Method for generating intraoral model and electronic device for performing same

Abstract

Disclosed is a method for generating an occlusion model. The method for generating an occlusion model comprises the steps of: generating a first upper jaw model on the basis of upper jaw depth data about the upper jaw; generating a first lower jaw model on the basis of lower jaw depth data about the lower jaw; acquiring occlusion data about the occlusion state of the upper jaw and the lower jaw; and generating an occlusion model indicating the occlusion state of the upper jaw and the lower jaw on the basis of the upper jaw depth data, the lower jaw depth data, and the occlusion data, wherein the occlusion model includes a second upper jaw model and a second lower jaw model, and at least a portion of the shape of the second upper jaw model is different from at least a portion of the shape of the first upper jaw model, or at least a portion of the shape of the second lower jaw model is different from at least a portion of the shape of the first lower jaw model.

Description

Method for creating an intraoral model and an electronic device for performing the same

[0001] The present disclosure relates to a method for generating an intraoral model and an electronic device for performing the same, and more particularly, to a method for generating a 3D intraoral model using scan data acquired using an intraoral scanner.

[0002] Digital Impression Scanning (DIS) is the process of digitizing the interior of the oral cavity using a 3D scanner, replacing the traditional physical impression (which involves taking a mold of the oral cavity's interior). This method uses an intraoral scanner (usually an intraoral scanner) to precisely scan a patient's teeth, gums, and oral structure, then converts them into a digital 3D model.

[0003] 3D models are used to create prosthetics (crowns, bridges, implants) and orthodontic devices in dentistry and orthodontics. If the 3D model is inaccurate, the resulting prosthesis may not fit properly in the oral cavity or may have functional issues, so a high level of accuracy is required.

[0004] Dental professionals insert an intraoral scanner into a patient's mouth to perform a scan. This process can be uncomfortable for both the dental professional and the patient. Scanner operation can be particularly challenging in confined spaces. Therefore, a scanning method that simplifies the scanning process and provides a user-friendly interface is needed.

[0005] The technical challenge that the present disclosure seeks to solve is to increase the accuracy of a 3D occlusion model through model optimization.

[0006] Another technical challenge that the present disclosure seeks to address is to improve user convenience by simplifying the scanning procedure.

[0007] According to one embodiment of the present disclosure, a method for generating an intraoral model may be provided, including: a step of generating a first maxilla model representing the maxilla based on maxillary depth data including depth information for the maxilla; a step of generating a first mandibular model representing the mandible based on mandibular depth data including depth information for the mandible; a step of acquiring occlusion data regarding an occlusion state of the maxilla and the mandible; and a step of generating an occlusion model representing the occlusion state of the maxilla and the mandible based on the maxillary depth data, the mandibular depth data, and the occlusion data; wherein the occlusion model includes a second maxillary model and a second mandibular model, and at least a portion of a shape of the second maxillary model is different from at least a portion of a shape of the first maxillary model, or at least a portion of a shape of the second mandibular model is different from at least a portion of a shape of the first mandibular model.

[0008] The step of generating the above occlusion model may include a step of obtaining the second maxillary model and the second mandibular model by modifying at least one of the first maxillary model and the first mandibular model based on the occlusion data.

[0009] The step of generating the above occlusion model may include a step of optimizing at least a portion of pose information corresponding to at least one of the upper jaw depth data and the lower jaw depth data based on the occlusion data, and a step of generating the occlusion model based on the upper jaw depth data, the lower jaw depth data, and the optimized pose information.

[0010] The above occlusion data includes occlusion depth data including depth information for the upper jaw and the lower jaw in an occlusion state, and the step of optimizing at least a part of the pose information may include a step of modifying pose information corresponding to the upper jaw depth data or the lower jaw depth data based on the occlusion depth data when depth information included in the occlusion depth data is different from depth information included in the upper jaw depth data or the lower jaw depth data.

[0011] The above occlusion data may be obtained by scanning the upper jaw and the lower jaw with an oral scanner while the upper jaw and the lower jaw are in occlusion, obtained based on a pattern formed on an occlusion sheet, or set by a user of the oral scanner.

[0012] The first maxillary model and the second maxillary model may differ in at least part of surface information of teeth included in the maxilla, or in at least part of relative positional relationships between teeth included in the maxilla.

[0013] The method for generating the oral cavity model further includes a step of aligning the first maxillary model and the first mandibular model based on the occlusion data to generate an initial occlusion model; and a step of displaying the initial occlusion model; wherein the initial occlusion model may include the first maxillary model and the first mandibular model.

[0014] The above occlusion model can be generated when user input for optimizing the initial occlusion model is obtained through a user interface.

[0015] The above occlusion model can be generated when the accuracy of the initial occlusion model is determined to be less than a predetermined value.

[0016] When the above occlusion data is acquired through an occlusion scan that scans the occlusion state of the upper jaw and the lower jaw, the occlusion model can be generated and displayed in real time while the occlusion scan is performed.

[0017] According to another embodiment of the present disclosure, an electronic device may be provided, comprising: a communication interface including at least one communication circuit; a memory including at least one instruction; and a processor; wherein the processor executes the at least one instruction to generate a first maxilla model representing the maxilla based on maxillary depth data including depth information about the maxilla, generate a first mandibular model representing the mandible based on mandibular depth data including depth information about the mandible, obtain occlusion data regarding an occlusion state of the maxilla and the mandible, and generate an occlusion model representing the occlusion state of the maxilla and the mandible based on the maxillary depth data, the mandibular depth data, and the occlusion data, wherein the occlusion model includes a second maxilla model and a second mandibular model, and at least a portion of a shape of the second maxilla model is different from at least a portion of a shape of the first maxilla model, or at least a portion of a shape of the second mandibular model is different from at least a portion of a shape of the first mandibular model.

[0018] The processor can obtain the second maxillary model and the second mandibular model by modifying at least one of the first maxillary model and the first mandibular model based on the occlusion data.

[0019] The processor can optimize pose information of an oral scanner used to obtain the maxillary depth data and the mandibular depth data corresponding to the maxillary depth data, the mandibular depth data, and the occlusion data, and generate the occlusion model based on the maxillary depth data, the mandibular depth data, and the optimized pose information of the oral scanner.

[0020] The above occlusion data includes occlusion depth data including depth information for the upper jaw and the lower jaw in an occlusion state, and the processor can modify pose information corresponding to the upper jaw depth data or the lower jaw depth data based on the occlusion depth data when depth information included in the occlusion depth data is different from depth information included in the upper jaw depth data or the lower jaw depth data.

[0021] The above occlusion data may be obtained by scanning the upper jaw and the lower jaw with an oral scanner while the upper jaw and the lower jaw are in occlusion, obtained based on a pattern formed on an occlusion sheet, or set by a user of the oral scanner.

[0022] The first maxillary model and the second maxillary model may differ in at least part of surface information of teeth included in the maxilla, or in at least part of relative positional relationships between teeth included in the maxilla.

[0023] According to another embodiment of the present disclosure, a depth data optimization method may be provided, including: a step of obtaining a 3D model of the maxilla using 3D point clouds of the maxilla obtained through an maxilla scan that scans the maxilla; a step of obtaining a 3D model of the mandible using 3D point clouds of the mandible obtained through a mandibular scan that scans the mandible; a step of obtaining occlusion 3D point clouds through an occlusion scan that scans an occlusion state of the maxilla and the mandible; and a step of optimizing at least a part of a connection relationship between the 3D point clouds of the maxilla or at least a part of a connection relationship between the 3D point clouds of the mandible based on the occlusion 3D point clouds.

[0024] According to the above optimization, the shape of the upper jaw 3D model or the lower jaw 3D model can be updated.

