Intelligent reconstruction method for missing tooth morphology based on contralateral tooth mirror transformation

Abstract

The present application relates to the technical field of image data processing, in particular to a missing tooth shape intelligent reconstruction method based on contralateral tooth mirror image transformation. According to the patient's masseter axial ultrasound image and temporal muscle axial ultrasound image, the robustness of each side of the masticatory muscle of the patient's both cheeks is determined; the average wear degree of each side of the patient's both cheeks is measured, and then a regression equation of the average wear degree and the robustness is constructed; the coordination coefficient between the missing tooth side and the contralateral side of the patient is determined by using the regression equation, and then it is judged whether the contralateral homonym tooth of the missing tooth needs to be corrected; if correction is needed, the wear degree correction coefficient of the contralateral homonym tooth is constructed, and then the contralateral homonym tooth of the missing tooth is corrected, and the missing tooth shape reconstruction is carried out based on the corrected contralateral homonym tooth. The present application corrects the contralateral homonym tooth of the missing tooth, so that the missing tooth shape reconstruction is more consistent with the dynamic coordination of masticatory movement.

Description

Technical Field

[0001] This invention relates to the field of image data processing technology, and specifically to an intelligent reconstruction method for the morphology of missing teeth based on contralateral tooth mirror transformation. Background Technology

[0002] Contralateral tooth mirror transformation for missing tooth morphology reconstruction is a traditional digital-aided design method that replicates a digital 3D model of the patient's contralateral healthy tooth at the missing tooth location as a prototype for the restoration. This technology efficiently provides an initial tooth morphology template tailored to individual needs, serving as the starting point for missing tooth morphology design, and is particularly advantageous in reconstructing teeth with complex morphologies, such as molars. Currently, combining mirror technology with advanced artificial intelligence and modeling techniques allows for the reconstruction of missing teeth to satisfy both mirror relationships and the continuity of tooth alignment, as well as the cusp-fossa interlocking relationship of the opposing teeth. This results in a reconstructed missing tooth model that better reflects the dynamic coordination of mastication movements, leading to faster and more efficient missing tooth reconstruction.

[0003] Because molars are frequently used in daily life and are among the most prone to wear, when a molar is lost, it is necessary to use the contralateral corresponding tooth to reconstruct the shape of the missing tooth. However, due to differences in individual chewing habits, the degree of wear on teeth on different sides varies. Current techniques that directly use the contralateral corresponding tooth to reconstruct the shape of the missing tooth ignore the asymmetry of wear on different sides and cannot accurately correct the shape of the contralateral corresponding tooth. This can easily lead to the reconstructed shape of the missing tooth not conforming to the dynamic coordination of chewing movements. Summary of the Invention

[0004] To address the technical problem that existing technologies, which directly use the contralateral corresponding tooth to reconstruct the morphology of missing teeth, often result in reconstructed morphologies that do not conform to the dynamic coordination of chewing movements, the present invention aims to provide an intelligent reconstruction method for the morphology of missing teeth based on the mirror transformation of the contralateral tooth. The specific technical solution adopted is as follows:

[0005] This invention proposes an intelligent reconstruction method for the morphology of missing teeth based on contralateral tooth mirror transformation. The method includes the following steps:

[0006] Acquire axial ultrasound images of each posterior molar on each side of the patient's cheeks, as well as axial ultrasound images of the masseter muscle and temporalis muscle on each side of the patient's cheeks from the three-dimensional digital model of the dental arch corresponding to the patient's oral cavity.

[0007] Based on the axial ultrasound images of the masseter muscle and the temporalis muscle, the robustness characteristics of the masseter and temporalis muscles were analyzed to determine the robustness of the masticatory muscles on each side of the patient's cheeks.

[0008] The sharpness of the cusps and the flatness of the occlusal surface of each molar are analyzed to determine the average wear degree on each cheek of the patient. Based on the average wear degree and the robustness, a regression equation is constructed for the average wear degree and the robustness. The regression equation is used to predict the predicted average wear degree on the edentulous cheek of the current patient. Based on the predicted average wear degree, the coordination coefficient between the edentulous cheek and the contralateral cheek is obtained.

[0009] Based on the coordination coefficient between the side with missing teeth and the opposite side, it is determined whether the corresponding tooth on the opposite side of the missing tooth needs to be corrected. If correction is required, the theoretical wear degree of the missing tooth is estimated based on the strength of the masticatory muscles on the side with missing teeth, and the wear degree correction coefficient of the corresponding tooth on the opposite side is determined. The morphology of the missing tooth is reconstructed using the wear degree correction coefficient of the corresponding tooth on the opposite side of the missing tooth.

[0010] Preferably, the method for determining the robustness includes:

[0011] Each axial ultrasound image of the masseter muscle on each side of the patient's cheeks includes the inner edge of the superficial fascia of the masseter muscle and the inner edge of the deep fascia of the masseter muscle. The inner edge of the superficial fascia of the masseter muscle is used as the upper boundary, and the inner edge of the deep fascia of the masseter muscle is used as the lower boundary. The maximum metric distance between the upper and lower boundaries is used as the thickness of the masseter muscle in each axial ultrasound image of the masseter muscle, and the area between the upper and lower boundaries is used as the cross-sectional area of ​​the masseter muscle in each axial ultrasound image of the masseter muscle.

[0012] Based on the maximum thickness and maximum cross-sectional area of ​​the masseter muscle in all axial ultrasound images of the masseter muscle, the robustness coefficient of the masseter muscle on each side of the patient's cheeks was determined.

[0013] Each axial ultrasound image of the temporalis muscle on each side of the patient's cheeks includes the inner edge of the superficial fascia of the temporalis muscle and the inner edge of the deep fascia of the temporalis muscle. Based on the inner edge of the superficial fascia of the temporalis muscle and the inner edge of the deep fascia of the temporalis muscle, the robustness coefficient of the temporalis muscle on each side of the patient's cheeks is determined.

[0014] The product of the robustness coefficient of the masseter muscle and the robustness coefficient of the temporalis muscle is calculated as the robustness of the masticatory muscles on each side of the patient's cheeks.

[0015] Preferably, the method for obtaining the robustness coefficient of the temporalis muscle includes:

[0016] The thickness and cross-sectional area of ​​the temporalis muscle in each axial ultrasound image are determined based on the inner edges of the superficial and deep fascia of the temporalis muscle.

[0017] The robustness coefficient of the temporalis muscle on each side of the patient's cheeks was determined based on the maximum thickness and maximum cross-sectional area of ​​the temporalis muscle in all axial ultrasound images of the temporalis muscle.

[0018] Preferably, the method for obtaining the average wear level includes:

[0019] With the crown major axis of each posterior molar as the central axis, rotate along a predetermined direction of the circumference. After each rotation by a predetermined angle, obtain the intersection line between the longitudinal section of the posterior tooth and the surface of the posterior tooth. Stop after one full rotation. The set of all the intersection lines is taken as the intersection line set; the intersection line is composed of a discrete point sequence.

