Region determination method and 3D model processing device

Abstract

This invention relates to a region determination method and a three-dimensional model processing apparatus. One aspect of this disclosure provides a region determination method for determining a region corresponding to an object from a three-dimensional model relating to the oral cavity. The region determination method includes the following steps: acquiring the three-dimensional model; determining seed points on the three-dimensional model; determining reference points on the three-dimensional model based on the seed points; gradually expanding a selection area based on the reference points to determine a region corresponding to the object; and displaying the determined region on the three-dimensional model.

Description

Technical Field

[0001] This disclosure relates to a method and apparatus for processing a three-dimensional model, and more specifically, to a method and apparatus for determining a region corresponding to an object body from a three-dimensional model relating to the oral cavity. Background Technology

[0002] Dental computer-aided design / computer-aided manufacturing (CAD / CAM) technology has been widely used in dental treatment, especially in fillings. The most important aspect of using CAD / CAM in dental treatment is obtaining precise three-dimensional data of the patient's teeth, gums, jawbone, and other physical features. During dental treatment, utilizing this three-dimensional data allows for accurate calculations via computer.

[0003] For example, in dental CAD / CAM treatment, in order to obtain three-dimensional data of the object, methods such as computed tomography (CT), magnetic resonance imaging (MRI), and optical scanning can be used.

[0004] In the field of dental CAD / CAM, 3D scanning devices are widely used. These devices acquire 3D surface shape information using light reflected from an object; for example, they can acquire tooth impressions, plaster models of those impressions, or 3D models of tooth surfaces. Surface data is recorded as a polygonal mesh and can include the positional information of the object's surface vertices and the connectivity between them. Alternatively, surface data can be recorded as a point cloud and can also include the positional information of the object's surface vertices. Summary of the Invention

[0005] The problem the invention aims to solve

[0006] When a 3D model is obtained from scan data of oral cavity and plaster models, the obtained model can be used to virtually design prostheses or develop orthodontic plans.

[0007] To design virtual prostheses and orthodontic plans, information about the object (e.g., a single tooth, gum, etc.) is required. Therefore, information such as the object region can be attached to the 3D model.

[0008] However, in the past, selecting the object's region involved manually selecting the corresponding area from the 3D model. This process, however, was time-consuming and involved setting unnecessary regions.

[0009] means for solving problems

[0010] One aspect of this disclosure provides a region determination method for determining a region corresponding to an object from a three-dimensional model of the oral cavity, wherein the region determination method includes the following steps: acquiring the three-dimensional model, determining seed points on the three-dimensional model, determining reference points on the three-dimensional model based on the seed points, gradually expanding the selection area based on the reference points to determine the region corresponding to the object, and displaying the determined region on the three-dimensional model.

[0011] In addition, one embodiment of this disclosure provides a region determination method, wherein the step of determining the reference point includes the following steps: determining the reference point based on the curvature value of the seed point.

[0012] In addition, one embodiment of this disclosure provides a region determination method, characterized in that the three-dimensional model is acquired by a three-dimensional scanning device and includes surface shape information of multiple teeth and gums in the oral cavity, wherein the object is a tooth or gum.

[0013] In addition, one embodiment of this disclosure provides a region determination method, wherein the step of determining the seed point includes the following steps: displaying the three-dimensional model, and determining the seed point based on user input to the displayed three-dimensional model.

[0014] Additionally, one embodiment of this disclosure provides a region determination method, wherein the step of determining the reference point includes the following steps: determining the reference point based on the curvature value of the seed point determined on the three-dimensional model; the curvature value of the seed point includes at least one of curvature value k1 and curvature value k2, wherein the curvature value k1 is the curvature value with the largest absolute value among the curvature values ​​realized by the curve intersecting the normal plane including the normal of the seed point and the surface of the object, and the curvature value k2 is the curvature value realized by the curve intersecting the curve of the orthogonal normal plane including the normal of the seed point and the surface of the object.

[0015] In addition, one embodiment of this disclosure provides a region determination method, wherein the step of determining the reference point includes the following steps: when the curvature value of the seed point determined on the three-dimensional model has a value within a predetermined range, the seed point is determined as a reference point; and when the curvature value of the seed point does not have a value within the predetermined range, other points with curvature values ​​within the predetermined range are determined as reference points.

[0016] In addition, one embodiment of this disclosure provides a region determination method, wherein the step of determining a region corresponding to the object body includes the following steps: determining a first region with curvature values ​​within a critical range based on the curvature value of the reference point by gradually expanding the selected region from the reference point.

[0017] In addition, one embodiment of this disclosure provides a region determination method, wherein the step of determining the region corresponding to the object body further includes the following step: repeatedly expanding and shrinking the determined first region to determine the second region corresponding to the object body.

[0018] Additionally, one embodiment of this disclosure provides a region determination method, wherein the step of determining a region corresponding to the object body includes the following steps: determining a first region with curvature values ​​within a critical range based on the curvature value of the reference point by gradually expanding the selected region from the reference point; the region determination method further includes the following steps: changing the critical range based on the user's drag input, and determining a second region based on the changed critical range.

[0019] In addition, one embodiment of this disclosure provides a region determination method, wherein the step of determining the seed point includes the following steps: dividing the three-dimensional model into multiple regions corresponding to multiple objects, and determining the seed point in one of the multiple regions.

[0020] Additionally, one embodiment of this disclosure provides a region determination method, wherein the region determination method further includes the following steps: displaying an image on the three-dimensional model showing multiple teeth and tooth numbers corresponding to each tooth, and receiving user input for selecting a first tooth among the multiple teeth as the object; the step of determining the reference point includes the following steps: determining the reference point on the first tooth.

[0021] Another aspect of this disclosure provides a three-dimensional model processing apparatus for processing a three-dimensional model of a mouth, wherein the three-dimensional model processing apparatus includes: a display for displaying an image rendered from the three-dimensional model, and at least one processor for determining seed points on the three-dimensional model, determining reference points on the three-dimensional model based on the seed points, progressively expanding a selection area based on the reference points to determine a region corresponding to an object, and controlling the display to display the determined region on the three-dimensional model.

[0022] In addition, one embodiment of this disclosure provides a three-dimensional model processing apparatus, characterized in that the display shows the three-dimensional model, and the at least one processor determines the seed points based on user input to the displayed three-dimensional model.

[0023] In addition, one embodiment of this disclosure provides a three-dimensional model processing apparatus, characterized in that the at least one processor determines a first region with curvature values ​​within a critical range based on the curvature value of the reference point by gradually expanding the selected region from the reference point, and repeatedly performs region expansion and contraction processing from the determined first region to determine a second region corresponding to the object.

[0024] In addition, one embodiment of this disclosure provides a three-dimensional model processing device, characterized in that the display shows an image of a plurality of teeth and tooth numbers corresponding to each tooth on the three-dimensional model, and the at least one processor receives user input for selecting a first tooth among the plurality of teeth as the object, and determines the reference point on the first tooth.

[0025] Another aspect of this disclosure provides a region determination method for determining a region from a three-dimensional model, wherein the region determination method includes the following steps: acquiring a three-dimensional model of an oral cavity, determining at least a portion of the regions to be selected within the oral cavity, determining a first region corresponding to the region to be selected from the three-dimensional model based on the determined at least a portion of the regions, and displaying the determined first region.

