the outlier removed point cloud data of the oral structure space characteristics obtained after outlier removal processing by using methods such as point cloud registration, curved surface reconstruction and the like, so that the point cloud data obtained from different visual angles or scanning are fused into a complete model, then a curved surface reconstruction algorithm, such as a grid-based method or a voxel method, is utilized to generate an initial three-dimensional space model of the oral structure, and finally the initial three-dimensional reconstruction space model of the oral structure is obtained.
Step S155, performing texture mapping rendering processing on the initial spatial model of the three-dimensional reconstruction of the oral cavity structure based on the oral cavity structure standard image set so as to generate a three-dimensional spatial model of the oral cavity internal structure.
According to the embodiment of the invention, the surface detail information and the texture information in the two-dimensional image are intensively analyzed from the oral structure standard image and mapped into the oral structure three-dimensional reconstruction initial space model for optimization, so that the sense of reality and the visual effect of the model are enhanced, the aspects of illumination, shadow, materials and the like of the model are rendered, and finally the oral structure three-dimensional space model is generated.
According to the invention, firstly, the oral structure space feature analysis is carried out on the oral structure standard image set, so that the complexity and feature distribution of the oral internal structure can be deeply known, the analysis relates to detailed researches on various features, forms and space distribution in the image, such as the position, the shape, the size and the like of teeth, and through the step, the oral structure space feature data can be obtained, thereby providing an important basis for the subsequent processing process. And secondly, feature point cloud conversion processing is carried out on the oral cavity structure space feature data, so that feature point information in the image space feature can be converted into point cloud data in a three-dimensional space, the processing process can convert two-dimensional information in the image space feature into more specific and visual three-dimensional data, so that the spatial feature of the oral cavity structure can be more clearly presented, and basic data guarantee can be provided for subsequent three-dimensional reconstruction through the conversion process. Then, outlier elimination processing is carried out on the three-dimensional space characteristic point cloud data of the oral structure, so that abnormal points or interference points existing in the conversion process are eliminated, the accuracy and reliability of the point cloud data are improved, and the step can ensure that the follow-up three-dimensional modeling process is not interfered by identifying and eliminating the outlier, so that the quality of a final three-dimensional model is ensured. And then, the point cloud data are eliminated by outliers of the spatial characteristics of the oral cavity structure to reconstruct the three-dimensional model of the oral cavity structure, and the work relates to the technologies of reconstructing curved surfaces, voxelization and the like by utilizing the point cloud data so as to generate an accurate and precise three-dimensional reconstruction initial spatial model of the oral cavity structure, thereby providing a reliable foundation for subsequent model processing and analysis. Finally, texture mapping rendering processing is carried out on the initial space model of the three-dimensional reconstruction of the oral cavity structure based on the standard image set of the oral cavity structure, so that texture information of the oral cavity structure can be mapped onto the three-dimensional model, rendering processing is carried out, the generated three-dimensional model is more vivid and has real appearance characteristics, the processing enables the three-dimensional space model of the internal structure of the oral cavity to have visualization and expressive force, and therefore important support is provided for further research and practice of subsequent tooth occlusion characteristic analysis.
Preferably, step S153 includes the steps of:
Carrying out local density estimation on the three-dimensional space feature point cloud data of the oral cavity structure to obtain a local density estimation value of each three-dimensional space feature point of the oral cavity structure;
According to the embodiment of the invention, a proper window size or a neighborhood range is selected at each point in three-dimensional space characteristic point cloud data of an oral structure by using a kernel density estimation technology to perform density estimation calculation so as to calculate the point number of each characteristic point cloud in the neighborhood, and the point density around each characteristic point cloud is determined by dividing the point number by the volume or the area of the neighborhood, so that a local density estimated value of each three-dimensional space characteristic point of the oral structure is finally obtained.
Preferably, the density center point clustering processing is carried out on the three-dimensional space feature point cloud data of the oral cavity structure based on the local density estimated value of each three-dimensional space feature point of the oral cavity structure, so as to obtain the three-dimensional space feature density center point of the oral cavity structure;
According to the embodiment of the invention, the local density estimated value of each three-dimensional spatial feature point of the oral structure obtained by combining quantization calculation is used for carrying out cluster analysis on the corresponding three-dimensional spatial feature point cloud data of the oral structure by using a density-based clustering algorithm, so that the feature point cloud is divided into different cluster clusters by setting a proper density threshold and a neighborhood parameter, the center point of each cluster is determined to be used as a density center point, namely, a core point with high density in the point cloud data, and finally the three-dimensional spatial feature density center point of the oral structure is obtained.
Preferably, based on the three-dimensional space feature density central point of the oral structure, the density gap degree statistical calculation is carried out on other three-dimensional space feature points in the three-dimensional space feature point cloud data of the oral structure by utilizing a point cloud density gap degree calculation formula so as to obtain a point cloud density gap degree value between the three-dimensional space feature point of the oral structure and the density central point;
according to the embodiment of the invention, a proper point cloud density gap calculation formula is formed by combining the number parameter, the spatial Euclidean distance value, the spatial position parameter, the local density estimation value, the local density adjustment coefficient, the local density gradient adjustment coefficient and related parameters of three-dimensional space feature points, so that the density gap statistical calculation is carried out on other three-dimensional space feature points in the three-dimensional space feature point cloud data of the oral cavity structure, the density distribution difference condition between each feature point and the density center point of the cluster to which the feature point belongs is measured, and finally the point cloud density gap value between the three-dimensional space feature point and the density center point of the oral cavity structure is obtained.
