Oral cavity image processing apparatus and oral cavity image processing method

Abstract

Disclosed embodiments relate to an oral image processing apparatus and an oral image processing method, and an oral image processing method according to an embodiment can include a step of acquiring a three-dimensional oral model regarding an oral cavity, a step of acquiring curvature information of the three-dimensional oral model, a step of acquiring roughness information of the three-dimensional oral model based on the curvature information, a step of acquiring a color of the three-dimensional oral model based on the roughness information, and a step of displaying the three-dimensional oral model based on the acquired color.

Description

Technical Field

[0001] The disclosed embodiments relate to an oral cavity image processing apparatus and an oral cavity image processing method, specifically, to an apparatus and method for processing oral cavity images to provide roughness information about a three-dimensional oral cavity model. Background Technology

[0002] A recent method for obtaining information about a patient's oral cavity is to acquire images of the oral cavity by inserting an oral scanner into the patient's mouth. By scanning the patient's mouth with an oral scanner, three-dimensional data about the patient's teeth, gums, jawbone, and other structures can be obtained. This acquired three-dimensional data can then be used for dental treatment or correction.

[0003] In particular, to insert the restoration into the tooth, the tooth supporting the restoration is shaped into a bridge abutment teeth, and the restoration is then inserted into the shaped tooth. At this point, to ensure the tooth supporting the restoration is smoothly shaped, information about the tooth's roughness is needed. However, existing techniques for observing the roughness of scanned data have limitations in applicability to oral models because they do not take into account the inherent geometric information of the tooth. Summary of the Invention

[0004] The problem the invention aims to solve

[0005] The purpose of the disclosed embodiments is to provide an apparatus and a method for processing oral images that can provide roughness information about a three-dimensional oral cavity model.

[0006] means for solving problems

[0007] An oral cavity image processing method according to one embodiment may include: a step of obtaining a three-dimensional oral cavity model of the oral cavity, a step of obtaining curvature information of the three-dimensional oral cavity model, a step of obtaining roughness information of the three-dimensional oral cavity model based on the curvature information, a step of obtaining the color of the three-dimensional oral cavity model based on the roughness information, and a step of displaying the three-dimensional oral cavity model based on the obtained color.

[0008] According to one embodiment, the step of obtaining curvature information of a three-dimensional oral cavity model includes: obtaining curvature values ​​of multiple points in the three-dimensional oral cavity model; the step of obtaining roughness information of the three-dimensional oral cavity model based on the curvature information may include: obtaining roughness values ​​of the multiple points based on the curvature values ​​of the multiple points.

[0009] According to one embodiment, the step of obtaining roughness values ​​of multiple points may include: determining the roughness value of the first point based on the curvature value of at least one second point adjacent to the first point among the multiple points.

[0010] According to one embodiment, the step of obtaining roughness values ​​of multiple points may include: determining the roughness value of the first point based on the difference between the curvature value of at least one second point adjacent to the first point among the multiple points and the curvature value of the first point.

[0011] According to one embodiment, the step of obtaining roughness values ​​of multiple points may include: calculating the difference between the curvature value of each of a plurality of second points located within a preset first distance from a first point and the curvature value of the first point; determining a weighted value of the difference based on the distance between each of the plurality of second points and the first point; and determining the roughness value of the first point based on the difference and the weighted value for the plurality of second points.

[0012] The step of determining the roughness value of a first point according to one embodiment may include: calculating the average value of the differences based on the weighted values, and determining the calculated average value as the roughness value of the first point.

[0013] According to one embodiment, the step of obtaining roughness values ​​of multiple points may include: determining the roughness values ​​of the multiple points such that the rougher the surface of the three-dimensional oral cavity model where the multiple points are located, the larger the roughness values ​​of the multiple points; and the smoother the surface of the three-dimensional oral cavity model where the multiple points are located, the smaller the roughness values ​​of the multiple points.

[0014] According to one embodiment, the step of obtaining roughness values ​​of multiple points may include: determining the roughness values ​​of multiple points in the edge region or neck region of a tooth as preset values.

[0015] According to one embodiment, the step of obtaining the roughness value of the plurality of points includes: determining the roughness value of a first point among the plurality of points; the step of determining the roughness value of the first point may include: determining whether the first point is included in the edge region or cervical region of a tooth based on the distance between the first point, the third point farthest from the first point in a first direction and the fourth point farthest from the first point in a second direction, and the tangent of the first point, respectively; and if the first point is included in the edge region or cervical region of the tooth, determining the roughness value of the first point as a preset value.

[0016] According to one embodiment, the steps of obtaining the color of a three-dimensional oral cavity model include: determining the color of a point based on the roughness value of each of the plurality of points, and mixing the colors of the plurality of points to determine the color of a mesh composed of the plurality of points.

[0017] An oral cavity image processing apparatus according to one embodiment includes: a display, a memory for storing one or more instructions, and a processor; the processor performs the following operations by executing the one or more instructions stored in the memory: acquiring a three-dimensional oral cavity model of an oral cavity, acquiring curvature information of the three-dimensional oral cavity model, acquiring roughness information of the three-dimensional oral cavity model based on the curvature information, acquiring a color of the three-dimensional oral cavity model based on the roughness information, and controlling the display to display the three-dimensional oral cavity model based on the acquired color.

[0018] The effects of the invention

[0019] The oral cavity image processing apparatus and method according to the disclosed embodiments can provide roughness information about a three-dimensional oral cavity model, taking into account the geometry of the oral cavity. Therefore, the provided roughness information can be used to perform preparation work for shaping teeth into bridge abutment tooth morphologies, thereby reducing the time required for preparation work and improving the accuracy of preparation work. Attached Figure Description

[0020] The present invention can be readily understood through the following detailed description and the accompanying drawings, wherein reference numerals denote constituent elements.

[0021] Figure 1 This is a diagram illustrating a preparation (Prep) operation according to one embodiment.

[0022] Figure 2 This is a diagram illustrating an oral cavity image processing system according to an embodiment.

[0023] Figure 3 A diagram showing a three-dimensional oral cavity model according to one embodiment.

[0024] Figure 4 This is a figure illustrating a method for obtaining curvature information about a three-dimensional oral cavity model using an oral cavity image processing apparatus according to an embodiment.