[0020] For each intersection line in the intersection line set, the intersection line is divided into two equal parts, and corner point detection is performed on each part of the intersection line to obtain the target corner point in each part of the intersection line;

[0021] The straight line connecting the two nearest discrete points on both sides of the target corner point is taken as the cusp tangent. The sum of the measured distances between all discrete points in each part of the intersection line and the cusp tangent line is calculated as the sharpness of the cusp point in each part of the intersection line.

[0022] The sum of the sharpness of the cusps in the two intersecting lines after bisection is calculated as the cusp sharpness assessment value for each intersecting line;

[0023] Based on the straight line connecting the two target corner points in the intersection line of the two parts after bisection, determine the flatness evaluation value of the interlocking surface of each intersection line;

[0024] The wear assessment value of each posterior molar is determined based on the cusp sharpness assessment value and occlusal surface flatness assessment value of all the aforementioned intersections; the average wear degree of each cheek is calculated based on the wear assessment values ​​of all posterior molars on each cheek of the patient.

[0025] Preferably, the method for obtaining the occlusal surface flatness assessment value includes:

[0026] The straight line connecting the two target corner points in the intersection line after the two parts are divided into two equal parts is taken as the corner point line. The sum of the measured distances between all discrete points in the intersection line and the corner point line is calculated as the flatness evaluation value of the biting surface of each intersection line.

[0027] Preferably, the method for obtaining the regression equation includes:

[0028] A pre-defined population sample database is constructed, which includes data on the strength of the masticatory muscles on each side of the cheeks of the sample population and the average wear of the corresponding teeth. Using the strength data in the population sample database as the independent variable and the average wear of the corresponding teeth in the population sample database as the dependent variable, a linear regression method is used to obtain the regression equation between the strength of the masticatory muscles and the average wear.

[0029] Preferably, the method for obtaining the coordination coefficient includes:

[0030] The robustness of the masticatory muscles on the edentulous side of the patient's cheeks is calculated, and the current robustness of the masticatory muscles on the edentulous side of the patient's cheeks is used as the input of the regression equation to calculate the predicted average wear on the edentulous side of the patient's cheeks.

[0031] A coarse mirror image of the corresponding tooth on the opposite side of the missing tooth is made to the missing tooth location, and then the actual average wear on the patient's missing tooth side is calculated after the coarse mirror image.

[0032] Based on the predicted average wear degree and the actual average wear degree, the coordination coefficient between the patient's edentulous side and the contralateral side is obtained.

[0033] Preferably, the method for determining whether correction is needed includes:

[0034] If the coordination coefficient is less than or equal to a preset first threshold, then no correction is needed for the contralateral tooth of the missing tooth; if the coordination coefficient is greater than the preset first threshold, then correction is needed for the contralateral tooth of the missing tooth.

[0035] Preferably, the method for obtaining the wear correction coefficient includes:

[0036] The theoretical wear degree of the missing tooth is inferred based on the strength of the masticatory muscle on the side of the missing tooth, and the wear assessment value of the corresponding tooth on the opposite side of the missing tooth is calculated. Based on the wear assessment value of the corresponding tooth on the opposite side of the missing tooth and the theoretical wear degree of the missing tooth, the wear degree correction coefficient of the corresponding tooth on the opposite side is determined.

[0037] Preferably, the method for reconstructing the morphology of the missing tooth includes:

[0038] If the wear correction coefficient of the contralateral tooth is less than or equal to a preset second threshold, the Laplace smoothing algorithm is used to correct the contralateral tooth of the missing tooth.

[0039] If the wear correction coefficient of the contralateral tooth is greater than the preset second threshold, morphological expansion is used to correct the contralateral tooth with missing teeth for the cusp and marginal ridge area on the crown surface.

[0040] After correcting the contralateral tooth with the same name that is missing, the morphology of the missing tooth is reconstructed based on the corrected contralateral tooth with the same name.

[0041] The present invention has the following beneficial effects:

[0042] This invention provides a reliable data foundation for subsequent analysis of the robustness of the masseter and temporalis muscles and the wear degree of each posterior molar in a three-dimensional digital model of the patient's dental arch, including axial ultrasound images of the masseter and temporalis muscles on each side of the patient's cheeks. By accurately analyzing and measuring the robustness of the masseter and temporalis muscles, the strength of the masticatory muscles is more clearly demonstrated. Therefore, combining the robustness of the masseter and temporalis muscles allows for a more accurate measurement of the strength of the masticatory muscles, which is then used to accurately analyze the wear degree of the posterior molars. This is further enhanced by combining the sharpness of the cusps and the occlusal surface... The flatness of the teeth is used to more accurately determine the average wear level, and a regression equation is constructed between the average wear level and the strength of the masticatory muscles to accurately predict the average wear level on the edentulous side of the patient's cheeks. Using the prediction results and fully considering the asymmetry of wear levels on different sides, the coordination coefficient between the edentulous side and the contralateral side is accurately measured, thus accurately determining whether correction is needed for the contralateral tooth. Considering the theoretical wear condition of the missing tooth, a wear correction coefficient for the contralateral tooth is constructed for accurate morphological reconstruction of the contralateral tooth. This invention, by correcting the contralateral tooth, makes the morphological reconstruction of the missing tooth more consistent with the dynamic coordination of masticatory movements. Attached Figure Description

[0043] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 This is a flowchart illustrating a method for intelligent reconstruction of missing tooth morphology based on contralateral tooth mirror transformation, provided as an embodiment of the present invention. Detailed Implementation

[0045] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a method for intelligent reconstruction of missing tooth morphology based on contralateral tooth mirror transformation proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0046] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0047] This invention addresses the scenario where a patient has lost a mandibular posterior molar. Reconstructing the missing tooth using a mirror image of the contralateral tooth can be affected by the degree of tooth wear. Depending on individual dental habits, the wear on the two sides of the posterior molars can differ. Directly using the contralateral tooth for mirror image reconstruction can disrupt the occlusal relationship between the missing tooth and the maxillary teeth, easily leading to a reconstruction that does not conform to the dynamic coordination of chewing movements, thus affecting the patient's daily eating comfort. Therefore, this invention, before using the contralateral tooth for mirror image reconstruction, establishes a coordination coefficient between the patient's missing side and the contralateral side to determine if correction of the contralateral tooth is necessary. If correction is required, a wear correction coefficient is established to correct the contralateral tooth before mirror image reconstruction. This results in a more consistent reconstruction of the missing tooth's shape with the dynamic coordination of chewing movements. This invention is particularly suitable for recent tooth loss restoration scenarios, such as traumatic tooth loss, immediate implantation after extraction, or when assuming high symmetry of the patient's bilateral muscles before the lesion. In recent tooth loss restoration scenarios, the masticatory muscles have not yet shown significant disuse atrophy, and their morphological characteristics can still reflect the patient's long-term chewing habits and tooth wear characteristics.