Preferably, the outlier marking is carried out on the three-dimensional spatial feature point cloud data of the oral cavity structure according to the point cloud density gap value between the three-dimensional spatial feature point of the oral cavity structure and the density center point, so as to obtain the three-dimensional spatial feature density outlier of the oral cavity structure;
According to the embodiment of the invention, the point cloud density gap value between the three-dimensional space characteristic point and the density center point of the oral structure obtained through quantitative calculation is compared and judged according to the preset threshold value, so that the characteristic point with the point cloud density gap value exceeding a certain range threshold value is marked as an outlier to represent an abnormal point or a noise point in the point cloud data, and finally the three-dimensional space characteristic density outlier of the oral structure is obtained.
Preferably, the outlier of the three-dimensional spatial feature density of the oral cavity structure is removed from the cloud data of the three-dimensional spatial feature density of the oral cavity structure, so that the cloud data of the outlier of the spatial feature of the oral cavity structure is obtained.
According to the embodiment of the invention, the outlier of the density of the three-dimensional spatial features of the oral structure is removed from the cloud data of the three-dimensional spatial features of the oral structure, so that noise points or abnormal points in the cloud data are removed, a cleaner and more accurate point cloud data set is obtained, and finally the outlier removed point cloud data of the spatial features of the oral structure is obtained.
According to the method, firstly, the local density estimation is carried out on three-dimensional space characteristic point cloud data of the oral cavity structure, the step is to determine the data density around each point in the point cloud data, which is important for subsequent clustering and outlier detection, an estimated value about the density of the point can be obtained by calculating the number of adjacent points around each point, so that the characteristic of density distribution in the oral cavity structure is revealed, and the step is characterized in that the local density is estimated by calculating the number of points in a neighborhood around each point, so that the identification of dense areas and sparse areas in the oral cavity structure can be facilitated, important references are provided for subsequent data processing and analysis, and the identification of key areas and characteristic points in the oral cavity structure can be facilitated more accurately. Secondly, density center point clustering processing is carried out on the three-dimensional spatial feature point cloud data of the oral cavity structure based on the local density estimated value of the three-dimensional spatial feature point of each oral cavity structure, the purpose of the step is to divide the three-dimensional spatial feature point cloud data of the oral cavity structure into areas with similar density features, and find the center point of each area, and the key point of the step is that the point cloud data can be divided into different areas, and the center point of each area is determined, so that the distribution features of the oral cavity structure are better understood, and meanwhile, a foundation is provided for subsequent outlier detection and data analysis. Then, the density gap degree statistical calculation is carried out on other three-dimensional space feature points in the three-dimensional space feature point cloud data of the oral cavity structure by utilizing a point cloud density gap degree calculation formula based on the three-dimensional space feature density center point of the oral cavity structure, so as to measure the relative density difference between the three-dimensional space feature points of the oral cavity structure and the density center point. Then, the outlier marking is performed on the three-dimensional spatial feature point cloud data of the oral cavity structure according to the point cloud density gap value between the three-dimensional spatial feature point of the oral cavity structure and the density center point, so as to identify density outliers in the oral cavity structure, namely points with obviously different densities from surrounding points, wherein the key point of the step is to mark potential outliers, thereby helping further analyze the abnormal situation or the existing data errors in the oral cavity structure. Finally, the aim of eliminating the abnormal points in the point cloud data of the oral cavity structure is to eliminate the abnormal points in the point cloud data of the oral cavity structure by eliminating the density outlier from the point cloud data, so that a cleaner and more accurate point cloud data set is obtained, and the key point of the step is that the quality and the reliability of the oral cavity structure data can be improved, so that the quality of a final three-dimensional model is ensured.
Preferably, the calculation formula of the point cloud density gap degree is specifically:
Wherein Di is the point cloud density gap value between the ith oral structure three-dimensional space feature point and the density center point, N is the total number of other three-dimensional space feature points in the oral structure three-dimensional space feature point cloud data, i is a feature point item sub-index parameter, Di is the spatial Euclidean distance value between the ith oral structure three-dimensional space feature point and the oral structure three-dimensional space feature density center point, xi is the spatial position parameter of the ith oral structure three-dimensional space feature point, ρ (xi) is the local density estimated value of the ith oral structure three-dimensional space feature point, α is a local density adjustment coefficient, β is a local density gradient adjustment coefficient, and η is a correction coefficient of the point cloud density gap value.