[0025] Figure 5 This is a diagram illustrating an example of a dental image processing apparatus displaying curvature information of a three-dimensional dental model according to an embodiment.

[0026] Figure 6 This is a figure illustrating a method for acquiring roughness information of a three-dimensional oral cavity model using an oral cavity image processing apparatus according to an embodiment.

[0027] Figure 7 This is a diagram illustrating a method for determining roughness color using an oral cavity image processing apparatus according to an embodiment.

[0028] Figure 8This is a diagram illustrating a method for detecting edges or cervical margins in a three-dimensional oral cavity model using an oral image processing apparatus according to an embodiment.

[0029] Figure 9 This is a diagram illustrating an example of a dental image processing apparatus displaying roughness information of a three-dimensional dental model according to an embodiment.

[0030] Figure 10 This is a flowchart illustrating an oral cavity image processing method according to an embodiment.

[0031] Figure 11 This is a block diagram illustrating an oral cavity image processing apparatus according to an embodiment. Detailed Implementation

[0032] This specification describes the principles of the invention and discloses embodiments to clarify the scope of the invention and enable those skilled in the art to implement it. The disclosed embodiments can be implemented in various forms.

[0033] Throughout this specification, the same reference numerals refer to the same constituent elements. This specification does not describe all elements of the embodiments, and omit general content or repetition between embodiments within the scope of this invention. The term "part" (portion) used in this specification can be implemented in software or hardware, and according to embodiments, multiple "parts" can be implemented as one element, or one "part" can include multiple elements. The working principle and embodiments of the invention are described below with reference to the accompanying drawings.

[0034] In this specification, images may include images showing at least one tooth or an oral cavity including at least one tooth (hereinafter referred to as "oral cavity images").

[0035] Furthermore, the images in this specification may be two-dimensional images of the object, or three-dimensional models or images showing the object in three dimensions. Additionally, the images in this specification may refer to data required for two-dimensional or three-dimensional representation of the object, such as raw data acquired from at least one image sensor. Specifically, raw data is data acquired to generate oral images, and may be data acquired from at least one image sensor in an intraoral scanner (e.g., two-dimensional data) when scanning the inside of a patient's mouth as the object using an intraoral scanner. Alternatively, raw data may be data acquired from at least one image sensor in a desktop scanner when scanning a plaster model using a desktop scanner. Alternatively, raw data may be CAD data pre-stored in an oral image processing device. However, it is not limited to these.

[0036] In this specification, "object" may include teeth, gums, at least a portion of the oral cavity, and / or insertable artificial structures (e.g., orthodontic appliances, restorations, implants, artificial teeth, orthodontic aids inserted into the oral cavity, etc.), plaster models, impression models, etc. Orthodontic appliances may include at least one of frameworks, attachments, orthodontic screws, lingual orthodontic appliances, and removable orthodontic maintenance devices. For ease of explanation, the object is described as "oral cavity" in this specification; however, the embodiments of this disclosure are not limited to the oral cavity but also apply to insertable artificial structures, plaster models, impression models, etc. The oral cavity can be understood to include the concept of insertable artificial structures, plaster models, impression models, etc.

[0037] The embodiments will now be described in detail with reference to the accompanying drawings.

[0038] Figure 1 This is a diagram illustrating a preparation (Prep) operation according to one embodiment.

[0039] Reference Figure 1 In restorative treatment involving the insertion of a prosthesis 20 into a tooth, the tooth supporting the prosthesis 20 needs to be shaped into an abutment tooth. This process of shaping the tooth into an abutment tooth is called preparation, and the tooth shaped into an abutment tooth is called the preparation tooth 10. If a rough portion 15 exists on the surface of the preparation tooth 10, a precise fit may not be achieved when the prosthesis 20 is inserted due to the unevenness. Therefore, it is important to smooth the surface of the preparation tooth 10 before inserting the prosthesis 20. Typically, preparation involves repeated processes such as identifying the rough portion after one preparation and performing a second preparation on the rough portion to complete the preparation. At this time, to identify the rough portion 15 of the preparation tooth 10, information on the roughness of the preparation tooth 10 is required.

[0040] An oral cavity image processing apparatus according to one embodiment can provide roughness information about a three-dimensional oral cavity model in order to accurately perform preparation work. Hereinafter, with reference to the accompanying drawings, a method for providing roughness information about a three-dimensional oral cavity model using an oral cavity image processing apparatus according to one embodiment will be described.

[0041] Figure 2 This is a diagram illustrating an oral cavity image processing system according to an embodiment.

[0042] Reference Figure 2 An oral image processing system according to one embodiment includes an oral scanner 1000 and an oral image processing device 100.

[0043] An oral scanner 1000 according to one embodiment is a medical device for acquiring images of the oral cavity. Specifically, the oral scanner 1000 can be a device that acquires images of the oral cavity, including at least one tooth, by inserting itself into the oral cavity and scanning the teeth non-contactly.

[0044] Furthermore, the oral scanner 1000 may have a shape capable of entering and exiting the oral cavity, and uses at least one image sensor (e.g., an optical camera, etc.) to scan the inside of the patient's oral cavity. In order to image at least one surface of the teeth, gums, and artificial structures that can be inserted into the oral cavity (e.g., orthodontic appliances including braces and wires, dental implants, artificial teeth, orthodontic aids inserted into the oral cavity, etc.), which are the objects inside the oral cavity, the oral scanner 1000 can acquire surface information about the objects as raw data.

[0045] Image data acquired from the oral scanner 1000 can be transmitted to an oral image processing device 100 connected via a wired or wireless communication network.

[0046] The oral cavity image processing device 100 may be any electronic device that connects to the oral cavity scanner 1000 via a wired or wireless network, receives two-dimensional images acquired by scanning the oral cavity from the oral cavity scanner 1000, and generates, processes, displays, and / or transmits oral cavity images based on the received two-dimensional images.

[0047] The oral cavity image processing device 100 can generate information by processing two-dimensional image data received from the oral cavity scanner 1000, or it can generate an oral cavity image by processing the two-dimensional image data. Furthermore, the oral cavity image processing device 100 can display the generated information and the oral cavity image on the display 130.

