Orthodontic treatment monitoring method, apparatus, device, and storage medium

Abstract

Embodiments of the present disclosure relate to an orthodontic treatment monitoring method, device, equipment and storage medium, wherein the orthodontic treatment monitoring method comprises: acquiring a first dental arch model of a user at a current time; performing tooth separation processing on the first dental arch model to obtain a first digital dental arch model, wherein the first digital dental arch model comprises a first tooth model of at least one target tooth; for each target tooth, determining a deviation value between the first tooth model of the target tooth and a second tooth model of the target tooth, wherein the second tooth model is a tooth model of the tooth before the current time. According to the embodiments of the present disclosure, automatic comparison of the first tooth model and the second tooth model can be realized, thereby improving the orthodontic treatment monitoring efficiency.

Description

Technical Field

[0001] This disclosure relates to the field of computer technology, and in particular to a method, apparatus, device, and storage medium for monitoring orthodontic treatment. Background Technology

[0002] Orthodontic treatment involves periodically wearing braces to guide the teeth to grow in the direction designed by the braces, thereby gradually changing the position and posture of the teeth.

[0003] Currently, orthodontic treatment monitoring during the treatment process mainly relies on patients visiting the clinic regularly for checkups. Doctors visually assess the orthodontic progress at each stage of treatment. If the doctor finds that the orthodontic results are not developing in the direction planned, adjustments to the braces are necessary to ensure the smooth progress of treatment. However, this method of orthodontic treatment monitoring is inefficient and cannot meet the needs of users. Summary of the Invention

[0004] In order to solve the above-mentioned technical problems, or at least partially solve the above-mentioned technical problems, the present disclosure provides an orthodontic treatment monitoring method, device, equipment and storage medium.

[0005] A first aspect of this disclosure provides a method for monitoring orthodontic treatment, the method comprising:

[0006] Obtain the user's first dental model at the current moment;

[0007] The first dental model is processed by tooth segmentation to obtain a first digital dental model, wherein the first digital dental model includes a first tooth model of at least one target tooth;

[0008] For each target tooth, determine the deviation value between the first tooth model and the second tooth model of the target tooth, where the second tooth model is the tooth model of the tooth before the current time.

[0009] A second aspect of this disclosure provides an orthodontic treatment monitoring device, the device comprising:

[0010] The acquisition module is used to acquire the user's first dental model at the current moment;

[0011] The tooth segmentation module is used to segment the first dental model to obtain a first digital dental model, wherein the first digital dental model includes a first tooth model of at least one target tooth.

[0012] The determination module is used to determine the deviation value between the first tooth model and the second tooth model of the target tooth for each target tooth, wherein the second tooth model is the tooth model of the tooth before the current time.

[0013] A third aspect of this disclosure provides an electronic device comprising: a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the method described in the first aspect.

[0014] A fourth aspect of this disclosure provides a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the method of the first aspect described above.

[0015] The technical solution provided in this disclosure has the following advantages compared with the prior art:

[0016] The orthodontic treatment monitoring method, apparatus, device, and storage medium provided in this disclosure can acquire a first dental model of the user at the current moment, and perform tooth segmentation processing on the first dental model to obtain a first digital dental model. The first digital dental model includes a first tooth model of at least one target tooth. For each target tooth, the deviation value between the first tooth model and a second tooth model of the target tooth is determined, where the second tooth model is a tooth model of the tooth before the current moment. Using the above technical solution, automatic comparison between the first and second tooth models can be achieved. Compared with traditional visual comparison by doctors, the deviation value between the first and second tooth models can be obtained conveniently, quickly, and accurately, thus improving the efficiency of orthodontic treatment monitoring. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0018] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart of an orthodontic treatment monitoring method provided in an embodiment of this disclosure;

[0020] Figure 2 This is a flowchart of another orthodontic treatment monitoring method provided in this embodiment;

[0021] Figure 3 This is a schematic diagram of the structure of an orthodontic treatment monitoring device provided in an embodiment of this disclosure;

[0022] Figure 4 This is a schematic diagram of the structure of an electronic device according to an embodiment of this disclosure. Detailed Implementation

[0023] To better understand the above-mentioned objectives, features, and advantages of this disclosure, the solutions disclosed herein will be further described below. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0024] Numerous specific details are set forth in the following description in order to provide a full understanding of this disclosure, but this disclosure may also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only some, and not all, of the embodiments of this disclosure.

[0025] Figure 1 This is a flowchart illustrating an orthodontic treatment monitoring method provided in this disclosure, which can be executed by an electronic device. This electronic device can be exemplarily understood as a device with page display capabilities, such as a mobile phone, tablet computer, laptop computer, desktop computer, or smart TV. Figure 1 As shown, the method provided in this embodiment includes the following steps:

[0026] S110. Obtain the user's first dental model at the current moment.

[0027] In this embodiment of the disclosure, in order to monitor the user's orthodontic treatment, the electronic device needs to acquire the user's current dental model, i.e., the first dental model.

[0028] Specifically, the first dental model includes a complete three-dimensional model of all upper teeth in the user's mouth at the current moment, and / or a complete three-dimensional model of all lower teeth in the user's mouth.

[0029] The specific representation of the first jaw model may include a three-dimensional point cloud model, a three-dimensional mesh model, etc., which are not limited here.