[0026] In addition, one embodiment of this disclosure provides a region determination method, wherein the step of determining the at least a portion of the region includes the following step: determining the at least a portion of the region based on user input.

[0027] In addition, one embodiment of this disclosure provides a region determination method, wherein the user input includes at least one action among clicking, hovering, and dragging.

[0028] In addition, one embodiment of this disclosure provides a region determination method, wherein the region determination method further includes the following steps: dividing the three-dimensional model into multiple regions corresponding to multiple teeth respectively; the step of determining the at least a portion of the regions includes the following steps: based on the divided three-dimensional model, selecting one of the multiple teeth, and determining the at least a portion of the regions based on seed points on the selected tooth.

[0029] Another aspect of this disclosure provides a region determination method for determining a region corresponding to an object from a three-dimensional model of the oral cavity. The region determination method includes the following steps: acquiring the three-dimensional model; determining seed points on the three-dimensional model; determining the seed points as reference points when the curvature values ​​of the seed points determined on the three-dimensional model are within a predetermined range; gradually expanding the selection area by selecting adjacent points whose curvature values ​​differ from the reference points within a critical range, thereby determining the region corresponding to the object; and displaying the determined region on the three-dimensional model.

[0030] Another aspect of this disclosure provides a three-dimensional model processing apparatus for processing a three-dimensional model of a dental cavity, wherein the three-dimensional model processing apparatus includes: a display for displaying an image rendered from the three-dimensional model; and at least one processor for determining seed points on the three-dimensional model, determining the seed points as reference points when the curvature values ​​of the seed points determined on the three-dimensional model are within a predetermined range, gradually expanding the selection area by selecting adjacent points whose curvature values ​​differ from the reference points within a critical range, thereby determining a region corresponding to an object body, and controlling the display to display the determined region on the three-dimensional model.

[0031] Invention Effects

[0032] According to the disclosed embodiments, the accuracy of selecting object regions can be improved and the required time can be shortened. Attached Figure Description

[0033] The present invention can be readily understood by taking into account the following detailed description and the corresponding drawings, and the reference numerals denote structural elements.

[0034] Figure 1 This is a diagram illustrating a three-dimensional model processing system of one embodiment.

[0035] Figure 2 This is a diagram illustrating a method for manually selecting the outer contour of a single tooth.

[0036] Figure 3 This is a block diagram illustrating an embodiment of a three-dimensional model processing system.

[0037] Figure 4 A flowchart illustrating a method for determining an object volume region from a 3D model using a 3D model processing apparatus according to an embodiment is shown.

[0038] Figure 5 This is a graph used to illustrate the curvature values ​​calculated from a seed point according to one embodiment.

[0039] Figure 6a This is a graph that uses color to represent the k1 values ​​of points on a tooth.

[0040] Figure 6b A graph showing the distribution of k1 values ​​on the tooth surface is displayed.

[0041] Figure 7 The image shows a seed point and a reference point selected on a tooth according to one embodiment.

[0042] Figure 8 This is a diagram illustrating the reference points determined for selecting a tooth region according to one embodiment.

[0043] Figure 9a It is a diagram representing a region with curvature values ​​within a critical range on a three-dimensional model of multiple teeth, according to one embodiment.

[0044] Figure 9b This is a diagram showing a sporadic selection of tooth regions according to one embodiment.

[0045] Figure 10a This is a diagram illustrating a method for expanding a tooth selection area according to one embodiment.

[0046] Figure 10b A diagram showing an enlarged tooth region according to one embodiment.

[0047] Figure 10c This is a diagram illustrating a method for shrinking an enlarged tooth region according to one embodiment.

[0048] Figure 10d A diagram showing the final tooth region determined according to one embodiment through a process of region expansion and reduction.

[0049] Figure 11a This is a diagram illustrating a method for expanding the tooth selection area based on user drag input according to an embodiment.

[0050] Figure 11b This is a diagram illustrating a method for expanding the tooth selection area based on user drag input according to an embodiment.

[0051] Figure 11c This is a diagram illustrating a method for expanding the tooth selection area based on user drag input according to an embodiment.

[0052] Figure 12 An example of a program's drive screen for a tooth region selection method applicable to one embodiment is shown.

[0053] Figure 13a An example of a program's drive screen for a tooth region selection method applicable to one embodiment is shown.

[0054] Figure 13b An example of a program's drive screen for a tooth region selection method applicable to one embodiment is shown.

[0055] Figure 13c An example of a program's drive screen for a tooth region selection method applicable to one embodiment is shown.

[0056] Figure 14 An example of a program's drive screen for a tooth region selection method applicable to one embodiment is shown.

[0057] Figure 15 A block diagram of a three-dimensional model processing apparatus according to an embodiment is shown. Detailed Implementation

[0058] The disclosed embodiments clarify the scope of the invention, describe the principles of the invention, and disclose embodiments to enable those skilled in the art to implement the invention. The disclosed embodiments can be implemented in various forms.

[0059] Throughout this specification, the same reference numerals refer to the same constituent elements. The disclosed embodiments do not illustrate all elements of the embodiments, and general content belonging to the technical field of the invention or repetitive content between embodiments is omitted. The term "part" (portion) as used in this specification can be implemented by software or hardware. According to embodiments, multiple "parts" can be implemented as a single element, or a single "part" can contain multiple elements. Hereinafter, the operating principle and embodiments of the invention are described with reference to the accompanying drawings.

[0060] In this disclosure, "object" refers to the subject being photographed and may include a person, an animal, or a part thereof. For example, an object may include a part of the body (organs or organs, etc.), an artificial structure or phantom that can be attached to or inserted into the object. For example, an object may include teeth, gums, at least a portion of the oral cavity and / or artificial structures that can be inserted into the oral cavity (e.g., orthodontic appliances including braces and wires, dental implants, artificial teeth, dental restorations including inlays and high-mounted inlays, orthodontic aids inserted into the oral cavity, etc.), teeth or gums with attached artificial structures, etc.

[0061] In this disclosure, "image" can be a two-dimensional image of an object or a three-dimensional model or image representing the object in a three-dimensional form. In this disclosure, an image can include both two-dimensional frames and three-dimensional frames. For example, an image can include: a two-dimensional frame, including two-dimensional images of an object acquired from different viewpoints; or a three-dimensional frame, represented in the form of a point cloud or a polygonal mesh.

[0062] Additionally, in this disclosure, "data" can refer to information required to represent an object in two or three dimensions, such as raw data acquired from at least one image sensor. Specifically, raw data can be two-dimensional images acquired to generate a three-dimensional model of the object. Raw data can be two-dimensional images acquired from different viewpoints using multiple image sensors when scanning the object with a 3D scanner (e.g., an intraoral scanner). Furthermore, in this disclosure, "data" can refer to a three-dimensional model representing the three-dimensional characteristics of an object, which includes at least one of teeth, gums, and artificial structures attached to teeth or gums.

[0063] Hereinafter, embodiments will be described in detail with reference to the accompanying drawings.

[0064] Figure 1 This is a diagram illustrating a three-dimensional model processing system of one embodiment.