According to the invention, a specific mathematical model is used and verified to obtain a point cloud density gap degree calculation formula, the point cloud density gap degree calculation formula is used for carrying out density gap degree statistics calculation on other three-dimensional space feature points in three-dimensional space feature point cloud data of an oral cavity structure, the point cloud density gap degree calculation formula aims at quantitatively describing the density gap degree between the three-dimensional space feature points of the oral cavity structure and a density center point, and by means of the measurement mode, outlier points in the oral cavity structure, namely points with abnormally high or abnormally low density compared with other points, can be identified. Secondly, the spatial distance from each point to the center point is calculated in the formula, and then the density condition of the points is adjusted and corrected through the local density estimated value and the corresponding adjusting parameters, so that the density gap condition of the points can be described more accurately by comprehensively considering the position and the local density information of the points. Meanwhile, the Euclidean distance and the local density information are used in the formula for comprehensive calculation, so that a point cloud density gap value is obtained and used for quantifying the point cloud density gap between the description point and the center point, and the distance value can well reflect the density condition of the point and further is used for identifying the outlier. The points with abnormal density can be effectively identified through the calculated density clearance value, and the accurate cleaning and processing of the characteristic points of the oral cavity structure can be realized, so that the accuracy and the reliability of the oral cavity structure analysis are improved. In summary, the formula fully considers the point cloud density gap value Di between the three-dimensional spatial feature point of the ith oral structure and the density center point, the total number N of other three-dimensional spatial feature points in the three-dimensional spatial feature point cloud data of the oral structure, the feature point item sub-index parameter i, the spatial Euclidean distance value Di between the three-dimensional spatial feature point of the ith oral structure and the three-dimensional spatial feature density center point of the oral structure, the spatial position parameter xi of the three-dimensional spatial feature point of the ith oral structure, the local density estimated value ρ (xi) of the three-dimensional spatial feature point of the ith oral structure, the local density adjustment coefficient alpha, the local density gradient adjustment coefficient beta, the correction coefficient eta of the point cloud density gap value, and a functional relationship is formed according to the correlation relationship between the point cloud density gap value Di between the three-dimensional spatial feature point of the ith oral structure and the density center point of the ith oral structure and the above parametersThe formula can realize the density gap degree statistical calculation process of other three-dimensional space feature points in the three-dimensional space feature point cloud data of the oral structure, and meanwhile, the correction coefficient eta of the point cloud density gap degree value can be introduced to be adjusted according to the error condition in the calculation process, so that the accuracy and the applicability of the point cloud density gap degree calculation formula are improved.
Preferably, step S155 includes the steps of:
carrying out oral surface and texture feature analysis on the oral structure standard image set to obtain oral structure surface feature data and oral structure texture feature data;
according to the embodiment of the invention, the characteristic analysis is carried out on the standard image set of the oral cavity structure by using the image characteristic processing technology so as to extract the surface characteristics and the texture characteristics of the oral cavity structure, wherein the surface characteristics relate to the information on the aspects of the shape, the outline and the like of the internal structure of the oral cavity, the texture characteristics refer to the texture details of the surface of the oral cavity structure, such as wrinkles, concave-convex and the like, and finally the surface characteristic data of the oral cavity structure and the texture characteristic data of the oral cavity structure are obtained.
Preferably, the three-dimensional reconstruction initial space model of the oral structure is subjected to surface detail optimization based on the surface feature data of the oral structure to obtain a three-dimensional space surface optimization model of the oral structure;
According to the embodiment of the invention, the surface detail of the reconstructed three-dimensional reconstruction initial space model of the oral structure is optimized by combining the analysis-obtained oral structure surface characteristic data through the grid editing, surface fitting and other technologies, so that the geometric shape of the model is effectively improved, the model is more in line with the actual form of the oral structure surface, and finally the three-dimensional space surface optimization model of the oral structure is obtained.
Preferably, texture mapping matching optimization is carried out on the three-dimensional space surface optimization model of the oral structure based on the texture feature data of the oral structure, so as to obtain a three-dimensional space texture mapping optimization model of the oral structure;
According to the embodiment of the invention, texture mapping algorithm, texture fusion technology and the like are used in combination with analysis of the texture feature data of the oral structure to optimize the texture feature of the three-dimensional space surface optimization model of the oral structure, so that the texture feature is mapped to the surface of the three-dimensional model to keep continuity and authenticity of textures, the final three-dimensional space model is ensured to have a vivid texture effect, and the three-dimensional space texture mapping optimization model of the oral structure is finally obtained.
Preferably, the model rendering process is performed on the three-dimensional texture mapping optimization model of the oral cavity structure to generate a three-dimensional spatial model of the oral cavity internal structure.
According to the embodiment of the invention, the three-dimensional space texture mapping optimization model of the oral cavity structure is rendered by using rendering methods in the aspects of illumination, shadow, materials and the like, so that the sense of reality and visual effect of the model are increased, the oral cavity structure model is presented as a vivid three-dimensional space model, and finally the three-dimensional space model of the oral cavity internal structure is generated.