[0048] The following description, in conjunction with the accompanying drawings, details a specific scheme for an intelligent reconstruction method for the morphology of missing teeth based on contralateral tooth mirror transformation provided by the present invention.

[0049] Please see Figure 1 The diagram illustrates a flowchart of a method for intelligent reconstruction of missing tooth morphology based on contralateral tooth mirror transformation, according to an embodiment of the present invention. The method includes the following steps:

[0050] Step S101: Obtain axial ultrasound images of each posterior molar on each side of the patient's cheeks, the masseter muscle on each side of the patient's cheeks, and the temporalis muscle on each side of the patient's cheeks from the three-dimensional digital model of the dental arch corresponding to the patient's oral cavity.

[0051] To fully account for the asymmetry in wear on different sides of the teeth and to more accurately correct the morphology of the contralateral tooth of the missing tooth, it is first necessary to obtain axial ultrasound images of the masseter muscle and temporalis muscle on each side of the patient's mouth. This will be used to more accurately analyze the robustness of the masseter and temporalis muscles. At the same time, each posterior molar on each side of the patient's mouth will be obtained from the three-dimensional digital model of the dental arch. This will allow for more accurate extraction of the wear degree of each posterior molar on each side of the patient's mouth, thus providing a reliable data foundation for the subsequent analysis of tooth wear.

[0052] In one specific implementation of this invention, an intraoral scanner is used to scan the patient's oral cavity to obtain a three-dimensional digital model of the dental arch, which includes the edentulous area, the contralateral corresponding tooth, adjacent teeth, and opposing teeth. The three-dimensional digital model of the dental arch includes each posterior molar on each side of the patient's cheeks.

[0053] In one specific implementation of this invention, acquiring axial ultrasound images of the masseter muscle and temporalis muscle on each side of the patient's cheeks using a high-frequency linear array ultrasound probe includes:

[0054] The patient lies supine with their entire body completely relaxed, and their upper and lower teeth slightly separated but not touching. An ultrasound coupling agent is applied to the surface of the high-frequency linear array ultrasound probe. Using the probe, axial ultrasound images of the masseter muscle are acquired on each side of the patient's cheeks at preset fixed intervals of 2 mm, moving from the top of the head down to the jaw.

[0055] The patient lies supine with their head turned to the side in a relaxed state. An ultrasound coupling agent is applied to the surface of the high-frequency linear array ultrasound probe. The high-frequency linear array ultrasound probe is used to acquire axial ultrasound images of each temporalis muscle on each side of the patient's cheeks at a preset fixed interval of 2 mm, along the direction from the top of the head to the jaw.

[0056] Step S102: Based on the axial ultrasound images of the masseter muscle and the temporalis muscle, analyze the robustness characteristics of the masseter and temporalis muscles to determine the robustness of the masticatory muscles on each side of the patient's cheeks.

[0057] The degree of wear on a patient's molars is related to their daily dental habits. For example, if a patient habitually chews food using only their right side, the wear on the right-side molars will be higher, and the right-side masticatory muscles will be more developed. Therefore, the degree of wear on one side of the patient's cheeks is related to the development of the masticatory muscles on that side. Analyzing the strength of the masticatory muscles can be used to evaluate a patient's daily dental habits and tooth wear, thus more accurately analyzing the asymmetry of tooth wear on different sides.

[0058] Furthermore, to accurately determine the relationship between masticatory muscles and tooth wear, it is necessary to accurately quantify the strength of the masticatory muscles in the patient's cheeks. The masticatory muscles of the cheeks are a group of muscles responsible for jaw closure and chewing, including the temporalis, masseter, medial pterygoid, and lateral pterygoid muscles. The muscle groups mainly related to daily dental habits include the masseter and temporalis muscles. Among them, the masseter muscle is located on both sides of the cheeks and is responsible for providing the main vertical closing force. When a patient habitually chews food on one side, the masseter muscle on the frequently used side will be more developed, and the wear of the molars on the frequently used side is often more severe. The temporalis muscle has a more complex structure. The temporalis muscle group is roughly divided into anterior, middle, and posterior fibers. The anterior fibers mainly provide the closing force and the force in the clenching state, while the wear of the posterior molars mainly occurs in the clenching state.

[0059] Because axial ultrasound images of the masseter muscle can accurately reflect the strength of the masseter muscle, and axial ultrasound images of the temporalis muscle can accurately reflect the strength of the temporalis muscle, by analyzing the strength of the masseter and temporalis muscles, the strength of the masticatory muscles on each side of the patient's cheeks can be accurately measured. If the strength of the masticatory muscles on one side of the patient's cheeks is higher, it indicates that the patient habitually uses the teeth on that side to chew food, and the teeth on that side are more likely to have more severe wear.

[0060] Step S103: Analyze the cusp sharpness and occlusal surface flatness of each molar to determine the average wear degree on each cheek of the patient; construct a regression equation for the average wear degree and the robustness based on the average wear degree and the robustness; use the regression equation to predict the predicted average wear degree on the edentulous cheek of the current patient, and obtain the coordination coefficient between the edentulous cheek and the contralateral cheek based on the predicted average wear degree.

[0061] When mirroring a patient's missing teeth, the most significant factor affecting the mirroring effect is the asymmetry in the wear of the teeth on both cheeks. This asymmetry can disrupt the occlusal relationship of the upper and lower jaws at the site of the missing tooth, so it is necessary to quantify the wear degree of the molars. Furthermore, the main functional structures of molars include cusps and ridges. The cusps are responsible for piercing the surface of food, while the ridges are responsible for grinding the food after piercing. Therefore, the wear characteristics of molars are mainly manifested in the cusps and ridges. The more severe the wear of the molars, the lower the sharpness of the cusps and ridges, and the smoother the occlusal surface of the molars.

[0062] To more accurately quantify the wear of molars, it is necessary to analyze the cusp sharpness and occlusal surface flatness of each molar on each cheek side of the patient. A lower cusp sharpness indicates lower cusp and ridge sharpness of the molar; a lower occlusal surface flatness indicates a smoother occlusal surface. Therefore, by combining the cusp sharpness and occlusal surface flatness of each molar, the average wear on each cheek side of the patient can be measured more accurately. A higher average wear indicates more severe wear on the molars on that side.

[0063] The difference in wear between the edentulous side and the contralateral side cannot be directly calculated because the wear degree of the missing teeth cannot be directly measured. Therefore, in order to infer the average wear degree of the edentulous side using the strength of the masticatory muscles, a regression analysis is needed on the average wear degree and the strength of the muscles. This allows for the accurate determination of the regression equation between the average wear degree and the strength of the muscles, reflecting the regression relationship between them and enabling an accurate estimation of the average wear degree of the edentulous side based on the strength of the masticatory muscles.