[0065] like Figure 1 As shown, a three-dimensional model processing system according to an embodiment of the present disclosure includes a three-dimensional scanning device 100 and a three-dimensional model processing device 300.

[0066] One embodiment of the three-dimensional model processing system uses a three-dimensional scanning device 100 to project patterned light onto an object, and obtains a three-dimensional model representing the shape of the object by scanning the object illuminated by the patterned light and utilizing the triangulation principle caused by pattern deformation. However, the method of obtaining a three-dimensional model by the three-dimensional scanning device 100 is not limited to this, and a variety of methods can be used to obtain the three-dimensional model depending on the implementation.

[0067] One embodiment of the 3D scanning apparatus 100 can transmit raw data acquired from an object to a 3D model processing apparatus 300. The 3D model processing apparatus 300 can generate a 3D model representing the surface shape of the object based on the received raw data. The 3D model can be point cloud data or polygon mesh data. Another embodiment of the 3D scanning apparatus 100 can reassemble the raw data acquired from the object to generate a 3D frame, and transmit the generated 3D frame to the 3D model processing apparatus 300.

[0068] One embodiment of the three-dimensional scanning device 100 may include a medical device for acquiring a three-dimensional model of the oral cavity. Specifically, the three-dimensional scanning device 100 is a device for inserting into the oral cavity and scanning teeth non-contactly to acquire a three-dimensional model of the oral cavity, which includes at least one tooth. Furthermore, the three-dimensional scanning device 100 may be designed to be inserted into and withdrawable from the oral cavity, and utilizes at least one image sensor (e.g., an optical camera) to scan the interior of the patient's oral cavity. Additionally, the three-dimensional scanning device 100 may be a desktop scanner.

[0069] The 3D scanning device 100 images the surface of at least one of the following: teeth, gums, and artificial structures that can be inserted into the oral cavity (e.g., orthodontic appliances including braces and wires, crowns, artificial teeth, orthodontic aids inserted into the oral cavity). This acquires surface information about the object as raw data. The 3D model processing device 300 performs 3D calculations such as merging based on the raw data to obtain a 3D model and displays an image of the rendered 3D model on a screen.

[0070] In one embodiment, the three-dimensional model processing device 300 can be connected to the three-dimensional scanning device 100 via a wired or wireless communication network, and can receive raw data or three-dimensional frames obtained from the scanned object from the three-dimensional scanning device 100.

[0071] The 3D model processing device 300 can be any electronic device that generates, processes, displays, and / or transmits a 3D model or image of an object based on received raw data or 3D frames. For example, the 3D model processing device 300 can be a computing device such as a smartphone, laptop, desktop computer, PDA, tablet computer, etc., but is not limited thereto.

[0072] The three-dimensional model processing device 300 can generate at least one of the information required for the diagnosis of the object and the image of the object based on the data received from the three-dimensional scanning device 100, and display the generated information and / or image on the display 320.

[0073] One embodiment of the three-dimensional model processing apparatus 300 can analyze a three-dimensional model or image of an object and can process, display and / or transmit the analysis results.

[0074] Additionally, in one embodiment, the 3D model processing device 300 can store and run dedicated software linked to the 3D scanning device 100. This dedicated software can be referred to as a dedicated program or a dedicated application. When the 3D model processing device 300 and the 3D scanning device 100 operate in conjunction, the dedicated software stored in the 3D model processing device 300 can connect to the 3D scanning device 100 and receive data acquired through scanning the object in real time. For example, in the i500, which corresponds to the company's i500 dental scanner, there is dedicated software for processing data acquired through dental scanning. The 3D model processing device 300 can store and run the dedicated software corresponding to the i500 product. The dedicated software can perform at least one action for acquiring, processing, storing, and / or transmitting a 3D model.

[0075] The dedicated software may be stored in the processor or memory of the 3D model processing apparatus 300. Additionally, the dedicated software may provide a user interface for using data obtained in the 3D scanning apparatus 100. The user interface screen provided in the dedicated software may include a 3D model of the object generated according to the disclosed embodiments. For example, in the disclosed embodiments, the user interface screen provided in the dedicated software may be any of the user interface screens shown in the accompanying drawings.

[0076] On the other hand, in order to design virtual prostheses and orthodontic plans, information about individual teeth may be needed, for example. Previously, to select the area corresponding to a single tooth, the tooth shape was manually selected from a 3D model of multiple teeth.

[0077] Figure 2 This is a diagram illustrating a method for manually selecting the outer contour of a single tooth.

[0078] like Figure 2 As shown, conventionally, users manually select the boundary region of the tooth 210 on the 3D model image 200. When the user selects a point on the boundary of the tooth 210, the 3D model processing device obtains the outer line 205 by connecting the points selected by the user, thereby determining the individual tooth region. Therefore, according to the prior art, the problem is that manually selecting a single tooth takes a lot of time or may result in the selection of unnecessary areas.

[0079] To address this problem, a method is proposed for the three-dimensional model processing apparatus 300 according to various embodiments of the present disclosure, which can quickly and automatically select object volume regions with high accuracy.

[0080] Figure 3 This is a block diagram illustrating an embodiment of a three-dimensional model processing system.

[0081] like Figure 3 As shown, a 3D model processing apparatus 300 of one embodiment can be connected to an external device or an external server via a wired or wireless communication network. The 3D model processing apparatus 300 of one embodiment can acquire and process data about an object from at least one of a 3D scanning device 31, a data acquisition device 32 (e.g., a medical diagnostic device such as a CT or MRI scanner), and a server 33. Alternatively, the 3D model processing apparatus 300 of one embodiment can acquire and process data pre-stored in its internal memory.

[0082] According to various embodiments of this disclosure, the three-dimensional model processing apparatus 300 can determine regions corresponding to at least one object from a three-dimensional model of the oral cavity. One embodiment of the three-dimensional model processing apparatus 300 can acquire a three-dimensional model of the oral cavity and determine at least a portion of the regions to be selected within the oral cavity. Another embodiment of the three-dimensional model processing apparatus 300 can determine at least a portion of the region based on user input. For example, user input may include at least one action among clicking, hovering, and dragging.

[0083] For example, the 3D model processing device 300 can divide the 3D model into multiple regions, each corresponding to a plurality of teeth. Based on the divided 3D model, the 3D model processing device 300 can select one tooth from the plurality of teeth. The 3D model processing device 300 can determine at least a portion of the region based on seed points on the selected tooth.

[0084] The 3D model processing device 300 can determine a first region corresponding to the region to be selected from the 3D model based on at least a defined portion of the region. The 3D model processing device 300 can display the determined first region.

[0085] The specific methods for selecting the object volume region using the 3D model processing device 300 according to various embodiments will be referred to below. Figures 4 to 14 Further details.

[0086] Figure 4 A flowchart illustrating a method for determining an object volume region from a 3D model using a 3D model processing apparatus according to an embodiment is shown.