According to the invention, firstly, the oral cavity surface and texture feature analysis is carried out on the standard image set of the oral cavity structure, so that the surface morphology and texture feature of the oral cavity structure can be deeply known, the geometric shape information of the oral cavity structure can be provided by acquiring the surface feature data, the fine change and texture feature of the oral cavity surface are reflected by the texture feature data, and the key point of the step is that basic data can be provided for subsequent three-dimensional reconstruction and optimization, and the real details and features of the oral cavity structure can be reserved. Secondly, the surface detail optimization is carried out on the initial space model of the three-dimensional reconstruction of the oral cavity structure based on the surface feature data of the oral cavity structure, so that the geometric shape of the model can be effectively improved, and the sense of reality and the fidelity of the model can be improved. By optimizing the surface details, the reconstructed oral cavity structure model is closer to the real anatomical structure, subsequent model application and analysis are facilitated, the key of the step is that the accuracy and the visualization effect of the oral cavity structure model are improved, and a reliable basis is provided for further analysis and processing. Then, texture mapping matching optimization is carried out on the three-dimensional space surface optimization model of the oral cavity structure based on the texture feature data of the oral cavity structure, so that the texture features of the real oral cavity structure can be mapped on the surface of the model, and the realism and fidelity of the model are enhanced. The texture mapping matching optimization can enable the surface of the model to have texture characteristics similar to the actual oral cavity structure, so that the visual effect in the oral cavity can be better simulated, the key point of the step is that the visual effect and fidelity of the space model can be improved, the model is enabled to be more in line with the appearance characteristics of the actual oral cavity structure, and therefore basic data guarantee is provided for the subsequent processing process. Finally, the optimized three-dimensional texture mapping model of the oral cavity structure is subjected to model rendering processing, so that the three-dimensional model of the oral cavity internal structure with high fidelity can be generated. Through model rendering processing, the oral cavity structure model can be presented as a lifelike image or video, the internal structure and texture characteristics of the oral cavity structure model are displayed, a visual tool and a visual reference are provided for the subsequent processing process, and the key point of the step is to provide a high-quality visual result of the oral cavity structure model, so that important support is provided for further research and practice of subsequent tooth occlusion characteristic analysis.
Preferably, step S2 comprises the steps of:
s21, carrying out tooth segmentation treatment on the three-dimensional space model of the oral cavity internal structure to obtain a three-dimensional space model of an oral cavity tooth structure area;
according to the embodiment of the invention, the tooth parts in the three-dimensional space model of the oral cavity internal structure are subjected to segmentation treatment by using a computer tomography treatment method, so that the tooth parts in the complex oral cavity structure are independently extracted, and finally the three-dimensional space model of the oral cavity tooth structure area is obtained.
S22, carrying out tooth structure size measurement treatment on the three-dimensional space model of the dental structure area of the oral cavity to obtain the size of the size range of the three-dimensional space model of the dental structure of the oral cavity;
According to the embodiment of the invention, the measuring tool or software is used for measuring the size of each tooth structure in the three-dimensional space model of the segmented oral cavity tooth structure area, so that the length, the width, the height and the like of the tooth structure are measured, the size of the size range of each tooth structure is estimated, and the size of the size range of the three-dimensional space model of the oral cavity tooth structure is finally obtained.
S23, carrying out tooth shape feature analysis on the three-dimensional space model of the dental structure area based on the size of the size range of the three-dimensional space model of the dental structure so as to obtain three-dimensional geometrical shape feature data of the dental structure;
According to the embodiment of the invention, the shape and characteristic analysis is carried out on the corresponding tooth structure in the three-dimensional space model of the dental structure area through combining the size range of the three-dimensional space model of the dental structure obtained through analysis, so that the characteristics of the geometrical shape, the outline and the like of the tooth are analyzed, and finally, the three-dimensional geometrical shape characteristic data of the dental structure is obtained.
S24, carrying out tooth space position feature analysis on the three-dimensional space model of the internal structure of the oral cavity to obtain three-dimensional space position feature data of the oral cavity;
According to the embodiment of the invention, the position recognition analysis is carried out on the corresponding tooth structure in the three-dimensional space model of the oral cavity internal structure by using the spatial position analysis method, so that the position and the relative position of the tooth structure on the three-dimensional space model of the oral cavity internal structure are analyzed, the specific position information of the tooth in the oral cavity is obtained, and finally the three-dimensional spatial position characteristic data of the oral cavity tooth is obtained.
And S25, carrying out inter-dental contact evaluation analysis on the three-dimensional space model of the oral cavity internal structure based on the three-dimensional geometrical shape feature data of the oral cavity teeth and the three-dimensional space position feature data of the oral cavity teeth to obtain the arrangement contact condition data of the oral cavity teeth.
According to the embodiment of the invention, the contact condition of the corresponding tooth structure in the three-dimensional space model of the oral cavity inner structure in the occlusion process is evaluated and analyzed by combining the three-dimensional geometrical shape characteristic data of the oral cavity teeth and the three-dimensional space position characteristic data of the oral cavity teeth obtained through analysis and using a contact mechanics theory and a simulation algorithm, so that the contact condition between the teeth, the stability of the contact point and the like are evaluated and analyzed, the arrangement contact condition between the teeth in the oral cavity in the occlusion process is evaluated and analyzed, and finally the arrangement contact condition data between the teeth in the oral cavity are obtained.