[0048] The oral imaging device 100 can be a computing device such as a smartphone, laptop computer, desktop computer, PDA, or tablet PC, and is not limited thereto.

[0049] Furthermore, the oral cavity image processing device 100 may also exist in the form of a server (or server device) for processing oral cavity images.

[0050] Furthermore, the oral scanner 1000 can transmit the raw data acquired by scanning the oral cavity to the oral image processing device 100 as is. In this case, the oral image processing device 100 can generate a three-dimensional model (three-dimensional oral image) representing the oral cavity based on the received raw data. According to one embodiment, the oral image processing device 100 can generate three-dimensional data (e.g., surface data) representing the surface shape of an object based on the received raw data.

[0051] According to one embodiment, the three-dimensional surface data can be in the form of point data or mesh data. For example, mesh data is in the form of multiple polygons (faces), where a polygon is a polygon formed by multiple fixed points. In this case, the polygon can be a triangle, a quadrilateral, or other polygonal shape. Depending on the shape of the polygon, the mesh data can be represented as a triangular mesh, a quadrilateral mesh, or a polygonal mesh.

[0052] According to one embodiment, a "three-dimensional oral cavity model" can be generated by three-dimensional modeling of the internal structure of the oral cavity based on received raw data, and therefore can be referred to as a "three-dimensional oral cavity model" or "three-dimensional oral cavity image". Hereinafter, models or images that display the oral cavity in two or three dimensions will be collectively referred to as "oral cavity images".

[0053] In addition, the oral image processing device 100 can analyze, process, display the generated oral images, and / or transmit the oral images to external devices.

[0054] As another example, the oral scanner 1000 can acquire raw data by scanning the oral cavity and process the acquired raw data to generate an image corresponding to the oral cavity as the object. Furthermore, the generated image can be transmitted to the oral cavity image processing device 100. In this case, the oral cavity image processing device 100 can analyze, process, display, and / or transmit the received image.

[0055] In the disclosed embodiments, the oral cavity image processing apparatus 100 is an electronic device capable of generating and displaying an oral cavity image that represents a three-dimensional oral cavity including one or more teeth, which will be described in detail below.

[0056] Figure 3 A diagram showing a three-dimensional oral cavity model according to one embodiment.

[0057] Reference Figure 3 According to one embodiment, the oral cavity image processing apparatus 100 can acquire three-dimensional oral cavity data. For example, it can be achieved by using... Figure 1 The oral scanner 1000 described herein scans at least one tooth to acquire oral data representing surface information of the oral cavity. According to one embodiment, the oral data may include point data or mesh data. For example, the oral data may include point location information, point normal vectors, point tangent vectors, mesh normal vectors, mesh location information, etc., but is not limited thereto.

[0058] The oral cavity image processing device 100 can generate a three-dimensional oral cavity model 310 based on oral cavity data. The three-dimensional oral cavity model 310 may include multiple points, and may include a triangular mesh composed of multiple points. However, it is not limited to this; the three-dimensional oral cavity model may be composed of other polygonal meshes such as quadrilaterals.

[0059] According to one embodiment, an oral cavity image processing apparatus 100 can acquire roughness information of multiple points in a three-dimensional oral cavity model based on acquired oral cavity data. This will be described in detail below with reference to the accompanying drawings.

[0060] Figure 4 This is a figure illustrating a method for obtaining curvature information about a three-dimensional oral cavity model using an oral cavity image processing apparatus according to an embodiment.

[0061] According to one embodiment, the oral image processing device 100 can acquire curvature information of multiple points in a three-dimensional oral model.

[0062] Curvature can be a value representing the degree of bending of a curve or surface. The curvature value of a specified point in a three-dimensional oral cavity model can represent the degree of bending of a curve defined on the surface of the object at that point. In this case, the degree of bending of multiple curves passing through the corresponding point will differ depending on the direction. Therefore, the oral cavity image processing device 100 can determine the maximum curvature value among multiple curvature values ​​at the corresponding point as the curvature value of that point, or determine the average of multiple curvature values ​​as the curvature value of the corresponding point. However, it is not limited to this.

[0063] For ease of explanation, Figure 4 China to Israel Figure 3 The method for obtaining curvature values ​​is explained using the first to sixth points (P1 to P6) in the first region 320 as a reference.

[0064] When the curve or surface passing through a point is convex, the oral image processing apparatus 100 according to one embodiment can determine the sign of the curvature value of the corresponding point as "+", and when the curve or surface passing through a point is concave, the oral image processing apparatus 100 according to one embodiment can determine the sign of the curvature value of the corresponding point as "-". For example, the oral image processing apparatus 100 can determine the sign of the curvature value of the fourth point P4 as "+" and the sign of the curvature value of the fifth point P5 as "-".

[0065] Furthermore, the oral cavity image processing device 100 can use the normal vectors of multiple grids adjacent to a point to determine the curvature value of the point. Here, a point being adjacent to a grid means that the grid includes the corresponding point as a vertex. For example, the fourth point P4 can be adjacent to grids M1, M2, M3, M4, M5, and M6 from the first to the sixth grid. Furthermore, the fifth point P5 can be adjacent to grids M3, M4, M7, M8, and M9.

[0066] The oral cavity image processing device 100 can determine the curvature value of a point based on the difference between at least two of the normal vectors of a plurality of grids adjacent to the point. In this case, the difference between the plurality of normal vectors can be represented by the angle between the plurality of normal vectors. For example, the oral cavity image processing device 100 can determine the curvature value of the fourth point P4 based on the angle between the normal vector 330 of the sixth grid M6 and the normal vector 340 of the third grid M3. Furthermore, the oral cavity image processing device 100 can determine the curvature value of the fifth point P5 based on the angle between the normal vector 340 of the third grid M3 and the normal vector 350 of the eighth grid M8.

