System, method, and electronic device for path hint in intraoral scanning

Abstract

Example embodiments of the present invention provide a system, a method, and an electronic device for path prompting in intraoral scanning. A computing device coupled to an intraoral scanner is configured to perform, for cumulative scan data of a three-dimensional surface of an oral cavity at a current moment by the intraoral scanner: obtaining a plurality of key points; determining whether a target key point is a key point to be enhanced based on a connection relationship between the target key point and a plurality of neighboring key points of the target key point on a relationship network; determining a dental arch morphological contour curve of the three-dimensional surface of the oral cavity based on the obtained plurality of key points; and determining a scan prompting path for subsequent supplementary scanning of a pair of target key points to be enhanced based on a positional relationship between the dental arch morphological contour curve and the pair of target key points to be enhanced among the determined plurality of key points to be enhanced.

Description

Technical Field

[0001] Embodiments of the present invention mainly relate to the field of intraoral tooth scanning, and more particularly, to a system, method, and electronic device for path prompting in intraoral scanning. Background Art

[0002] In existing intraoral scanning systems, most do not provide real-time scanning prompts. Generally, a demonstration video is presented and users are guided through teaching. Even if there are path prompts, the displayed prompt paths are relatively rough and are generally similar in direction, mainly including inner and outer side prompts. However, many users need appropriate and effective guidance to help them perform efficient scanning during the scan. Without path guidance, many users may not know how to improve their scanning results during the scan and may spend more time. Therefore, good path prompts can enable users to complete high-quality scans more easily and efficiently. Summary of the Invention

[0003] According to an exemplary embodiment of the present invention, there is provided a system, method, and electronic device for path prompting in intraoral scanning.

[0004] According to a first aspect of the present invention, there is provided a system for path prompting in intraoral scanning, including an intraoral scanner; and a computing device coupled to the intraoral scanner. The computing device is configured to perform the following steps on the cumulative scan data of the oral three-dimensional surface at the current moment by the intraoral scanner: Step S1: Analyze the cumulative scan data to obtain a plurality of key points and a relationship network including the plurality of key points; Step S2: Use each key point among the plurality of key points as a target key point, and perform the following operations for each target key point: Based on the relationship network, determine the strength of the connection relationship between the target key point and a plurality of neighboring key points of the target key point on the relationship network, and compare the strength with a strength threshold to determine whether the target key point is a key point to be strengthened, where the distance between the plurality of neighboring key points and the target key point is within a first threshold range; Step S3: Based on the obtained plurality of key points, determine the arch contour curve of the oral three-dimensional surface; and Step S4: Determine the relative positions of a pair of target key points to be strengthened among the determined plurality of key points to be strengthened with respect to the arch contour curve of the oral three-dimensional surface, and based on the determined relative positions, determine a scan prompt path for subsequent supplementary scanning of the pair of target key points to be strengthened.

[0005] In some embodiments, to perform step S2, the computing device is configured to: pair the target key point with at least one neighboring key point among the multiple neighboring key points to obtain at least one pair of paired key points; for each pair of paired key points among the at least one pair of paired key points, fit a target plane based on the two paired key points and the normal vectors of the two paired key points; and for each pair of paired key points, determine the sum of the vertical distances from the multiple target path points on the target path from the target key point to the neighboring key point paired with it to the target plane as the strength of the connection relationship for each pair of paired key points; and based on the comparison between the strength and the strength threshold, determine whether the target key point is a key point to be strengthened.

[0006] In some embodiments, to determine whether the target key point is a key point to be strengthened, the computing device is configured to: determine the intersection line of the target plane and the relationship network as the target path; calculate the sum of the vertical distances from the multiple target path points on the target path to the target plane; determine whether the sum of the vertical distances is less than a second distance threshold, where the second distance threshold is the strength threshold; and based on determining that the sum of the vertical distances is greater than the second distance threshold, determine that the target key point is a key point to be strengthened.

[0007] In some embodiments, to perform step S3, the computing device is configured to: project the multiple key points onto a two-dimensional plane, where the two-dimensional plane includes the vertical projection surface of the three-dimensional oral surface; and based on the coordinate information of the multiple key points on the two-dimensional plane, determine the arch shape contour curve of the three-dimensional oral surface.

[0008] In some embodiments, to perform step S4, the computing device is configured to: determine multiple key points to be strengthened that have a connection relationship with a target key point to be strengthened in the relationship network to obtain multiple pairs of key points to be strengthened belonging to a group for the target key point to be strengthened; select each pair of key points to be strengthened among the multiple pairs of key points to be strengthened as a pair of target key points to be strengthened; perform the following operations for a pair of target key points to be strengthened: based on the position of the extension line of the normal vector of each target key point to be strengthened in the pair of target key points to be strengthened relative to the arch shape contour curve, determine the relative position relationship of each target key point to be strengthened relative to the arch shape contour curve; and based on the determined relative position relationship and the arch shape contour curve, determine the scanning prompt path for the subsequent supplementary scan for the pair of target key points to be strengthened.

[0009] In some embodiments, the computing device is further configured to: determine a plurality of scanning prompt paths for multiple pairs of key points to be strengthened; assign weights to the plurality of scanning prompt paths respectively based on the vertical crossing degrees of the plurality of scanning prompt paths and the dental arch morphological contour curve; and select a target scanning prompt path with a weight higher than a threshold weight for display.

[0010] In some embodiments, the computing device further assigns weights to the scanning prompt paths for each pair of key points to be strengthened based on the normal vector angle difference of each pair of key points to be strengthened among the multiple pairs of key points to be strengthened.

[0011] In some embodiments, the computing device is further configured to: for the cumulative scanning data after the global scanning of the oral three-dimensional surface by the intraoral scanner, perform steps S1 to S4 to obtain an updated relationship network and a relationship area to be optimized in the relationship network.

[0012] In some embodiments, the computing device is further configured to: after the global scanning of the oral three-dimensional surface by the intraoral scanner, divide the oral three-dimensional surface into multiple regions based on the scanned point cloud, and assign corresponding weights to the multiple regions respectively.

[0013] In some embodiments, the corresponding weight includes a scanning quality metric threshold, and the computing device is further configured to: after the global scanning of the oral three-dimensional surface by the intraoral scanner, for a target vertex in the three-dimensional mesh model mesh of the oral three-dimensional surface, calculate a scanning quality metric for the target vertex based on the quality of the neighborhood point cloud of the target vertex to compare with the scanning quality metric threshold.

[0014] In some embodiments, the corresponding weight includes a curvature threshold, and the computing device is further configured to: after the global scanning of the oral three-dimensional surface by the intraoral scanner, perform a curvature detection on the three-dimensional mesh model mesh, and perform a diffusion operation on a region with a curvature greater than the curvature threshold to make the region larger.