According to the invention, firstly, the tooth part in the complex oral cavity structure can be extracted independently by carrying out tooth segmentation treatment on the three-dimensional space model of the oral cavity inner structure, so that the three-dimensional space model of the oral cavity tooth structure area is obtained, and the key point of the step is that a foundation can be provided for subsequent tooth correlation analysis, so that the fine analysis on the characteristics of the shape, the position and the like of the tooth is possible. Secondly, the size range of the teeth can be obtained by carrying out tooth structure size measurement processing on the three-dimensional space model of the oral cavity tooth structure area, and the key point of the step is that the size reference can be provided for subsequent analysis to help evaluate the size change range of the teeth, thereby providing data support for personalized analysis of the oral cavity structure. Then, by analyzing the tooth shape feature of the three-dimensional space model of the dental structure region based on the size of the size range of the three-dimensional space model of the dental structure, the geometrical feature of the tooth, such as the shape, curvature, etc., can be revealed, and the key point of this step is to help doctors or researchers understand the morphological feature of the dental structure, thereby providing data support for the subsequent processing procedure. Then, by carrying out tooth space position feature analysis on the three-dimensional space model of the internal structure of the oral cavity, specific position information of the teeth in the oral cavity can be obtained, and the key point of the step is that the relative position relation among the teeth can be known, so that basis is provided for evaluating the problems of tooth arrangement, occlusion and the like. Finally, by carrying out interdental contact evaluation analysis on the three-dimensional space model of the internal structure of the oral cavity based on the three-dimensional geometric shape feature data of the oral cavity teeth and the three-dimensional space position feature data of the oral cavity teeth, the contact condition between the teeth can be evaluated, including the number of contact points, the contact area and the like, and the key point of the step is to help evaluate the arrangement condition and the occlusion function of the teeth, and provide data support for the subsequent occlusion feature analysis process, so that the accuracy and individuation of oral cavity health management are promoted.
Preferably, step S25 comprises the steps of:
step S251, performing tooth occlusion simulation analysis on the three-dimensional space model of the internal structure of the oral cavity to obtain an internal tooth occlusion simulation process of the oral cavity;
According to the embodiment of the invention, the three-dimensional space model of the structure in the oral cavity is imported into simulation software, corresponding simulation parameters of the occlusion process of equipment such as material properties, loading conditions and the like are started, and meanwhile, simulation analysis is performed on the occlusion process of teeth in the oral cavity by starting the simulation software, so that the contact and occlusion processes among the teeth are simulated, the conditions of movement, stress distribution and the like among the teeth are observed, and finally, the occlusion simulation process of the teeth in the oral cavity is obtained.
Step S252, carrying out bite contact area recognition analysis on the intraoral dental bite simulation process based on the three-dimensional geometrical shape feature data of the intraoral teeth and the three-dimensional spatial position feature data of the intraoral teeth to obtain intraoral dental bite contact areas;
According to the embodiment of the invention, the recognition analysis of the occlusion contact area is carried out on the occlusion simulation process of the teeth in the oral cavity by combining the three-dimensional geometrical shape characteristic data of the teeth in the oral cavity and the three-dimensional space position characteristic data of the teeth in the oral cavity, so that the contact area of the teeth in the oral cavity in the occlusion process is recognized and determined, and finally the occlusion contact area of the teeth in the oral cavity is obtained.
Step 253, performing contact mechanical response simulation analysis on the intra-oral dental occlusion simulation process according to the intra-oral dental occlusion contact area to obtain intra-oral dental contact pressure distribution data;
according to the embodiment of the invention, the contact mechanics theory and the simulation algorithm are used for carrying out response simulation analysis on the contact mechanics behavior of the corresponding intraoral teeth in the occlusion contact area in the intraoral teeth occlusion simulation process by combining the identification, so that the mechanical response of intraoral teeth in the occlusion process, including pressure distribution and the like, is simulated, the contact pressure distribution situation among teeth is revealed, and the intraoral teeth contact pressure distribution data is finally obtained.
Step S254, carrying out real-time tracking analysis on contact points in the intra-oral tooth occlusion simulation process to obtain inter-oral tooth occlusion contact point movement status data;
According to the embodiment of the invention, the real-time tracking analysis of the contact points is carried out on the dental occlusion simulation process in the oral cavity by setting the contact point tracking algorithm in the simulation software, so that the contact points of teeth in the occlusion contact areas are tracked in real time, the movement condition of the dental occlusion contact points in the oral cavity is recorded, the dynamic change condition of the contact points in the dental occlusion process in the oral cavity is captured, and finally the movement condition data of the dental occlusion contact points in the oral cavity is obtained.
And S255, carrying out inter-dental contact evaluation analysis on the intra-oral dental occlusion simulation process based on intra-oral dental contact pressure distribution data and intra-oral dental occlusion contact point movement condition data to obtain inter-oral dental tooth arrangement contact condition data.
According to the method, the contact degree evaluation algorithm is used for evaluating and analyzing the arrangement contact condition among teeth in the intraoral teeth occlusion simulation process through the combination of the intraoral teeth contact pressure distribution data and the intraoral teeth occlusion contact point movement condition data obtained through analysis, so that the contact condition among teeth, the stability of contact points and the like are evaluated and analyzed, the arrangement contact condition among the intraoral teeth is evaluated and analyzed, and finally the intraoral teeth arrangement contact condition data is obtained.