[0064] Therefore, the regression equation is used to predict the average wear degree of the current patient's edentulous sides. Based on the predicted average wear degree, the coordination coefficient between the edentulous side and the contralateral side is obtained. The coordination coefficient reflects the difference in wear degree between the edentulous side and the contralateral side. The larger the coordination coefficient, the greater the possibility of asymmetry in wear degree between the edentulous side and the contralateral side. Subsequently, it is necessary to accurately correct the corresponding tooth on the contralateral side of the missing tooth.

[0065] Step S104: Based on the coordination coefficient between the patient's edentulous side and the contralateral side, determine whether it is necessary to correct the contralateral tooth of the missing tooth; if correction is required, infer the theoretical wear degree of the missing tooth based on the strength of the masticatory muscles on the edentulous side, and determine the wear degree correction coefficient of the contralateral tooth of the missing tooth; use the wear degree correction coefficient of the contralateral tooth of the missing tooth to reconstruct the morphology of the contralateral tooth of the missing tooth.

[0066] When the coordination coefficient between the missing tooth side and the opposite side is too large, it indicates that the coordination of wear between the two sides is too low. It is necessary to analyze the reasons for the low coordination of wear between the missing tooth side and the opposite side. The reasons can generally be divided into two situations: one is that the patient has a serious problem of unilateral chewing, which leads to the lack of coordination of wear between the missing tooth side and the opposite side; the other is that the missing tooth is caused by the adjacent tooth tilting, which leads to the value of the calculated wear degree being too large, thus making the wear degree between the missing tooth side and the opposite side uncoordinated.

[0067] Therefore, by using the coordination coefficient between the side of the missing tooth and the opposite side, it is determined whether correction of the corresponding tooth on the opposite side is necessary. If correction is required, the theoretical wear degree of the missing tooth is estimated by the strength of the masticatory muscles on the side of the missing tooth. This theoretical wear degree characterizes the wear degree of the missing tooth under ideal conditions. Then, using the theoretical wear degree of the missing tooth, the wear degree correction coefficient of the corresponding tooth on the opposite side is accurately determined. A larger wear degree correction coefficient indicates excessive wear of the corresponding tooth on the opposite side, requiring correction of the cusps and marginal ridge areas on the crown surface of the corresponding tooth on the opposite side. Finally, based on the corrected corresponding tooth on the opposite side, the morphology of the missing tooth is reconstructed, making the reconstructed morphology more consistent with the dynamic coordination of chewing movements and avoiding affecting the patient's daily eating comfort.

[0068] Preferably, in some implementations of the embodiments of the present invention, the method for determining the robustness includes:

[0069] The masseter muscles, located on either side of the cheeks, are responsible for providing the main vertical closing force. When a patient habitually chews food on one side, the masseter muscle on that side will be more developed, and the wear on the molars on that side will often be more severe. Therefore, the strength of the masseter muscles can be used to infer a patient's chewing habits and the degree of wear on the molars. Moreover, the strength of the masseter muscles is mainly reflected by their biting force, which is related to the length and thickness of the masseter muscle fiber group.

[0070] Each axial ultrasound image of the masseter muscle on each side of the patient's cheeks includes the inner edge of the superficial fascia and the inner edge of the deep fascia of the masseter muscle. Each axial ultrasound image of the masseter muscle on each side of the patient's cheeks is used as input to the Canny edge detection algorithm. The Canny edge detection algorithm is used to extract the edges within each axial ultrasound image of the masseter muscle. Then, the outer and inner sides of the skin in each axial ultrasound image of the masseter muscle are manually marked. Generally, the right side of the axial ultrasound image of the masseter muscle is the outer side of the skin, and the left side of the axial ultrasound image of the masseter muscle is the inner side of the skin.

[0071] The edge closest to the outer side of the skin in each axial ultrasound image of the masseter muscle is taken as the inner edge of the superficial fascia of the masseter muscle, and the edge closest to the inner side of the skin in each axial ultrasound image of the masseter muscle is taken as the inner edge of the deep fascia of the masseter muscle. Then, the inner edge of the superficial fascia of the masseter muscle is taken as the upper boundary, and the inner edge of the deep fascia of the masseter muscle is taken as the lower boundary. The maximum distance between the upper boundary and the lower boundary in the direction from the inner side of the skin to the outer side of the skin is taken as the thickness of the masseter muscle in each axial ultrasound image of the masseter muscle.

[0072] Meanwhile, the area formed by connecting the left endpoint of the upper and lower boundaries and the right endpoint of the upper and lower boundaries is taken as the masseter muscle region, and the area of ​​the masseter muscle region is taken as the cross-sectional area of ​​the masseter muscle in each axial ultrasound image of the masseter muscle.

[0073] Among them, the maximum thickness of the masseter muscle can reflect the strength of the masseter muscle. The greater the maximum thickness of the masseter muscle, the stronger the masseter muscle is. Since the axial ultrasound image is a cross-sectional area parallel to the muscle fibers, the maximum cross-sectional area of ​​the masseter muscle determines the number of the largest masseter muscle fibers that the masseter muscle can accommodate. The larger the maximum cross-sectional area of ​​the masseter muscle, the more the masseter muscle can accommodate, and the stronger the masseter muscle is.

[0074] Therefore, based on the above analysis, the robustness coefficient of the masseter muscle on each side of the patient's cheeks was determined according to the maximum thickness and maximum cross-sectional area of ​​the masseter muscle in all the aforementioned axial ultrasound images. The larger the robustness coefficient of the masseter muscle on a certain side, the higher the degree of wear on the posterior molars on that side of the patient's cheeks, and the more significant the robustness of the masticatory muscle on that side.

[0075] In one specific implementation of this invention, the formula for calculating the strength coefficient of the masseter muscle on each side of the patient's cheeks is as follows: In the formula, The strength coefficient of the masseter muscle on each side of the patient's cheeks. It is a maximum-minimum normalization function. The maximum thickness of the masseter muscle in all axial ultrasound images of the masseter muscle on each side of the patient's cheeks. The maximum cross-sectional area of ​​the masseter muscle in all axial ultrasound images of the masseter muscle on each side of the patient's cheeks. The maximum and minimum values ​​in the calculation of the maximum-minimum normalization function are determined from the maximum and minimum values ​​of the robustness coefficient of the masseter muscle on each side of the cheeks in normal adults.

[0076] Meanwhile, each axial ultrasound image of the temporalis muscle on each side of the patient's cheeks includes the inner edge of the superficial fascia of the temporalis muscle and the inner edge of the deep fascia of the temporalis muscle. Each axial ultrasound image of the temporalis muscle on each side of the patient's cheeks is used as input to the Canny edge detection algorithm. The Canny edge detection algorithm is used to extract the edges within each axial ultrasound image of the temporalis muscle. Then, the outer and inner sides of the skin in each axial ultrasound image of the temporalis muscle are manually marked. Generally, the right side of the axial ultrasound image of the temporalis muscle is the outer side of the skin, and the left side of the axial ultrasound image of the temporalis muscle is the inner side of the skin.