[0015] According to a second aspect of the present invention, there is provided a method for path prompting for intraoral scanning. The method includes performing the following steps on the cumulative scanning data of the three-dimensional surface of the oral cavity at the current moment by an intraoral scanner: Step S1: Analyze the cumulative scanning data to obtain a plurality of key points and a relationship network including the plurality of key points; Step S2: Take each of the plurality of key points as a target key point, and perform the following operations for each target key point: Based on the relationship network, determine the strength of the connection relationship between the target key point and a plurality of neighboring key points of the target key point on the relationship network, and compare the strength with a strength threshold to determine whether the target key point is a key point to be strengthened, and the distance between the plurality of neighboring key points and the target key point is within a first threshold range; Step S3: Based on the obtained plurality of key points, determine the arch shape contour curve of the three-dimensional surface of the oral cavity; and Step S4: Determine the relative positions of a pair of target key points to be strengthened among the determined plurality of key points to be strengthened with respect to the arch shape contour curve, and based on the determined relative positions, determine the scanning prompt path for the subsequent supplementary scanning of the pair of target key points to be strengthened.

[0016] In some embodiments, Step S2 includes: Pairing the target key point with at least one neighboring key point among the plurality of neighboring key points to obtain at least one pair of paired key points; For each pair of paired key points among the at least one pair of paired key points, fit a target plane based on the two paired key points and the normal vectors of the two paired key points; and For each pair of paired key points, determine the sum of the vertical distances from a plurality of target path points on the target path from the target key point to the neighboring key point paired with it to the target plane as the strength of the connection relationship for each pair of paired key points, and based on the comparison of the strength with the strength threshold, determine whether the target key point is a key point to be strengthened.

[0017] In some embodiments, determining the sum of the vertical distances from a plurality of target path points on the target path from the target key point to the neighboring key point paired with it to the target plane as the strength of the connection relationship for each pair of paired key points, and based on the comparison of the strength with the strength threshold, determining whether the target key point is a key point to be strengthened: Determine the intersection line of the target plane and the relationship network as the target path; Calculate the sum of the vertical distances from a plurality of target path points on the target path to the target plane; Determine whether the sum of the vertical distances is less than a second distance threshold, where the second distance threshold is the strength threshold; and Based on determining that the sum of the vertical distances is greater than the second distance threshold, determine that the target key point is a key point to be strengthened.

[0018] In some embodiments, Step S3 includes: Projecting the plurality of key points onto a two-dimensional plane, where the two-dimensional plane includes the vertical projection surface of the three-dimensional surface of the oral cavity; and Based on the coordinate information of the plurality of key points on the two-dimensional plane, determine the arch shape contour curve of the three-dimensional surface of the oral cavity.

[0019] In some embodiments, step S4 includes: determining a plurality of key points to be strengthened that have connection relationships with a target key point to be strengthened in a relationship network, so as to obtain multiple pairs of key points to be strengthened for the target key point to be strengthened that belong to a group; selecting each pair of key points to be strengthened in the multiple pairs of key points to be strengthened as a pair of target key points to be strengthened; performing the following operations on a pair of target key points to be strengthened: determining the relative position relationship of each target key point to be strengthened with respect to the dental arch form contour curve based on the position of the extension line of the normal vector of each target key point to be strengthened in the pair of target key points to be strengthened relative to the dental arch form contour curve; and determining a scanning prompt path for subsequent supplementary scanning for the pair of target key points to be strengthened based on the determined relative position relationship and the dental arch form contour curve.

[0020] In some embodiments, the method further includes: determining a plurality of scanning prompt paths for the multiple pairs of key points to be strengthened; assigning weights to the multiple scanning prompt paths respectively based on the vertical intersection degrees of the multiple scanning prompt paths with the dental arch form contour curve; and selecting a target scanning prompt path with a weight higher than a threshold weight for display.

[0021] In some embodiments, the method further includes: after the global scanning of the oral three-dimensional surface by the intraoral scanner is completed, performing steps S1 to S4 on the cumulative scanning data to obtain an updated relationship network and a relationship area to be optimized in the relationship network.

[0022] In some embodiments, the method further includes: after the global scanning of the oral three-dimensional surface by the intraoral scanner is completed, dividing the oral three-dimensional surface into multiple regions based on the scanned point cloud, and respectively assigning corresponding weights to the multiple regions; the corresponding weights include a scanning quality metric threshold, and after the global scanning of the oral three-dimensional surface by the intraoral scanner is completed, for a target vertex in the three-dimensional mesh model mesh of the oral three-dimensional surface, calculating a scanning quality metric for the target vertex based on the quality of the neighborhood point cloud of the target vertex to compare with the scanning quality metric threshold; or the corresponding weights include a curvature threshold, and after the global scanning of the oral three-dimensional surface by the intraoral scanner is completed, performing a curvature detection on the three-dimensional mesh model mesh, and performing a diffusion operation on a region with a curvature greater than the curvature threshold to make the region larger.

[0023] According to a third aspect of the present invention, there is provided an electronic device, comprising: a processor; and a memory storing executable instructions which, when executed by the processor, cause the electronic device to at least: for the cumulative scan data of the oral three-dimensional surface at the current moment by an intraoral scanner, perform the following steps: Step S1: Analyze the cumulative scan data to obtain a plurality of key points and a relationship network including the plurality of key points; Step S2: Take each of the plurality of key points as a target key point, and perform the following operations for each target key point: Based on the relationship network, determine the strength of the connection relationship between the target key point and a plurality of neighboring key points of the target key point on the relationship network, and compare the strength with a strength threshold to determine whether the target key point is a key point to be strengthened, and the distance between the plurality of neighboring key points and the target key point is within a first threshold range; Step S3: Based on the plurality of key points obtained, determine the arch contour curve of the oral three-dimensional surface; and Step S4: Determine the relative positions of a pair of target key points to be strengthened among the determined plurality of key points to be strengthened with respect to the arch contour curve, and based on the determined relative positions, determine a scan prompt path for subsequent supplementary scanning of the pair of target key points.

[0024] It should be understood that the content described in the summary of the invention section is not intended to limit the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In conjunction with the accompanying drawings and with reference to the following detailed description, the above and other features, advantages and aspects of the embodiments of the present invention will become more apparent. In the drawings, the same or similar reference numerals denote the same or similar elements, wherein:

[0026] Figure 1 An intraoral scanning system according to some example embodiments of the present invention is shown;

[0027] Figure 2 A schematic diagram showing the flow of a method for intraoral scanning according to some embodiments of the present invention is shown;

[0028] Figure 3A A schematic diagram showing a relationship network for a part of an arch according to some embodiments of the present invention, in which there are path points, a plurality of key points, and the determined key points to be strengthened;

[0029] Figure 3B A schematic diagram showing a curve obtained by performing convex hull detection according to some embodiments of the present invention is shown;

[0030] Figure 3CSchematic diagram showing a curve obtained by performing convex hull detection according to some embodiments of the present invention;

[0031] Figure 4A Schematic diagram showing a scanning prompt path for a target key point to be strengthened according to some embodiments of the present invention;

[0032] Figure 4B Schematic diagram showing, according to some embodiments of the present invention Figure 4A an enlarged schematic diagram of a part of

[0033] Figures 5A to 5E Schematic diagram showing a scanning path prompt according to some embodiments of the present invention;

[0034] Figure 6A Schematic diagram showing quality detection for an entire dental arch according to some embodiments of the present invention;

[0035] Figure 6B and Figure 6C Schematic diagram showing hierarchical area diffusion display according to some embodiments of the present invention; and

[0036] Figure 7 Block diagram showing a computing device capable of implementing multiple embodiments of the present invention. Detailed Description of the Invention

[0037] Embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although some embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. On the contrary, these embodiments are provided to more thoroughly and completely understand the present invention. It should be understood that the drawings and embodiments of the present invention are for illustrative purposes only and are not used to limit the protection scope of the present invention.