[0087] In step S401, the three-dimensional model processing apparatus 300 of one embodiment can acquire a three-dimensional model of the oral cavity. For example, a three-dimensional model can be acquired, which includes surface shape information of multiple teeth, gums, and / or artificial structures within the oral cavity. For example, the three-dimensional model can be scan data acquired by a three-dimensional scanning device. The three-dimensional model processing apparatus 300 can acquire the three-dimensional model from an external device such as a three-dimensional scanning device or an external server. Alternatively, the three-dimensional model processing apparatus 300 can acquire a three-dimensional model pre-stored in its internal memory.

[0088] One embodiment of the three-dimensional model processing apparatus 300 can select seed points on a three-dimensional model that are inferred to correspond to an object. A seed point is a point selected to determine the region corresponding to the object. For example, the three-dimensional model processing apparatus 300 can select a seed point on the first tooth among a plurality of teeth represented by the three-dimensional model.

[0089] As an example, the 3D model processing device 300 can select seed points based on user input.

[0090] To receive user input selecting a seed point, the 3D model processing device 300 first displays an image rendered from the 3D model on a screen. The 3D model processing device 300 displays the 3D model, receives user input selecting a point on the displayed 3D model, and determines a seed point on the 3D model based on the location of the selected point.

[0091] Figure 7 This shows a portion of the three-dimensional model displayed by the three-dimensional model processing device 300. The three-dimensional model processing device 300 can receive user input to select a seed point 701 on the three-dimensional model.

[0092] In order to select a seed point in three-dimensional space based on user input to an image displayed on a 2D screen, the 3D model processing device 300 can determine the 3D coordinate values ​​corresponding to the location of the received user input. For example, user input for selecting a seed point may include: a tapping action on a touch screen, an action of positioning the mouse pointer within the screen (e.g., hovering), an action of positioning the mouse pointer within the screen and clicking, or an action of clicking and then dragging the mouse, etc.

[0093] For example, the 3D model processing apparatus 300 can obtain the x and y coordinate values ​​of the displayed image in the screen coordinate system based on the position of the user's mouse click input. The 3D model processing apparatus 300 transforms the obtained x and y coordinate values ​​into the coordinate system of the 3D model and determines seed points within the 3D model represented by a triangular mesh. The 3D model processing apparatus 300 can determine the vertices corresponding to the transformed coordinate values ​​as seed points.

[0094] As another example, the 3D model processing device 300 can automatically select seed points by analyzing the 3D model.

[0095] As another example, the 3D model processing device 300 can select a region as a seed point.

[0096] One embodiment of the three-dimensional model processing apparatus 300 can divide a three-dimensional model into regions corresponding to multiple object bodies. The three-dimensional model processing apparatus 300 can determine a seed point on one of the multiple regions identified through the division.

[0097] Specifically, the 3D model processing device 300 can divide a 3D model. As an example, the 3D model processing device 300 can use templates or artificial intelligence to divide the 3D model into regions corresponding to at least one tooth and regions corresponding to the gums, and can also divide regions relating to multiple teeth into regions corresponding to a single tooth.

[0098] However, existing methods for selecting regions corresponding to a predetermined object (e.g., teeth or gums) by dividing a 3D model have limitations in accurately selecting regions corresponding to the object. Depending on the scanner's noise or resolution, the tooth region determined by division may include only a portion of the actual tooth region, or it may include regions outside the actual tooth region. Therefore, existing methods have limitations in accurately identifying the region of a single tooth. Therefore, a 3D model processing apparatus 300 of one embodiment can select seed points on the regions inferred to correspond to the object by the division after performing the first division. This embodiment can be performed without user input.

[0099] In step S402, a three-dimensional model processing apparatus 300 of one embodiment can determine a reference point on the three-dimensional model. The three-dimensional model processing apparatus 300 of one embodiment can determine the reference point on the three-dimensional model based on the curvature value of a seed point.

[0100] Curvature is an indicator of the degree of curvature of a surface, and can be expressed as the reciprocal of the surface radius. The curvature value of a predetermined point on the surface of an object can represent the degree of curvature of at least one curve that passes through the predetermined point and is defined on the surface of the object. In this case, the degree of curvature of the curve passing through the predetermined point can change depending on the direction. Therefore, the three-dimensional model processing apparatus 300 of one embodiment can determine the maximum curvature value as the curvature value of the predetermined point, but this disclosure is not limited thereto.

[0101] When the curvature value of a seed point determined on a 3D model is within a predetermined range, the 3D model processing apparatus 300 of one embodiment can determine the seed point as a reference point. Conversely, when the curvature value of the seed point is not within the predetermined range, the 3D model processing apparatus 300 can determine other points with curvature values ​​within the predetermined range as reference points.

[0102] As another example, when the seed point is a defined area (e.g., a divided area), the 3D model processing device 300 can determine at least one reference point within that area. When there is more than one reference point, the area corresponding to the object body is determined by merging the selected areas from each reference point.

[0103] In step S403, the three-dimensional model processing apparatus 300 of one embodiment can determine the region corresponding to the object body by gradually expanding the selected area based on a reference point. The three-dimensional model processing apparatus 300 can determine the region corresponding to the object body by gradually expanding the selected area based on the curvature value of the reference point.

[0104] The three-dimensional model processing device 300 can determine the region corresponding to the object body with curvature values ​​within a critical range based on the curvature values ​​of the reference point.

[0105] As a reference value for selecting the object volume region, the three-dimensional model processing device 300 may use the k1 value of the reference point, or simultaneously use the k1 value and the k2 value, or use the smaller value of the k1 value and the k2 value.

[0106] In another embodiment, the three-dimensional model processing apparatus 300 can determine a first region corresponding to an object with curvature values ​​within a critical range based on the curvature values ​​of a reference point. The three-dimensional model processing apparatus 300 determines a second region corresponding to the object by repeatedly performing region expansion and contraction processing within the determined first region. The three-dimensional model processing apparatus 300 can then determine the second region as the final region corresponding to the object.

[0107] At this point, the 3D model processing device 300 can change the critical range for determining the curvature value of the object's volume region based on the user's drag input. The 3D model processing device 300 can then determine the region corresponding to the object based on the changed critical range.

[0108] In step S404, the three-dimensional model processing apparatus 300 of one embodiment can display regions on the three-dimensional model that are determined to correspond to the object. The three-dimensional model processing apparatus 300 can use color, shading, lines, or textures to distinguish between regions that represent regions determined to correspond to the object and other regions.

[0109] The following description will use the case of determining the region corresponding to a first tooth from a three-dimensional model of multiple teeth as an example to illustrate the specific method of operation of this disclosure. However, various embodiments of this disclosure are not limited to determining tooth regions on a three-dimensional model. As mentioned above, the method of this disclosure can also be applied to determine regions corresponding to at least one of teeth, gingiva, and artificial structures. Repeated descriptions will be omitted.

[0110] Figure 5 This is a graph used to illustrate the curvature values ​​calculated from a seed point according to one embodiment.

[0111] One embodiment of the three-dimensional model processing apparatus 300 can calculate the curvature value of seed point 501.