[0077] The edge closest to the lateral skin in each axial ultrasound image of the temporalis muscle is taken as the inner edge of the superficial fascia of the temporalis muscle, and the edge closest to the medial skin in each axial ultrasound image of the temporalis muscle is taken as the inner edge of the deep fascia of the temporalis muscle. Therefore, the robustness coefficient of the temporalis muscle on each side of the patient's cheeks can be determined based on the inner edges of the superficial and deep fascia of the temporalis muscle.

[0078] Preferably, in some implementations of the present invention, the method for obtaining the robustness coefficient of the temporalis muscle includes:

[0079] The temporalis muscle has a relatively complex structure. Its muscle group is roughly divided into anterior, middle, and posterior fibers. The anterior fibers primarily provide the force for closing the mouth and the force during clenching, while wear on the posterior molars mainly occurs during clenching. Therefore, the strength of the temporalis muscle can be assessed based on the strength of its anterior fibers. The analysis method for the strength of the anterior fibers is the same as that for the masseter muscle; the strength of the temporalis muscle is mainly related to its maximum thickness and maximum cross-section.

[0080] Therefore, the inner edge of the superficial fascia of the temporalis muscle is taken as the upper boundary, and the inner edge of the deep fascia of the temporalis muscle is taken as the lower boundary. In the direction from the inner side of the skin to the outer side of the skin, the maximum distance between the upper and lower boundaries is taken as the thickness of the temporalis muscle in each axial ultrasound image of the temporalis muscle.

[0081] Meanwhile, the area formed by connecting the left endpoint of the upper and lower boundaries and the right endpoint of the upper and lower boundaries is taken as the temporalis muscle region, and the area of ​​the temporalis muscle region is taken as the cross-sectional area of ​​the temporalis muscle in each axial ultrasound image of the temporalis muscle.

[0082] The maximum thickness of the temporalis muscle reflects its strength; the greater the maximum thickness, the stronger the temporalis muscle. The maximum cross-sectional area of ​​the temporalis muscle determines the number of the largest anterior temporalis fibers it can accommodate; the larger the maximum cross-sectional area, the more the largest temporalis fibers it can accommodate, and the stronger the temporalis muscle.

[0083] Therefore, the robustness coefficient of the temporalis muscle on each cheek was determined based on the maximum thickness and maximum cross-sectional area of ​​the temporalis muscle in all axial ultrasound images. A higher robustness coefficient on a particular cheek indicates greater wear on the posterior molars on that side and a more significant robustness of the masticatory muscles on that side.

[0084] In one specific implementation of this invention, the formula for calculating the strength coefficient of the temporalis muscle on each side of the patient's cheeks is as follows: In the formula, The strength coefficient of the temporalis muscle on each side of the patient's cheeks. The maximum thickness of the temporalis muscle in all axial ultrasound images of the temporalis muscle on each side of the patient's cheeks. The maximum cross-sectional area of ​​the temporalis muscle in all axial ultrasound images of the temporalis muscle on each side of the patient's cheeks is defined as follows: The maximum and minimum values ​​in the calculation of the maximum-minimum normalization function are determined from the maximum and minimum values ​​of the robustness coefficient of the temporalis muscle on each side of the cheeks in normal adults.

[0085] Because the anterior fibers of the masseter and temporalis muscles work synergistically during biting, and when a patient has a severe unilateral chewing habit, the strength of both the masseter and temporalis muscles on that side will significantly increase. Therefore, based on the strength coefficients of the temporalis muscles on each side of the patient's cheeks, the product of the strength coefficients of the masseter and temporalis muscles is calculated as the strength of the masticatory muscles on each side of the patient's cheeks. Higher strength of the masticatory muscles on one side of the patient's cheeks indicates that the patient habitually uses that side to chew food, and the teeth on that side are more likely to experience more severe wear.

[0086] Preferably, in some implementations of the present invention, the method for obtaining the average wear level includes:

[0087] When mirroring a patient's missing teeth, the most significant factor affecting the mirroring effect is the asymmetry in the wear of the teeth on both cheeks. This asymmetry can disrupt the occlusal relationship of the upper and lower jaws at the site of the missing tooth, so it is necessary to quantify the wear degree of the molars. Furthermore, the main functional structures of molars include cusps and ridges. The cusps are responsible for piercing the surface of food, while the ridges are responsible for grinding the food after piercing. Therefore, the wear characteristics of molars are mainly manifested in the cusps and ridges. The more severe the wear of the molars, the lower the sharpness of the cusps and ridges, and the smoother the occlusal surface of the molars.

[0088] Since the occlusal surface of a molar is a three-dimensional curved surface, assessing its flatness requires converting the three-dimensional surface into a two-dimensional curve to extract more accurate data for the analysis of each molar. Simultaneously, each molar possesses a clinical crown-long axis. Rotating around this axis as the central axis reveals the curve changes of the cusps and ridges in a plane, including the occlusal surface curve. This curve can also reflect the sharpness of the cusps and ridges, used to assess the degree of wear on posterior teeth.

[0089] To accurately analyze the cusp sharpness and occlusal surface flatness of each molar, in the three-dimensional digital model of the dental arch, the crown-long axis of each molar is obtained using oral CAD software via the highest buccal and lingual points and the cervical reference point. Using this crown-long axis as the central axis, the tooth is rotated along a predetermined direction. After each predetermined rotation, the intersection line between the longitudinal section of the molar and the surface of the molar is obtained, until a full rotation is completed. The set of all these intersection lines is considered as the intersection line set, which consists of a discrete point array. The predetermined direction can be clockwise or counterclockwise. In one specific implementation of this invention, the predetermined direction is clockwise, and the predetermined angle is 5 degrees.

[0090] The line of intersection between the longitudinal section and the surface of the posterior teeth includes the curves on both sides of the posterior molars and the curve formed by the occlusal surface. The curves on both sides of the posterior molars are generally relatively smooth, while the curve formed by the occlusal surface often contains cusps and sockets. When the wear of the posterior molars is minor, the curve at the cusps is sharp; conversely, when the wear is significant, the curve at the cusps appears smoother compared to when there is only slight wear. Therefore, the smoothness of the curve at the cusps in the line of intersection can be used to assess the degree of wear of the posterior molars.

[0091] For each intersection line in the intersection line set, there are generally three corner points: the positions of the tooth cusps on both sides and the position of the tooth socket in the middle. Since the starting point and the ending point of the intersection line are the left and right intersection points of the crown surface and the gingiva, the intersection line is divided into two parts: the starting point to the tooth socket corner point and the tooth socket corner point to the ending point. Each part of the intersection line contains a corner point formed by a tooth cusp. Corner point detection is performed on each part of the intersection line after the division to obtain the target corner point in each part of the intersection line, which represents the corner point formed by the tooth cusp position.