[0038] In the description of the embodiments of the present invention, the term "including" and its like should be understood as an open inclusion, i.e., "including but not limited to". The term "based on" should be understood as "at least partially based on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". Terms such as "first", "second", etc. may refer to different or the same objects. There may be other explicit and implicit definitions hereinafter.

[0039] Figure 1Shown is an intraoral scanning system 100 according to some example embodiments of the present invention. The intraoral scanning system 100 includes an intraoral scanner 110 and a computing device 120 (such as a laptop computer, a desktop computer, etc.) coupled together. Such a communication link between the intraoral scanner 110 and the computing device 120 allows captured images and control commands to be transmitted from the intraoral scanner 110 to the computing device 120 for further processing. The communication link can be implemented via a wired connection (such as a Universal Serial Bus (USB)) or a wireless connection (such as Wi-Fi (Wireless Fidelity)). It should be understood that other communication implementations are also possible.

[0040] The intraoral scanner 110 can be a handheld device that a dentist (or a dental assistant) can insert into a patient's oral cavity to capture images. As shown, the intraoral scanner 110 includes a tip 101 and a body 102. The tip 101 can be a detachable component or integrated with the intraoral scanner 110. At the top of the tip 101, there is a camera or an optical system 103 for capturing images of teeth and surrounding tissues (such as gums). In addition, the intraoral scanner 110 can include one or more buttons (not shown), and the dentist can press the button(s) to control the system 100, including but not limited to capturing images of the patient's oral cavity, starting or stopping the scan, selecting the mode of the system, or controlling the view of the 3D image of the oral structure.

[0041] The computing device 120 can include a screen 115 or be connected to a screen 115 for displaying a user interface such as a graphical user interface (GUI). The GUI may include a visualization of the scan data, such as a 3D representation of the patient's oral cavity, and UI elements such as menus or icons. The dentist can interact with the UI elements to control the intraoral scanning system 100 and examine the 3D representation displayed on the screen 115. Most commonly, the dentist uses an input device 125 (such as a mouse or a keyboard connected to the computing device 120) to interact with the UI elements.

[0042] During intraoral scanning, for areas with poor scanning quality, it generally refers to the situation where the amount of data captured by the scan is poor (possibly due to issues such as scanning duration, angle, exposure, etc.), or the roughness of the scanning technique leads to errors in the connection relationship of the data network, resulting in stratification or insufficient details in the constructed geometric form. For example, during the scanning process, different scanning durations are applied to different areas of the entire dental arch. Generally, the scanning time for the anterior tooth area is shorter than that for the molar area. Coupled with the relatively less obvious features in the anterior tooth area, the scanning data for the anterior teeth will be relatively sparse.

[0043] For example, the prompts generated by different scanning techniques are quite different. The prompt for loop scanning mainly prompts the user to make up the connection between the inner and outer sides, while the Z-shaped scanning method mainly prompts the unilateral connection. Different device users have different techniques, and the data networks constructed by loop scanning and Z-shaped scanning vary greatly. For example, the overall error caused by loop scanning will be larger.

[0044] For the above-mentioned areas with scanning differences, supplementary scanning needs to be performed, and the user needs to be prompted on how to perform the supplementary scanning. Many users need appropriate and effective guidance to help them perform efficient scanning when scanning. Without path guidance, many users may not know how to improve their scanning results and will spend more time. Therefore, good path prompts will enable users to complete high-quality scanning more easily and efficiently.

[0045] However, in the designs of most traditional manufacturers, real-time scanning prompts are not provided. Generally, a demonstration video is presented to guide users through teaching. The prompts of manufacturers with path prompts are relatively rough, and the directions of the paths are roughly the same, all of which are inner and outer side prompts, and cannot give specific prompts according to the actual scanning technique and area. For example, traditional prompts only simply prompt the areas that are not scanned and have gaps and holes, but these areas can be captured by the user with the naked eye, and there is no need for prompts. As for other areas that cannot be observed by the naked eye, traditional scanning path methods often cannot prompt them.

[0046] Therefore, an improved scanning path optimization method is needed, which can not only prompt the user for those areas visible to the naked eye, but also prompt the user to optimize and improve the scanning path through internal data relationships. Among them, the direction of the optimized path needs to give specific prompts according to the actual scanning technique and area (that is, according to the real-time scanning results, which may vary due to different scanning techniques and areas).

[0047] The following will refer to Figures 2 to 7 to describe a method for intraoral scanning according to some embodiments of the present invention.

[0048] Figure 2 FIG. shows a schematic diagram of a process 200 of a method for intraoral scanning according to some embodiments of the present invention. Each step of this process 200 is performed on the cumulative scanning data of the oral three-dimensional surface by the intraoral scanner at the current moment. Figure 3A FIG. shows a schematic diagram of a relationship network 300 of a part of the dental arch according to some embodiments of the present invention. In this relationship network, there are path points (gray dots), multiple key points (green pentagrams), and the determined key points to be strengthened (red pentagrams).

[0049] In block 210, based on the real-time scan of the oral three-dimensional surface by the intraoral scanner (i.e., the cumulative scan data at the current moment), a plurality of key points are obtained. In one embodiment, the plurality of key points are obtained by downsampling the scanned data points (e.g., the path points obtained above).

[0050] After processing the point cloud data of the real-time scan of the oral three-dimensional surface, a plurality of path points can be obtained, such as Figure 3A shown, the small gray dots are a series of path points obtained according to the scan data. From the perspective of the movement of the scanner, these path points can reflect the movement trajectory and process of the scanner during scanning in the oral cavity, as if the scanner scans along the path connected by these path points.

[0051] In some embodiments, these path points can be spatially downsampled according to distance (e.g., in the range of 3 mm to 8 mm, such as 5 mm) and angle (e.g., in the range of 40° to 70°, such as 60°) to select a plurality of key points. This can reduce the data volume while retaining representative points. For the distance condition, traverse the path points and calculate the distance between adjacent path points. If the distance is less than, for example, 5 mm, then perform screening. For the angle condition, calculate the included angle between three adjacent path points. If the included angle is less than, for example, 60°, then perform screening. As Figure 3A shown, the icons represented by the green pentagrams and red pentagrams are some key points obtained according to the downsampling, and these key points are some of the obtained path points. Those skilled in the art should understand that the above distance values and angle values are merely exemplary, and other distance values and angle values can be adopted according to the different point cloud data collected.