[0025] According to another embodiment of the present disclosure, a pose information optimization method may be provided, including: obtaining a maxilla 3D model based on maxilla 3D images and pose information corresponding to each of the maxilla 3D images; obtaining a mandibular 3D model based on mandibular 3D images and pose information corresponding to each of the mandibular 3D images; obtaining an occlusion 3D model based on occlusion 3D images and pose information corresponding to each of the occlusion 3D images; and improving at least a portion of the pose information corresponding to each of the maxilla 3D images or at least a portion of the pose information corresponding to each of the mandibular 3D images based on the pose information corresponding to each of the occlusion 3D images.

[0026] According to the above improvement, the shape of the upper jaw 3D model or the lower jaw 3D model can be updated.

[0027] The above exemplary embodiments and other exemplary embodiments will be explained or clarified by the detailed description set forth below of exemplary embodiments to be read in connection with the accompanying drawings.

[0028] The disclosed technology may have the following effects. However, this does not mean that a particular embodiment must include all or only the following effects, and thus the scope of the disclosed technology should not be construed as being limited thereby.

[0029] According to one embodiment of the present disclosure, the accuracy of a 3D occlusion model can be improved through model optimization.

[0030] According to another embodiment of the present disclosure, the scanning procedure can be simplified to improve user convenience.

[0031] The above is not intended to be an exhaustive list of all aspects of the present disclosure. It should be understood that the present disclosure encompasses all methods, devices, and systems capable of being implemented from all appropriate combinations of the various aspects disclosed in the detailed description and claims below, as well as the summaries herein. Furthermore, the detailed description of the embodiments of the present disclosure may directly or implicitly disclose any benefits that may be achieved or anticipated by the embodiments of the present disclosure. For example, various anticipated benefits resulting from the embodiments of the present disclosure will be disclosed in the detailed description that follows.

[0032] Aspects, features and advantages of specific embodiments of the present disclosure will become more apparent from the following description taken in conjunction with the accompanying drawings.

[0033] FIG. 1 is a schematic diagram illustrating an oral scanning system according to one embodiment of the present disclosure.

[0034] FIG. 2 is a flowchart illustrating a method for generating an occlusion model according to one embodiment of the present disclosure.

[0035] FIG. 3 is a flowchart illustrating a method for optimizing a 3D model according to one embodiment of the present disclosure.

[0036] FIG. 4 is a schematic diagram illustrating a method for generating an occlusion model according to one embodiment of the present disclosure.

[0037] FIG. 5 is a schematic diagram illustrating a method for generating an occlusion model according to another embodiment of the present disclosure.

[0038] FIG. 6 is a diagram for explaining a graph generation method according to one embodiment of the present disclosure.

[0039] FIG. 7 is a diagram showing a graph according to one embodiment of the present disclosure.

[0040] FIG. 8 is a drawing showing an occlusion model displayed according to one embodiment of the present disclosure.

[0041] FIG. 9 is a drawing showing an occlusion model displayed according to another embodiment of the present disclosure.

[0042] FIG. 10 is a flowchart illustrating a method for generating an occlusion model according to one embodiment of the present disclosure.

[0043] FIG. 11 is a drawing for explaining an occlusion scanning process according to one embodiment of the present disclosure.

[0044] FIG. 12 is a diagram for explaining a process of creating a connection relationship between occlusion depth data according to one embodiment of the present disclosure.

[0045] Figure 13 is a drawing showing a graph corresponding to Figure 12.

[0046] FIG. 14 is a block diagram showing the configuration of an oral scanning system according to one embodiment of the present disclosure.

[0047] The terms used in this specification will be briefly explained, and the present disclosure will be described in detail.

[0048] The terms used in the embodiments of this disclosure have been selected from widely used, current terms, taking into account the functions of this disclosure. However, these terms may vary depending on the intentions of those skilled in the art, precedents, the emergence of new technologies, etc. Furthermore, in certain cases, terms may be arbitrarily selected by the applicant, and in such cases, their meanings will be described in detail in the description of the relevant disclosure. Therefore, the terms used in this disclosure should not be defined simply as names of terms, but rather based on their meanings and the overall content of this disclosure.

[0049] The embodiments of the present disclosure are capable of various modifications and multiple embodiments. Specific embodiments are illustrated in the drawings and described in detail in the detailed description. However, this is not intended to limit the scope of the present disclosure to specific embodiments, but rather to encompass all modifications, equivalents, and alternatives falling within the scope of the disclosed concepts and techniques. In describing the embodiments, detailed descriptions of related known technologies will be omitted if they are deemed to obscure the main point.

[0050] Terms such as "first" and "second" may be used to describe various components, but the components should not be limited by these terms. These terms are used solely to distinguish one component from another.

[0051] Singular expressions include plural expressions unless the context clearly dictates otherwise. In this application, terms such as "comprise" or "consist of" are intended to indicate the presence of a feature, number, step, operation, component, part, or combination thereof described in the specification, but should be understood not to preclude the presence or addition of one or more other features, numbers, steps, operations, components, parts, or combinations thereof.

[0052] Below, with reference to the attached drawings, embodiments of the present disclosure are described in detail so that those skilled in the art can easily implement the present disclosure. However, the present disclosure may be implemented in various different forms and is not limited to the embodiments described herein. In addition, in the drawings, parts irrelevant to the description are omitted for clarity of description of the present disclosure, and similar parts are designated with similar reference numerals throughout the specification.

[0053] FIG. 1 is a schematic diagram illustrating an oral scanning system according to one embodiment of the present disclosure.

[0054] Referring to FIG. 1, an oral scanning system (1000) may include an oral scanner (100) and an electronic device (200). A user (1) may scan the inside of a patient's (2) oral cavity using the oral scanner (100). The user (1) may be a dental staff member. For example, dental staff members may include dentists, dental hygienists, dental assistants, orthodontists, dental technicians, and oral surgeons.

[0055] The oral scanner (100) can transmit scan data acquired during the scanning process to an electronic device (200). The electronic device (200) can generate a 3D model representing the inside of the oral cavity based on the scan data. In addition, the electronic device (200) can display the 3D model on the display. The user (1) can continue the scanning process while checking the 3D model displayed on the electronic device (200). The scanning target of the oral scanner (100) is not limited to the inside of the oral cavity of the patient (2), and may also include structures that are scheduled to be installed or applied inside the oral cavity in the future or are intermediate results for such installation or application, even if they are not currently located inside the oral cavity.

[0056] The electronic device (200) can be connected to the oral scanner (100) via a wired or wireless connection to exchange data. The electronic device (200) may be a desktop, laptop, tablet PC, or a computer designed as an embedded system specifically for the purpose of using the oral scanner (100). The electronic device (200) may be implemented by being physically or functionally integrated with the oral scanner (100).

[0057] The electronic device (200) can operate in multiple scan modes. For example, the electronic device (200) can operate in an upper jaw scan mode, a lower jaw scan mode, or an occlusal scan mode.

[0058] The maxillary scan mode may be a scan mode for scanning the maxilla. In the maxillary scan mode, the user (1) may scan the maxilla using the oral scanner (100). At this time, the oral scanner (100) may collect scan data for the maxilla, i.e., 'maxillary scan data'. In addition, the electronic device (200) may receive the maxillary scan data from the oral scanner (100) and create a maxillary model based on the data. Here, the maxillary model may refer to a 3D model representing the structure of the maxilla. Meanwhile, the reception of the maxillary scan data and the creation of the maxillary model may be performed in real time in the maxillary scan mode.

[0059] The mandibular scan mode may be a scan mode for scanning the mandible. In the mandibular scan mode, the user (1) may scan the mandible using the oral scanner (100). At this time, the oral scanner (100) may collect scan data for the mandible, i.e., 'mandibular scan data'. In addition, the electronic device (200) may receive the mandibular scan data from the oral scanner (100) and generate a mandibular model based on the scan data. Here, the mandibular model may refer to a 3D model representing the structure of the mandible. Meanwhile, the reception of the mandibular scan data and the generation of the mandibular model may be performed in real time in the mandibular scan mode.