[0030] Specifically, there are various ways to obtain the first jaw model. Typical examples are described below, but they do not constitute a limitation of this application.

[0031] For example, a first dental model can be obtained using a dental scanner. For instance, an intraoral scanner can be used to scan the corresponding area within the user's mouth, directly generating and saving the user's first dental model. Preferably, a dental scanner with scanning accuracy down to the micrometer level is used. Alternatively, a first dental model can be obtained directly using cone-beam computed tomography (CT). However, this method is not the only option.

[0032] S120. Perform tooth segmentation processing on the first dental model to obtain a first digital dental model, wherein the first digital dental model includes a first tooth model of at least one target tooth.

[0033] In this embodiment of the disclosure, in order to perform adjustment operations such as moving and rotating any tooth in the first dental model to achieve individual alignment of the same tooth in the first dental model and the second dental model and thus determine the deviation value, the electronic device needs to perform tooth separation processing on the first dental model to obtain the first digital dental model.

[0034] Specifically, the first digital dental model includes a first tooth model for each tooth, and each first tooth model is an independent model. It should be noted that the first digital dental model only includes the first tooth model for each tooth and does not include non-tooth parts such as alveolar bone.

[0035] Specifically, the target teeth are those that require monitoring during orthodontic treatment.

[0036] Specifically, the tooth segmentation process here can be performed manually to identify and segment each tooth in the first jaw model, or the tooth identification model of each tooth can be obtained by first identifying the teeth in the first jaw model through a model object recognition algorithm, and then the tooth identification model of each tooth can be segmented by a model segmentation algorithm to obtain the first tooth model of each tooth. Each first tooth model is an independent model.

[0037] S130. For each target tooth, determine the deviation value between the first tooth model and the second tooth model of the target tooth.

[0038] In this embodiment of the disclosure, the electronic device can pre-store a second digital dental model, which includes a second tooth model for each tooth. Thus, for each target tooth that requires orthodontic treatment monitoring, the deviation value between the first tooth model and the second tooth model of the target tooth can be determined.

[0039] Specifically, the second dental model includes a complete three-dimensional model of all upper teeth in the user's mouth up to the current moment, and / or a complete three-dimensional model of all lower teeth in the user's mouth. "Up to the current moment" can refer to any point in time prior to the current moment, such as before treatment or after the last treatment, but is not limited to this.

[0040] The specific representation of the second jaw model can include a three-dimensional point cloud model, a three-dimensional mesh model, etc., and is not limited here.

[0041] Specifically, by performing tooth segmentation on the second dental model, a second digital dental model can be obtained. The tooth segmentation method for the second dental model is similar to that for the first dental model, and will not be elaborated here. It should be noted that the second digital dental model only includes the second tooth model for each tooth, excluding non-tooth parts such as alveolar bone.

[0042] The second digital dental model includes a second tooth model for each tooth, and the second tooth model for each tooth is an independent model.

[0043] Specifically, the deviation value is the difference between the first tooth model and the second tooth model of the same tooth. This difference can include differences in position, posture, etc. Accordingly, the deviation value can include parameters such as position deviation and posture deviation.

[0044] Specifically, there are several ways to determine the deviation value. The following are typical examples, but are not limited to these.

[0045] In some embodiments, S130 may include: for each target tooth, directly registering the first tooth model and the second tooth model of the target tooth to obtain the transformation matrix corresponding to the target tooth, and determining the deviation value based on the transformation matrix corresponding to the target tooth, thereby obtaining the deviation value corresponding to each target tooth.

[0046] Those skilled in the art can use any possible registration algorithm to register the first tooth model and the second tooth model; no limitation is made here.

[0047] Specifically, the transformation matrix includes translation and rotation matrices. The specific calculation process and methods for determining the deviation value based on the transformation matrix are not specified here.

[0048] It is understandable that, because the embodiments of this disclosure can automatically compare the first and second tooth models and obtain quantitative comparison results (i.e., deviation values), compared with traditional visual comparison by doctors, it can reduce the burden on doctors, increase the comparison speed, reduce confusion and misjudgment, and detect some minor deviations that are not easily detected by the naked eye, thereby improving the accuracy of the comparison results. Therefore, the embodiments of this disclosure can conveniently, quickly, and accurately obtain the deviation values ​​between the first and second tooth models, thereby improving the efficiency of orthodontic treatment monitoring. Furthermore, the embodiments of this disclosure achieve full digitalization. If the user's first and second digital dental models, and the deviation values ​​of each target tooth in the first dental model, are subsequently transmitted via the Internet or other means to doctors located in different geographical locations for review, the user can receive advice and guidance from expert doctors in different geographical locations during dental diagnosis or follow-up visits. This allows expert doctors to provide professional services to a wider range of patients without geographical constraints, and also greatly facilitates doctors' tracking and monitoring of the patient's treatment process, further contributing to the timely advancement, adjustment, and improvement of treatment plans.

[0049] This embodiment of the disclosure can acquire a user's first dental model and perform tooth segmentation processing on the first dental model to obtain a first digital dental model. The first digital dental model includes a first tooth model of at least one target tooth. For each target tooth, the deviation value between the first tooth model and a second tooth model is determined, where the second tooth model is a tooth model of the tooth at a time prior to the current moment. Using this technical solution, automatic comparison between the first and second tooth models can be achieved. Compared to traditional visual comparison by doctors, this method allows for convenient, quick, and accurate acquisition of the deviation value between the first and second tooth models, thus improving the efficiency of orthodontic treatment monitoring.