[0067] The oral cavity image processing device 100 can determine the curvature value of a point such that the greater the difference between the normal vectors of multiple adjacent grids, the larger the curvature value; and the smaller the difference between the normal vectors of multiple grids, the smaller the curvature value. For example, since the angle between the normal vector 330 of the sixth grid M6 adjacent to the fourth point P4 and the normal vector 340 of the third grid M3 is greater than the angle between the normal vector 340 of the third grid M3 adjacent to the fifth point P5 and the normal vector 350 of the eighth grid M8, the curvature value of the fourth point P4 can be determined to be greater than the curvature value of the fifth point P5. For example, the curvature value of the fourth point P4 can be determined to be 0.7, and the curvature value of the fifth point P5 can be determined to be 0.1.

[0068] Furthermore, using the same method, the curvature value of the first point P1 can be determined as -0.1, the curvature value of the second point P2 can be determined as 0, the curvature value of the third point P3 can be determined as -0.3, and the curvature value of the sixth point P6 can be determined as -0.2.

[0069] However, not limited to this, the oral cavity image processing apparatus 100 according to one embodiment can determine the curvature values ​​of multiple points in a three-dimensional oral cavity model using various methods. The oral cavity image processing apparatus 100 can determine the magnitude of the curvature value of a point based on the normal vectors of multiple points in the three-dimensional oral cavity model. For example, the oral cavity image processing apparatus 100 can determine the magnitude of the curvature value of the fifth point P5 based on the difference between the normal vector of the fourth point P4 adjacent to the fifth point P5 and the normal vector of the sixth point P6 adjacent to the fifth point P5.

[0070] In addition to the methods described above, the oral cavity image processing apparatus 100 according to one embodiment can use various known curvature calculation methods to determine the curvature values ​​of multiple points in a three-dimensional oral cavity model.

[0071] Figure 5 This is a diagram illustrating an example of a dental image processing apparatus displaying curvature information of a three-dimensional dental model according to an embodiment.

[0072] Reference Figure 5The oral cavity image processing device 100 can display a curvature mode menu 510 on the user interface screen for displaying curvature information of a three-dimensional oral cavity model. When a user input selecting the curvature mode menu 510 is received, the oral cavity image processing device 100 can display the curvature information 520 of the three-dimensional oral cavity model using color. For example, the oral cavity image processing device 100 can determine the color of each point based on the curvature value of each point in the three-dimensional oral cavity model. At this time, the oral cavity image processing device 100 can use a color bar that represents the correspondence between color and curvature value to map the color corresponding to the curvature value of each point to each point. In addition, the oral cavity image processing device 100 can determine the color of the mesh by mixing the colors of multiple points that make up the mesh. The oral cavity image processing device 100 can display multiple points and multiple meshes in the three-dimensional oral cavity model using the determined colors. For example, the oral cavity image processing device 100 can display areas with large curvature values ​​as red and areas with small curvature values ​​as blue in the three-dimensional oral cavity model. However, it is not limited to this.

[0073] Figure 6 This is a figure illustrating a method for acquiring roughness information of a three-dimensional oral cavity model using an oral cavity image processing apparatus according to an embodiment.

[0074] According to one embodiment, an oral cavity image processing apparatus 100 can acquire roughness information of multiple points in a three-dimensional oral cavity model based on curvature information. Roughness can be a value representing the vertical state of a surface, i.e., the degree of curvature. The roughness value of a point in the three-dimensional oral cavity model can be determined as follows: when comparing the curvature value of the corresponding point with the curvature values ​​of multiple surrounding points, if the difference is large, the roughness value is large; if the difference is small, the roughness value is small.

[0075] exist Figure 6 The method for obtaining roughness values ​​using the fourth point P4 as a reference is explained.

[0076] Reference Figure 6 According to one embodiment, the oral cavity image processing apparatus 100 can calculate the difference between the curvature value of the point whose roughness value is to be calculated and the curvature values ​​of each point within a preset radius centered on the corresponding point. For example, when calculating the roughness value of the fourth point P4, the curvature values ​​of multiple points (first point P1, second point P2, third point P3, fifth point P5, and sixth point P6) located within a radius R1 centered on the fourth point P4 can be used. In this case, R1 can be 0.5 mm, but this is just an example and can have other values.

[0077] The oral cavity image processing device 100 can calculate the difference c1 (e.g., 0.8) between the curvature values ​​of the first point P1 and the fourth point P4, the difference c2 (e.g., 0.7) between the curvature values ​​of the second point P2 and the fourth point P4, the difference c3 (e.g., 1) between the curvature values ​​of the third point P3 and the fourth point P4, the difference c5 (e.g., 0.8) between the curvature values ​​of the fifth point P5 and the fourth point P4, and the difference c6 (e.g., 0.9) between the curvature values ​​of the sixth point P6 and the fourth point P4.

[0078] The oral cavity image processing apparatus 100 can calculate an average value by applying weighted values ​​to each calculated difference. The weighted values ​​applied to each difference can be determined in a manner inversely proportional to the distance between multiple points. For example, the oral cavity image processing apparatus 100 can determine a larger weighted value for the difference in curvature values ​​between the point where the roughness value is to be calculated and a closer point, and a smaller weighted value for the difference in curvature values ​​between the point where the roughness value is to be calculated and a farther point.

[0079] For example, the oral image processing device 100 can apply the largest weighting value w3 (e.g., 0.9) to the difference c3 (e.g., 1) between the curvature value of the third point P3, which is closest to the fourth point P4, and the curvature value of the fourth point P4, and apply the smallest weighting value w6 (e.g., 0.1) to the difference c6 (e.g., 0.9) between the curvature value of the sixth point P6, which is farthest from the fourth point P4, and the curvature value of the fourth point P4. However, the above values ​​are merely examples, and various weighting values ​​can be applied.

[0080] When determining the weighting values, the oral cavity image processing device 100 can calculate an average value (e.g., 0.412) by applying the weighting values ​​to the calculated differences. The calculated average value can be determined as the roughness value of the fourth point P4.

[0081] The oral cavity image processing device 100 can determine the roughness value of each point in the three-dimensional oral cavity model by means of the method described above.

[0082] Figure 7 This is a diagram illustrating a method for determining roughness color using an oral cavity image processing apparatus according to an embodiment.