[0060] The occlusion scan mode may be a scan mode for scanning occlusion. In the occlusion scan mode, the user (1) may use the oral scanner (100) to scan the occlusion, i.e., the upper and lower jaws in an occlusion state. At this time, the oral scanner (100) may collect scan data for occlusion, i.e., 'occlusion scan data'. The electronic device (200) may receive the occlusion scan data from the oral scanner (100) and define the relative positional relationship between the upper and lower jaws. In addition, the electronic device (200) may generate an occlusion model based on the occlusion scan data. Here, the occlusion model is a 3D model representing the occlusion state of the upper and lower jaws, and may represent the structures of the upper and lower jaws in an occlusion state. The occlusion state may mean a state in which the teeth of the upper and lower jaws interlock with each other. Meanwhile, the reception of the occlusion scan data and the generation of the occlusion model may be performed in real time in the occlusion scan mode.

[0061] FIG. 2 is a flowchart illustrating a method for generating an occlusion model according to one embodiment of the present disclosure.

[0062] Referring to FIG. 2, the electronic device (200) can generate a first maxillary model based on maxillary depth data (S210). At this time, the electronic device (200) can operate in maxillary scan mode. The first maxillary model can be a 3D model representing the structure of the maxilla of the patient (2).

[0063] Maxillary depth data may include depth information about the maxilla. For example, maxillary depth data may include 3D point clouds, 3D images, depth maps, RGB-D data, Time-of-Flight (ToF) data, LiDAR data, and Computed Tomography (CT) data.

[0064] Maxillary depth data can be acquired from maxillary scan data. For example, if the maxillary scan data is a stereo image composed of a pair of RGB images, the electronic device (200) can align the stereo images to generate a disparity map and derive a depth map based on the disparity map. Furthermore, the electronic device (200) can acquire a 3D point cloud based on the depth map.

[0065] The electronic device (200) can generate a first maxillary model based on maxillary depth data and pose information of the oral scanner (100) corresponding to the maxillary depth data. Here, the correspondence between the maxillary depth data and the pose information of the oral scanner (100) may mean a temporal correspondence, that is, the maxillary depth data and the pose information of the oral scanner (100) are for the same point in time. The pose information of the oral scanner (100) may include the position and posture of the oral scanner (100). For example, the electronic device (200) can estimate a relative pose change by comparing features included in two consecutive depth maps. More detailed information regarding a method for acquiring pose information will be described later with reference to FIG. 3.

[0066] In another embodiment, the maxillary scan data may include depth information about the maxilla. For example, the scan data acquired by the oral scanner (100) may itself be a 3D point cloud. In this case, the electronic device (200) may use the maxillary scan data and pose information of the oral scanner (100) to create a first maxillary model.

[0067] The electronic device (200) can generate a first mandibular model based on mandibular depth data (S220). At this time, the electronic device (200) can operate in mandibular scan mode. The first mandibular model may be a 3D model representing the structure of the patient's (2) mandibular jaw.

[0068] This step has the same characteristics as step S210 except that the target is the mandible rather than the maxilla, and thus the description of S210 described above can be applied as is. For example, the electronic device (200) can generate a second maxilla model based on mandibular depth data and pose information of the oral scanner (100) corresponding to the mandibular depth data.

[0069] Additionally, since the mandibular depth data has the same characteristics as the maxillary depth data, except that the target is the mandible, not the maxilla, refer to the description of the maxillary depth data described above. Similarly, the mandibular scan data has the same characteristics as the maxillary scan data, except that the target is the mandible, not the maxilla, refer to the description of the maxillary scan data described above.

[0070] The electronic device (200) can acquire occlusion data regarding the occlusion state of the maxilla and mandible (S230). The occlusion state may refer to a state in which the teeth of the maxilla and mandible interlock with each other. In other words, the occlusion data may include information regarding the state in which the maxilla and mandible interlock with each other.

[0071] In one embodiment, the occlusion data may be occlusion depth data acquired through an occlusion scan. The occlusion depth data may include depth information for the maxilla and mandible in an occlusion state. For example, the occlusion depth data may include a 3D point cloud, a 3D image, a depth map, RGB-D data, Time-of-Flight (ToF) data, LiDAR data, and Computed Tomography (CT) data.

[0072] Occlusal depth data can be obtained from occlusion scan data. For example, the electronic device (200) can receive occlusion scan data from the oral scanner (100) and derive occlusion depth data based on the occlusion scan data. Since occlusion scan data has the same characteristics as maxillary scan data, except for differences in the scan target, the description of maxillary scan data described above is referred to.

[0073] In another embodiment, occlusion data can be acquired using an occlusal sheet. The occlusion data can be acquired based on a pattern formed on the occlusal sheet by the patient's bite.

[0074] In another embodiment, the occlusion data may be set by a user of the oral scanner (100) (e.g., a dental professional). The occlusion data may be set using oral scanning software running on the electronic device (200).

[0075] In another embodiment, occlusion data may be generated by combining the above-described embodiments. For example, the electronic device (200) may generate new occlusion scan data by combining occlusion scan data and occlusion data set by the user.

[0076] Meanwhile, the steps according to FIG. 2 are not limited to the specified order, and each step may be performed in various orders or simultaneously. For example, S220 may be performed before S210.

[0077] The electronic device (200) can generate an occlusion model representing the occlusion state of the upper and lower jaws based on maxillary depth data, mandibular depth data, and occlusion data (S240). The occlusion model can have a shape in which the upper and lower jaws are interlocked, i.e., a state in which the patient's mouth is closed.

[0078] The occlusion model may include a second maxillary model and a second mandibular model. At least a portion of the shape of the second maxillary model may differ from at least a portion of the shape of the first maxillary model. Alternatively, at least a portion of the shape of the second mandibular model may differ from at least a portion of the shape of the first mandibular model. Specifically, the second maxillary model may have higher shape accuracy than the first maxillary model. The second mandibular model may have higher shape accuracy than the first mandibular model. Shape accuracy may be an indicator of how similar the maxillary / mandibular models are to the actual structures of the maxillary / mandibular joints. In other words, high shape accuracy may mean low shape errors. That is, the electronic device (200) may acquire a maxillary / mandibular model with improved accuracy in S240 compared to S210 and S220. This may be made possible by the electronic device (200) performing optimization to improve the accuracy of the maxillary / mandibular models.

[0079] The shape differences in the model can include both individual tooth shape differences and overall arch shape differences. Individual tooth shape differences can refer to differences in surface information for each tooth. Overall arch shape differences can refer to differences in the relative positional relationships between teeth. Model optimization is described below.

[0080] FIG. 3 is a flowchart illustrating a method for optimizing a 3D model according to one embodiment of the present disclosure.

[0081] Referring to FIG. 3, the electronic device (200) can estimate pose information of the oral scanner based on an image acquired by the oral scanner (S310). The oral scanner (100) may include an optical sensor for scanning the inside of the oral cavity (e.g., a structured light projector, a stereo camera, or other optical depth sensors), an inertial sensor (IMU) for estimating the movement of the oral scanner, or a separate imaging sensor. The image (or 3D point cloud) acquired from the optical sensor includes data on the surface of teeth and surrounding tissues in the oral cavity, and a change in the viewpoint of the oral scanner (100) can be estimated based on this data.

[0082] The electronic device (200) can estimate the change in movement between consecutive images (or 3D data) acquired by the oral scanner (100) at regular time intervals, calculate the relative positional displacement of the oral scanner (100), and sequentially accumulate the calculated displacement. Specifically, the electronic device (200) can compare and align data acquired at one point in time with data acquired at another point in time, and calculate the rotation and translation factors between the two points in time. Through this, the electronic device (200) can relatively estimate the position at another point in time based on the position of the oral scanner (100) at one point in time.

[0083] The electronic device (200) can extract keypoints from the outline or grooves of teeth. For example, irregular patterns of internal oral structures, such as the surface of teeth, can be used as keypoints. The electronic device (200) can determine the movement of the oral scanner (100) by matching the keypoints with each other. The electronic device (200) can repeat this process at regular intervals or frame units, thereby tracking the path along which the oral scanner (100) moves within the oral cavity in real time.