[0112] The 3D model processing apparatus 300 can calculate the curvature value of the curve intersected by the normal plane, which includes the normal vector 531 (or normal line) of the seed point 501, and the tooth surface 520. The 3D model processing apparatus 300 can determine that, among the calculated curvature values, the absolute value of the curvature value k1 of the curve intersected by the first normal plane 542 and the tooth surface 520 is the largest. Additionally, the 3D model processing apparatus 300 can calculate the curvature value k2 of the curve intersected by the normal plane 544, which is orthogonal to the first normal plane 542 and includes the normal vector of the seed point 501, and the tooth surface 520. The 3D model processing apparatus 300 can use at least one of the values ​​k1 and k2 as the curvature value of the seed point 501.

[0113] Figure 6a This is a graph that uses color to represent the k1 values ​​of points on a tooth.

[0114] like Figure 6a As shown, points on the cusps (the raised areas within a tooth) have relatively large k1 values ​​and are therefore displayed in red. Conversely, points on the grooves (the recessed areas within a tooth) and on the boundaries between the tooth and gum have relatively small k1 values ​​and are displayed in blue.

[0115] Figure 6b A graph showing the distribution of k1 values ​​on the tooth surface is displayed. More specifically, Figure 6b It can be a graph representing the frequency distribution of k1 values ​​at points on the tooth surface across different intervals.

[0116] Reference Figure 6b It is known that points on the tooth surface have a similar distribution centered around the average value, and most points have a k1 value within a predetermined range. Therefore, a three-dimensional model processing device 300 of one embodiment can identify a region including points with curvature values ​​(e.g., k1 values) within a predetermined range as a tooth region.

[0117] At this point, accuracy depends on which point is used as a reference to select the tooth region. For example, if the user selects a seed point at the cusp of the tooth, the tooth region can be selected relatively accurately; conversely, if the user selects a seed point at the groove of the tooth, the tooth region can be selected relatively inaccurately.

[0118] Therefore, the 3D model processing apparatus 300 can improve the accuracy of region selection by determining a reference point for selecting a tooth region based on the curvature value of the seed point. In one embodiment, the 3D model processing apparatus 300 can determine the seed point as the reference point when the curvature value of the seed point is within a predetermined range. Conversely, when the curvature value of the seed point is not within the predetermined range, the 3D model processing apparatus 300 can determine other points with curvature values ​​within the predetermined range as reference points. The 3D model processing apparatus 300 can also determine the point closest to the seed point among points with curvature values ​​within the predetermined range as the reference point.

[0119] When the curvature value of the selected seed point does not fall within a predetermined range, the 3D model processing apparatus 300 can search for the point closest to the seed point among points whose curvature values ​​fall within the predetermined range. For example, the predetermined range could be the range of curvature values ​​represented by the cusp region of a tooth. The 3D model processing apparatus 300 can search for points within a specified distance (e.g., 0.01 to 0.02 mm) from the seed point, and gradually expand the search area, while simultaneously determining the points whose curvature values ​​fall within the predetermined range as reference points.

[0120] Figure 7 The image shows a seed point and a reference point selected on a tooth according to one embodiment.

[0121] like Figure 7 As shown, when the seed point 701 selected by the user is located in the groove of a tooth, the k1 value of the seed point 701 is calculated to be very low. When the 3D model processing device 300 determines that the k1 value of the seed point 701 exceeds a predetermined range, it can determine other points as reference points. That is, since the selected seed point 701 is not a point on the cusp of the tooth, the 3D model processing device 300 can determine that other points should be used as reference points to select the tooth region. Therefore, the 3D model processing device 300 searches the surrounding area of ​​the seed point 701 and determines the point whose curvature value falls within the predetermined range and is closest to the seed point 701 as the reference point 703.

[0122] The reason for not using the seed point selected by the user as the reference point, but instead using points whose curvature values ​​fall within a predetermined range (e.g., the range of curvature values ​​in the cusp region) as the reference point, is that the accuracy of region selection can only be improved when tooth regions are selected based on points with curvature values ​​within the predetermined range.

[0123] Reference Figure 6a The images of teeth show points on the boundary between teeth and gums, with relatively low k1 values ​​shown in blue, while points in the tooth region mostly have k1 values ​​around the average and are shown in yellow.

[0124] In one embodiment, the three-dimensional model processing apparatus 300 expands the region centered on a reference point and selects regions with curvature values ​​within a critical range as tooth regions based on the curvature value of the reference point. Therefore, when the reference point is included in the blue region (i.e., the region with a relatively low k1 value), the three-dimensional model processing apparatus 300 can easily exceed the blue region when expanding the selected region from the reference point.

[0125] The following is for reference Figure 8 This is explained in detail by comparing the curvature values ​​of the reference point with those within the predetermined range and those outside the predetermined range.

[0126] Figure 8 This is a diagram illustrating the reference points determined for selecting a tooth region according to one embodiment.

[0127] Figure 8The diagram shows the range of k1 values ​​for the tooth boundary region and the range of k1 values ​​for the cusp region. One embodiment of the three-dimensional model processing apparatus 300 can use the range of k1 values ​​for the cusp region as a predetermined range for determining a reference point. However, this disclosure is not limited to the embodiment of "using the range of k1 values ​​for the cusp region as a predetermined range," and the predetermined range for determining the reference point can be determined in various ways.

[0128] like Figure 8 As shown, when the curvature value of the first reference point cp1 is within a predetermined range, the three-dimensional model processing device 300 can select the region with curvature values ​​within the critical range as the tooth region, based on the curvature value of the first reference point cp1. At this time, the region whose curvature value differs from that of the first reference point cp1 is within the critical range and will not exceed the tooth boundary.

[0129] On the other hand, if the curvature value of the second reference point cp2 is outside a predetermined range, the three-dimensional model processing device 300 can select regions with curvature values ​​within a critical range as tooth regions, based on the curvature value of the second reference point cp2. In this case, regions with curvature values ​​differing from the second reference point cp2 within the critical range may include a portion of the tooth boundary region; therefore, the region selected based on the second reference point cp2 may extend beyond the tooth boundary. Thus, in one embodiment, the three-dimensional model processing device 300 can determine reference points with k1 values ​​within a predetermined range (e.g., the range of k1 values ​​possessed by the cusp region).

[0130] For reference Figure 7 and Figure 8 As shown, the groove region and boundary region of the tooth on the upper surface of the tooth have low curvature values. Therefore, when selecting a region with a curvature value within a critical range based on the curvature value of a reference point, the groove region on the upper surface of the tooth may not be selected. Therefore, the three-dimensional model processing device 300 of one embodiment can select the final region corresponding to the tooth by repeatedly expanding and shrinking the region from sporadically selected tooth regions. Hereinafter, refer to Figures 9a to 10d This section provides a detailed explanation of the process of regional expansion and contraction.

[0131] Figure 9a It is a diagram representing a region with curvature values ​​within a critical range on a three-dimensional model of multiple teeth, according to one embodiment.

[0132] Figure 9aThis shows a portion of an image rendered from a 3D model. The 3D model processing apparatus 300 can determine regions with curvature values ​​within a critical range, based on the curvature values ​​of a reference point. The 3D model processing apparatus 300 can display the curvature values ​​within the critical range in a predetermined color (e.g., green) on a color bar 901, also based on the curvature values ​​of the reference point. Furthermore, the 3D model processing apparatus 300 can display the region 913 with curvature values ​​within the critical range in the same predetermined color.

[0133] Figure 9b This is a diagram showing a sporadic selection of tooth regions according to one embodiment.