[0050] In another embodiment of this disclosure, a first dental model is subjected to tooth segmentation processing to obtain a first digital dental model, including:

[0051] S121. Perform tooth identification on the first jaw model to obtain a tooth identification model for each tooth.

[0052] Specifically, tooth identification is performed on each tooth in the first dental model. This tooth identification process can be done manually by selecting the identification bounding box; alternatively, a 3D object recognition algorithm can be used to identify the first dental model, thereby obtaining a tooth identification model for each tooth. For example, a trained neural network model capable of identifying individual teeth from a 3D dental model can be used for identification. However, it is not limited to these methods.

[0053] S122. Perform model segmentation on the tooth recognition model of each tooth in the first dental model to obtain the first tooth model of each tooth, thereby obtaining the first digital dental model.

[0054] Specifically, each tooth in the first dental model is segmented to obtain a first digital dental model. Each tooth in this first digital dental model is an independent model. This step segments each tooth identification model identified in S122. This segmentation process can be manual; alternatively, a 3D object segmentation algorithm can be used to segment each tooth in the first dental model to obtain the first digital dental model. For example, a trained neural network model capable of segmenting each tooth from a 3D tooth model can be used. However, this is not the only option.

[0055] Understandably, by performing tooth recognition and model segmentation on the first dental model, a first digital dental model can be obtained that allows for individual rotation and translation of each tooth. This facilitates the subsequent alignment of the first and second dental models to obtain deviation values. Furthermore, obtaining the first digital dental model through the two steps of tooth recognition and model segmentation makes the acquisition of the first digital dental model simple and easy to implement, which helps to reduce the difficulty of orthodontic monitoring and treatment.

[0056] Figure 2 This is a flowchart of another orthodontic treatment monitoring method provided in this disclosure. This disclosure optimizes the above embodiments and can be combined with various optional solutions from one or more of the above embodiments.

[0057] like Figure 2 As shown, this orthodontic treatment monitoring method may include the following steps.

[0058] S210, Obtain the user's first dental model at the current moment.

[0059] Specifically, S210 is similar to S110, and will not be described in detail here.

[0060] S220. Perform tooth segmentation processing on the first dental model to obtain a first digital dental model, wherein the first digital dental model includes a first tooth model of at least one target tooth.

[0061] Specifically, S220 is similar to S120, and will not be described in detail here.

[0062] S230. Register the first digital dental model and the user's second digital dental model to obtain the overall transformation matrix.

[0063] Specifically, registration involves obtaining the transformation matrix (i.e., rotation and translation matrix) between two 3D models to merge 3D models in different coordinate systems into a unified coordinate system, thereby achieving the alignment of the two 3D models.

[0064] In this embodiment of the disclosure, the first digital dental model and the second digital dental model are registered, that is, the two are aligned to obtain a transformation matrix (i.e., the overall transformation matrix) that merges the two into a unified coordinate system.

[0065] Those skilled in the art can use any possible registration algorithm to register the first digital dental model and the second digital dental model, such as coarse registration algorithms, or fine registration algorithms such as Iterative Closest Point (ICP) algorithm, Non-rigid Iterative Closest Point (NICP) algorithm, etc., but are not limited to these.

[0066] Specifically, as mentioned above, the first dental model includes a three-dimensional model of all upper teeth in the user's mouth at the current moment (referred to as the first maxillary model) and / or a three-dimensional model of all lower teeth in the user's mouth (referred to as the first mandibular model). Correspondingly, the first digital dental model includes the first digital maxillary model corresponding to the first maxillary model and / or the first digital mandibular model corresponding to the first mandibular model. The second digital dental model includes the second digital maxillary model corresponding to the second maxillary model and / or the second digital mandibular model corresponding to the second mandibular model.

[0067] In some embodiments, if the first dental model includes only the first maxillary model or the first mandibular model, then the first digital maxillary model and the second digital maxillary model are registered to obtain an overall transformation matrix; or, the first digital mandibular model and the second digital mandibular model are registered to obtain an overall transformation matrix.

[0068] In other embodiments, if the first dental model includes a first maxillary model and a first mandibular model, the first digital dental model and the second digital dental model can be directly registered to obtain an overall transformation matrix; alternatively, the first digital maxillary model and the second digital maxillary model can be registered to obtain an overall transformation matrix corresponding to the maxilla, which serves as the overall transformation matrix corresponding to the target tooth located on the maxilla; and the first digital mandibular model and the second digital mandibular model can be registered to obtain an overall transformation matrix corresponding to the mandible, which serves as the overall transformation matrix corresponding to the target tooth located on the mandible.

[0069] S240. For each target tooth, continue to register the first tooth model of the target tooth in the first digital dental model and the second tooth model of the target tooth in the second digital dental model to obtain the single tooth transformation matrix corresponding to the target tooth.

[0070] Specifically, after registering the first digital dental model and the user's second digital dental model, the first and second tooth models of each tooth have been initially aligned. To further align the first and second tooth models of each target tooth, on the basis of the initial alignment, the first and second tooth models of each target tooth can be registered to obtain a transformation matrix (i.e., a single-tooth transformation matrix) that merges the first and second tooth models of the target tooth into a unified coordinate system.