[0083] Reference Figure 7According to one embodiment, an oral cavity image processing apparatus 100 can determine the roughness color of each point based on the roughness value of each point in a three-dimensional oral cavity model. The oral cavity image processing apparatus 100 can use a color bar 700 to map the color corresponding to the roughness value of each point to each point. For example, if the roughness value of the first point P1 is 5.73, the oral cavity image processing apparatus 100 can determine the first color 710 corresponding to 5.73 in the color bar 700 as the roughness color of the first point P1. Furthermore, if the roughness value of the second point P2 is 0.412, the second color 730 corresponding to 0.412 in the color bar 700 can be determined as the roughness color of the second point P2. Furthermore, if the roughness value of the third point P3 is 0.418, the third color 720 corresponding to 0.418 in the color bar 700 can be determined as the roughness color of the third point P3.

[0084] On the other hand, according to one embodiment, the color bar 700 can be set as follows: the larger the roughness value, the red is mapped, and the smaller the roughness value, the green is mapped, but it is not limited thereto. Furthermore, the oral cavity image processing apparatus 100 can change the color mapped in the color bar 700 and the roughness value range of the mapped predetermined color. For example, the oral cavity image processing apparatus 100 can change the range of roughness values ​​of the fourth color 760 (e.g., green) mapped in the color bar 700 based on user input of directly inputting a first value 740 or user input of moving the triangle icon 750 up and down.

[0085] Furthermore, when determining the roughness colors of the first point P1, the second point P2, and the third point P3, the oral cavity image processing apparatus 100 according to one embodiment can determine the color of the first triangular mesh M1 composed of the first point P1, the second point P2, and the third point P3. For example, the oral cavity image processing apparatus 100 can determine the roughness color of the first triangular mesh M1 by mixing the roughness colors of the first point P1, the second point P2, and the third point P3. In this case, the first triangular mesh M1 can be represented by a single color or by a gradient of multiple colors. However, it is not limited to this.

[0086] Figure 8 This is a diagram illustrating a method for detecting edges or cervical margins in a three-dimensional oral cavity model using an oral image processing apparatus according to an embodiment.

[0087] In a 3D oral cavity model, the cervical region or marginal region, which serves as the boundary between teeth and gums, inevitably has a large curvature value in its shape and structure. The cervical region refers to the neck of the tooth or the area adjacent to it, while the marginal region refers to the edge of the tooth or the area adjacent to it.

[0088] Because the curvature values ​​of the cervical or marginal regions are large, the roughness values ​​of the corresponding regions are always also large. Therefore, when providing roughness information of the three-dimensional oral cavity model to confirm the preparation status, the oral cavity image processing device 100 can process the roughness values ​​of the cervical or marginal regions to 0 or a preset value. For example, if the roughness values ​​of the cervical or marginal regions are large, it can be understood that the corresponding regions also require additional preparation.

[0089] An oral cavity image processing apparatus 100 according to one embodiment can detect the cervical region or marginal region in a three-dimensional oral cavity model. Hereinafter, refer to... Figure 8 The method for determining whether a predetermined point is located in the cervical region or the marginal region is explained.

[0090] The oral cavity image processing device 100 can determine whether the fourth point P4 is located in the cervical region or the marginal region. The oral cavity image processing device 100 can detect the two outermost reference points among a plurality of points located within a preset radius R2 centered on the fourth point P4. For example, the oral cavity image processing device 100 can detect the first point P1 and the sixth point P6 as reference points.

[0091] The oral image processing device 100 measures the distance K1 between the tangent 830 of the normal vector 820 of the fourth point P4 and the first point P1, and the distance K2 between the tangent 830 of the normal vector 820 of the fourth point P4 and the sixth point P6. When the average value of K1 and K2 is above a preset threshold, it can be determined that the fourth point P4 is located in the cervical region or the marginal region.

[0092] According to one embodiment, the oral image processing device 100 can set the roughness value of multiple points located in the cervical region or edge region to 0 or a preset value.

[0093] Figure 9 This is a diagram illustrating an example of a dental image processing apparatus displaying roughness information of a three-dimensional dental model according to an embodiment.

[0094] Reference Figure 9 The oral cavity image processing device 100 can display a roughness mode menu 910 on the user interface screen for displaying roughness information of a three-dimensional oral cavity model. When user input is received to select the roughness mode menu 910, the oral cavity image processing device 100 can display the roughness information 920 of the three-dimensional oral cavity model using color. For example, as Figure 7As shown and illustrated, when determining the roughness color of multiple points and meshes in a 3D oral cavity model, the points and meshes can be displayed using a specific color. In this case, areas with small roughness values ​​can be displayed using a first color 930 (e.g., green), and areas displayed by the first color can represent areas that do not require additional preparation work. Conversely, areas with large roughness values ​​can be displayed using a second color 940 (e.g., yellow) or a third color 950 (e.g., red), and areas displayed by the second color 940 or the third color 950 can represent areas that require additional preparation work.

[0095] In addition, such as Figure 8 As shown and illustrated, the roughness values ​​of multiple points and multiple meshes located in the cervical region or the edge region of the tooth can be set to 0 or a preset value. In this case, 0 or the preset value can be mapped to the first color 930, such as... Figure 9 As shown, the cervical region 960 or the marginal region 970 can be displayed using a first color (e.g., green) that indicates an area that does not require additional preparation work.

[0096] Figure 10 This is a flowchart illustrating an oral cavity image processing method according to an embodiment.

[0097] Reference Figure 10 According to one embodiment, the oral image processing device 100 can acquire oral data and acquire a three-dimensional oral model based on the oral data (S1010).

[0098] Oral data can be acquired by scanning at least one tooth using an oral scanner 1000. In this case, not only the tooth but also the adjacent gingiva can be scanned. According to one embodiment, the oral data can be point data or mesh data, and can be data representing surface information of the oral cavity. For example, oral data may include point location information, point normal vectors, point tangent vectors, mesh normal vectors, mesh location information, etc., but is not limited to these.

[0099] Furthermore, the oral cavity image processing device 100 can generate a three-dimensional oral cavity model based on oral cavity data. In this case, the three-dimensional oral cavity model may include multiple points, or it may include a triangular mesh composed of multiple points. However, it is not limited to this; the three-dimensional oral cavity model may be composed of other polygonal meshes such as quadrilaterals.

[0100] According to one embodiment, the oral image processing device 100 can acquire curvature information of multiple points in a three-dimensional oral model (S1020).