According to the invention, the dental occlusion simulation analysis is performed on the three-dimensional space model of the oral cavity internal structure, so that the occlusion process of the teeth in the oral cavity can be simulated, and the dynamic behavior of the teeth during occlusion is known. Secondly, by carrying out occlusion contact area recognition analysis on the occlusion simulation process of the teeth in the oral cavity based on the three-dimensional geometrical shape feature data of the teeth in the oral cavity and the three-dimensional space position feature data of the teeth in the oral cavity, the contact area of the teeth in the oral cavity in the occlusion process can be determined, and the key point of the step is that the contact area between teeth can be accurately recognized, so that a foundation is provided for subsequent contact mechanics response simulation and analysis. Then, by carrying out a contact mechanical response simulation analysis on the dental occlusion simulation process according to the dental occlusion contact area in the oral cavity, the mechanical response of the teeth in the oral cavity in the occlusion process can be simulated, including pressure distribution and the like, and the key point of the step is to reveal the contact pressure distribution condition between teeth, thereby helping to understand the mechanical characteristics in the dental occlusion process in the oral cavity. And then, by carrying out real-time tracking analysis on the contact points in the dental occlusion simulation process in the oral cavity, the movement condition of the occlusion contact points between teeth in the oral cavity can be tracked and recorded in real time, so that the dynamic change of the contact points in the dental occlusion process in the oral cavity can be captured, and key data are provided for further occlusion analysis. Finally, the interdental contact evaluation analysis is carried out on the intraoral dental occlusion simulation process based on intraoral dental contact pressure distribution data and intraoral dental occlusion contact point movement status data, so that the arrangement contact status of intraoral dental teeth can be comprehensively evaluated, the comprehensive evaluation of the intraoral dental occlusion status can be provided, and data support is provided for the subsequent occlusion characteristic analysis process.
Preferably, step S3 comprises the steps of:
s31, carrying out tooth occlusion relation analysis on the three-dimensional space model of the internal structure of the oral cavity to obtain tooth occlusion relation data of the internal structure of the oral cavity;
According to the embodiment of the invention, the interaction and the relationship between the teeth on the three-dimensional space model of the internal structure of the oral cavity are analyzed by using the occlusion relationship analysis method, so that the contact points, the occlusion modes and the like between the teeth in the model are checked to evaluate and analyze the malocclusion relationship and the occlusion relationship between the teeth, and finally the occlusion relationship data of the teeth in the oral cavity are obtained.
S32, carrying out bite point identification analysis on the three-dimensional space model of the oral cavity internal structure based on the dental bite relationship data in the oral cavity to obtain dental bite points in the oral cavity;
According to the embodiment of the invention, the bite points among the teeth on the three-dimensional space model of the oral cavity internal structure are identified and marked by using computer-aided analysis software or algorithm in combination with the dental bite relationship data in the oral cavity obtained through analysis, so that the points or areas which are in contact with each other among the teeth are obtained, the marks are determined as the bite points among the teeth, and finally the dental bite points in the oral cavity are obtained.
S33, carrying out bite point positioning analysis on the tooth bite points in the oral cavity to obtain data of the bite points of the teeth in the oral cavity;
According to the embodiment of the invention, the coordinate system of the three-dimensional space model is used for carrying out positioning analysis on the tooth biting points in the oral cavity obtained through marking, so that the specific position of the three-dimensional coordinate of each biting point is determined, and finally the tooth biting point data of the oral cavity are obtained.
S34, carrying out tooth occlusion connection relation excavation analysis on the three-dimensional space model of the oral cavity internal structure based on the tooth arrangement contact condition data of the oral cavity so as to obtain tooth connection relation in the oral cavity occlusion process;
according to the embodiment of the invention, the connection relation mining algorithm is used for mining and analyzing the occlusion connection relation among teeth on the three-dimensional space model of the oral cavity internal structure by combining the dental tooth arrangement contact condition data obtained through analysis, so that the contact or occlusion relation among teeth and the properties and characteristics of the relation are analyzed and determined, the interaction condition among teeth in the oral cavity occlusion process is known, and finally the dental tooth connection relation in the oral cavity occlusion process is obtained.
And S35, carrying out tooth occlusal surface connection division on the three-dimensional space model of the oral cavity internal structure according to the dental interdental connection relation and the dental occlusal point position data in the oral cavity occlusion process so as to generate an oral cavity dental occlusal connection surface.
According to the embodiment of the invention, the connection relation between teeth in the dental occlusion process and the dental occlusion point position data obtained by the previous analysis are combined to carry out the connection treatment of the dental occlusion surfaces on the teeth in the three-dimensional space model of the internal structure of the oral cavity, so that the teeth form an occlusion surface together, and the teeth are identified and connected to finally generate the dental occlusion connection surface.