[0084] Meanwhile, the path estimation of the oral scanner (100) may gradually accumulate errors (drift) due to factors such as system noise, measurement errors, and feature point matching failures. The accumulated errors may cause the two data sets to not exactly match for overlapping areas when the oral scanner (100) circles the inside of the oral cavity and revisits the same area or scans adjacent surfaces of teeth from multiple angles.

[0085] The electronic device (200) can optimize the pose information of the oral scanner (100) (S320). When the oral scanner revisits the same or similar space it has previously passed through, the electronic device (200) can compare the scan data acquired in the past with the current scan data to correct the accumulated error. The electronic device (200) can accurately determine the actual relative position between the current position of the oral scanner (100) and the previous position of the oral scanner (revisited point), thereby globally reflecting the accumulated error that occurred in the intermediate section and readjusting the entire oral scanner trajectory. Through this, the pose information of the oral scanner (100) is optimized, and the 3D model can also be optimized by reflecting the optimized pose information.

[0086] Specifically, the electronic device (200) can compare and analyze a specific area (e.g., a unique pattern on a tooth surface, a groove on an occlusal surface, or a tooth arrangement feature) observed in the past with a currently observed area while the oral scanner (100) moves inside the oral cavity. The electronic device (200) can recognize that they are the same area by comparing the feature points included in a previously acquired feature point cloud or image patch with the feature points included in a currently acquired image or point cloud. Since teeth in the oral cavity have a complex structure and each individual has a unique shape, the same point can be re-recognized with a relatively high reliability if an appropriate feature extraction and matching algorithm is used. When a loop is detected, the electronic device (200) can update the connection status on the odometry trajectory through the relative transformation relationship between the current position of the oral scanner (100) and the position at the same point in the past. Here, a loop may mean a situation in which the oral scanner (100) rescans an area that has already been scanned.

[0087] The electronic device (200) can optimize the pose information of the oral scanner (100) using a graph optimization method. Specifically, the electronic device (200) can model the entire oral scanner path as nodes and edges. At this time, each node means a camera pose captured by the oral scanner (100) at a certain point in time, and the edge can be expressed as a relative transformation between adjacent nodes or a relative transformation detected in loop closing. The electronic device (200) can perform a global optimization process so that the connection information (edge) obtained through loop closing minimizes the error function for all nodes and edges. Through this, the accumulated error can be evenly distributed and corrected, thereby improving the alignment accuracy of the entire 3D scan model.

[0088] During the process of generating an occlusion model, the electronic device (200) may perform optimization on the maxillary / mandibular scan data, maxillary / mandibular depth data, or maxillary / mandibular model. Optimization may include a process of increasing the accuracy of a 3D model (e.g., maxillary / mandibular model, occlusion model) so that it more closely resembles the actual oral structure. Through optimization, the occlusion model can increase its similarity to the actual oral structure. Furthermore, the accuracy of the occlusion model can be improved.

[0089] The electronic device (200) according to the present disclosure may utilize a graph optimization technique as an embodiment of a model optimization method. Graph optimization may include a process of generating a graph based on pose information of an oral scanner (100) while acquiring scan data, and utilizing the scan data to generate an optimal pose and 3D model based on the graph. In one embodiment, nodes of the graph represent pose information of the oral scanner (100), and edges of the graph may represent relative relationships or movements between poses. Furthermore, such a graph may also be referred to as a "pose graph."

[0090] The electronic device (200) can repeat graph optimization to minimize the total error of the 3D model. During this process, the shapes of the maxillary and mandibular models constituting the occlusion model may be changed. Existing oral scanning systems generate maxillary and mandibular models, then treat them as rigid bodies and only adjust the relative positional relationship between the maxillary and mandibular models to generate the occlusion model. In contrast, the electronic device (200) performs optimization without treating the maxillary and mandibular models as rigid bodies, thereby improving the shape accuracy of the maxillary and mandibular models through optimization.

[0091] For example, if a foreign substance is scanned during the upper / lower jaw scanning process or noise occurs in the upper / lower jaw scan data, shape inconsistencies may occur in the upper / lower jaw models. In such cases, existing oral scanning systems only adjust the relative positional relationship of the upper / lower jaw models with shape inconsistencies based on occlusion data, but the electronic device (200) can improve shape inconsistencies in the upper / lower jaw models through optimization.

[0092] Below, several embodiments regarding the creation of an occlusion model are described.

[0093] The electronic device (200) can optimize pose information of the oral scanner (100) corresponding to maxillary depth data, mandibular depth data, and occlusion data. The occlusion data can include occlusion depth data including depth information for the maxilla and mandible in an occlusion state. At this time, the electronic device (200) can determine whether the depth information included in the occlusion depth data is different from the depth information included in the maxillary depth data or the mandibular depth data. If the depth information included in the occlusion depth data is different from the depth information included in the maxillary depth data or the mandibular depth data, the electronic device (200) can modify the pose information corresponding to the maxillary depth data or the mandibular depth data based on the occlusion depth data.

[0094] For example, for the same tooth, if the depth information included in the occlusion depth data is different from the depth information included in the maxillary depth data, the electronic device (200) can modify the depth information included in the maxillary depth data to be identical to the depth information included in the occlusion depth data. As another example, the electronic device (200) can modify the pose information of the oral scanner (100) corresponding to the occlusion depth data by preferentially referring to the maxillary depth data and the mandibular depth data. Alternatively, the pose information of the oral scanner (100) can be modified by combining the maxillary depth data and the mandibular depth data with the occlusion depth data. The electronic device (200) can generate an occlusion model based on the maxillary depth data, the mandibular depth data, and the optimized pose information of the oral scanner (100).

[0095] The electronic device (200) can obtain a second maxillary model and a second mandibular model by modifying at least one of the first maxillary model and the first mandibular model based on the occlusion data. The electronic device (200) can obtain second maxillary depth data by modifying the first maxillary depth data used to generate the first maxillary model based on the occlusion data. Alternatively, the electronic device (200) can obtain second mandibular depth data by modifying the first mandibular depth data used to generate the first mandibular model. The electronic device (200) can obtain the second maxillary / mandibular model by reconstructing the first maxillary / mandibular model based on the second maxillary / mandibular depth data.

[0096] An occlusion model can be generated based on a user command of the oral scanner (100). For example, the electronic device (200) can align a first maxillary model and a first mandibular model based on occlusion data to generate an initial occlusion model. The electronic device (200) can display the initial occlusion model on a display. At this time, the initial occlusion model can include a first maxillary model and a first mandibular model. The user can view the initial occlusion model and determine whether to optimize it. When user input for optimizing the initial occlusion model is obtained through the user interface, the electronic device (200) can optimize the initial occlusion model to generate an occlusion model.

[0097] The occlusion model can be generated without a user command of the oral scanner (100). In one embodiment, the electronic device (200) can evaluate the accuracy of the initial occlusion model. If the accuracy of the initial occlusion model is determined to be less than a predetermined value, the electronic device (200) can optimize the initial occlusion model to generate the occlusion model. If the accuracy of the initial occlusion model is determined to be greater than or equal to the predetermined value, the electronic device (200) may not optimize the initial occlusion model. In another embodiment, the electronic device (200) may optimize the initial occlusion model regardless of the accuracy of the initial occlusion model.

[0098] Meanwhile, the occlusion model may be generated in real time during a scan session of the oral scanner (100) and displayed on the display. For example, the occlusion model may be generated in real time and displayed on the display while occlusion scan data is being acquired.

[0099] FIG. 4 is a schematic diagram illustrating a method for generating an occlusion model according to one embodiment of the present disclosure.