[0134] Figure 9b A three-dimensional model represented by a triangular mesh is shown. In one embodiment, a three-dimensional model processing apparatus 300 gradually expands the selection area by selecting adjacent points whose curvature values ​​differ from the reference point within a critical range, starting from a reference point. When expanding the selection area, the three-dimensional model processing apparatus 300 stops expanding the selection area when it reaches the tooth boundary region because the difference in curvature values ​​from the reference point is above the critical range. Therefore, as... Figure 9b As shown, the 3D model processing device 300 can identify the boundary region between teeth and gums. However, the dental groove region, which is recessed on the upper surface of the tooth, is not included in the region initially selected by the 3D model processing device 300.

[0135] Therefore, in one embodiment, the three-dimensional model processing device 300 expands the selection area by filling the empty spaces of the sporadic selection areas.

[0136] Figure 10a This is a diagram illustrating a method for expanding a selection area according to one embodiment.

[0137] One embodiment of the three-dimensional model processing apparatus 300 can expand the selection area by selecting a triangular mesh 1013 adjacent to the boundary of a first selection area 1011.

[0138] Figure 10b A diagram showing an enlarged tooth region according to one embodiment.

[0139] like Figure 10b As shown, by expanding the selection area, you can select areas that were not previously selected. Figure 10b The enlarged tooth region 1022 shown does not include empty spaces.

[0140] Figure 10c This is a diagram illustrating a method for reducing an enlarged tooth region according to one embodiment.

[0141] In one embodiment, a three-dimensional model processing apparatus 300 narrows the selection region by excluding triangular meshes 1033 from the selection region, the triangular meshes 1033 being regions adjacent inwardly to the boundary of an enlarged tooth region 1022.

[0142] Figure 10d A diagram showing the final tooth region determined according to one embodiment through a process of region expansion and reduction.

[0143] One embodiment of the three-dimensional model processing apparatus 300 can ultimately determine the region 1040 corresponding to the tooth by repeatedly expanding and shrinking the selected tooth region a predetermined number of times.

[0144] On the other hand, in one embodiment, the three-dimensional model processing apparatus 300 can select a tooth region with a curvature value within a fixed critical range, based on the curvature value of a reference point. That is, the three-dimensional model processing apparatus 300 can select a tooth region whose curvature value differs from that of the reference point within a fixed critical range. For example, according to one embodiment, the three-dimensional model processing apparatus 300 can determine a reference point based on the location clicked by the user and select a tooth region whose curvature value differs from that of the reference point within a fixed critical range.

[0145] However, this disclosure is not limited to this embodiment. One embodiment of the three-dimensional model processing apparatus 300 can select a tooth region with a curvature value within a predetermined critical range, regardless of the curvature value of the reference point.

[0146] According to another embodiment, the 3D model processing device 300 can select a tooth region by dynamically determining a critical range based on user drag input. The 3D model processing device 300 changes the critical range of curvature values ​​used to select the tooth region based on the dragging user input. The 3D model processing device 300 can select the tooth region based on the changed critical range.

[0147] Figure 11a , Figure 11b and Figure 11c This is a diagram illustrating a method for expanding the tooth selection area based on user drag input according to an embodiment.

[0148] Figure 11a , Figure 11b and Figure 11c This shows an image rendered from a 3D model.

[0149] like Figure 11aAs shown, when a user clicks on any location on the 3D model, the 3D model processing device 300 can determine a seed point 1103 corresponding to the clicked location. The 3D model processing device 300 can determine that the curvature value of the seed point 1103 exceeds a predetermined range and determine a reference point 1101 adjacent to the seed point 1103. The 3D model processing device 300 can select a region with curvature values ​​within a first range, based on the curvature value of the reference point 1101. The first range can be a pre-set critical range.

[0150] When the user drags the pointer from seed point 1103 to first point 1105, the 3D model processing device 300 can change the critical range from a first range to a second range. The second range can be a larger value than the first range. The 3D model processing device 300 can make the value of the critical range increase with the increase of the dragging distance. The 3D model processing device 300 can select a region with curvature values ​​within the second range based on the curvature value of the reference point 1101 and display the selected region.

[0151] like Figure 11b As shown, when the user drags the pointer further to the second point 1107, the 3D model processing device 300 can change the critical range from the second range to a third range. The third range can be a larger value than the second range. The 3D model processing device 300 can increase the critical range as the dragging distance increases. As the critical range increases, the area selected by the 3D model processing device 300 also expands. The 3D model processing device 300 can select an area with curvature values ​​within the third range, based on the curvature value of the reference point 1101, and display the selected area. It can be seen that in... Figure 11b The selected area is more than in Figure 11a The selected area is larger.

[0152] like Figure 11c As shown, when the user drags the pointer further, i.e., from seed point 1103 to the third point 1109, the 3D model processing device 300 can change the critical range from the third range to the fourth range. The fourth range can be larger than the third range. The 3D model processing device 300 can select a region with curvature values ​​within the fourth range, based on the curvature value of the reference point 1101, and display the selected region. It can be seen that in... Figure 11c The selected area is more than in Figure 11b The selected area is larger.

[0153] The 3D model processing device 300 expands the selection area by increasing the critical range as the user drags the input distance, while not further expanding the selection area into regions with curvature values ​​below the critical value. The 3D model processing device 300 can determine the critical value so that the selection area is not expanded beyond the boundaries of the teeth and gums.

[0154] The following is for reference Figures 12 to 14 This describes the user interface provided to implement the aforementioned tooth region selection method. However, this disclosure is not limited to the example shown in the figures, and the implementation can be varied in many ways.

[0155] Figures 12 to 14 An example of a program's drive screen for a tooth region selection method applicable to one embodiment is shown.

[0156] like Figure 12 As shown, the 3D model processing device 300 can display a 3D model formed by dividing the 3D model to identify regions corresponding to multiple teeth. The 3D model processing device 300 can assign a unique number to each tooth and automatically determine and display the regions corresponding to each tooth on the screen. The 3D model processing device 300 can display an image on the 3D model showing multiple teeth and their corresponding tooth numbers.

[0157] Users can check if the selection of a single tooth region is correct. Users can confirm that the region corresponding to tooth 1201 contains empty spaces and determine that the tooth region has been incorrectly selected and needs to be reselected. Users can select tooth 1201 or click the icon marked with the tooth's inherent number 27.

[0158] When the user selects a tooth to reserve, such as Figure 13a As shown, the 3D model processing device 300 can display a pop-up window asking whether to reselect the area of ​​the predetermined tooth. When it receives user input requesting to reselect the tooth area using the smart selection function (e.g., user input clicking icon 1301), as... Figure 13b As shown, the 3D model processing device 300 can display a magnified image of a predetermined tooth portion.

[0159] like Figure 13b As shown, since a portion of the upper surface of tooth 27 is not accurately selected, the user can click the icon 1334 to deselect all selected areas. When the user input of clicking the deselect icon 1334 is received, the 3D model processing device 300 can display a pop-up window 1321 prompting for the intelligent selection function.