[0101] The curvature value of a specified point in a three-dimensional oral cavity model can represent the degree of curvature of a curve defined on the surface of the object at the corresponding point. When the curve or surface passing through the point is convex, the oral cavity image processing device 100 can determine the sign of the curvature value of the corresponding point as "+", and when the curve or surface passing through the point is concave, the oral cavity image processing device 100 can determine the sign of the curvature value of the corresponding point as "-".

[0102] Furthermore, the oral cavity image processing device 100 can determine the curvature value of a point using the normal vectors of multiple grids adjacent to the point. The oral cavity image processing device 100 can determine the curvature value of a corresponding point based on the difference between at least two of the normal vectors of the multiple grids adjacent to the point. In this case, the difference between the multiple normal vectors can be represented by the angle between the multiple normal vectors. The oral cavity image processing device 100 can determine the curvature value of a point such that the larger the angle between the normal vectors of the multiple adjacent grids, the larger the curvature value, and the smaller the angle between the normal vectors of the multiple grids, the smaller the curvature value. Because in Figure 4 The method for determining the curvature value of a point is described in detail in the document, so its detailed description will be omitted.

[0103] According to one embodiment, the oral cavity image processing device 100 can acquire roughness information of multiple points in a three-dimensional oral cavity model based on curvature information (S1030).

[0104] Roughness can be a value representing the degree of curvature of a surface, i.e., the extent of its bending. The oral cavity image processing device 100 can determine the roughness value as follows: when comparing the curvature value of a point in a three-dimensional oral cavity model with the curvature values ​​of multiple surrounding points, a large difference indicates a large roughness value, and a small difference indicates a small roughness value. Because in Figure 6 The method for calculating the roughness value of a point is described in detail in the document, so its detailed description will be omitted.

[0105] According to one embodiment, the oral cavity image processing device 100 can determine the color of a three-dimensional oral cavity model based on roughness information of multiple points (S1040).

[0106] An oral cavity image processing apparatus 100 according to one embodiment can determine the roughness color of each point based on the roughness value of each point in a three-dimensional oral cavity model. For example, the oral cavity image processing apparatus 100 can use a color bar to map the color corresponding to the roughness value of each point to each point. Furthermore, when determining the roughness color of multiple points, the oral cavity image processing apparatus 100 can determine the roughness color of the mesh by mixing the roughness colors of the multiple points that make up the mesh. Since already... Figure 7 The details are explained in detail in the document, so the details will be omitted.

[0107] Furthermore, according to one embodiment, the oral image processing device 100 can detect the cervical region or the edge region of the tooth, which serves as the boundary between the tooth and the gingiva, in a three-dimensional oral model, set the roughness value of the cervical or edge region to 0 or a preset value, and determine the roughness color as a first color (e.g., green).

[0108] According to one embodiment, the oral image processing device 100 can display a three-dimensional oral model based on a determined color (S1050).

[0109] The oral cavity image processing device 100 can display the roughness information of a three-dimensional oral cavity model using color based on user input that selects a roughness mode. For example, in step 1040 (S1040), when the roughness color of multiple points and multiple meshes in the three-dimensional oral cavity model is determined, the oral cavity image processing device 100 can display the multiple points and multiple meshes using the determined color.

[0110] Figure 11 This is a block diagram illustrating an oral cavity image processing apparatus according to an embodiment.

[0111] Figure 10 The oral cavity image processing method shown can be executed by the oral cavity image processing device 100. Therefore, Figure 10 The method for processing oral images shown can be a flowchart illustrating the operation of the oral image processing device 100.

[0112] Reference Figure 11 The oral cavity image processing device 100 may include a communication interface 110, a user interface 120, a display 130, a memory 140, and a processor 150.

[0113] The communication interface 110 can communicate with at least one external electronic device (e.g., an oral scanner 1000, a server, or an external medical device) via a wired or wireless communication network. The communication interface 110 can communicate with at least one external electronic device under the control of the processor 150.

[0114] Specifically, the communication interface 110 may include at least one short-range communication module, which communicates according to communication standards such as Bluetooth, Wi-Fi, Bluetooth Low Energy (BLE), Near Field Communication / Radio Frequency Identification (NFC / RFID), Wi-Fi Direct, Ultra Wideband (UWB), or ZigBee.

[0115] Furthermore, the communication interface 110 may also include a remote communication module that communicates with a server supporting long-distance communication in accordance with remote communication standards. Specifically, the communication interface 110 may include a remote communication module that communicates via a network used for Internet communication. Additionally, the communication interface 110 may include a remote communication module that communicates via a communication network conforming to communication standards such as 3G, 4G, and / or 5G.

[0116] Furthermore, the communication interface 110 may include at least one port that can be connected to an external electronic device via a wired cable for wired communication with the external electronic device (e.g., an oral scanner). Thus, the communication interface 110 is capable of communicating with an external electronic device that is wiredly connected via at least one port.

[0117] The user interface 120 can receive user input for controlling the oral imaging processing device 100. The user interface 120 may include: a touch panel for detecting user touch, buttons for receiving user press operations, and user input devices, including, but not limited to, a mouse or keyboard for specifying or selecting a point on the user interface screen.

[0118] Furthermore, the user interface 120 may include a voice recognition device for speech recognition. For example, the voice recognition device may be a microphone, capable of receiving voice commands or voice requests from the user. Thus, the processor 150 can control the execution of operations corresponding to the voice commands or voice requests.

[0119] The display 130 displays a screen. Specifically, the display 130 may display a predetermined screen under the control of the processor 150. Specifically, the display 130 may display a user interface screen including a generated oral cavity image based on data acquired by scanning the patient's oral cavity through the oral scanner 1000. Alternatively, the display 130 may display a user interface screen including information related to the patient's dental treatment.

[0120] Memory 140 may store at least one instruction. Furthermore, memory 140 may store at least one instruction executed by processor 150. Additionally, memory 140 may store at least one program executed by processor 150. Furthermore, memory 140 may store data received from the oral scanner 1000 (e.g., raw data acquired by scanning the oral cavity). Alternatively, memory 140 may store an oral cavity image (three-dimensional oral cavity model) representing the oral cavity. According to one embodiment, memory 140 may include one or more instructions for providing roughness information of the three-dimensional oral cavity model. According to one embodiment, memory 140 may include one or more instructions for performing the methods disclosed in this specification to provide roughness information of the three-dimensional oral cavity model.