According to the invention, the dental occlusion relation analysis is performed on the three-dimensional space model of the oral cavity internal structure, so that the interaction and the relation between the teeth in the oral cavity can be deeply known, the analysis can help to evaluate the malocclusion relation and the occlusion problem between the teeth, and an important reference can be provided for the subsequent processing process. By obtaining the dental occlusion relationship data in the oral cavity, the position and angle of each tooth and the contact condition with surrounding teeth can be systematically recorded, and accurate basic information is provided for the subsequent occlusion point identification process. Secondly, the bite point recognition analysis is carried out on the three-dimensional space model of the oral cavity internal structure based on the tooth bite relationship data in the oral cavity so as to determine the bite points of the teeth in the oral cavity, and the step aims at accurately positioning key bite points in the oral cavity and provides an accurate basis for further analysis of the oral cavity structure. By identifying the bite points, the anatomical features and functional mechanisms of the oral structure may be better understood. Then, by performing a positional analysis of the teeth bite point within the mouth, specific positional data of the teeth bite point can be obtained, which data provides data support for subsequent processing. Then, the tooth occlusion connection relation mining analysis is carried out on the three-dimensional space model of the internal structure of the oral cavity based on the tooth arrangement contact condition data of the oral cavity so as to know the connection mode and interaction between teeth in the oral cavity, and the analysis is helpful for revealing the functional connection between the teeth, so that a more comprehensive visual angle is provided for subsequent occlusion surface connection division. Finally, the tooth occlusal surface connection division is carried out on the three-dimensional space model of the internal structure of the oral cavity according to the tooth interdental connection relation in the occlusion process of the oral cavity and the tooth occlusal point position data of the oral cavity, and the purpose of the step is to generate an occlusion connecting surface of the oral cavity, so that finer and accurate information is provided for further analysis of the oral cavity structure. By dividing the occlusion connecting surface, the overall shape and functional characteristics of the oral cavity structure can be better understood, and more scientific and effective support is provided for subsequent occlusion characteristic analysis.
Preferably, step S4 comprises the steps of:
S41, carrying out bite inclination angle measurement treatment on the bite connection surface of the oral cavity teeth to obtain the bite inclination angle of the oral cavity teeth;
According to the embodiment of the invention, the inclination angle of the occlusion connecting surfaces of the oral teeth on the three-dimensional space model is measured by using an angle measuring instrument or a computer-aided measuring tool, so that the inclination angle of each occlusion connecting surface is accurately measured, and is recorded in a digital form, and finally, the occlusion inclination angle of the oral teeth is obtained.
Step S42, carrying out inclined curvature statistical calculation on the dental occlusion connecting surface based on the dental occlusion inclined angle to obtain dental occlusion inclined curvature;
According to the embodiment of the invention, the statistical calculation of the inclined curvature is carried out on the corresponding dental occlusion connecting surface by combining the measured dental occlusion inclined angle through a statistical method, so that the curvature degree of the occlusion connecting surface, namely the inclined degree of the occlusion connecting surface, is quantitatively calculated, and finally the dental occlusion inclined curvature is obtained.
Step S43, calculating the occlusion parallelism of the occlusion connecting surface of the oral cavity teeth by utilizing an occlusion parallelism calculation formula based on the occlusion inclination angle of the oral cavity teeth and the occlusion inclination curvature of the oral cavity teeth so as to obtain the occlusion surface parallelism of the teeth;
According to the embodiment of the invention, a proper occlusion parallelism calculation formula is formed by combining the tooth length, the tooth horizontal position parameter, the oral tooth occlusion inclination angle, the oral tooth occlusion inclination curvature, the distance value between adjacent teeth, the tooth occlusion application force and related parameters, so that the occlusion parallelism calculation is performed on the oral tooth occlusion connecting surface, the parallelism of the tooth occlusion surface is calculated quantitatively, and finally the tooth occlusion surface parallelism is obtained.
The calculation formula of the occlusion parallelism is as follows:
wherein p is the parallelism of the dental occlusion surface, L is the length of teeth on the dental occlusion connecting surface, L is the horizontal position parameter of teeth on the dental occlusion connecting surface, θ is the dental occlusion inclination angle, C is the dental occlusion inclination curvature, e is the distance value between adjacent teeth on the dental occlusion connecting surface, F (L) is the dental occlusion force applied on the dental occlusion connecting surface at the horizontal position L, and ε is the correction coefficient of the parallelism of the dental occlusion surface;
According to the invention, a specific mathematical model is used and verified to obtain an occlusion parallelism calculation formula, which is used for carrying out occlusion parallelism calculation on the occlusal connection surfaces of the oral teeth, and the occlusion parallelism calculation formula aims at evaluating the parallelism degree of the occlusal connection surfaces of the oral teeth, which is critical to oral health and occlusion functions, and through the step, the parallelism degree of the occlusal surfaces of the teeth can be quantitatively evaluated, so that guidance is provided for further processing and adjustment. The integral part of the formula covers the tooth situation at various locations on the occlusal connection of the oral teeth, wherein,This section describes the contribution of tooth inclination angle and curvature to parallelism, whileThis section describes the contribution of the occlusal force to parallelism, which takes into account a combination of factors such as the inclination, curvature and occlusal force of the teeth. In addition, the application of the occlusion parallelism calculation formula enables the parallelism of the occlusion connecting surface of the oral cavity and the teeth to be quantitatively evaluated, so that the quality and the adaptability of the occlusion surface are determined, and the non-parallelism condition of the occlusion surface of the teeth can be found through the calculation of the occlusion parallelism, so that guidance and basis are provided for subsequent adjustment and treatment, and the method has important significance in the aspects of oral correction, restoration, functional adjustment and the like. In summary, the formula fully considers the parallelism p of the dental occlusion surface, the length L of the teeth on the dental occlusion connecting surface, the horizontal position parameter L of the teeth on the dental occlusion connecting surface, the dental occlusion inclination angle theta, the dental occlusion inclination curvature C, the distance value e between adjacent teeth on the dental occlusion connecting surface, the dental occlusion force F (L) on the dental occlusion connecting surface at the horizontal position L, the correction coefficient epsilon of the parallelism of the dental occlusion surface, and forms a functional relation according to the correlation relation between the parallelism p of the dental occlusion surface and the parametersThe formula can realize the calculation process of the occlusion parallelism of the occlusion connecting surface of the oral teeth, and meanwhile, the correction coefficient epsilon of the parallelism of the occlusion surface of the teeth can be introduced to adjust according to the error condition in the calculation process, so that the accuracy and the applicability of the calculation formula of the occlusion parallelism are improved.