[0052] Registration relationship mapping can be performed on these path points. Constructing the registration relationship graph between path points helps to understand the spatial association between points subsequently. The method of graph theory can be used to construct a graph structure with each path point as a node of the graph and the registration relationship between nodes as an edge. The path points are mainly used to provide path dependence for the connection network detection of key points. As Figure 3A shown, each path point represented by a small gray dot is used as a node of the graph, and the registration relationship between two nodes is used as an edge (e.g., the line segment connecting two path points as Figure 3A shown), Figure 3A shown, the graph structure forms the relationship network 300 between path points. The shown relationship network 300 only targets a part of the dental arch, and a complete relationship network 300 for the entire dental arch can be established in a similar manner.

[0053] In block 220, based on the relationship network, determine the strength of the connection relationship between the target key point and multiple neighboring key points of the target key point on the relationship network, and compare the strength with a strength threshold to determine whether the target key point is a key point to be strengthened, that is, determine whether the relationship between the target key point and one or more other key points needs to be strengthened. The target key point is each key point among the multiple key points obtained by the above-mentioned downsampling. That is to say, for each key point, it is necessary to determine whether it is a key point that needs to be strengthened. As for the key point that needs to be strengthened, it means that the connection relationship between this key point and at least one other key point is not strong enough, and it is necessary to strengthen the connection relationship between this key point and the at least one other key point. In some embodiments, the distance between the multiple neighboring key points and the target key point is within a first threshold (for example, 15 mm).

[0054] In one embodiment, the relationship network is a graph network constructed by taking each path point as a node of the graph and the registration relationship between the path points as an edge, as Figure 3A shown.

[0055] To determine whether the target key point is a key point to be strengthened, multiple operations can be performed. The operations include: for each target key point ( Figure 3A each green pentagram shown), search for multiple neighboring key points within its radius (for example, 15 mm), from near to far, and pair the key points according to the principle of non-repeating selection of points within a threshold angle (for example, 45°). That is to say, pair the target key point with at least one of the multiple neighboring key points to obtain at least one pair of paired key points. Those skilled in the art should understand that the above radius value and angle value are only exemplary, and according to the different point cloud data collected, other radius values and angle values can be used.

[0056] The operations also include: using a pair of paired key points and their normal vectors to fit a plane. That is to say, based on the normal vectors of each pair of paired key points and the pair of key points, a target plane can be fitted. For example, key point A and its neighboring key point B form the first pair of paired key points, and a first target plane can be fitted for the first pair of paired key points; key point A and its neighboring key point C form the second pair of paired key points, and a second target plane can be fitted for the second pair of paired key points.

[0057] When fitting the first target plane, key point A is offset by a distance in the direction of its normal vector, and key point B is offset by a distance in the direction of its normal vector. The center on the line connecting the offset key point A' and the offset key point B' is determined. Then, the first line segment is obtained by connecting this center and key point A, and the second line segment is obtained by connecting this center and key point B. The first target plane is fitted based on the first line segment and the second line segment. Similar processing is performed on the paired key points A and key point C to obtain the second target plane. The normal vector direction of the key point is calculated based on the normal of the scanned point cloud, for example, obtained by weighted averaging the normals of each point cloud near the key point. Therefore, the target plane of a pair of paired key points can be fitted based on the paired key points and the respective normal vectors of the two paired key points.

[0058] The intersection line of the fitted first target plane and the relationship network 300 is the first theoretical shortest path; the intersection line of the fitted second target plane and the relationship network 300 is the second theoretical shortest path, and the first or second theoretical shortest path can be used as the target path.

[0059] However, perform a breadth-first search (BFS) of the graph for each pair of paired key points, that is, determine whether the sum of the distances from all path points on the theoretical shortest path (or target path) to the above-mentioned fitted plane falls within a threshold range (for example, 5 mm). For example, determine whether the sum of the first vertical distances from the path points on the first theoretical shortest path to the first target plane is within the threshold range, and whether the sum of the second vertical distances from the path points on the second theoretical shortest path to the second target plane is within the threshold range. The above sum of vertical distances is a way to represent the strength between two key points. Although the sum of the above vertical distances is used to represent the strength between two key points, those skilled in the art should be clear that other methods can be used to determine the strength of the connection relationship between two key points. As long as the strength of the connection relationship between two key points on the relationship network is determined to judge whether the relationship between the two key points needs to be strengthened, it falls within the scope of the present invention.

[0060] If the sum of the first vertical distances is within the threshold range, it is considered that the scanning path from key point A to key point B is a good scanning path, and the relationship between key point A and key point B does not need to be strengthened. Otherwise, it is considered that the scanning path from key point A to key point B is a poor scanning path, and the relationship between key point A and key point B needs to be strengthened. Therefore, based on the sum of the vertical distances from multiple target path points (preferably, path points on the relationship network 300) on the path from the target key point to a paired neighboring key point to the target plane, it can be determined whether the target key point is a key point to be strengthened. As Figure 3AAs shown, after the above calculations, the relationships between the key points indicated by the red five-pointed stars need to be further strengthened (the dashed lines shown in the figure indicate that the relationships between them need to be further strengthened), and these red five-pointed stars are the determined key points to be strengthened.

[0061] In block 230, based on the multiple key points obtained, the arch shape contour curve of the oral three-dimensional surface is determined. The dental arch is a structure in three-dimensional space. When performing analysis, to simplify the problem, the key points in three-dimensional space need to be projected onto a two-dimensional plane (this two-dimensional plane is the arch fitting plane for the arch shape), and this two-dimensional plane includes the vertical projection surface of the oral three-dimensional surface. This two-dimensional plane is obtained by fitting the multiple key points obtained, and it can retain the relative positional relationships between the key points to the greatest extent. For example, when placing the dental arch model on the tabletop, the tabletop is the plane where the arch fitting plane is located. These key points projected onto the arch fitting plane form a two-dimensional point set. By performing a convex hull detection on this point set, the boundary contour of the point set can be obtained, and this boundary contour is the arch shape contour curve, that is, based on the coordinate information of the multiple key points on the vertical projection surface, the arch shape contour curve is determined.

[0062] Figure 3B Shows a schematic diagram of the curve obtained by performing a convex hull detection according to some embodiments of the present invention; and Figure 3C Shows a schematic diagram of the curve obtained by performing a concave hull detection according to some embodiments of the present invention.

[0063] The convex hull is the smallest convex polygon that contains all the key points, and it can reflect the approximate external contour of the dental arch, as Figure 3B shown, this curve shows the approximate external contour of the dental arch. The concave hull can further refine this contour and reflect some concave parts in the dental arch, such as the gaps between teeth, etc., so as to more accurately reflect the shape of the dental arch, as Figure 3C shown, this curve has more detailed depressions to more accurately reflect the shape of the dental arch. That is to say, according to the convex and concave hull detections, the arch shape contour of the oral three-dimensional surface can be obtained therefrom.