[0121] The processor 150 executes at least one instruction stored in the memory 140 to control the execution of a desired operation. The at least one instruction may be stored in the internal memory of the processor 150 or in the memory 140, which is included separately from the processor within a data processing device.

[0122] Specifically, the processor 150 executes at least one instruction to control at least one structure within the data processing device, thereby performing a predetermined operation. Therefore, even though the example illustrates the processor performing a predetermined operation, it also implies that the processor controls at least one structure within the data processing device to perform the predetermined operation.

[0123] According to one embodiment, a processor 150 scans at least one tooth to acquire oral cavity data by executing one or more instructions stored in a memory 140. The oral cavity data according to one embodiment can be point data or mesh data, and can be data representing surface information of the oral cavity. For example, the oral cavity data may include point location information, point normal vectors, point tangent vectors, mesh normal vectors, mesh location information, etc., but is not limited thereto.

[0124] Furthermore, the processor 150 generates a three-dimensional oral cavity model based on oral cavity data by executing one or more instructions stored in the memory 140. The three-dimensional oral cavity model may include multiple points, or multiple meshes composed of those points.

[0125] Furthermore, the processor 150 can acquire curvature information of multiple points in the three-dimensional oral cavity model by executing one or more instructions stored in the memory 140. Because in Figure 4 The method for determining the curvature values ​​of predetermined points in a three-dimensional oral cavity model is described in detail, so its detailed description will be omitted.

[0126] Processor 150 can acquire roughness information of multiple points in a three-dimensional oral cavity model based on curvature information by executing one or more instructions stored in memory 140. Processor 150 can determine the roughness value in the following manner: when comparing the curvature value of a point in the three-dimensional oral cavity model with the curvature values ​​of multiple surrounding points, a larger difference indicates a larger roughness value, and a smaller difference indicates a smaller roughness value. Because in Figure 6 The method for calculating the roughness value of a point is described in detail in the document, so its detailed description will be omitted.

[0127] Processor 150 can determine the color of a three-dimensional oral cavity model based on roughness information from multiple points by executing one or more instructions stored in memory 140. For example, processor 150 can use a color bar to map the color corresponding to the roughness value of each point to each point. Furthermore, processor 150 can determine the roughness color of the mesh by mixing the roughness colors of the multiple points that make up the mesh.

[0128] The processor 150 can detect the cervical region or edge region of the tooth that serves as the boundary between the tooth and the gum in the three-dimensional oral cavity model by executing one or more instructions stored in the memory 140, set the roughness value of the cervical or edge region to 0 or a preset value, and determine the roughness color as a first color (e.g., green).

[0129] The processor 150 can control the display 130 to display a three-dimensional oral cavity model based on a determined roughness color by executing one or more instructions stored in the memory 140.

[0130] According to one example, the processor 150 may be embodied in the form of at least one internal processor and a memory device (e.g., random access memory (RAM), read-only memory (ROM), etc.) for storing at least one of programs, instructions, signals, and data stored in the internal processor for processing or use.

[0131] Furthermore, the processor 150 may include a graphics processing unit (GPU) for processing graphics corresponding to the video. Additionally, the processor may be implemented as a system-on-a-chip (SoC) integrating cores and a graphics processing unit (GPU). Furthermore, the processor may include multiple cores beyond a single core. For example, the processor may include dual-core, triple-core, quad-core, hexa-core, octa-core, deca-core, dodecathlon, hexadecimal, and so on.

[0132] In the disclosed embodiments, the processor 150 may generate an oral image based on a two-dimensional image received from the oral scanner 1000.

[0133] Specifically, the communication interface 110 can receive data acquired from the oral scanner 1000, such as raw data acquired by scanning the oral cavity, under the control of the processor 150. Furthermore, the processor 150 can generate a three-dimensional oral cavity image representing the oral cavity based on the raw data received from the communication interface 110. For example, the oral scanner 1000 may include an L-camera corresponding to the left field of view and an R-camera corresponding to the right field of view to reconstruct a three-dimensional image using optical triangulation. Moreover, the oral scanner can acquire L-image data corresponding to the left field of view and R-image data corresponding to the right field of view from the L-camera and the R-camera, respectively. Subsequently, the oral scanner can send the raw data, including the L-image data and the R-image data, to the communication interface 110 of the oral cavity image processing device 100.

[0134] Then, the communication interface 110 can transmit the received raw data to the processor 150, and the processor 150 generates a three-dimensional oral cavity image based on the received raw data.

[0135] Furthermore, the processor 150 can directly receive three-dimensional oral cavity images from external servers, medical devices, etc., via the control communication interface 110. In this case, the processor can acquire three-dimensional oral cavity images without generating three-dimensional oral cavity images based on raw data.

[0136] According to the disclosed embodiments, the processor 150 performing operations such as "extracting", "acquiring", and "generating" can refer to the case where the processor 150 directly performs the operations described above by executing at least one instruction in the processor 150, and the case where it controls other constituent elements to perform the operations described above.

[0137] To implement the embodiments disclosed in this specification, the oral cavity image processing device 100 may include Figure 7 A portion of the constituent elements shown may also include Figure 7 More constituent elements than those shown.

[0138] Furthermore, the oral image processing device 100 can store and execute dedicated software that works in conjunction with the oral scanner. This dedicated software can be referred to as a dedicated program, tool, or application. When the oral image processing device 100 and the oral scanner 1000 operate in conjunction, the dedicated software stored in the oral image processing device 100 is connected to the oral scanner 1000 and can receive data acquired through oral cavity scanning in real time. For example, dedicated software exists in Medit's i500 oral scanner product for processing data acquired through oral cavity scanning. Specifically, Medit has created and released "Medit Link" software for processing, managing, using, and / or transmitting data acquired from an oral scanner (e.g., the i500). "Dedicated software" refers to an operable program, tool, or application that works in conjunction with the oral scanner; therefore, it can be used with various oral scanners developed and sold by various manufacturers. Furthermore, the dedicated software described above can be created and released separately from the oral scanner that performs the oral cavity scan.