[0071] Those skilled in the art can use any possible registration algorithm to register the first digital dental model and the historical digital tooth model, such as coarse registration algorithms or fine registration algorithms such as IPC and NICP, but are not limited to these.

[0072] S250. Determine the deviation value corresponding to the target tooth based on the overall transformation matrix and the single-tooth transformation matrix corresponding to the target tooth.

[0073] Specifically, the transformation matrix typically includes a rotation matrix and a translation matrix. Therefore, the overall transformation matrix can include both an overall rotation matrix and an overall translation matrix, while the individual tooth transformation matrix can include both an individual tooth rotation matrix and an individual tooth translation matrix. Thus, for each target tooth, multiplying the overall rotation matrix and the individual tooth rotation matrix corresponding to that target tooth yields the rotation matrix, and multiplying the overall translation matrix and the individual tooth translation matrix yields the translation matrix. Based on the rotation and translation matrices corresponding to that target tooth, the positional and orientation deviations of that target tooth in the past can be determined.

[0074] In this embodiment of the present disclosure, by registering the first digital dental model and the second digital dental model, the initial alignment of the entire teeth can be achieved. Further registration of the first and second dental models of the target teeth can achieve the further alignment of the target teeth. After the entire teeth are initially aligned uniformly, fine-tuning is performed to achieve more precise alignment of the target teeth, which can improve the alignment efficiency and thus improve the efficiency of obtaining deviation values. This is beneficial to improving the overall efficiency of orthodontic treatment monitoring.

[0075] In another embodiment of this disclosure, a first digital dental model and a user's second digital dental model are registered to obtain an overall transformation matrix, including:

[0076] S231. Perform coarse registration on the first digital dental model and the second digital dental model to obtain the first transformation matrix;

[0077] Specifically, coarse registration refers to registration when the relative poses of two 3D models are completely unknown, which can provide good initial values ​​for the transformation matrix for fine registration.

[0078] Those skilled in the art can use any possible coarse registration algorithm to perform coarse registration on the first and second digital dental models, and there are no limitations here. For example, feature-based coarse registration methods, coarse registration methods based on the random sample consensus (RANSAC) framework, etc., can be used, but are not limited to these.

[0079] S232. Continue to perform fine registration on the first and second digital dental models to obtain the second transformation matrix;

[0080] Specifically, fine registration involves calculating a more accurate transformation matrix given an initial value of the transformation matrix (which is likely already correct).

[0081] Those skilled in the art can use any possible fine registration algorithm to continue fine registration of the first and second digital dental models after coarse registration (i.e., after initial alignment), without limitation here. For example, ICP, NICP, etc. can be used, but are not limited to these.

[0082] S233. Determine the overall transformation matrix based on the first transformation matrix and the second transformation matrix.

[0083] Specifically, the first transformation matrix includes a first rotation matrix and a first translation matrix, the second transformation matrix includes a second rotation matrix and a second translation matrix, and correspondingly, the overall transformation matrix includes an overall rotation matrix and an overall translation matrix. The product of the first rotation matrix and the second rotation matrix is ​​used as the overall rotation matrix, and the product of the first translation matrix and the second translation matrix is ​​used as the overall translation matrix.

[0084] Understandably, coarse registration of the first and second digital dental models can achieve rapid initial alignment. Then, fine registration can be performed based on the initial alignment to achieve a more precise alignment. This can improve the alignment speed and accuracy of the first and second digital dental models.

[0085] In another embodiment of this disclosure, coarse registration is performed on the first digital dental model and the second digital dental model to obtain a first transformation matrix, including:

[0086] Extract feature points of preset teeth from the first digital dental model to obtain multiple first feature points; establish a first coordinate system corresponding to the first digital dental model based on the multiple first feature points; extract feature points of preset teeth from the second digital dental model to obtain multiple second feature points; establish a second coordinate system corresponding to the second digital dental model based on the multiple second feature points; determine the first transformation matrix corresponding to aligning the first coordinate system with the second coordinate system.

[0087] Specifically, the predefined teeth may include incisors, canines, and / or molars, etc., wherein the feature points of incisors may include the midpoint of the incisal edge, the feature points of canines may include the cusp, the feature points of molars may include the cusp, etc., but are not limited to these.

[0088] The number of the first feature points and the number of the second feature points can be set by those skilled in the art according to the actual situation. There is no limitation here, as long as there are more than or equal to 3.

[0089] For example, three first feature points are obtained by extracting the incisal midpoint from any incisor, the cusp from any canine, and the cusp from any molar in the first digital dental model; a first coordinate system is established based on these three first feature points. Similarly, three second feature points are obtained by extracting the incisal midpoint from any incisor, the cusp from any canine, and the cusp from any molar in the second digital dental model; a second coordinate system is established based on these three second feature points. However, this is not the only possible approach.

[0090] The first and second feature points can be extracted using any possible method; no restrictions are imposed here.

[0091] Specifically, the first and second coordinate systems can be established in any possible way, without any restrictions here.