S44, carrying out tooth occlusion contour shape recognition analysis on the dental tooth occlusion connecting surface to obtain a tooth occlusion surface contour shape;
According to the embodiment of the invention, the contour shape of the dental occlusion connecting surface of the oral cavity obtained by connection is identified and analyzed by using a computer vision algorithm, so that the contour shape of the dental occlusion surface is identified and obtained to know the morphological characteristics of the dental occlusion surface, such as the concave-convex degree, the irregularity and the like, the occlusion relation among teeth is revealed, and finally the contour shape of the dental occlusion surface is obtained.
And S45, carrying out tooth occlusion adjustment processing on the three-dimensional space model of the internal structure of the oral cavity based on the parallelism degree of the tooth occlusion surface and the outline shape of the tooth occlusion surface so as to generate an oral cavity tooth occlusion surface adjustment scheme.
According to the embodiment of the invention, the three-dimensional space model of the internal structure of the oral cavity is adjusted by combining the parallelism of the occlusal surface and the outline shape of the occlusal surface obtained by the previous analysis by using a computer-aided design tool or a three-dimensional simulation method, so that the internal structure of the oral cavity is adjusted according to the information of the parallelism and the outline shape of the occlusal surface, the occlusal surface of the tooth is enabled to be parallel, and the outline shape of the occlusal surface of the tooth meets the requirements of the anatomical structure and the function of the oral cavity, so that a targeted occlusal adjustment scheme is formulated, the effects of correcting the malocclusion of the tooth, improving the occlusal function and the like are realized, and finally, the occlusal surface adjustment scheme of the oral cavity is generated.
According to the invention, the occlusion inclination angle measurement treatment is carried out on the occlusion connecting surface of the oral cavity teeth, so that the inclination angle of the occlusion surface of the teeth can be accurately measured to know the occlusion condition among the teeth, the measurement treatment is helpful for determining the occlusion position and angle of the teeth, and important data is provided for further analysis of the oral cavity structure. By obtaining the occlusion inclination angle of the oral teeth, whether the occlusion relationship between the teeth is normal or not can be estimated, and a basis is provided for subsequent occlusal surface curvature calculation. Secondly, the inclination curvature of the occlusion connecting surface of the oral cavity and the teeth is obtained by carrying out the statistical calculation of the inclination curvature of the occlusion connecting surface of the oral cavity and the teeth based on the inclination angle of the occlusion of the oral cavity, and the calculation process aims at quantifying the inclination degree of the occlusion surface and provides a quantification index for the analysis and evaluation of the oral cavity structure. By counting the inclined curvature, the morphological characteristics and the inclination degree of the occlusal surface of the teeth can be known more accurately, and more objective data support is provided for the subsequent processing process. Then, the occlusion parallelism calculation is carried out on the occlusion connecting surface of the oral cavity teeth by utilizing an occlusion parallelism calculation formula based on the occlusion inclination angle of the oral cavity teeth and the occlusion inclination curvature of the oral cavity teeth, and the calculation process aims at evaluating the parallelism degree of the occlusion surface of the teeth, so that important references are provided for the evaluation of the oral cavity structure and the establishment of an occlusion adjustment scheme. The relative position relationship between the occlusal surfaces of the teeth can be judged by calculating the parallelism, so that a quantitative basis is provided for the adjustment process of the occlusal problem of the teeth. Then, the dental occlusion contour shape recognition analysis is carried out on the dental occlusion connecting surface so as to recognize and analyze the contour shape of the dental occlusion surface to know the morphological characteristics of the dental occlusion surface, and the analysis is helpful for revealing the occlusion relation and the morphological characteristics among teeth and providing more comprehensive information for the evaluation of the oral cavity structure. By identifying the contour shape of the occlusal surfaces of the teeth, the contact condition and morphological characteristics between the teeth can be better understood, thereby providing more accurate reference for the subsequent occlusal adjustment process. Finally, the three-dimensional space model of the internal structure of the oral cavity is subjected to tooth occlusion adjustment treatment based on the parallelism degree of the tooth occlusion surface and the outline shape of the tooth occlusion surface, and the step aims at making a targeted tooth occlusion adjustment scheme according to the analysis result, providing guidance for the adjustment and repair of the occlusion process of the oral cavity structure, and correcting the misjaw of the teeth and improving the occlusion function by adjusting the tooth occlusion surface, so that the oral cavity health level and the life quality are improved.
The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.
The foregoing is only a specific embodiment of the invention to enable those skilled in the art to understand or practice the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.