[0064] As Figure 2 shown, in block 240, based on the positional relationship between the arch shape contour curve and a pair of target key points to be strengthened among the multiple determined key points to be strengthened, a scanning prompt path for the subsequent supplementary scanning of the pair of target key points to be strengthened is determined.

[0065] Figure 4A Shows a schematic diagram of the scanning prompt path for the target key points to be strengthened according to some embodiments of the present invention.

[0066] Specifically, to determine the scanning prompt path for subsequent supplementary scans, the computing device 120 may perform multiple operations. These operations may include: determining multiple key points to be strengthened that have connection relationships with a target key point to be strengthened in the relationship network 300, so as to obtain multiple pairs of key points to be strengthened belonging to a group for the target key point to be strengthened.

[0067] As Figure 4A shown, for the target key point to be strengthened 41 (the target key point to be strengthened is shown as a five-pointed star in Figure 4A ), the key points to be strengthened that have connection relationships with it in the relationship network 300 include four key points to be strengthened, namely points 411, 412, 413, and 414 (to be distinguished from the target key point to be strengthened, these key points to be strengthened are not shown in the shape of a five-pointed star in Figure 4A ; they are respectively at one end of the corresponding dotted line, and the other end of the corresponding dotted line is the target key point to be strengthened 41). There are connection relationships between point 41 and points 411, 412, 413, and 414 in the relationship network 300. As Figure 4A shown, these key points to be strengthened in each rectangular box have connection relationships on the relationship network 300, so they are attributed to a group. For other target key points to be strengthened 42, 43, 44, 45, and 46, there are also multiple key points to be strengthened that have connection relationships in the relationship network 300, and the multiple key points to be strengthened in the rectangular box are attributed to a group.

[0068] As Figure 4A shown, although the small rectangular box for the target key point to be strengthened 42 is located inside the large rectangular box for the target key point to be strengthened 41, it should be understood that the small rectangular box represents a different group of key points to be strengthened from the large rectangular box. The group of key points to be strengthened in the small rectangular box includes point 42 and one of its paired key points (not shown).

[0069] Therefore, point 41 and point 411 form a pair of target key points to be strengthened, point 41 and point 412 form a pair of target key points to be strengthened, point 41 and point 413 form a pair of target key points to be strengthened, and point 41 and point 414 form a pair of target key points to be strengthened. Select any one of them as the target key point to be strengthened and perform the following operations on it. For example, based on the normal vectors of each target key point in a pair of target key points to be strengthened (for example, point 41 and point 411), determine each target key point relative to the dental arch morphological contour curve (as Figure 3CThe relative positional relationship (as shown); and based on the determined relative positional relationship and the dental arch morphological contour curve, determining the scanning prompt path for subsequent supplementary scanning of a pair of target key points to be strengthened. For example, extend the direction of the point position of the normal vector of each target key point to be strengthened to determine whether there is an intersection or intersection point with the dental arch curve contour curve (i.e., the convex hull). In the case of an intersection or intersection point, determine the specific orientation of the intersection point on the convex hull to determine whether the intersection point is outside the convex hull or inside the concave hull, so as to determine whether the target key point is facing the oral cavity interior (for example, the key point is on the inner surface side of the tooth) or facing the oral cavity exterior (for example, the key point is on the outer surface side of the tooth). If a pair of target key points to be strengthened are both on the inner or outer side of the dental arch, the scanning prompt path is along one side of the dental arch. If one of a pair of target key points to be strengthened is on the inner side and the other is on the outer side, the scanning prompt path intersects with the dental arch.

[0070] Therefore, detect the position correlation of the start and end of the connection of this pair of key points (for example, point 41 and point 411). For example, according to the normal vector, it can be detected whether the two key points are inside or outside the convex hull (as Figure 3B described), and then combined with the dental arch information of the convex hull and the relative positions of these two key points, the accurate position of the prompt path on the dental arch can be fitted.

[0071] As Figure 4B More specifically shown, for a pair of target key points to be strengthened composed of point 41 and point 411, a scanning prompt path as shown by line segment L1 can be determined through the above operations. For a pair of target key points to be strengthened composed of point 41 and point 412, a scanning prompt path as shown by line segment L2 can be determined through the above operations. For a pair of target key points to be strengthened composed of point 41 and point 413, a scanning prompt path as shown by line segment L3 can be determined through the above operations. For a pair of target key points to be strengthened composed of point 41 and point 414, a scanning prompt path as shown by line segment L4 can be determined through the above operations. Therefore, for the target key point 41 to be strengthened, four scanning prompt paths L1, L2, L3, and L4 are determined.

[0072] When displaying these paths, the optimal one can be selected for display. To determine the optimal path, the computing device 120 can perform the following operations: Based on the vertical intersection degrees of each of the multiple scanning prompt paths (for example, scanning prompt paths L1, L2, L3, and L4) with the dental arch morphological contour curve (as Figure 3C shown), assign weights to the multiple scanning prompt paths respectively, and select the target scanning prompt path with a weight higher than the threshold weight for display.

[0073] For example, key points to be enhanced within the same network are grouped together (indicated by a rectangular box). The highest-scoring scan path is selected for display. Each scan path's score is determined by the angle difference between the normal vectors connecting the two endpoints and / or the degree of perpendicular intersection with the dental arch. Generally, points on opposite sides of the tooth (inside and outside) have the greatest difference, providing more comprehensive information. Groups of fitted paths with close intersections and distances are also selected for display based on the aforementioned calculated scores.

[0074] For example, Figure 4B As shown, according to the score of each scan prompt path, it is determined that the scan path L2 has the highest score, and thus the scan path L2 is displayed, as shown in FIG. Figure 4B As shown, the white three-dimensional arrow shows the prompt scanning path corresponding to the path L2. Similar operations are performed for other target key points 42, 43, 44, 45 and 46 to be strengthened, so as to screen out the scanning path with the highest score for display.

[0075] According to the method 200 for scanning path prompts of an embodiment of the present invention, an analysis is performed on the scanned data source, and a relationship network is established to optimize the entire result. Not only are the user prompted with those areas visible to the naked eye, but the user is also prompted to optimize and improve based on the internal data relationships. The data source obtained from the intraoral scanning instrument is usually point cloud data, which records the three-dimensional structural information inside the mouth. In order to make full use of this data and optimize the scanning results, a relationship network can be constructed to associate different data points and explore the internal relationships therein. By analyzing this relationship network, not only can the problem areas visible to the naked eye be discovered, but also the hidden data associations can be revealed, thereby providing users with comprehensive optimization suggestions.

[0076] In addition, the scanning path prompting method according to the present invention performs basically real-time scanning path prompts for the current scanning results, and the areas scanned at different times are different. When the user scans different areas, different prompts can be made for different areas according to the real-time scanning path prompting of the present invention, so that the prompted path is more in line with the user's scanning technique. For example, the connection between the inner and outer sides, the connection between the outer side of a single side and the inner side of a single side, prompts at the upper jaw, and so on. The prompts generated by different scanning techniques are also completely different. The prompts of the loop scanning mainly prompt the user to make up for the connection between the inner and outer sides, and the Z-shaped scanning method mainly prompts the unilateral connection. In addition, the prompts for the implant will be relatively different, because the scanning data of the implant is sparser than the data collected from normal teeth, so the path prompts for the implant will allow the user to collect implant data more comprehensively.