[0092] Specifically, the first and second coordinate systems are aligned by moving the origin to coincide, aligning the X-axis of the first coordinate system with the X-axis of the second coordinate system, aligning the Y-axis of the first coordinate system with the Y-axis of the second coordinate system, and aligning the Z-axis of the first coordinate system with the Z-axis of the second coordinate system. Aligning the first and second coordinate systems yields the first transformation matrix.

[0093] Understandably, the aforementioned method for coarse registration of the first and second digital dental models is logically simple and easy to implement, which helps reduce the difficulty of coarse registration. Furthermore, when using a neural network model that identifies individual teeth from a 3D tooth model, and a neural network model that segments each tooth from the 3D tooth model to obtain the first digital dental model, the feature points on each tooth are accurately obtained during this segmentation process. Multiple first feature points can then be selected directly from the acquired feature points, making the acquisition of first feature points more accurate and simpler. This makes the first coordinate system more stable and faster to establish. The same applies to the second coordinate system, thereby improving the stability, robustness, and acquisition efficiency of the first transformation matrix.

[0094] In another embodiment of this disclosure, establishing a first coordinate system corresponding to a first digital dental model based on a plurality of first feature points includes: performing planar fitting on the plurality of first feature points to obtain a first fitting plane; taking the center point of the first fitting plane as the origin of the first coordinate system and the normal of the first fitting plane as the Z-axis of the first coordinate system; determining the Y-axis of the first coordinate system based on the center points of the two incisors in the first digital dental model and the origin of the first coordinate system (i.e., taking the line connecting the center points of the two incisors and the origin of the first coordinate system as the Y-axis of the first coordinate system); and determining the X-axis of the first coordinate system based on the origin of the first coordinate system, the Y-axis of the first coordinate system, and the Z-axis of the first coordinate system.

[0095] Accordingly, a second coordinate system is established based on multiple second feature points to correspond to the second digital dental model, including: performing planar fitting on the multiple second feature points to obtain a second fitting plane; taking the center point of the second fitting plane as the origin of the second coordinate system and the normal of the second fitting plane as the Z-axis of the second coordinate system; determining the Y-axis of the second coordinate system based on the center points of the two incisors in the first digital dental model and the origin of the second coordinate system (i.e., taking the line connecting the center points of the two incisors and the origin of the second coordinate system as the Y-axis of the second coordinate system); and determining the X-axis of the second coordinate system based on the origin of the second coordinate system, the Y-axis of the second coordinate system, and the Z-axis of the second coordinate system.

[0096] Specifically, the first and second fitting planes can be obtained by any possible plane fitting method, without any limitation here.

[0097] Specifically, the center point of the two incisors refers to the midpoint of the line connecting the center point of one incisor to the center point of the other incisor.

[0098] Of course, the origin of the first coordinate system can also be the location of a certain first feature point, and correspondingly, the origin of the second coordinate system can also be the location of the second feature point corresponding to the first feature point, etc., but it is not limited to these. The line connecting the center point of a certain incisor in the first digital dental model and the origin of the first coordinate system can be used as the Y-axis of the first coordinate system, and correspondingly, the origin of the second coordinate system can also be the line connecting the center point of the incisor and the origin of the second coordinate system, etc., but it is not limited to these.

[0099] It is understandable that the center point of the first fitting plane is a relatively significant point in the first fitting plane, and the center points of the two incisors are also relatively significant points corresponding to the first digital dental model. Their specific positions are easier to determine accurately. In this way, the method of establishing the first coordinate system is simple and easy to implement. The same applies to the second coordinate system. This helps to improve the speed of establishing the coordinate system, thereby improving the efficiency of obtaining the first transformation matrix.

[0100] In another embodiment of this disclosure, the first tooth model of the target tooth in the first digital dental model and the second tooth model of the target tooth in the second digital dental model are further registered to obtain the single-tooth transformation matrix corresponding to the target tooth, including:

[0101] S2411. Obtain the preset local registration area on the target tooth;

[0102] Specifically, the local registration region is the reference area used when performing local registration of the first tooth model and the second tooth model. The local registration region can be any area on the target tooth, and there is no limitation here.

[0103] S2412. Determine the first target region on the first tooth model of the target tooth that corresponds to the local registration region, and the second target region on the second tooth model of the target tooth that corresponds to the local registration region.

[0104] Specifically, the first target region and the second target region are both regions that correspond to the local registration regions when they are presented on the model. The difference is that the first target region is located on the first tooth model of the target tooth, and the second target region is located on the second tooth model of the target tooth.

[0105] S2413. Continue to perform fine registration on the first target region and the second target region to obtain the single-tooth transformation matrix corresponding to the target tooth.

[0106] Those skilled in the art can use any possible fine registration algorithm to perform fine registration of the first target region and the second target region, and there is no limitation here. For example, ICP, NICP, etc. can be used, but it is not limited to these.

[0107] Understandably, for the target tooth, by precisely registering the first target region on the first tooth model and the second target region on the second tooth model to achieve alignment of the first tooth model and the second tooth model, the area to be aligned can be reduced, which is beneficial for achieving rapid and accurate alignment of the first tooth model and the second tooth model.