[0092] The straight line connecting the two nearest discrete points on either side of the target corner is taken as the cusp tangent. The sum of the measured distances between all discrete points in each part of the intersection and the cusp tangent is calculated as the sharpness of the cusp in each part of the intersection. The measured distance is the Euclidean distance. The sharpness of the cusp reflects the sharpness of the cusp on one side of the posterior molar; the larger the measured distance, the sharper the cusp.

[0093] Therefore, by combining the sharpness of the cusps on the other side of the molar, the sum of the sharpness of the cusps in the two intersecting lines after bisection is calculated as the cusp sharpness assessment value for each intersecting line. The larger the cusp sharpness assessment value, the greater the sharpness of the cusps reflected in the intersecting line.

[0094] Since the portion between the two cusps in the intersection line is the intersection of the occlusal surface and the plane, the higher the wear of the molar, the flatter the curve between the two cusps, approaching a straight line. Therefore, the occlusal surface flatness assessment value of each intersection line can be determined based on the straight line connecting the two target corner points in the two bisected intersection lines.

[0095] Preferably, in some implementations of the present invention, the method for obtaining the occlusal surface flatness evaluation value includes:

[0096] The higher the wear of the molars, the flatter the curve between the two cusps, approaching a straight line. Therefore, the straight line connecting the two target corner points in the intersection of the two bisecting parts is taken as the corner line. If the metric distance between all discrete points in the intersection and the corner line is smaller, it indicates that the corner line is closer to a straight line, representing a higher degree of flatness of the occlusal surface between the two cusps.

[0097] Therefore, the sum of the metric distances between the lines connecting all discrete points and corner points in the intersection line is calculated as the occlusal surface flatness evaluation value for each intersection line. The metric distance is the Euclidean distance; the smaller the occlusal surface flatness evaluation value, the greater the flatness of the occlusal surface reflected in the intersection line.

[0098] Since the wear of posterior molars is a holistic process, there is no situation where the cusps are highly sharp while the occlusal surface is relatively flat. Therefore, there is a correlation between the sharpness of the cusps and the flatness of the occlusal surface. The wear degree of posterior molars at all surface intersections can be calculated by summing the products of the cusp sharpness assessment value and the occlusal surface flatness assessment value.

[0099] Therefore, the wear assessment value for each posterior molar is determined based on the cusp sharpness assessment value and occlusal surface flatness assessment value for all the aforementioned intersection lines. The wear assessment value reflects the degree of wear of each posterior molar; a higher wear assessment value indicates a greater degree of wear on each posterior molar.

[0100] Then, the mean of the wear assessment values ​​of all posterior molars on each cheek of the patient was calculated as the average wear degree on each cheek of the patient, which was used to characterize the average level of wear degree of posterior molars on each cheek of the patient.

[0101] In one specific implementation of this invention, the method for calculating the wear assessment value of each posterior molar is as follows: In the formula, The wear assessment value for each posterior molar is given. It is an exponential function with the natural constant as its base. The preset scaling factor is 0.5. The number of intersection lines in the intersection line set. The cusp sharpness assessment value for the intersection line described in the i-th clause. The flatness evaluation value of the interlocking surface of the i-th intersection line.

[0102] In the formula for wear assessment, the cusp sharpness assessment value and the occlusal surface flatness assessment value decrease as the wear of the posterior molar increases. The smaller the product of the cusp sharpness assessment value and the occlusal surface flatness assessment value, the greater the wear of the posterior molar.

[0103] Preferably, in some implementations of the embodiments of the present invention, the method for obtaining the regression equation includes:

[0104] For two different patients, when the strength of the masticatory muscles on one side is the same, the average wear of the molars on that side tends to be similar. Therefore, there is a deterministic regression relationship between the strength of the masticatory muscles and the average wear of the molars. Thus, a pre-defined population sample database is constructed, containing data on the strength of the masticatory muscles on each cheek of a large sample population and the corresponding average wear data of the teeth. This sample population covers different ages, genders, and chewing habits. Using the strength data in the population sample database as the independent variable and the corresponding average wear data as the dependent variable, a linear regression method is used to obtain the regression equation between the strength of the masticatory muscles and the average wear. This regression equation includes the regression equation between the strength of the masticatory muscles on the edentulous side of the patient's cheek and the average wear, used to characterize the deterministic regression relationship between the strength of the masticatory muscles and the average wear of the molars.

[0105] Preferably, in some implementations of the embodiments of the present invention, the method for obtaining the coordination coefficient includes:

[0106] The regression equation can characterize the deterministic regression relationship between the strength of the masticatory muscles on the edentulous side of the patient's cheeks and the average wear of the molars. Therefore, the predicted average wear of the edentulous side of the patient's cheeks can be predicted by using the regression equation corresponding to the edentulous side of the patient's cheeks and the strength of the masticatory muscles on the edentulous side of the patient's cheeks.

[0107] Therefore, the robustness of the masticatory muscles on the edentulous side of the patient's cheeks is calculated, and the current robustness of the masticatory muscles on the edentulous side of the patient's cheeks is used as the input to the regression equation of the current robustness of the masticatory muscles on the edentulous side of the patient's cheeks and the average wear degree, so as to calculate the predicted average wear degree on the edentulous side of the patient's cheeks.

[0108] If the wear of the corresponding tooth on the mirror side is highly coordinated with the wear of the tooth on the side with the missing tooth, the difference between the actual wear of the missing tooth measured after mirroring and the predicted average wear is small; if the difference between the actual wear of the missing tooth measured after mirroring and the predicted average wear is large, it indicates that the wear of the posterior molars on both cheeks of the patient has seriously affected the coordination.

[0109] Therefore, a coarse mirror image of the corresponding tooth on the opposite side of the missing tooth is projected onto the edentulous area. The actual average wear degree on the edentulous side after the coarse mirror image is then calculated. Based on the predicted average wear degree and the actual average wear degree, a coordination coefficient is obtained between the edentulous side and the opposite side. This coordination coefficient reflects the asymmetry of wear degree between the edentulous side and the opposite side; the larger the coordination coefficient, the more significant the asymmetry of wear degree between the edentulous side and the opposite side.

[0110] In one specific implementation of this invention, the coordination coefficient is calculated as follows: In the formula, This refers to the coordination coefficient between the edentulous side and the contralateral side of the patient. This represents the predicted average wear on the edentulous sides of the patient's cheeks. This represents the actual average wear on the side of the patient with missing teeth after coarse mirror imaging.

[0111] In the formula for the coordination coefficient, the larger the absolute difference between the predicted average wear degree and the actual average wear degree, the more uncoordinated the wear degree between the edentulous side and the contralateral side. The predicted average wear degree in the denominator is for normalization. The range of the coordination coefficient is [0, 1]. The closer the coordination coefficient is to 0, the better the coordination of the wear degree between the edentulous side and the contralateral side.