[0077] Figures 5A to 5E A schematic diagram illustrating scan path hints according to some embodiments of the present invention is shown.

[0078] Figure 5A The arrow shown is a hint path for enhanced scanning in subsequent scans. Figure 5B The box shown is the area of the current scan. Figure 5B The area corresponding to the arrow shown is the area that has been scanned at the moment before the current scan. The presence of an arrow in this area indicates that the previous scan result was not good, and it needs to be scanned again in subsequent scans. The arrow shows the scanning path for supplementary scanning. Arrow prompts will appear during the scanning process. Generally, the arrows will give prompts later so as not to block the user's current scanning area and to keep the current scanning area stable. Then the user operates the scanner according to the direction indicated by the arrow, and the prompts will disappear after the scanning network becomes rich.

[0079] In addition, the entire scanning process can be recorded and the user can play it back. During the playback process, the scanning path will be prompted so that the user can observe their own operation method to adjust and optimize, thereby helping the user find a relaxed and efficient scanning method suitable for themselves.

[0080] Figures 5C to 5D It shows a schematic diagram of the reverse arc of the arrow in the paradise area according to an embodiment of the present invention, which shows the scanning direction and scanning path for subsequent supplementary scanning of the paradise area. Figure 5E The green area of... indicates the area with poor scanning quality. Therefore Figure 5E The path indicated by the hint arrow of... follows these green areas, so as to perform supplementary scanning of these green areas in subsequent scans.

[0081] It should be noted that Figure 2 The process 200 shown is executed for the cumulative scan data of the current moment of the oral three-dimensional surface by the intraoral scanner. For the scan data obtained at the next moment of the current moment, the process 200 is also executed, so that the scanning hint path can be basically real-time displayed at the next moment. In addition, for the cumulative scan data after the global scan ends, the process 200 is also executed, and an updated relationship network 300 and the relationship area to be optimized of the relationship network can be obtained. Therefore, according to the method for scanning path hint of the present invention, quality detection can also be performed after the scan stops, so as to be able to give hints for imperfect areas and the generated hierarchical three-dimensional mesh model mesh. That is to say, after the user stops scanning, point cloud quality detection, mesh quality detection, and network relationship detection will be performed, and the user will be prompted on the scan result as to which places need supplementary scanning and in what way to perform supplementary scanning. During this process, the data scanned previously can also be imported for overall detection. Through iterative processing of multiple scans, the area or key points that need to be optimized in the relationship network can be found more accurately.

[0082] The following will refer to Figures 6A to 6C to describe the quality detection after the scan ends.Figure 6A Shows a schematic diagram for quality inspection of the entire dental arch according to some embodiments of the present invention; and Figure 6B and Figure 6C Shows a schematic diagram of hierarchical area diffusion display according to some embodiments of the present invention.

[0083] Generally during the scanning process, different scanning durations are applied to various areas of the entire dental arch. Generally, the scanning time in the anterior tooth area is shorter than that in the molar area. Coupled with the different degrees of distinctiveness of the features in each area, the scanning data in each area will be sparse or dense. It is crucial to give a prompt for sparse areas. Moreover, the sensitivity of different areas to data is also different. For example, the maxillary palate area is not a key area in the orthodontic mode, while the implant post is a quite crucial and special area in the implant mode. Therefore, the detection of different areas will consider the actual situation at that time to give necessary prompts to the user. In addition, the generated mesh will also have some local hierarchical areas due to scanning errors and differences in scanning techniques. In the current situation where the requirements for mesh resolution and accuracy are getting higher and higher, the detection of these key areas is also quite crucial.

[0084] Considering the above problems, in some embodiments according to the present invention, during the quality inspection after the scanning stops, prompts will be given for imperfect areas and the generated hierarchical three-dimensional mesh model (mesh). Therefore, the point cloud of the entire scan is divided into regions to distinguish different regions such as teeth, gums, implant posts, etc., and different quality weights are given. That is to say, after the global scan of the oral three-dimensional surface by the intraoral scanner is completed, based on the scanned point cloud, the oral three-dimensional surface is divided into multiple regions, and corresponding weights are assigned to multiple regions (for example, teeth, gums, implant posts, etc.). Therefore, the weights of different regions are different. For example, the tooth region is more important for subsequent analysis and can be assigned a higher weight.

[0085] As Figure 6A shown, the area indicated by arrow 61 shows that there is a hole here, and this hole can be represented by a color different from that of other areas. From Figure 6A it can be seen that the color here is darker compared to other places.

[0086] As Figure 6A shown, the area indicated by arrow 62 shows that there is a layer here. This layered area may be caused by scanning errors and differences in scanning techniques, and the layered area can be displayed through different colors. From Figure 6A it can be seen that the color of this area is also darker, different from the colors of other areas. By using colors to distinguish the scanning quality of each area, areas with poor scanning quality can be clearly seen at a glance.

[0087] In some embodiments, the corresponding weights include a scanning quality metric threshold. After the global scanning of the oral three-dimensional surface by the intraoral scanner is completed, for a target vertex in the three-dimensional mesh model mesh of the oral three-dimensional surface (the target vertex is a point in the point cloud), based on the quality of the neighborhood point cloud of the target vertex, a scanning quality metric for the target vertex is calculated to be compared with the scanning quality metric threshold. If the comparison shows that the scanning quality is poor, the target vertex and its adjacent area will be highlighted when being displayed.

[0088] For example, in order to obtain Figure 6A the quality detection schematic diagram shown, the scanning quality can be calculated for the target vertex according to the quality of the target vertex and its neighborhood point cloud. Similar processing is done for each target vertex, then the quality detection schematic diagram of the entire dental arch can be obtained, and different qualities can be displayed in different colors.

[0089] Extract features that can distinguish teeth and gums based on the geometric features (such as the position, normal vector, curvature, etc. of the points) and color information (if any) of the point cloud data. For example, the tooth surface is usually smoother and has a relatively smaller curvature, while the gum surface may be rougher and have a larger curvature.

[0090] In some embodiments, the corresponding weights include a curvature threshold. After the global scanning of the oral three-dimensional surface by the intraoral scanner is completed, curvature detection is performed on the three-dimensional mesh model mesh, and for regions with a curvature greater than the curvature threshold, a diffusion operation is performed to make the regions larger.

[0091] As Figure 6B and Figure 6C shown, it can be seen that there are wrinkles in the area around the teeth, that is to say, the curvature of this part is larger and greater than the curvature threshold. Therefore, a diffusion operation is performed on this area, so that this area becomes larger. There may be a layering phenomenon in this area, and the diffused area can be marked with different colors to more clearly show the layered area.

