Oral image modeling method and device

Abstract

The present invention discloses a method and device for modeling an oral cavity image. The method defines an oral cavity detection system according to the detection direction of the oral cavity detection space, the detection route of the oral cavity detection space, and the detection speed of the oral cavity detection part, thereby realizing multi-dimensional control of the detection direction of the oral cavity detection space, the detection route of the oral cavity detection space, and the detection speed of the oral cavity detection part, thereby ensuring the accuracy of the oral cavity detection system. The method defines a high-level overall image according to a primary overall image, multiple sub-oral cavity images, and abnormal positions of the oral cavity; the method constructs a final oral cavity image according to the high-level overall image, the oral habits of the user, and the primary overall image, thereby realizing multiple interactions among the high-level overall image, the oral habits of the user, and the primary overall image, and comprehensively considering the primary overall image, abnormal positions of the oral cavity, the oral habits of the user, and the high-level overall image, thereby ensuring multi-dimensional control of the final oral cavity image and improving the modeling accuracy of the final oral cavity image.

Description

Technical Field

[0001] The present invention relates to the technical field of oral images, and in particular to a method and device for modeling oral images. Background Art

[0002] With the development of science and technology, oral images refer to images obtained by photographing or imaging the internal structures of the oral cavity. Oral images present the characteristics of the interior of the oral cavity. In the existing technology, oral detection parts detect the oral detection space and directly output oral images without fully considering the detection direction and detection route of the oral detection space, which affects the accuracy of the final oral image modeling. Summary of the Invention

[0003] The purpose of the present invention is to overcome the deficiencies of the prior art, and the present invention provides a method and device for modeling oral images.

[0004] The embodiment of the present invention provides a modeling method for an oral cavity image, which is applied to a modeling scenario of an oral cavity image;

[0005] The oral image modeling method includes:

[0006] Defining an oral detection space based on the user's oral space and tooth space;

[0007] Defining the spatial layout of the oral detection space according to the traversal of the oral detection space, and defining the detection direction of the oral detection space according to the spatial layout of the oral detection space, the shape of the oral detection space, and the arrangement of teeth;

[0008] Defining the detection route of the oral detection space according to the detection direction of the oral detection space, the shape of the oral detection part, and the range of movement of the oral detection part;

[0009] An oral inspection system is defined based on the inspection direction of the oral inspection space, the inspection route of the oral inspection space, and the inspection speed of the oral inspection parts;

[0010] In the oral detection system, multiple detection areas are defined based on the oral detection system and the oral detection space, and corresponding sub-oral images are collected according to the directional shooting of the multiple detection areas;

[0011] A primary overall image is collected based on the interaction between the oral detection part and the oral detection system, and an advanced overall image is defined based on the primary overall image, multiple sub-oral images and abnormal positions of the oral cavity; the final oral image is constructed based on the advanced overall image, the user's oral habits and the primary overall image.

[0012] In an embodiment of the present invention, through the method in the embodiment of the present invention, the detection route of the oral detection space is defined according to the detection direction of the oral detection space, the shape of the oral detection part, and the activity range of the oral detection part; the oral detection system is defined according to the detection direction of the oral detection space, the detection route of the oral detection space, and the detection speed of the oral detection part, thereby realizing multi-dimensional control of the detection direction of the oral detection space, the detection route of the oral detection space, and the detection speed of the oral detection part, thereby ensuring the accuracy of the oral detection system.

[0013] Furthermore, in the oral detection system, an advanced overall image is defined based on the primary overall image, multiple sub-oral images and abnormal positions of the oral cavity; the final oral image is constructed based on the advanced overall image, the user's oral habits and the primary overall image, realizing multiple interactions of the advanced overall image, the user's oral habits and the primary overall image, and comprehensively considering the primary overall image, abnormal positions of the oral cavity, the user's oral habits and the advanced overall image, ensuring multi-dimensional control of the final oral image and improving the modeling accuracy of the final oral image. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 is a flow chart of a method for modeling an oral cavity image in an embodiment of the present invention;

[0015] Figure 2 is a schematic flow chart of S11 in the oral image modeling method in an embodiment of the present invention;

[0016] Figure 3 is a schematic flow chart of S12 in the oral image modeling method in an embodiment of the present invention;

[0017] Figure 4 is a schematic flow chart of S13 in the oral image modeling method in an embodiment of the present invention;

[0018] Figure 5 is a schematic flow chart of S14 in the oral image modeling method in an embodiment of the present invention;

[0019] Figure 6 is a schematic flow chart of S15 in the oral image modeling method in an embodiment of the present invention;

[0020] Figure 7 is a schematic flow chart of S16 in the oral image modeling method in an embodiment of the present invention;

[0021] Figure 8 Schematic diagram of the structure of the oral image modeling device in an embodiment of the present invention. DETAILED DESCRIPTION

[0022] The technical solutions in the embodiments of the present invention will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present invention.