[0108] In another embodiment of this disclosure, the first tooth model of the target tooth in the first digital dental model and the second tooth model of the target tooth in the second digital dental model are further registered to obtain the single-tooth transformation matrix corresponding to the target tooth, including:

[0109] S2421. Extract feature points from the first tooth model of the target tooth to obtain at least one third feature point;

[0110] S2422. Extract feature points from the second tooth model of the target tooth to obtain at least one fourth feature point;

[0111] Specifically, the feature point can be any point on the target tooth that has characteristic properties, such as the tooth socket, but is not limited to this.

[0112] Specifically, the feature point identification process can be performed by manually selecting feature points; or by using a feature point recognition algorithm to extract feature points from the first tooth model and the second tooth model, thereby obtaining the third and fourth feature points. For example, a trained neural network model that can identify feature points from the model can be used for feature point recognition, but it is not limited to these methods.

[0113] S2423. Perform fine registration of at least one third feature point and at least one fourth feature point to obtain a single tooth transformation matrix.

[0114] Those skilled in the art can use any possible fine registration algorithm to register at least one third feature point and at least one fourth feature point, and there is no limitation here. For example, ICP, NICP, etc. can be used, but are not limited to these.

[0115] Understandably, for the target tooth, by performing precise registration on the third feature point on the first tooth model and the fourth feature point on the second tooth model to achieve alignment of the first tooth model and the second tooth model, the number of points to be aligned can be reduced, which is beneficial to achieving fast and accurate alignment of the first tooth model and the second tooth model.

[0116] In another embodiment of this disclosure, after determining the deviation value between the first tooth model and the second tooth model of the target tooth for each target tooth, the method further includes: generating a comparison report between the first digital dental model and the user's second digital dental model, wherein the comparison report includes the overlapping first tooth model and the second tooth model corresponding to each target tooth, and different numerical ranges of the deviation value between the overlapping first tooth model and the second tooth model are marked with different colors; and outputting the comparison report.

[0117] Specifically, after determining the deviation values ​​between the first and second tooth models corresponding to each target tooth, a comparison report can be generated for each target tooth in the first and second digital jaw models. This comparison report can be presented in the form of a three-dimensional comparison image. In practical applications, the positions of the first and second tooth models of the target teeth can be overlapped at least, and different numerical ranges of the corresponding deviation values ​​between the first and second tooth models can be marked with different colors. For example, the larger the numerical range of the deviation value, the darker the color. This allows for a clear and direct assessment of the difference between the user's current dental condition and their historical dental condition from the comparison report, thus quickly understanding the treatment effect. Of course, depending on the actual situation, the magnitude of the deviation value can also be marked on the color differences of the above three-dimensional comparison image to make it clear at a glance and reduce human judgment errors.

[0118] Specifically, after generating the comparison report, it can be output, for example, as an electronic document in various formats, which can be sent to users for sharing; or the comparison report can be printed to form a paper version, which is beneficial for doctors to explain to users on-site.

[0119] Understandably, generating comparison reports allows for a direct and clear assessment of the difference between a user's current and historical dental condition through variations in color, providing the user with a clear understanding of the orthodontic process and improving their treatment experience. Furthermore, outputting comparison reports facilitates secondary processing, such as sharing and printing.

[0120] Figure 3 This is a schematic diagram of the structure of an orthodontic treatment monitoring device provided in an embodiment of this disclosure. This orthodontic treatment monitoring device can be understood as the aforementioned electronic device or a functional module within the aforementioned electronic device. For example... Figure 3 As shown, the orthodontic treatment monitoring device 300 includes:

[0121] Module 310 is used to acquire the user's first dental model at the current moment;

[0122] Tooth segmentation module 320 is used to perform tooth segmentation processing on the first dental model to obtain a first digital dental model, wherein the first digital dental model includes a first tooth model of at least one target tooth.

[0123] The determination module 330 is used to determine the deviation value between the first tooth model and the second tooth model of the target tooth for each target tooth, wherein the second tooth model is the tooth model of the tooth before the current time.

[0124] In another embodiment of this disclosure, the determining module 330 may include:

[0125] The first registration submodule is used to register the first digital dental model and the user's second digital dental model to obtain the overall transformation matrix;

[0126] The second registration submodule is used to continue registering the first tooth model of the target tooth in the first digital dental model and the second tooth model of the target tooth in the second digital dental model for each target tooth, so as to obtain the single tooth transformation matrix corresponding to the target tooth.

[0127] The determination submodule is used to determine the deviation value corresponding to the target tooth based on the overall transformation matrix and the single-tooth transformation matrix corresponding to the target tooth.

[0128] In yet another embodiment of this disclosure, the first registration submodule may include:

[0129] The first registration unit is used to perform coarse registration on the first digital dental model and the second digital dental model to obtain the first transformation matrix.

[0130] The second registration unit is used to continue fine registration of the first digital dental model and the second digital dental model to obtain the second transformation matrix.

[0131] The first determining unit is used to determine the overall transformation matrix based on the first transformation matrix and the second transformation matrix.

[0132] In another embodiment of this disclosure, the first registration submodule may include:

[0133] The first extraction unit is used to extract feature points of preset teeth in the first digital dental model to obtain multiple first feature points;

[0134] The first establishment unit is used to establish a first coordinate system corresponding to the first digital dental model based on multiple first feature points;

[0135] The second extraction unit is used to extract feature points of preset teeth in the second digital dental model to obtain multiple second feature points;

[0136] The second establishment unit is used to establish the second coordinate system corresponding to the second digital dental model based on multiple second feature points;

[0137] The second determining unit is used to determine the first transformation matrix corresponding to aligning the first coordinate system with the second coordinate system.