[0092] Figure 6B and Figure 6C The left picture is the picture without diffusion processing, Figure 6B and Figure 6C the right picture of

[0093] In traditional methods, most of them detect the density of the scan and the holes, without considering regional and type differences. By adding the distinction of different regions (such as teeth, gums, implant posts, etc.) and having different detection strategies for different regions (for example, different quality weights or curvature weights), users can better perform supplementary scans for a certain region of interest. The direct detection of the mesh also enables users to analyze the final required results. Analyzing the generated results may better meet the needs of users compared to analyzing the data source.

[0094] Figure 7 FIG. shows a schematic block diagram of an exemplary device 700 that can be used to implement embodiments of the present invention. Device 700 can be used to implement Figure 1 computing device 120. As shown, device 700 includes a central processing unit (CPU) 701, which can execute various appropriate actions and processes according to computer program instructions stored in a read-only memory (ROM) 702 or computer program instructions loaded from a storage unit 708 into a random access memory (RAM) 703. In RAM 703, various programs and data required for the operation of device 700 can also be stored. CPU 701, ROM 702, and RAM 703 are connected to each other via a bus 704. An input / output (I / O) interface 705 is also connected to bus 704.

[0095] Multiple components in device 700 are connected to I / O interface 705, including: an input unit 706, such as a keyboard, mouse, etc.; an output unit 707, such as various types of displays, speakers, etc.; a storage unit 708, such as a disk, optical disc, etc.; and a communication unit 709, such as a network card, modem, wireless communication transceiver, etc. Communication unit 709 allows device 700 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0096] Processing unit 701 executes each of the methods and processes described above. For example, in some embodiments, any one of the above processes can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as storage unit 708. In some embodiments, part or all of the computer program can be loaded and / or installed onto device 700 via ROM 702 and / or communication unit 709. When the computer program is loaded into RAM 703 and executed by CPU 701, one or more steps of any one of the processes described above can be executed. Alternatively, in other embodiments, CPU 701 can be configured to execute any one of the above processes by any other suitable means (such as by means of firmware).

[0097] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. By way of example, and without limitation, the types of hardware logic components that can be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on a chip (SOCs), complex programmable logic devices (CPLDs), and the like.

[0098] In the context of this invention, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0099] Moreover, although the operations are depicted in a particular order, this should be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed to achieve the desired result. In certain circumstances, multitasking and parallel processing may be advantageous. Likewise, although a number of specific implementation details are included in the above discussion, these should not be construed as limiting the scope of the invention. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single implementation. Conversely, various features that are described in the context of a single implementation can also be implemented separately or in any suitable sub-combination in multiple implementations.

[0100] Although the subject matter has been described in language specific to structural features and / or methodological logical acts, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are merely example forms of implementing the claims.

Claims

1. A system for path prompting in intraoral scanning, comprising Intraoral scanner; and a computing device coupled to the intraoral scanner, configured to perform the following steps on the cumulative scan data of the three-dimensional oral surface at the current moment by the intraoral scanner: Step S1: Analyze the cumulative scan data to obtain a plurality of key points and a relationship network including the plurality of key points; Step S2: Take each key point in the plurality of key points as a target key point, and perform the following operations for each target key point: Based on the relationship network, determine the strength of the connection relationship between the target key point and a plurality of neighboring key points of the target key point on the relationship network, and compare the strength with a strength threshold to determine whether the target key point is a key point to be strengthened, where the distance between the plurality of neighboring key points and the target key point is within a first threshold range; Step S3: Based on the obtained plurality of key points, determine the arch shape contour curve of the three-dimensional oral surface; and Step S4: Determine the relative positions of a pair of target key points to be strengthened among the determined plurality of key points to be strengthened with respect to the arch shape contour curve, and based on the determined relative positions, determine the scan prompt path for the subsequent supplementary scan of the pair of target key points to be strengthened.

2. The system according to claim 1, wherein in order to perform step S2, the computing device is configured to: Pair the target key point with at least one neighboring key point among the plurality of neighboring key points to obtain at least one pair of paired key points; For each pair of paired key points among the at least one pair of paired key points, fit a target plane based on the two paired key points and the normal vectors of the two paired key points; and For each pair of paired key points, determine the sum of the perpendicular distances from the plurality of target path points on the target path from the target key point to the neighboring key point paired with it to the target plane as the strength of the connection relationship for each pair of paired key points, and based on the comparison of the strength with the strength threshold, determine whether the target key point is the key point to be strengthened.

3. The system according to claim 2, wherein in order to determine whether the target key point is the key point to be strengthened, the computing device is configured to: Determine the intersection line of the target plane and the relationship network as the target path; Calculate the sum of the perpendicular distances from the plurality of target path points on the target path to the target plane; Determine whether the sum of the perpendicular distances is less than a second distance threshold, where the second distance threshold is the strength threshold; and Based on determining that the sum of the perpendicular distances is greater than the second distance threshold, determine that the target key point is the key point to be strengthened.

4. The system according to claim 1, wherein in order to perform step S3, the computing device is configured to: Project the plurality of key points onto a two-dimensional plane, where the two-dimensional plane includes the vertical projection surface of the three-dimensional oral surface; and Determine the arch contour curve of the oral three-dimensional surface based on the coordinate information of the multiple key points on the two-dimensional plane.

5. The system according to claim 1, wherein to perform step S4, the computing device is configured to: Determine multiple key points to be strengthened that have a connection relationship with a target key point to be strengthened in the relationship network, so as to obtain multiple pairs of key points to be strengthened for the target key point to be strengthened that belong to a group; Select each pair of key points to be strengthened in the multiple pairs of key points to be strengthened as the pair of target key points to be strengthened; Perform the following operations on the pair of target key points to be strengthened: Based on the position of the extension line of the normal vector of each target key point to be strengthened in the pair of target key points to be strengthened relative to the arch contour curve, determine the relative position relationship of each target key point to be strengthened relative to the arch contour curve; And Based on the determined relative position relationship and the arch contour curve, determine the scanning prompt path for the subsequent supplementary scanning of the pair of target key points to be strengthened.

6. The system according to claim 5, wherein the computing device is further configured to: For the multiple pairs of key points to be strengthened, determine multiple scanning prompt paths; Based on the vertical intersection degree of each of the multiple scanning prompt paths with the arch contour curve, assign weights to the multiple scanning prompt paths respectively; and Select a target scanning prompt path with a weight higher than a threshold weight for display.

7. The system according to claim 6, wherein the computing device further assigns weights to the scanning prompt paths for each pair of key points to be strengthened based on the normal vector angle difference of each pair of key points to be strengthened in the multiple pairs of key points to be strengthened.

8. The system according to any one of claims 1 to 5, wherein the computing device is further configured to: For the cumulative scan data after the global scan of the oral three-dimensional surface by the intraoral scanner, perform steps S1 to S4 to obtain the updated relationship network and the relationship area to be optimized of the relationship network.

9. The system according to any one of claims 1 to 5, wherein the computing device is further configured to: After the global scan of the oral three-dimensional surface by the intraoral scanner is completed, divide the oral three-dimensional surface into multiple regions based on the scanned point cloud, and assign corresponding weights to the multiple regions respectively.