[0160] Following the instructions in pop-up window 1321, the user clicks or clicks and drags to any position on tooth #27 to select the tooth region. The specific method for the 3D model processing device 300 to select the tooth region based on user input can be found in [reference needed]. Figures 4 to 1 The description in section 1 is as described above. Repeated explanations will be omitted.

[0161] like Figure 13cAs shown, when it is determined that the tooth area has been accurately selected and there are no empty spaces, the user can click the "confirm" icon 1323 to confirm the selection.

[0162] When user input is received after clicking the confirmation icon 1323 (indicating selection is complete), such as Figure 14 As shown, the 3D model processing device 300 can return to the initial screen displaying all the teeth. It can be seen that, through the intelligent selection function of one embodiment, the area 1401 of tooth number 27 has been accurately reselected.

[0163] As described above, the three-dimensional model processing apparatus 300 of one embodiment of the present disclosure can accurately and quickly select a single tooth region with only a few clicks (or drags) by the user, thereby making it convenient for the user and shortening the working time.

[0164] Figure 15 A block diagram of a three-dimensional model processing apparatus according to an embodiment is shown.

[0165] Figure 15 The 3D model processing apparatus 300 shown can execute 3D model processing methods according to various embodiments of the present disclosure, and is applicable to... Figures 1 to 14 The explanation is as follows. Therefore, content that is repeated above will be omitted.

[0166] One embodiment of the three-dimensional model processing apparatus 300 can be connected to an external device such as a three-dimensional scanning device or an external server via a wired or wireless communication network to acquire a three-dimensional model of an object.

[0167] The 3D model processing apparatus 300 can be any electronic device capable of generating, processing, displaying, and / or transmitting 3D images of an object based on an acquired 3D model. According to various embodiments of this disclosure, the 3D model processing apparatus 300 can be a fixed terminal or a mobile terminal. The 3D model processing apparatus 300 can be a computing device such as a smartphone, laptop computer, desktop computer, PDA, tablet computer, etc., but is not limited thereto.

[0168] Reference Figure 15 The three-dimensional model processing device 300 may include a processor 310, a display 320, a communication interface 330, a user input unit 340, and a memory 350.

[0169] In one embodiment, the processor 310 can control a three-dimensional model processing device 300 to perform an intended action by executing at least one instruction. The at least one instruction may be stored in the internal memory (not shown) included in the processor 310 or in a separate memory 350.

[0170] In one embodiment, the processor 310 can control at least one structure included within the three-dimensional model processing apparatus 300 to perform an intended action by executing at least one instruction. Therefore, even when describing the case where the processor 310 performs a predetermined action, it can be understood that the processor 310 controls at least one structure in a manner that causes at least one structure included within the three-dimensional model processing apparatus 300 to perform a predetermined action.

[0171] The processor 310 in one embodiment may include: RAM (not shown) for storing signals or data input from outside the 3D model processing apparatus 300, or serving as a storage area corresponding to various operations performed in the 3D model processing apparatus 300; ROM (not shown) for storing a control program and / or multiple instructions for controlling the 3D model processing apparatus 300; and at least one internal processor (not shown) for executing at least one instruction.

[0172] Additionally, the processor 310 may include a graphics processing unit for processing graphics corresponding to the video. Furthermore, the processor 310 may be implemented as a system-on-a-chip (SoC) integrating a core and a GPU.

[0173] In the disclosed embodiments, processor 310 can generate an image by rendering a three-dimensional model of the oral cavity. For example, the three-dimensional model may include surface shape information of the oral cavity, which includes at least one of a plurality of teeth, gums, and artificial structures.

[0174] The display 320 can display a predetermined screen under the control of the processor 310. Specifically, the display 320 can display a user interface screen including a three-dimensional model. Alternatively, the display 320 can display a user interface screen including information related to the diagnosis and treatment of the subject.

[0175] The communication interface 330 can communicate with at least one external electronic device (not shown) or server (not shown) via a wired or wireless communication network.

[0176] The user input unit 340 can receive user input for controlling the 3D model processing device 300. The user input unit 340 may include user input devices, such as a touchpad for sensing user touch, buttons for receiving user press operations, a mouse or keyboard for referring to or selecting a location on the user interface screen, etc., but not limited to these.

[0177] Additionally, the user input unit 340 may include a voice recognition device (not shown) for recognizing speech. For example, the voice recognition device (not shown) may be a microphone, and it may receive voice commands or voice requests from the user. Thus, the processor 310 may perform control to execute actions corresponding to the voice commands or voice requests.

[0178] The memory 350 may store at least one instruction executed by the processor 310. Additionally, the memory 350 may store at least one program executed by the processor 310. Furthermore, the memory 350 may store data received from external devices or external servers (e.g., raw data acquired by scanning an object, two-dimensional image data, three-dimensional models, etc.). The memory 350 may store an object image representing the object in three dimensions.

[0179] In one embodiment of this disclosure, the processor 310 can control the overall operation of the three-dimensional model processing device 300 by executing a program stored in the memory 350.

[0180] The specific method by which processor 310 processes the 3D model to select the object volume region is applicable to [the following]. Figure 4 The explanation will be provided, and repeated explanations will be omitted.

[0181] First, in one embodiment, the processor 310 can acquire a three-dimensional model of the oral cavity. The processor 310 can determine reference points on the three-dimensional model and, based on these reference points, gradually expand the selected area to determine the region corresponding to the object. The processor 310 can then display the region corresponding to the object on the three-dimensional model via a display 320.

[0182] In one embodiment, the processor 310 can automatically or manually determine seed points on a 3D model and determine reference points based on the curvature values ​​of the seed points. The processor 310 can gradually expand the selection area based on the curvature values ​​of the reference points to determine the region corresponding to the object volume.

[0183] For example, processor 310 may select a seed point on a first tooth among a plurality of teeth represented by a 3D model. Processor 310 may control display 320 to display an image rendered from the 3D model on a screen. Processor 310 may receive user input for selecting a point on the rendered image and determine the seed point on the 3D model based on the position of the selected point on the rendered image.

[0184] In one embodiment, the processor 310 can determine a reference point on a first tooth based on the curvature value of a seed point. The processor 310 can use at least one of a k1 value and a k2 value as the curvature value of the seed point. In another embodiment, the processor 310 can determine a reference point for selecting a tooth region based on the curvature value of the seed point, thereby improving region selection accuracy.

[0185] When the curvature value of the seed point is within a predetermined range, the processor 310 can determine the seed point as a reference point. Conversely, when the curvature value of the seed point is not within the predetermined range, the processor 310 can determine other points with curvature values ​​within the predetermined range as reference points. The processor 310 can determine the nearest point whose curvature value falls within the predetermined range as the reference point.

[0186] When the curvature value of the selected seed point does not fall within a predetermined range, the processor 310 can search for the point closest to the seed point among the points whose curvature values ​​fall within the predetermined range. The processor 310 can search for points within a specified distance (e.g., 0.01 to 0.02 mm) from the seed point and gradually expand the search area, while determining the points whose curvature values ​​fall within the predetermined range as reference points.

[0187] In one embodiment, the processor 310 can gradually expand the selected area based on the curvature value of a reference point to determine the region corresponding to the first tooth.

[0188] The processor 310 selects a tooth region with curvature values ​​within a critical range based on the curvature value of the reference point by gradually expanding the selection region from the reference point.