[0112] Preferably, in some implementations of the present invention, the method for determining whether correction is needed includes:

[0113] If the coordination coefficient is less than or equal to a preset first threshold, it indicates that the coordination of wear between the patient's edentulous side and the contralateral side is reasonable. In this case, no correction is needed for the contralateral tooth with the same name as the missing tooth, and the contralateral tooth with the same name can be used directly as a mirror model of the missing tooth. If the coordination coefficient is greater than the preset first threshold, it indicates that the coordination of wear between the patient's edentulous side and the contralateral side is poor. In this case, correction is needed for the contralateral tooth with the same name as the missing tooth. The preset first threshold is set to 0.2.

[0114] Preferably, in some implementations of the present invention, the method for obtaining the wear correction coefficient includes:

[0115] When the coordination coefficient is too large, the coordination of the wear degree between the missing tooth side and the opposite side is too low. It is necessary to analyze the reasons for the low coordination of the wear degree between the missing tooth side and the opposite side. The reasons can generally be divided into two situations: one is that the patient has a serious unilateral chewing problem, which leads to the lack of coordination of the wear degree between the missing tooth side and the opposite side; the other is that the missing tooth is caused by the missing tooth, and the adjacent tooth of the missing tooth is tilted, which leads to the value of the calculated wear degree being too large, thus making the wear degree between the missing tooth side and the opposite side uncoordinated.

[0116] Simultaneously, before correcting the contralateral tooth with the missing tooth, it is necessary to estimate the theoretical wear degree of the missing tooth by assessing the strength of the masticatory muscles on the edentulous side. This theoretical wear degree characterizes the wear degree of the missing tooth under ideal conditions. Then, using the theoretical wear degree of the missing tooth, the wear degree correction coefficient of the contralateral tooth with the same name is accurately determined. A larger wear degree correction coefficient indicates that the wear degree of the contralateral tooth with the same name is excessive, requiring correction of the cusps and marginal ridge areas on the crown surface of the contralateral tooth with the same name.

[0117] Therefore, the theoretical wear degree of the missing tooth is inferred based on the strength of the masticatory muscles on the side of the missing tooth. Specifically, based on the regression equation and the strength of the masticatory muscles on the side of the missing tooth in the current patient's cheeks, the predicted average wear degree on the side of the missing tooth in the current patient's cheeks is predicted. The product of the predicted average wear degree and the number of molars on the side of the missing tooth in the current patient's cheeks is taken as the cumulative wear degree on the side of the missing tooth in the current patient's cheeks. The wear assessment value of all molars present on the side of the missing tooth in the current patient's cheeks is subtracted from the cumulative wear degree to obtain the theoretical wear degree of the missing tooth.

[0118] Theoretical wear can be used to adjust mirrored teeth, making their wear more consistent. The wear assessment value of the contralateral tooth with the missing tooth can be directly calculated. A wear correction coefficient can be obtained from the wear assessment value of the contralateral tooth with the missing tooth and the theoretical wear of the missing tooth. Therefore, the wear assessment value of the contralateral tooth with the missing tooth is calculated, and the wear correction coefficient is determined based on this value and the theoretical wear of the missing tooth. A larger wear correction coefficient indicates a higher degree of wear on the contralateral tooth with the missing tooth.

[0119] In one specific implementation of this invention, the wear correction coefficient is calculated as follows: In the formula, This is the wear correction factor for the contralateral tooth of the same name. The wear assessment value is for the contralateral tooth with the same name that is missing. This represents the theoretical wear and tear of a missing tooth.

[0120] Preferably, in some implementations of the present invention, the method for reconstructing the morphology of missing teeth includes:

[0121] Tooth wear is caused by the patient's daily habits and is a physiological wear. It can be corrected by using the Laplace smoothing algorithm or morphological dilation to correct the contralateral tooth of the missing tooth.

[0122] Therefore, if the wear correction coefficient of the contralateral tooth is less than or equal to the preset second threshold, it indicates that the wear degree of the contralateral tooth is less than the theoretical wear degree of the missing tooth, meaning the wear degree of the contralateral tooth is relatively small. The Laplace smoothing algorithm can then be used to correct the wear degree of the contralateral tooth of the missing tooth, making it closer to the theoretical wear degree of the missing tooth. The preset second threshold is set to 1.

[0123] If the wear correction coefficient of the contralateral tooth is greater than the preset second threshold, it means that the wear degree of the contralateral tooth is greater than the theoretical wear degree of the missing tooth, that is, the wear degree of the contralateral tooth is larger. Then, morphological expansion is used to correct the contralateral tooth of the missing tooth on the cusp and marginal ridge area of ​​the crown surface, so that the wear degree of the contralateral tooth approaches the theoretical wear degree of the missing tooth.

[0124] After correcting the contralateral tooth with the same name that is missing, the morphology of the missing tooth is reconstructed based on the corrected contralateral tooth with the same name.

[0125] Preferably, in some implementations of the present invention, the method for reconstructing the morphology of missing teeth includes:

[0126] (1) The three-dimensional digital model of the dental arch corresponding to the patient's oral cavity includes the mandibular model and the maxillary and mandibular models. The best fitting symmetry plane is obtained by automatic surface matching in the mandibular model. Then, the corresponding tooth on the opposite side of the corrected missing tooth is mirrored to the missing tooth using the best fitting symmetry plane as the mirror reference.

[0127] (2) Construct a digital virtual patient based on the three-dimensional data of the maxilla and the three-dimensional data of the repaired mandible, and keep the upper and lower teeth in an occlusal state in the digital virtual patient.

[0128] (3) Finally, observe whether there is a gap or penetration at the occlusion of the mirror tooth and the maxillary tooth in the model. If there is a gap, adjust the overall height of the mirror tooth upward; otherwise, adjust the height of the tooth downward to ensure that the mirrored tooth meets the requirement of extensive contact of the bilateral posterior molars when the cusps interlock.