[0139] The oral image processing device 100 can store and execute dedicated software corresponding to the i500 product. The transmission software can perform at least one operation for acquiring, processing, storing, and / or transmitting oral images. The dedicated software can be stored in a processor. Furthermore, the dedicated software can provide a user interface for using data acquired from the oral scanner. The user interface screen provided by the dedicated software can include oral images generated according to the disclosed embodiments.

[0140] A method for processing oral images according to an embodiment of the present disclosure is implemented in the form of program commands executable by various computer mechanisms and recorded in a computer-readable medium. Furthermore, embodiments of the present disclosure may use a computer-readable storage medium containing one or more programs including at least one instruction for performing the method for processing oral images.

[0141] The computer-readable storage medium may include, individually or in combination, program instructions, 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 such as ROMs, RAMs, and flash memory for storing and executing program instructions.

[0142] The device-readable storage medium may be provided in the form of a non-transitory storage medium. "Non-transitory storage medium" can mean a tangible device. Furthermore, "non-transitory storage medium" may include buffers for temporary data storage.

[0143] According to one embodiment, methods for processing oral images according to various embodiments disclosed in this specification can be provided by being included in a computer program product. The computer program product can be distributed in the form of a device-readable storage medium (e.g., a compact disc read-only memory, CD-ROM). Alternatively, it can be distributed (e.g., downloaded or uploaded) directly or online between two user devices (e.g., smartphones) through an app store (e.g., a game store). Specifically, the computer program product according to the disclosed embodiments may include a storage medium recording a program comprising at least one instruction to perform the methods for processing oral images according to the disclosed embodiments.

[0144] 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 using the basic concepts of the present invention as defined in the claims are also within the scope of the present invention.

Claims

1.An oral cavity image processing method, comprising: acquiring a three-dimensional oral cavity model of an oral cavity, acquiring curvature information including curvature values of a plurality of points included in the three-dimensional oral cavity model, acquiring roughness information including roughness values of the plurality of points included in the three-dimensional oral cavity model based on the curvature information, acquiring a color of the three-dimensional oral cavity model based on the roughness information, and displaying the three-dimensional oral cavity model based on the acquired color. The step of acquiring the roughness information includes: determining a roughness value of at least one point included in an edge region or a neck region of a tooth among the plurality of points as a preset value. 2.The oral cavity image processing method of claim 1, wherein The step of acquiring the roughness information includes: determining a roughness value of a first point among the plurality of points based on a curvature value of at least one second point adjacent to the first point among the plurality of points. 3.The oral cavity image processing method of claim 1, wherein The step of acquiring the roughness information includes: determining a roughness value of a first point among the plurality of points based on a difference between a curvature value of at least one second point adjacent to the first point among the plurality of points and a curvature value of the first point. 4.The oral cavity image processing method of claim 1, wherein The step of acquiring the roughness information includes: calculating a difference between a curvature value of each of a plurality of second points within a preset first distance from a first point among the plurality of points and a curvature value of the first point, determining a weighted value of the difference based on a distance between each of the plurality of second points and the first point, and determining a roughness value of the first point based on the difference value and the weighted value for the plurality of second points. 5.The oral cavity image processing method of claim 4, wherein The step of determining the roughness value of the first point includes: calculating an average value of the difference value based on the weighted value, and determining the calculated average value as the roughness value of the first point. 6.The oral cavity image processing method of claim 1, wherein The step of acquiring the roughness information includes: determining roughness values of the plurality of points such that the roughness values of the plurality of points are greater as a surface of the three-dimensional oral cavity model on which the plurality of points are located is rougher, and the roughness values of the plurality of points are smaller as the surface of the three-dimensional oral cavity model on which the plurality of points are located is smoother. 7.The oral cavity image processing method of claim 1, wherein The step of acquiring the roughness information includes: determining a roughness value of a first point among the plurality of points, The step of determining the roughness value of the first point includes: ​ determining whether the first point is included in an edge region or a cervical region of a tooth based on distances between tangent lines of the first point, a third point that is farthest from the first point in a first direction among a plurality of points located within a preset second distance from the first point, and a fourth point that is farthest from the first point in a second direction, and in a case where the first point is included in the edge region or the cervical region of the tooth, determining a roughness value of the first point as a preset value. 8.The oral cavity image processing method of claim 1, wherein the acquiring of the color of the three-dimensional oral cavity model comprises: determining a color of a point based on a roughness value of each of the plurality of points, and mixing the colors of the plurality of points to determine a color of a mesh constituted by the plurality of points. 9.An oral cavity image processing apparatus comprising: a display, a memory configured to store one or more instructions, and a processor; the processor, by executing the one or more instructions stored in the memory, acquires a three-dimensional oral cavity model regarding an oral cavity, acquires curvature information including curvature values of a plurality of points included in the three-dimensional oral cavity model, acquires roughness information including roughness values of the plurality of points included in the three-dimensional oral cavity model based on the curvature information, acquires a color of the three-dimensional oral cavity model based on the roughness information, controls the display to display the three-dimensional oral cavity model based on the acquired color, the processor, determines a roughness value of at least one point included in an edge region or a cervical region of a tooth among the plurality of points as a preset value. 10.The oral cavity image processing apparatus of claim 9, wherein the processor, by executing the one or more instructions stored in the memory, acquires a roughness value of a first point among the plurality of points based on a curvature value of at least one second point adjacent to the first point among the plurality of points. 11.The oral cavity image processing apparatus of claim 9, wherein the processor, by executing the one or more instructions stored in the memory, acquires a roughness value of a first point among the plurality of points based on a difference between a curvature value of at least one second point adjacent to the first point among the plurality of points and a curvature value of the first point. 12.The oral cavity image processing apparatus of claim 9, wherein the processor, by executing the one or more instructions stored in the memory, calculates a difference between a curvature value of each of a plurality of second points located within a preset first distance from a first point among the plurality of points and a curvature value of the first point, determines a weighted value of the difference based on a distance between each of the plurality of second points and the first point, acquires a roughness value of the first point based on the difference value and the weighted value for the plurality of second points. ​ ​ ​ ​ ​

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