[0100] Referring to FIG. 4, the electronic device (200) can generate a first maxillary model (21) and a first mandibular model (22). The electronic device (200) can generate the first maxillary model (21) based on maxillary depth data, and can generate the first mandibular model (22) based on mandibular depth data. The electronic device (200) can optimize the first maxillary model (21) and the first mandibular model (22) based on occlusal depth data (23) to generate an occlusion model (24) including a second maxillary model (25) and a second mandibular model (26). Although the occlusion model (24) is generated using the occlusal depth data (23), it is also possible to use other occlusion data in addition to the occlusal depth data (23).

[0101] The second maxillary model (25) may have a different shape from the first maxillary model (21), or the second mandibular model (26) may have a different shape from the first mandibular model (22). For example, the shape accuracy of the second maxillary model (25) may be higher than that of the first maxillary model (21), or the shape accuracy of the second mandibular model (26) may be higher than that of the first mandibular model (22).

[0102] Optimization for the first maxillary model (21) and the first mandibular model (22) can be performed by modifying the pose information of the oral scanner (100) corresponding to the maxillary and mandibular depth data and the occlusal depth data (23), or by directly modifying the first maxillary model (21) and the first mandibular model (22).

[0103] The first maxillary model (21) and the first mandibular model (22) may be models that have already been optimized regardless of the occlusal depth data (23). For example, the electronic device (200) may generate the first maxillary model (21) by optimizing the pose information of the oral scanner (100) corresponding to the maxillary depth data. At this time, the electronic device (200) may repeatedly update the first maxillary model (21) so that the shape error of the first maxillary model (21) is minimized. Similarly, the electronic device (200) may generate the first mandibular model (22) by optimizing the pose information of the oral scanner (100) corresponding to the mandibular depth data. That is, the first maxillary model (21) and the first mandibular model (22) may be first optimized without the occlusal depth data (23) and then secondarily optimized using the occlusal depth data (23).

[0104] FIG. 5 is a schematic diagram illustrating a method for generating an occlusion model according to another embodiment of the present disclosure.

[0105] Referring to FIG. 5, the electronic device (200) can align the first maxillary model (21) and the first mandibular model (22) based on the occlusion depth data (23). The electronic device (200) can compare the depth information included in the occlusion depth data (23) with the depth information included in the maxillary / mandibular depth data used to generate the first maxillary model (21) and the first mandibular model (22), and extract corresponding feature points. In addition, the electronic device (200) can align the first maxillary model (21) and the first mandibular model (22) using the feature points.

[0106] For example, in the occlusion depth data (23), a first feature point and a second feature point can be extracted, in the maxillary depth data, a third feature point corresponding to the first feature point can be extracted, and in the mandibular depth data, a fourth feature point corresponding to the second feature point can be extracted. At this time, the electronic device (200) can move and / or rotate the first maxillary model (21) so that the first feature point and the third feature point match, and can move and / or rotate the first mandibular model (22) so that the second feature point and the fourth feature point match. Through this, the electronic device (200) can align the first maxillary model (21) and the first mandibular model (22) based on the occlusion depth data (23). The electronic device (200) can improve the accuracy of the alignment by using a plurality of feature points, and can repeatedly perform the alignment so that the distance error between the feature points becomes less than a set threshold value. Through this feature-based alignment method, the electronic device (200) can create a three-dimensional oral model that reflects the patient's actual occlusion state.

[0107] Accordingly, the electronic device (200) can generate an initial occlusion model (27). In the process of generating the initial occlusion model (27), only the relative positional relationship between the first maxillary model (21) and the first mandibular model (22) can be determined without modification to the first maxillary model (21) and the first mandibular model (22). Accordingly, the initial occlusion model (27) can include the first maxillary model (21) and the first mandibular model (22).

[0108] The electronic device (200) can provide the user with feedback on the scan results by displaying the initial occlusion model (27). Accordingly, the user can evaluate whether there are any shape inconsistencies in the initial occlusion model (27). Based on the evaluation results, the user can determine whether to optimize the initial occlusion model (27). To assist the user's evaluation, the electronic device (200) can visually highlight areas with a high probability of shape inconsistencies from other areas.

[0109] When a user inputs a command to optimize the initial occlusion model (27) through the user interface, the electronic device (200) can optimize the initial occlusion model (27). Optimization of the initial occlusion model (27) can be performed by changing the pose corresponding to the maxillary and mandibular depth data based on the occlusion depth data (23) or the pose or edge information corresponding to the occlusion depth data (23). Alternatively, optimization of the initial occlusion model (27) can be performed by changing the pose information corresponding to each of the occlusion depth data and the maxillary and mandibular depth data so that the total error is minimized based on the edge information corresponding to the occlusion depth data and the maxillary and mandibular depth data.

[0110] Since the initial occlusion model (27) is generated without modifying the first maxillary model (21) and the first mandibular model (22), it can be generated quickly with fewer resources compared to the occlusion model (24). Therefore, the electronic device (200) can quickly provide the user with feedback on the scan results. Furthermore, optimization is performed only when the user determines that optimization is necessary, thereby preventing unnecessary waste of resources. For features other than those described above, please refer to FIG. 4.

[0111] FIG. 6 and FIG. 7 are diagrams illustrating a model optimization method according to one embodiment of the present disclosure. FIG. 6 is a diagram illustrating a graph generation method according to one embodiment of the present disclosure, and FIG. 7 is a diagram illustrating a graph according to one embodiment of the present disclosure.

[0112] Referring to FIG. 6, a user can move the oral scanner (100) to scan the lower jaw (40). The oral scanner (100) can obtain scan data for the lower jaw (40) (abbreviated as lower jaw scan data).

[0113] The electronic device (200) receives the mandibular scan data from the oral scanner (100) and can generate a graph based on the data. In addition, the electronic device (200) can generate depth maps (41, 42, 43, 44) based on the mandibular scan data. The electronic device (200) can obtain pose information of the oral scanner (100) corresponding to each depth map (41, 42, 43, 44) by utilizing the Visual Odometry technique. Thereafter, the electronic device (200) can construct a graph by generating nodes (N1, N2, N3, N4) representing pose information and edges representing constraints between the nodes (N1, N2, N3, N4) by utilizing the Graph SLAM technique. Additionally, the electronic device (200) can map nodes (N1, N2, N3, N4) and depth maps (41, 42, 43, 44).

[0114] Referring to FIG. 7, the electronic device (200) can generate a mandibular graph (52) corresponding to the mandible (40) in the above manner. In the same manner, the electronic device (200) can generate a maxillary graph (51) based on maxillary scan data and an occlusion graph (53) based on occlusion scan data. Each graph can be generated in real time during a scan session.

[0115] The electronic device (200) can optimize the occlusion model based on the maxillary graph (51), the mandibular graph (52), and the occlusion graph (53). For example, the electronic device (200) can connect the maxillary graph (51), the mandibular graph (52), and the occlusion graph (53) to generate a single integrated graph. Then, the electronic device (200) can modify the connection structure of the integrated graph until the shape error of the occlusion model is minimized (e.g., until it becomes smaller than a predetermined value). At this time, the electronic device (200) can detect and correct the shape error of the occlusion model using a graph optimization technique. Thereafter, the electronic device (200) can reconstruct the occlusion model based on the modified integrated graph.

[0116] Before optimizing the occlusion model, the electronic device (200) can optimize the maxillary model and the mandibular model, respectively. For example, if a maxillary graph (51) is generated through an maxillary scan, the electronic device (200) can optimize the maxillary model by modifying the connection structure of the maxillary graph (51) regardless of other graphs. In the same manner, the electronic device (200) can optimize the mandibular model by modifying the connection structure of the mandibular graph (52).

[0117] Meanwhile, model optimization can be performed in real time while scan data is being acquired. For example, the electronic device (200) can generate and optimize a maxillary model while maxillary scan data is being acquired. Furthermore, the electronic device (200) can generate and optimize an occlusion model while occlusion scan data is being acquired. In another embodiment, the occlusion model is generated in real time, and optimization can be performed later according to user commands.