[0138] In another embodiment of this disclosure, the first establishing unit may include:

[0139] The first fitting subunit is used to perform plane fitting on multiple first feature points to obtain a first fitting plane;

[0140] The first determining sub-unit is used to take the center point of the first fitting plane as the origin of the first coordinate system and the normal of the first fitting plane as the Z-axis of the first coordinate system.

[0141] The second determining subunit is used to determine the Y-axis of the first coordinate system based on the center points of the two incisors in the first digital dental model and the origin of the first coordinate system;

[0142] The third determining sub-unit is used to determine the X-axis of the first coordinate system based on the origin of the first coordinate system, the Y-axis of the first coordinate system, and the Z-axis of the first coordinate system.

[0143] Accordingly, the second establishment unit may include:

[0144] The second fitting subunit is used to perform plane fitting on multiple second feature points to obtain a second fitting plane;

[0145] The fourth determining sub-unit is used to take the center point of the second fitting plane as the origin of the second coordinate system and the normal of the second fitting plane as the Z-axis of the second coordinate system.

[0146] The fifth determining subunit is used to determine the Y-axis of the second coordinate system based on the center points of the two incisors in the first digital dental model and the origin of the second coordinate system;

[0147] The sixth determining sub-unit is used to determine the X-axis of the second coordinate system based on the origin, the Y-axis, and the Z-axis of the second coordinate system.

[0148] In another embodiment of this disclosure, the second registration submodule may include:

[0149] The acquisition unit is used to acquire a preset local registration area on the target tooth;

[0150] The third determining unit is used to determine the first target region on the first tooth model of the target tooth that corresponds to the local registration region, and the second target region on the second tooth model of the target tooth that corresponds to the local registration region.

[0151] The third registration unit is used to continue fine registration of the first target region and the second target region to obtain the single-tooth transformation matrix corresponding to the target tooth.

[0152] In another embodiment of this disclosure, the second registration submodule may include:

[0153] The third extraction unit is used to extract feature points on the first tooth model of the target tooth to obtain at least one third feature point.

[0154] The fourth extraction unit is used to extract feature points on the second tooth model of the target tooth to obtain at least one fourth feature point;

[0155] The fourth registration unit is used to perform fine registration of at least one third feature point and at least one fourth feature point to obtain a single tooth transformation matrix.

[0156] The apparatus provided in this embodiment can execute the methods of any of the above embodiments, and its execution method and beneficial effects are similar, so they will not be described again here.

[0157] This disclosure also provides an electronic device, which includes: a memory storing a computer program; and a processor for executing the computer program, wherein when the computer program is executed by the processor, it can implement the methods of any of the above embodiments.

[0158] Example, Figure 4 This is a schematic diagram of the structure of an electronic device according to an embodiment of this disclosure. See below for details. Figure 4 The diagram illustrates a structural schematic suitable for implementing the electronic device 400 in the embodiments of this disclosure. The electronic device 400 in the embodiments of this disclosure may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 4 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0159] like Figure 4As shown, electronic device 400 may include a processing device (e.g., a central processing unit, a graphics processor, etc.) 401, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 402 or a program loaded from storage device 408 into random access memory (RAM) 403. RAM 403 also stores various programs and data required for the operation of electronic device 400. Processing device 401, ROM 402, and RAM 403 are interconnected via bus 404. Input / output (I / O) interface 405 is also connected to bus 404.

[0160] Typically, the following devices can be connected to I / O interface 405: input devices 406 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 407 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 408 including, for example, magnetic tapes, hard disks, etc.; and communication devices 409. Communication device 409 allows electronic device 400 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 4 An electronic device 400 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively.

[0161] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication device 409, or installed from storage device 408, or installed from ROM 402. When the computer program is executed by processing device 401, it performs the functions defined in the methods of embodiments of this disclosure.

[0162] It should be noted that the computer-readable medium described in this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0163] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.

[0164] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0165] The aforementioned computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to:

[0166] Obtain the user's first dental model at the current moment;

[0167] The first dental model is processed by tooth segmentation to obtain a first digital dental model, wherein the first digital dental model includes a first tooth model of at least one target tooth;

[0168] For each target tooth, determine the deviation value between the first tooth model and the second tooth model of the target tooth, where the second tooth model is the tooth model of the tooth before the current time.

[0169] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including but not limited to object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0170] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0171] The units described in the embodiments of this disclosure can be implemented in software or hardware. The names of the units are not, in some cases, intended to limit the specific unit.

[0172] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0173] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0174] This disclosure also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it can implement the methods of any of the above embodiments. The execution method and beneficial effects are similar, and will not be described again here.