[0189] As a reference value for selecting a tooth region, the processor 310 may use the reference point value k1 or both k1 and k2. In one embodiment, the processor 310 selects the final region corresponding to a tooth by repeatedly expanding and shrinking the region from sporadically selected tooth regions.

[0190] On the other hand, in one embodiment, the processor 310 can select a tooth region with a curvature value within a fixed critical range, based on the curvature value of a reference point. That is, the processor 310 can select a tooth region whose curvature value differs from that of the reference point within a fixed critical range.

[0191] However, this disclosure is not limited to this embodiment. In one embodiment, the processor 310 can select a tooth region with curvature values ​​within a predetermined critical range, regardless of the curvature value of the reference point.

[0192] According to another embodiment, processor 310 can fluidly determine a critical range to select a tooth region based on user drag input. Processor 310 can vary the critical range of curvature values ​​used for selecting the tooth region based on the curvature value of a reference point and the user drag input. Processor 310 can select the tooth region based on the varied critical range. For example, processor 310 can increase the value of the critical range as the drag distance increases. As the value of the critical range increases, processor 310 can expand the selection region. However, processor 310 expands the selection region by increasing the value of the critical range as the user drags the distance, without further expanding the selection region into regions with curvature values ​​below a predetermined value. Processor 310 can determine a predetermined value so that the selection region is not expanded beyond the boundaries of the teeth and gums.

[0193] The three-dimensional model processing methods according to the various embodiments of this disclosure described above can be implemented in the form of program commands and can be recorded in a computer-readable medium, which can be executed by various computer devices. Furthermore, embodiments of this disclosure can provide a computer-readable recording medium recording one or more programs, said programs including at least one instruction for executing the three-dimensional model acquisition method.

[0194] Computer-readable storage media can be individual or in combination, including program commands, data files, data structures, etc. Examples of computer-readable storage media include magnetic media such as hard disks, floppy disks, and magnetic tapes; optical media such as CD-ROMs and DVDs; magneto-optical media such as floppy disks; and hardware devices configured to store and execute program commands, such as read-only memory (ROM), random access memory (RAM), and flash memory.

[0195] The machine-readable storage medium can be provided as a non-transitory storage medium. "Non-transitory storage medium" means that the storage medium is a tangible device. Furthermore, "non-transitory storage medium" can include buffers for temporarily storing data.

[0196] According to one embodiment, methods for displaying oral images according to the various embodiments disclosed herein may be provided in a computer program product. The computer program product may be distributed in the form of a machine-readable storage medium (e.g., a compact disc read-only memory, CD-ROM). Alternatively, it may be distributed directly, online (e.g., downloaded or uploaded) between two user devices (e.g., smartphones) via an application store (e.g., the Play Store, etc.).

[0197] The embodiments have been described in detail above, but the scope of the present invention is not limited thereto. Various modifications and improvements made by those skilled in the art that utilize the basic concepts of the present invention as defined in the claims also fall within the scope of the present invention.

[0198] Explanation of reference numerals in the attached figures

[0199] 300: Three-dimensional model processing device

[0200] 310: Processor

[0201] 320: Monitor

[0202] 330: Communication Interface

[0203] 340: User Input Section

[0204] 350: Memory.

Claims

1. A region determination method of determining a region corresponding to an object body from a three-dimensional model of an oral cavity, wherein the region determination method comprises the steps of: acquiring the three-dimensional model, determining a seed point on the three-dimensional model, determining the seed point as a reference point when a curvature value of the seed point determined on the three-dimensional model has a value within a predetermined range, gradually expanding a selection region by selecting adjacent points having a difference in curvature value from the reference point within a critical range, thereby determining a region corresponding to an object body, changing the critical range based on a user's drag input, determining the region corresponding to the object body based on the changed critical range, and displaying the determined region on the three-dimensional model; and as the distance of the drag input increases, increasing the changed critical range.

2. The region determination method according to claim 1, wherein the three-dimensional model is acquired by a three-dimensional scanning device and includes surface shape information of a plurality of teeth and gums within the oral cavity, and the object body is a tooth or a gum.

3. The region determination method according to claim 1, wherein the step of determining the seed point comprises the steps of: displaying the three-dimensional model, and determining the seed point based on a user input with respect to the displayed three-dimensional model.

4. The region determination method according to claim 1, wherein the curvature value of the seed point includes at least one of a curvature value kl and a curvature value k2, the curvature value kl is a curvature value having a maximum absolute value, which is realized by a curve intersecting a normal plane including a normal of the seed point and a curved surface of the object body, the curvature value kl is a curvature value realized by a curve intersecting a first normal plane among the normal planes and the curved surface of the object body, and the curvature value k2 is a curvature value realized by a curve intersecting an orthogonal normal plane, which is orthogonal to the first normal plane and includes a normal of the seed point, and the curved surface of the object body.

5. The region determination method according to claim 1, further comprising the step of: determining another point having a curvature value within the predetermined range as a reference point when the curvature value of the seed point does not have a value within the predetermined range.

6. The region determination method according to claim 1, wherein the step of determining a region corresponding to the object body further comprises the step of: repeatedly performing region expansion and reduction processing from the selection region to determine the region corresponding to the object body.

7. The region determination method according to claim 1, wherein the step of determining the seed point comprises the steps of: dividing the three-dimensional model into a plurality of regions corresponding to a plurality of object bodies, and determining the seed point on one region among the plurality of regions.

8. The region determination method according to claim 1, wherein the region determination method further comprises the steps of: displaying an image in which a plurality of teeth and tooth numbers corresponding to the respective teeth are displayed on the three-dimensional model, and receiving a user input for selecting a first tooth among the plurality of teeth as the object body; and the step of determining the seed point comprises the step of: determining the seed point on the first tooth. ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ 5. The region determination method of claim 1, wherein, ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ 9. A three-dimensional model processing apparatus that processes a three-dimensional model of an oral cavity, wherein the three-dimensional model processing apparatus includes: a display that displays a video rendered from the three-dimensional model, and at least one processor that determines a seed point on the three-dimensional model, determines the seed point as a reference point when a curvature value of the seed point determined on the three-dimensional model has a value within a predetermined range, gradually expands a selection region by selecting adjacent points having a difference in curvature value from the reference point within a critical range, thereby determining a region corresponding to an object body, changes the critical range based on a user's drag input, determines the region corresponding to the object body based on the changed critical range, and controls the display to display the determined region on the three-dimensional model; increases the changed critical range as a distance of the drag input increases.

10. The three-dimensional model processing apparatus according to claim 9, wherein the display displays the three-dimensional model, the at least one processor determines the seed point based on a user input with respect to the displayed three-dimensional model.

11. The three-dimensional model processing apparatus according to claim 9, wherein the at least one processor repeatedly performs region expansion and reduction processing from the selection region to determine the region corresponding to the object body.

12. The three-dimensional model processing apparatus according to claim 9, wherein the display displays a video in which a plurality of teeth and tooth numbers corresponding to the respective teeth are displayed on the three-dimensional model, the at least one processor receives a user input for selecting a first tooth among the plurality of teeth as the object body, and determines the seed point on the first tooth.

Images