[0118] FIG. 8 is a drawing showing an occlusion model displayed according to one embodiment of the present disclosure.

[0119] Referring to FIG. 8, four screens (61, 62, 63, 64) may be sequentially displayed on the display (240). A first maxillary model (21) may be displayed on the first screen (61). At this time, the electronic device (200) may operate in maxillary scan mode. A first mandibular model (22) may be displayed on the second screen (62). At this time, the electronic device (200) may operate in mandibular scan mode. If the mandibular scan is performed before the maxillary scan, the second screen (62) may be displayed before the first screen (61). Each model may be generated and displayed in real time while the maxillary / mandibular scan is in progress.

[0120] After the upper / lower jaw scan is completed, an occlusion scan may be performed. At this time, the electronic device (200) may operate in an occlusion scan mode. While the occlusion scan is in progress, a third screen (63) may be displayed. The third screen (63) may indicate whether the occlusion scan was successful. For example, before the occlusion scan is successful, the first upper jaw model (21) and the first lower jaw model (22) may be displayed as being independently spaced from each other. Afterwards, if there is an area (A) in which the occlusion scan is successful, the first upper jaw model (21) and the first lower jaw model (22) may be displayed as being combined around the area (A). In addition, the area (A) in which the occlusion scan is successful may be highlighted to be visually distinct from other areas.

[0121] The success of the occlusal scan may indicate whether the occlusal relationship between the first maxillary model (21) and the first mandibular model (22) has been successfully derived. The derivation of the occlusal relationship may be determined by whether the registration between the maxillary depth data, mandibular depth data, and occlusal depth data has been successfully achieved. The Iterative Closest Point (ICP) algorithm may be used in this registration process.

[0122] The fourth screen (64) may display an occlusion model (24) including a second maxillary model (25) and a second mandibular model (26). The occlusion model (24) may be a model for which optimization has been completed. Accordingly, the second maxillary model (25) may have a different shape from the first maxillary model (21), or the second mandibular model (26) may have a different shape from the first mandibular model (22). Although not shown, the fourth screen (64) may further display additional information related to optimization (e.g., improved results resulting from optimization).

[0123] FIG. 9 is a drawing showing an occlusion model displayed according to another embodiment of the present disclosure.

[0124] Referring to FIG. 9, five screens (61, 62, 63, 65, 64) can be sequentially displayed on the display (240). Compared to FIG. 6, a fifth screen (65) can be additionally displayed. For a description of the remaining screens (61, 62, 63, 64), refer to FIG. 8, and here, only the fifth screen (65) will be described.

[0125] The fifth screen (65) may display the initial occlusion model (27) and UI elements (71) for optimization progress. Areas (A1, A2) where the occlusion scan was successful may be highlighted to be visually distinct from other areas.

[0126] The transition from the third screen (63) to the fifth screen (65) can be made upon completion of the occlusion scan, i.e., upon final success of the occlusion scan. The final success of the occlusion scan can be determined based on whether the number of successfully scanned areas (A1, A2) exceeds a predetermined standard or whether the degree of alignment between the maxillary, mandibular, and occlusion depth data exceeds a predetermined value.

[0127] Although not shown, the fifth screen (65) may further display additional information regarding the initial occlusion model (27). The additional information regarding the initial occlusion model (27) may include the shape accuracy or shape error of the initial occlusion model (27). This information may be provided for the entire model or for each detailed region included in the model. The additional information regarding the initial occlusion model (27) may be expressed in various ways. For example, the shape accuracy of each detailed region may be displayed using color or patterns.

[0128] Additionally, additional information regarding the initial occlusion model (27) may include whether the initial occlusion model (27) requires optimization. For example, a message recommending optimization of the initial occlusion model (27) may be additionally displayed on the fifth screen (65). The electronic device (200) may diagnose whether optimization is necessary based on the shape accuracy or shape error of the initial occlusion model (27).

[0129] Based on the additional information about the initial occlusion model (27) described above, the user can determine whether the model is optimized. When the user selects a UI element (71), the electronic device (200) can optimize the initial occlusion model (27).

[0130] FIG. 10 is a flowchart illustrating a method for generating an occlusion model according to one embodiment of the present disclosure.

[0131] Referring to FIG. 10, the electronic device (200) can obtain maxillary depth data (S810). The electronic device (200) can generate an maxillary model based on the maxillary depth data. The electronic device (200) can obtain mandibular depth data (S820). The electronic device (200) can generate a mandibular model based on the mandibular depth data. The scanning order of the maxilla and mandibular jaws can be flexibly changed, and thus the generation order of the depth data and 3D model can also be changed.

[0132] The electronic device (200) can acquire first occlusion depth data and second occlusion depth data that do not overlap each other (S830). The first occlusion depth data and the second occlusion depth data can be acquired based on occlusion scans of two independent areas that do not overlap each other. For example, the first occlusion depth data may correspond to the first area, and the second occlusion depth data may correspond to the second area.

[0133] Acquisition of two occlusal depth data can be accomplished in a single occlusal scan mode. For example, two occlusal depth data can be acquired by the user freely scanning any area without separate area selection.

[0134] The electronic device (200) can obtain a connection relationship between the first occlusion depth data and the second occlusion depth data based on the maxillary depth data and the mandibular depth data (S840). Creating a connection relationship between the two occlusion depth data may mean an operation of interrelating the two occlusion depth data. For example, the operation of interrelating the two occlusion depth data may include an operation of connecting two graphs corresponding to the two occlusion depth data, respectively.

[0135] The electronic device (200) can create a connection relationship between the depth data by aligning different depth data. For example, the electronic device (200) can align the maxillary depth data with the first occlusion depth data to obtain a connection relationship between the maxillary depth data and the first occlusion depth data. In addition, the electronic device (200) can align the maxillary depth data with the second occlusion depth data to obtain a connection relationship between the maxillary depth data and the second occlusion depth data. Accordingly, a connection relationship between the first and second occlusion depth data can also be obtained. In the same manner, a connection relationship between the first and second occlusion depth data can be obtained by aligning the mandibular depth data with the first and second occlusion depth data.

[0136] Depth data alignment can be achieved based on similarity between the depth data. For example, if the maxillary depth data and the first occlusion depth data contain depth information with a similarity greater than a preset value, the electronic device (200) can align the maxillary depth data and the first occlusion depth data. The alignment process may use the Iterative Closest Point (ICP) algorithm.

[0137] The electronic device (200) can generate an occlusion model based on the connection relationship between the maxillary depth data, the mandibular depth data, the first occlusion depth data, and the second occlusion depth data (S850). The electronic device (200) can generate an integrated graph based on the graph corresponding to each depth data. When generating the integrated graph, the connection relationship between the first and second occlusion depth data can be utilized.

[0138] In the above-described embodiment, the electronic device (200) may generate the integrated graph by modifying the pose information of the maxillary depth data and the mandibular depth data by giving priority to the first occlusion depth data and the second occlusion depth data when generating the integrated graph. As another example, the electronic device (200) may generate the integrated graph by giving priority to the maxillary depth data and the mandibular depth data when generating the integrated graph, by giving priority to the maxillary depth data and the mandibular depth data, by giving priority to the pose information of the first occlusion depth data and the second occlusion depth data. As yet another example, the electronic device (200) may generate the integrated graph by optimizing the pose information of the maxillary depth data, the mandibular depth data, the first occlusion depth data, and the second occlusion depth data so as to minimize the sum of the total errors. Here, the pose information of the depth data refers to the pose information of the oral scanner (100) that temporally corresponds to the corresponding depth data.

[0139] FIG. 11 is a drawing for explaining an occlusion scanning process according to one embodiment of the present disclosure.

[0140] Referring to FIG. 11, a user can scan the oral cavity of a patient in an occluded state using an oral scanner (100). Before scanning the oral cavity, the user can select a scan mode in the oral scanning software running on the electronic device (200). For example, the user can select the occlusion scan mode and then proceed with an occlusion scan. Similarly, the user can select the maxillary scan mode and then proceed with an maxillary scan, and select the mandibular scan mode and then proceed with a mandibular scan.