[0175] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0176] The above description is merely a specific embodiment of this disclosure, enabling those skilled in the art to understand or implement it. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not to be limited to the embodiments described herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for monitoring orthodontic treatment, characterized in that, include: Obtain the user's first dental model at the current moment; The first dental model is subjected to tooth segmentation processing to obtain a first digital dental model, wherein the first digital dental model includes a first tooth model of at least one target tooth; For each target tooth, the deviation value between the first tooth model and the second tooth model of the target tooth is determined, wherein the second tooth model is the tooth model of the tooth before the current time, the second digital dental model includes the second tooth model of each tooth, the second digital dental model is obtained by performing tooth segmentation processing on the second dental model, and the second dental model is the dental model of the user before the current time; For each target tooth, determining the deviation value between the first tooth model and the second tooth model of the target tooth includes: The first digital dental model and the user's second digital dental model are registered to obtain the overall transformation matrix; For each target tooth, the first tooth model of the target tooth in the first digital dental model and the second tooth model of the target tooth in the second digital dental model are registered to obtain the single tooth transformation matrix corresponding to the target tooth; The deviation value corresponding to the target tooth is determined based on the overall transformation matrix and the single-tooth transformation matrix corresponding to the target tooth.

2. The method according to claim 1, characterized in that, The registration of the first digital dental model and the user's second digital dental model to obtain an overall transformation matrix includes: Coarse registration is performed on the first digital dental model and the second digital dental model to obtain the first transformation matrix; Continue to perform fine registration on the first digital dental model and the second digital dental model to obtain the second transformation matrix; The overall transformation matrix is ​​determined based on the first transformation matrix and the second transformation matrix.

3. The method according to claim 2, characterized in that, The coarse registration of the first digital dental model and the second digital dental model to obtain the first transformation matrix includes: Extract feature points of preset teeth from the first digital dental model to obtain multiple first feature points; A first coordinate system corresponding to the first digital dental model is established based on the plurality of first feature points; Feature points of preset teeth are extracted from the second digital dental model to obtain multiple second feature points; A second coordinate system corresponding to the second digital dental model is established based on the plurality of second feature points; Determine the first transformation matrix that aligns the first coordinate system with the second coordinate system.

4. The method according to claim 3, characterized in that, The step of establishing a first coordinate system corresponding to the first digital dental model based on the plurality of first feature points includes: A first fitting plane is obtained by performing plane fitting on the plurality of first feature points; The center point of the first fitting plane is taken as the origin of the first coordinate system, and the normal of the first fitting plane is taken as the Z-axis of the first coordinate system. The Y-axis of the first coordinate system is determined based on the center points of the two incisors in the first digital dental model and the origin of the first coordinate system. The X-axis of the first coordinate system is determined based on the origin of the first coordinate system, the Y-axis of the first coordinate system, and the Z-axis of the first coordinate system. Accordingly, establishing the second coordinate system corresponding to the second digital dental model based on the plurality of second feature points includes: A second fitting plane is obtained by performing plane fitting on the plurality of second feature points; The center point of the second fitting plane is taken as the origin of the second coordinate system, and the normal of the second fitting plane is taken as the Z-axis of the second coordinate system. The Y-axis of the second coordinate system is determined based on the center points of the two incisors in the second digital dental model and the origin of the second coordinate system; The X-axis of the second coordinate system is determined based on the origin, the Y-axis, and the Z-axis of the second coordinate system.

5. The method according to claim 1, characterized in that, The next step involves registering the first tooth model of the target tooth in the first digital dental model and the second tooth model of the target tooth in the second digital dental model to obtain the single-tooth transformation matrix corresponding to the target tooth, including: Obtain a pre-defined local registration area on the target tooth; Determine a first target region on a first tooth model of the target tooth that corresponds to the local registration region, and a second target region on a second tooth model of the target tooth that corresponds to the local registration region; Continue to perform fine registration on the first target region and the second target region to obtain the single-tooth transformation matrix corresponding to the target tooth.

6. The method according to claim 1, characterized in that, The next step involves registering the first tooth model of the target tooth in the first digital dental model and the second tooth model of the target tooth in the second digital dental model to obtain the single-tooth transformation matrix corresponding to the target tooth, including: Feature points are extracted from the first tooth model of the target tooth to obtain at least one third feature point; Feature points are extracted from the second tooth model of the target tooth to obtain at least one fourth feature point; The at least one third feature point and at least one fourth feature point are precisely registered to obtain the single-tooth transformation matrix.

7. An orthodontic treatment monitoring device, characterized in that, include: The acquisition module is used to acquire the user's first dental model at the current moment; The tooth segmentation module is used to segment the first dental model to obtain a first digital dental model, wherein the first digital dental model includes a first tooth model of at least one target tooth. The determination module is used to determine the deviation value between the first tooth model and the second tooth model of the target tooth for each target tooth, wherein the second tooth model is the tooth model of the tooth before the current time, the second digital dental model includes the second tooth model of each tooth, the second digital dental model is obtained by performing tooth segmentation processing on the second dental model, and the second dental model is the dental model of the user before the current time. The determining module is specifically used for: The first digital dental model and the user's second digital dental model are registered to obtain the overall transformation matrix; For each target tooth, the first tooth model of the target tooth in the first digital dental model and the second tooth model of the target tooth in the second digital dental model are registered to obtain the single tooth transformation matrix corresponding to the target tooth; The deviation value corresponding to the target tooth is determined based on the overall transformation matrix and the single-tooth transformation matrix corresponding to the target tooth.

8. An electronic device, characterized in that, include: A processor and a memory, wherein the memory stores a computer program that, when executed by the processor, performs the method of any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The storage medium stores a computer program that, when executed by a processor, implements the method as described in any one of claims 1-6.

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