[0129] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0130] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A method for intelligent reconstruction of missing tooth morphology based on contralateral tooth mirror transformation, characterized in that, The method includes the following steps: Acquire axial ultrasound images of each posterior molar on each side of the patient's cheeks, as well as axial ultrasound images of the masseter muscle and temporalis muscle on each side of the patient's cheeks from the three-dimensional digital model of the dental arch corresponding to the patient's oral cavity. Based on the axial ultrasound images of the masseter muscle and the temporalis muscle, the robustness characteristics of the masseter and temporalis muscles were analyzed to determine the robustness of the masticatory muscles on each side of the patient's cheeks. The sharpness of the cusps and the flatness of the occlusal surface of each molar are analyzed to determine the average wear degree on each cheek of the patient. Based on the average wear degree and the robustness, a regression equation is constructed for the average wear degree and the robustness. The regression equation is used to predict the predicted average wear degree on the edentulous cheek of the current patient. Based on the predicted average wear degree, the coordination coefficient between the edentulous cheek and the contralateral cheek is obtained. Based on the coordination coefficient between the side with missing teeth and the opposite side, it is determined whether the corresponding tooth on the opposite side of the missing tooth needs to be corrected. If correction is required, the theoretical wear degree of the missing tooth is estimated based on the strength of the masticatory muscles on the side with missing teeth, and the wear degree correction coefficient of the corresponding tooth on the opposite side is determined. The morphology of the missing tooth is reconstructed using the wear degree correction coefficient of the corresponding tooth on the opposite side of the missing tooth. The method for obtaining the coordination coefficient includes: The robustness of the masticatory muscles on the edentulous side of the patient's cheeks is calculated, and the current robustness of the masticatory muscles on the edentulous side of the patient's cheeks is used as the input of the regression equation to calculate the predicted average wear on the edentulous side of the patient's cheeks. A coarse mirror image of the corresponding tooth on the opposite side of the missing tooth is made to the missing tooth location, and then the actual average wear on the patient's missing tooth side is calculated after the coarse mirror image. Based on the predicted average wear degree and the actual average wear degree, the coordination coefficient between the patient's edentulous side and the contralateral side is obtained; The method for obtaining the wear correction coefficient includes: The theoretical wear degree of the missing tooth is inferred based on the strength of the masticatory muscle on the side of the missing tooth, and the wear assessment value of the corresponding tooth on the opposite side of the missing tooth is calculated. Based on the wear assessment value of the corresponding tooth on the opposite side of the missing tooth and the theoretical wear degree of the missing tooth, the wear degree correction coefficient of the corresponding tooth on the opposite side is determined.

2. The intelligent reconstruction method for missing tooth morphology based on contralateral tooth mirror transformation according to claim 1, characterized in that, The methods for determining the robustness include: Each axial ultrasound image of the masseter muscle on each side of the patient's cheeks includes the inner edge of the superficial fascia of the masseter muscle and the inner edge of the deep fascia of the masseter muscle. The inner edge of the superficial fascia of the masseter muscle is used as the upper boundary, and the inner edge of the deep fascia of the masseter muscle is used as the lower boundary. The maximum metric distance between the upper and lower boundaries is used as the thickness of the masseter muscle in each axial ultrasound image of the masseter muscle, and the area between the upper and lower boundaries is used as the cross-sectional area of ​​the masseter muscle in each axial ultrasound image of the masseter muscle. Based on the maximum thickness and maximum cross-sectional area of ​​the masseter muscle in all axial ultrasound images of the masseter muscle, the robustness coefficient of the masseter muscle on each side of the patient's cheeks was determined. Each axial ultrasound image of the temporalis muscle on each side of the patient's cheeks includes the inner edge of the superficial fascia of the temporalis muscle and the inner edge of the deep fascia of the temporalis muscle. Based on the inner edge of the superficial fascia of the temporalis muscle and the inner edge of the deep fascia of the temporalis muscle, the robustness coefficient of the temporalis muscle on each side of the patient's cheeks is determined. The product of the robustness coefficient of the masseter muscle and the robustness coefficient of the temporalis muscle is calculated as the robustness of the masticatory muscles on each side of the patient's cheeks.

3. The intelligent reconstruction method for missing tooth morphology based on contralateral tooth mirror transformation according to claim 2, characterized in that, The methods for obtaining the strength coefficient of the temporalis muscle include: The thickness and cross-sectional area of ​​the temporalis muscle in each axial ultrasound image are determined based on the inner edges of the superficial and deep fascia of the temporalis muscle. The robustness coefficient of the temporalis muscle on each side of the patient's cheeks was determined based on the maximum thickness and maximum cross-sectional area of ​​the temporalis muscle in all axial ultrasound images of the temporalis muscle.

4. The intelligent reconstruction method for missing tooth morphology based on contralateral tooth mirror transformation according to claim 1, characterized in that, The method for obtaining the average wear level includes: With the crown major axis of each posterior molar as the central axis, rotate along a predetermined direction of the circumference. After each rotation by a predetermined angle, obtain the intersection line between the longitudinal section of the posterior molar and the surface of the posterior molar. Stop after one full rotation. The set of all the intersection lines is taken as the intersection line set; the intersection line is composed of a discrete point sequence. For each intersection line in the intersection line set, the intersection line is divided into two equal parts, and corner point detection is performed on each part of the intersection line to obtain the target corner point in each part of the intersection line; The straight line connecting the two nearest discrete points on both sides of the target corner point is taken as the cusp tangent. The sum of the measured distances between all discrete points in each part of the intersection line and the cusp tangent line is calculated as the sharpness of the cusp point in each part of the intersection line. The sum of the sharpness of the cusps in the two intersecting lines after bisection is calculated as the cusp sharpness assessment value for each intersecting line; Based on the straight line connecting the two target corner points in the intersection line of the two parts after bisection, determine the flatness evaluation value of the interlocking surface of each intersection line; The wear assessment value of each posterior molar is determined based on the cusp sharpness assessment value and occlusal surface flatness assessment value of all the aforementioned intersections; the average wear degree of each cheek is calculated based on the wear assessment values ​​of all posterior molars on each cheek of the patient.

5. The intelligent reconstruction method for missing tooth morphology based on contralateral tooth mirror transformation according to claim 4, characterized in that, The method for obtaining the occlusal surface flatness assessment value includes: The straight line connecting the two target corner points in the intersection line after the two parts are divided into two equal parts is taken as the corner point line. The sum of the measured distances between all discrete points in the intersection line and the corner point line is calculated as the flatness evaluation value of the biting surface of each intersection line.

6. The intelligent reconstruction method for missing tooth morphology based on contralateral tooth mirror transformation according to claim 1, characterized in that, The methods for obtaining the regression equation include: A pre-defined population sample database is constructed, which includes data on the strength of the masticatory muscles on each side of the cheeks of the sample population and the average wear of the corresponding teeth. Using the strength data in the population sample database as the independent variable and the average wear of the corresponding teeth in the population sample database as the dependent variable, a linear regression method is used to obtain the regression equation between the strength of the masticatory muscles and the average wear.

7. The intelligent reconstruction method for missing tooth morphology based on contralateral tooth mirror transformation according to claim 1, characterized in that, The methods for determining whether correction is needed include: If the coordination coefficient is less than or equal to a preset first threshold, then no correction is needed for the contralateral tooth of the missing tooth; if the coordination coefficient is greater than the preset first threshold, then correction is needed for the contralateral tooth of the missing tooth.

8. The intelligent reconstruction method for missing tooth morphology based on contralateral tooth mirror transformation according to claim 1, characterized in that, The intelligent reconstruction method for missing tooth morphology includes: If the wear correction coefficient of the contralateral tooth is less than or equal to a preset second threshold, the Laplace smoothing algorithm is used to correct the contralateral tooth of the missing tooth. If the wear correction coefficient of the contralateral tooth is greater than the preset second threshold, morphological expansion is used to correct the contralateral tooth with missing teeth for the cusp and marginal ridge area on the crown surface. After correcting the contralateral tooth with the same name that is missing, the morphology of the missing tooth is reconstructed based on the corrected contralateral tooth with the same name.

Images