[0141] In the case of occlusion scanning, unlike maxillary and mandibular scanning, the patient's maxilla and mandible are interlocked, so the intraoral space in which the oral scanner (100) can move is relatively more limited. Therefore, a technology is needed to improve the user's convenience during occlusion scanning.

[0142] The intraoral scanning software according to the present disclosure allows the user to scan independent, non-overlapping areas during an occlusion scan, without the need to maintain the intraoral scanner (100) within the oral cavity throughout the scanning session. For example, after scanning a first area (910), the user can remove the intraoral scanner (100) from the oral cavity and then scan a second area (920).

[0143] Existing oral scanning systems cannot perform this type of scanning, forcing continuous scanning. For example, if the overlap between depth data is interrupted, the user must rescan from that point or start over from the beginning. Therefore, the oral scanning system according to the present disclosure offers superior user convenience compared to existing oral scanning systems.

[0144] Furthermore, in conventional oral scanning systems, occlusion scanning could only be performed after selecting the occlusion scan mode and then additionally setting a specific scan area, such as the anterior region. In contrast, the oral scanning software of the present disclosure allows occlusion scanning to be performed without setting a specific scan area. For example, the first area (910) and the second area (920) may not be areas pre-selected by the user. Therefore, the present system offers greater scanning freedom compared to conventional oral scanning systems.

[0145] The electronic device (200) can obtain first occlusion depth data, which is depth data for the first region (910), and second occlusion depth data, which is depth data for the second region (920). The electronic device (200) can store the first and second occlusion depth data and utilize them in the subsequent occlusion model creation process.

[0146] FIG. 12 is a diagram for explaining a process of creating a connection relationship between occlusion depth data according to one embodiment of the present disclosure.

[0147] Referring to FIG. 12, a connection relationship between the first occlusion depth data (1031) and the second occlusion depth data (1032) can be generated based on the maxillary depth data (1010) and the mandibular depth data (1020). For example, the electronic device (200) can identify depth information common to the first occlusion depth data (1031) in the maxillary and mandibular depth data (1010, 1020). The electronic device (200) can generate a connection relationship between the maxillary and mandibular depth data (1010, 1020) and the first occlusion depth data (1031) based on the depth information. Similarly, the electronic device (200) can create a connection relationship between the maxillary and mandibular depth data (1010, 1020) and the second occlusion depth data (1032). This can create a connection relationship between the first occlusion depth data (1031) and the second occlusion depth data (1032). That is, the electronic device (200) can create a connection relationship between the first and second occlusion depth data (1031, 1032) via the maxillary and mandibular depth data (1010, 1020).

[0148] Figure 13 is a drawing showing a graph corresponding to Figure 12.

[0149] Referring to FIG. 13, the maxillary graph (1110) may correspond to maxillary depth data (1010), the mandibular graph (1120) may correspond to mandibular depth data (1020), and the first occlusion graph (1131) and the second occlusion graph (1132) may correspond to the first occlusion depth data (1031) and the second occlusion depth data (1032), respectively.

[0150] As described in FIG. 7, the electronic device (200) can generate an occlusion model using a graph optimization technique. At this time, the connection relationship between the first occlusion depth data (1031) and the second occlusion depth data (1032) can be reflected in the integrated graph.

[0151] FIG. 14 is a block diagram showing the configuration of an oral scanning system according to one embodiment of the present disclosure.

[0152] Referring to FIG. 14, an oral scanning system (1000) may include an oral scanner (100) and an electronic device (200). The oral scanner (100) may acquire scan data of the inside of a patient's oral cavity and transmit the scan data to the electronic device (200). The oral scanner (100) may include an optical sensor (e.g., a structured light projector, a stereo camera, or other optical depth sensor) for scanning the inside of the oral cavity, an inertial sensor (IMU) for estimating the movement of the oral scanner, or a separate imaging sensor.

[0153] The oral scanner (100) can acquire scan data using structured light, Time-of-Flight (ToF), LiDAR, Computed Tomography (CT), or ultrasound.

[0154] The electronic device (200) may include a communication interface (210), memory (220), processor (230), and display (240). The electronic device (200) may be a personal computer (PC), tablet, workstation, or smartphone.

[0155] The communication interface (210) may include at least one communication circuit. The communication interface (210) may receive scan data from the oral scanner (100). The communication interface (210) may include a wired interface and a wireless interface. The wired interface may include USB, Ethernet, HDMI, and Thunderbolt. The wireless interface may include Wi-Fi, Bluetooth, Zigbee, and NFC.

[0156] The memory (220) may store an operating system (OS) for controlling the overall operation of components of the electronic device (200) and commands or data related to components of the electronic device (200). In particular, the memory (220) may include instructions for controlling oral scanning software. The memory (120) may be implemented as a non-volatile memory (e.g., a hard disk, a solid state drive (SSD), a flash memory) or a volatile memory.

[0157] The processor (230) is electrically connected to the memory (220) and can control the overall functions and operations of the electronic device (200). The processor (230) can control the overall functions and operations of the electronic device (200) by executing instructions stored in the memory (220).

[0158] The processor (230) can generate a first maxillary model representing the maxilla based on maxillary depth data including depth information about the patient's maxilla. The processor (230) can generate a first mandibular model representing the mandible based on mandibular depth data including depth information about the patient's mandible.

[0159] The processor (230) can obtain occlusion data regarding the occlusion state of the maxilla and mandible. The occlusion data can be obtained by scanning the maxilla and mandible with an oral scanner (100) while the maxilla and mandible are in occlusion, obtained based on a pattern formed on an occlusion sheet, or set by a user of the oral scanner (100).

[0160] The processor (230) can generate an occlusion model representing the occlusion state of the maxilla and the mandible based on the maxillary depth data, the mandibular depth data, and the occlusion data. The occlusion model can include a second maxillary model and a second mandibular model. At least a part of the shape of the second maxillary model may be different from at least a part of the shape of the first maxillary model, or at least a part of the shape of the second mandibular model may be different from at least a part of the shape of the first mandibular model. The first maxillary model and the second maxillary model may differ in at least a part of surface information of teeth included in the maxilla, or at least a part of the relative positional relationship between teeth included in the maxilla. The first mandibular model and the second mandibular model may differ in surface information of teeth included in the mandible, or the relative positional relationship between teeth included in the mandible.

[0161] The processor (230) can optimize pose information of the oral scanner (100) corresponding to the maxillary depth data, the mandibular depth data, and the occlusion data. The processor (230) can generate an occlusion model based on the maxillary depth data, the mandibular depth data, and the pose information of the optimized oral scanner. The occlusion data can include occlusion depth data including depth information for the maxilla and the mandible in an occlusion state. If the depth information included in the occlusion depth data is different from the depth information included in the maxillary depth data or the mandibular depth data, the processor (230) can modify the pose information corresponding to the maxillary depth data or the mandibular depth data with the occlusion depth data as a priority.

[0162] The processor (230) can obtain a second maxillary model and a second mandibular model by modifying at least one of the first maxillary model and the first mandibular model based on the occlusion data.

[0163] The processor (230) can align the first maxillary model and the first mandibular model based on the occlusion data to create an initial occlusion model. The processor (230) can control the display (240) to display the initial occlusion model. The initial occlusion model can include the first maxillary model and the first mandibular model whose shapes have not been changed.

[0164] The processor (230) may generate an occlusion model when user input for optimizing the initial occlusion model is obtained through a user interface. Alternatively, the processor (230) may automatically generate an occlusion model when the accuracy of the initial occlusion model is determined to be less than a predetermined value.

[0165] The processor (230) can generate an occlusion model in real time while occlusion data is being acquired and display it on the display (240).