10. The system according to claim 9, wherein the corresponding weights include a scan quality metric threshold, and the computing device is further configured to: After the global scan of the oral three-dimensional surface by the intraoral scanner is completed, for a target vertex in the three-dimensional mesh model mesh of the oral three-dimensional surface, calculate a scan quality metric for the target vertex based on the quality of the neighborhood point cloud of the target vertex, and compare it with the scan quality metric threshold.

11. The system according to claim 9, wherein the corresponding weights include a curvature threshold, and the computing device is further configured to: after the intraoral scanner finishes a global scan of the three-dimensional oral surface, perform curvature detection on the three-dimensional mesh model mesh, and perform a diffusion operation on areas with curvature greater than the curvature threshold so as to increase the areas.

12. A method for path prompting in intraoral scanning, the method comprising: For the cumulative scan data of the current moment of the intraoral scanner for the three-dimensional oral surface, perform the following steps: Step S1: Analyze the cumulative scan data to obtain a plurality of key points and a relationship network including the plurality of key points; Step S2: Take each of the plurality of key points as a target key point, and for each target key point, perform the following operations: based on the relationship network, determine the strength of the connection relationship between the target key point and a plurality of neighboring key points of the target key point on the relationship network, and compare the strength with a strength threshold to determine whether the target key point is a key point to be strengthened, and the distance between the plurality of neighboring key points and the target key point is within a first threshold range; Step S3: Based on the plurality of key points obtained, determine the arch contour curve of the three-dimensional oral surface; and Step S4: Determine the relative positions of a pair of target key points to be strengthened among the determined plurality of key points to be strengthened with respect to the arch contour curve and a pair of target key points to be strengthened among the determined plurality of key points to be strengthened, and based on the determined relative positions, determine a scan prompt path for subsequent supplementary scans for the pair of target key points to be strengthened.

13. The method according to claim 12, wherein step S2 includes: Pair the target key point with at least one neighboring key point among the plurality of neighboring key points to obtain at least one pair of paired key points; For each pair of the at least one pair of paired key points, fit a target plane based on the two paired key points and the normal vectors of the two paired key points; and For each pair of paired key points, determine the sum of the perpendicular distances from the plurality of target path points on the target path on the relationship network from the target key point to the neighboring key point paired with it to the target plane as the strength of the connection relationship for each pair of paired key points, and based on the comparison between the strength and the strength threshold, determine whether the target key point is the key point to be strengthened.

14. The method according to claim 13, wherein determining the sum of the perpendicular distances from the plurality of target path points on the target path on the relationship network from the target key point to the neighboring key point paired with it to the target plane as the strength of the connection relationship for each pair of paired key points, and based on the comparison between the strength and the strength threshold, determining whether the target key point is the key point to be strengthened includes: Determine the intersection line of the target plane and the relationship network as the target path; Calculate the sum of the perpendicular distances from the plurality of target path points on the target path to the target plane; Determine whether the sum of the vertical distances is less than a second distance threshold, where the second distance threshold is the intensity threshold; and Based on determining that the sum of the vertical distances is greater than the second distance threshold, determine that the target key point is the key point to be strengthened.

15. The method according to claim 12, wherein determining the dental arch morphological contour curve of the oral three-dimensional surface based on the plurality of key points includes: Project the plurality of key points onto a two-dimensional plane, where the two-dimensional plane includes the vertical projection surface of the oral three-dimensional surface; And Based on the coordinate information of the plurality of key points on the two-dimensional plane, determine the dental arch morphological contour curve of the oral three-dimensional surface.

16. The method according to claim 12, wherein step S4 includes: Determine a plurality of key points to be strengthened that have a connection relationship with a target key point to be strengthened in the relationship network, so as to obtain multiple pairs of key points to be strengthened for the target key point to be strengthened that belong to a group; Select each pair of key points to be strengthened in the multiple pairs of key points to be strengthened as the pair of target key points to be strengthened; Perform the following operations on the pair of target key points to be strengthened: Based on the position of the extension line of the normal vector of each target key point to be strengthened in the pair of target key points to be strengthened relative to the dental arch morphological contour curve, determine the relative position relationship of each target key point to be strengthened relative to the dental arch morphological contour curve; And Based on the determined relative position relationship and the dental arch morphological contour curve, determine the scanning prompt path for the subsequent supplementary scan of the pair of target key points to be strengthened.

17. The method according to claim 16, further comprising: For the multiple pairs of key points to be strengthened, determine multiple scanning prompt paths; Based on the vertical crossing degree of each of the multiple scanning prompt paths and the dental arch morphological contour curve, assign weights to the multiple scanning prompt paths respectively; and Select a target scanning prompt path with a weight higher than the threshold weight for display.

18. The method according to any one of claims 12 to 16, further comprising: For the cumulative scan data after the global scan of the oral three-dimensional surface by the intraoral scanner is completed, execute steps S1 to S4 to obtain the updated relationship network and the relationship area to be optimized in the relationship network.

19. The method according to any one of claims 12 to 16, further comprising at least one of the following items: After the global scan of the oral three-dimensional surface by the intraoral scanner is completed, based on the scanned point cloud, divide the oral three-dimensional surface into multiple regions, and assign corresponding weights to the multiple regions respectively; The corresponding weight includes a scan quality metric threshold. After the global scan of the oral three-dimensional surface by the intraoral scanner is completed, for a target vertex in the three-dimensional mesh model (mesh) of the oral three-dimensional surface, calculate the scan quality metric for the target vertex based on the quality of the neighborhood point cloud of the target vertex, so as to compare with the scan quality metric threshold; or The corresponding weights include a curvature threshold. After the global scanning of the oral three-dimensional surface by the intraoral scanner is completed, curvature detection is performed on the three-dimensional mesh model mesh, and a diffusion operation is performed on the area where the curvature is greater than the curvature threshold, so as to increase the area.

20. An electronic device, comprising: a processor; and a memory storing executable instructions, which, when executed by the processor, cause the electronic device to at least: perform the following steps on the cumulative scan data of the current moment of the oral three-dimensional surface by the intraoral scanner: Step S1: Analyze the cumulative scan data to obtain a plurality of key points and a relationship network including the plurality of key points; Step S2: Use each of the plurality of key points as a target key point, and perform the following operations for each target key point: Based on the relationship network, determine the strength of the connection relationship between the target key point and a plurality of neighboring key points of the target key point on the relationship network, and compare the strength with a strength threshold to determine whether the target key point is a key point to be strengthened, where the distance between the plurality of neighboring key points and the target key point is within a first threshold range; Step S3: Based on the obtained plurality of key points, determine the arch shape contour curve of the oral three-dimensional surface; and Step S4: Determine the relative positions of a pair of target key points to be strengthened among the determined plurality of key points to be strengthened relative to the arch shape contour curve, and based on the determined relative positions, determine a scan prompt path for subsequent supplementary scanning of the pair of target key points to be strengthened.

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