[0166] Any other operations performed by the electronic device (200) may be considered to be performed by the processor (230) unless otherwise specified.

[0167] The display (240) can display various information under the control of the processor (230). For example, the display (240) can display a 3D model representing the patient's oral structure.

[0168] Although not shown, the electronic device (200) may include an input / output interface (I / O interface) that is connected to an input / output device. For example, the I / O interface may include a USB and Bluetooth connection to a mouse. The processor (230) may receive user input through the I / O interface.

[0169] Although the preferred embodiments of the present disclosure have been illustrated and described above, the present disclosure is not limited to the specific embodiments described above, and various modifications may be made by a person skilled in the art to which the present disclosure pertains without departing from the gist of the present disclosure as claimed in the claims, and such modifications should not be understood individually from the technical idea or prospect of the present disclosure.

[0170] The various embodiments described above may be implemented in a computer-readable recording medium using software, hardware, or a combination thereof, or a computer or similar device. In some cases, the embodiments described herein may be implemented in the processor itself. When implemented in software, the embodiments, such as the procedures and functions described herein, may be implemented as separate software modules. Each of the software modules may perform one or more functions and operations described herein.

[0171] Computer instructions for performing processing operations according to the various embodiments of the present disclosure described above may be stored on a non-transitory computer-readable medium. When executed by a processor, the computer instructions stored on the non-transitory computer-readable medium may cause a specific device to perform processing operations according to the various embodiments described above.

[0172] A non-transitory computer-readable medium refers to a medium that permanently stores data and can be read by a device, rather than a medium that stores data for a short period of time, such as a register, cache, or memory. Specific examples of non-transitory computer-readable media include CDs, DVDs, hard disks, Blu-ray discs, USBs, memory cards, and ROMs.

[0173] A device-readable storage medium may be provided in the form of a non-transitory storage medium. Here, the term "non-transitory storage medium" simply means a tangible device that does not contain signals (e.g., electromagnetic waves). This term does not distinguish between cases where data is permanently stored in the storage medium and cases where data is temporarily stored. For example, a "non-transitory storage medium" may include a buffer in which data is temporarily stored.

[0174] The methods according to various embodiments disclosed in this document may be provided as included in a computer program product. The computer program product may be traded as a product between a seller and a buyer. The computer program product may be distributed in the form of a machine-readable storage medium (e.g., compact disc read-only memory (CD-ROM)), or may be distributed online (e.g., downloaded or uploaded) via an application store (e.g., Play Store™) or directly between two user devices (e.g., smartphones). In the case of online distribution, at least a portion of the computer program product (e.g., a downloadable app) may be temporarily stored or temporarily generated in a machine-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or an intermediary server.

Claims

1. A step of generating a first maxillary model representing the maxilla based on maxillary depth data including depth information about the maxilla; A step of generating a first mandibular model representing the mandible based on mandibular depth data including depth information about the mandible; A step of obtaining occlusion data regarding the occlusion status of the upper jaw and the lower jaw; and A step of generating an occlusion model representing the occlusion state of the upper jaw and the lower jaw based on the upper jaw depth data, the lower jaw depth data, and the occlusion data; The above occlusion model is, Including a second maxillary model and a second mandibular model, At least a portion of the shape of the second maxillary model is different from at least a portion of the shape of the first maxillary model, or at least a portion of the shape of the second mandibular model is different from at least a portion of the shape of the first mandibular model. How to create an intraoral model.

2. In paragraph 1, The steps for creating the above occlusion model are: A step of obtaining the second maxillary model and the second mandibular model by modifying at least one of the first maxillary model and the first mandibular model based on the occlusion data, How to create an intraoral model.

3. In paragraph 1, The steps for creating the above occlusion model are: A step of optimizing at least a portion of pose information corresponding to at least one of the upper jaw depth data and the lower jaw depth data based on the above occlusion data, and A step of generating the occlusion model based on the upper jaw depth data, the lower jaw depth data, and the optimized pose information, How to create an intraoral model.

4. In paragraph 3, The above occlusion data is, Includes occlusion depth data including depth information for the upper jaw and the lower jaw in the occlusion state, The step of optimizing at least part of the above pose information is: In a case where the depth information included in the above occlusion depth data is different from the depth information included in the upper jaw depth data or the lower jaw depth data, a step of modifying the pose information corresponding to the upper jaw depth data or the lower jaw depth data based on the above occlusion depth data is included. How to create an intraoral model.

5. In paragraph 1, The above occlusion data is, Obtained by scanning the upper and lower jaws with an oral scanner while the upper and lower jaws are in an occlusion state, or obtained based on a pattern formed on an occlusion sheet, or set by a user of the oral scanner. How to create an intraoral model.

6. In paragraph 1, The above first maxillary model and the above second maxillary model, At least part of the surface information of the teeth included in the upper jaw is different, At least some of the relative positional relationships between the teeth included in the upper jaw are different, How to create an intraoral model.

7. In paragraph 1, A step of aligning the first maxillary model and the first mandibular model based on the occlusion data to create an initial occlusion model; and further comprising a step of displaying the initial occlusion model; The above initial occlusion model is, including the first maxillary model and the first mandibular model, How to create an intraoral model.

8. In paragraph 7, The above occlusion model is, When an optimization command for the initial occlusion model is entered through the user interface, it is generated. How to create an intraoral model.

9. In paragraph 7, The above occlusion model is, If the accuracy of the initial occlusion model is determined to be less than a predetermined value, How to create an intraoral model.

10. In paragraph 1, If the above occlusion data is obtained through an occlusion scan that scans the occlusion state of the upper jaw and the lower jaw, The above occlusion model is, While the above occlusion scan is being performed, it is generated and displayed in real time. How to create an intraoral model.

11. In electronic devices, A communication interface comprising at least one communication circuit; memory containing at least one instruction; and Processor; including; The processor executes at least one instruction, A first maxillary model representing the maxilla is generated based on maxillary depth data including depth information about the maxilla, Generating a first mandibular model representing the mandible based on mandibular depth data including depth information about the mandible, Obtaining occlusion data regarding the occlusion status of the upper and lower jaws, Generate an occlusion model representing the occlusion state of the upper jaw and the lower jaw based on the upper jaw depth data, the lower jaw depth data, and the occlusion data, The above occlusion model is, Including a second maxillary model and a second mandibular model, At least a portion of the shape of the second maxillary model is different from at least a portion of the shape of the first maxillary model, or at least a portion of the shape of the second mandibular model is different from at least a portion of the shape of the first mandibular model. Electronic devices.

12. In paragraph 11, The above processor, At least one of the first maxillary model and the first mandibular model is modified based on the occlusion data to obtain the second maxillary model and the second mandibular model. Electronic devices.

13. In paragraph 11, The above processor, Optimizing at least a portion of pose information corresponding to at least one of the upper jaw depth data and the lower jaw depth data based on the above occlusion data, Generating the occlusion model based on the maxillary depth data, the mandibular depth data, and the pose information of the optimized oral scanner. Electronic devices.

14. In paragraph 13, The above occlusion data is, Includes occlusion depth data including depth information for the upper jaw and the lower jaw in the occlusion state, The above processor, If the depth information included in the above occlusion depth data is different from the depth information included in the upper jaw depth data or the lower jaw depth data, the pose information corresponding to the upper jaw depth data or the lower jaw depth data is modified based on the above occlusion depth data. Electronic devices.

15. A step of obtaining a 3D model of the maxilla using 3D point clouds of the maxilla obtained through a maxilla scan that scans the maxilla; A step of obtaining a 3D model of the mandible using 3D point clouds of the mandible obtained through a mandibular scan that scans the mandible; A step of acquiring 3D occlusion point clouds through an occlusion scan that scans the occlusion state of the maxilla and mandible; and A step of optimizing at least a part of the connection relationship between the upper jaw 3D point clouds or at least a part of the connection relationship between the lower jaw 3D point clouds based on the above occlusion 3D point clouds; How to optimize depth data.

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