[0023] See also Figures 1 to 8 A modeling method for an oral image is applied to a modeling scenario of an oral image. The modeling method for an oral image includes:

[0024] Step S11: defining an oral detection space based on the user's oral space and tooth space;

[0025] Step S12: defining the spatial layout of the oral detection space according to the traversal of the oral detection space, and defining the detection direction of the oral detection space according to the spatial layout of the oral detection space, the shape of the oral detection space, and the arrangement of teeth;

[0026] Step S13: defining a detection route of the oral detection space according to the detection direction of the oral detection space, the shape of the oral detection piece, and the movable range of the oral detection piece;

[0027] Step S14: defining an oral inspection system according to the inspection direction of the oral inspection space, the inspection route of the oral inspection space, and the inspection speed of the oral inspection component;

[0028] Step S15: In the oral cavity detection system, multiple detection areas are defined based on the oral cavity detection system and the oral cavity detection space, and corresponding sub-oral cavity images are collected by directional shooting of the multiple detection areas;

[0029] Step S16: A primary overall image is collected based on the interaction between the oral detection part and the oral detection system, and an advanced overall image is defined based on the primary overall image, multiple sub-oral images, and abnormal positions of the oral cavity; a final oral image is constructed based on the advanced overall image, the user's oral habits, and the primary overall image.

[0030] refer to Figure 2 , in step S11, an oral detection space is defined based on the user's oral space and tooth space;

[0031] In the specific implementation process of the present invention, the specific steps may be:

[0032] S111: Collecting the user's location;

[0033] S112: Determine the user's facial space based on the detection of the user's location;

[0034] S113: triggering a dynamic change of the user's facial space based on the facial operation prompt, and collecting a plurality of change images according to the dynamic change of the user's facial space;

[0035] S114: defining the user's mouth space based on the first-layer recognition of the multiple changing images, and simultaneously defining the user's tooth space based on the second-layer recognition of the multiple changing images. At this time, the user's mouth space and the user's tooth space are synchronously detected;

[0036] S115: Define an oral cavity detection space according to the user's oral space and tooth space.

[0037] In an embodiment of the present application, the user's location is collected and introduced to control the user's location, thereby determining the user's facial space based on the detection of the user's location, realizing the detection of the user's location, thereby ensuring the dynamic detection of the user's location, and then accurately positioning the user's facial space.

[0038] Specifically, before any location information is collected, explicit user consent must be obtained and compliance with local data protection and privacy laws must be ensured. This can be achieved through GPS, Wi-Fi, Bluetooth, or cell tower-based location technology. The collected location information should be encrypted and stored, with access limited to authorized personnel or systems.

[0039] The system should be able to update the user's location information in real time and monitor its changes. This can be achieved by periodically re-collecting location information or using continuous positioning technology. The system should verify the accuracy of the collected location information to avoid misjudgments due to positioning errors.

[0040] If the user's location is known, the system can integrate cameras and sensors to capture images and videos of the user's area. These cameras and sensors should have high resolution and sensitivity to accurately identify facial features. Advanced facial recognition algorithms should be used to analyze the captured images and videos to determine the user's facial space. These algorithms should be trained and optimized to improve recognition accuracy and speed. When performing facial recognition, necessary privacy protection measures should be implemented, such as using privacy glass and masking non-target areas. Furthermore, captured images and videos should be promptly deleted or anonymized when no longer needed.

[0041] The system should be able to continuously track the user's location and dynamically update it as needed. This helps ensure that the system can adjust the viewing angle and focus of the camera and sensors as the user moves. Combining location information with facial recognition algorithms, the system should be able to accurately locate the user's face in space. This is achieved by calculating the distance, angle, and direction between the camera and the user's face. The system should be able to automatically adjust camera and sensor settings based on real-time feedback to ensure accurate spatial positioning of the face. The system should also provide a user-friendly interface and controls so that users can manually adjust settings as needed.

[0042] Throughout the entire process, local data protection and privacy laws must be strictly adhered to. This includes obtaining user consent, protecting user data, and limiting data access and use. The system should provide users with transparency and accountability regarding the use of location information and facial recognition. This includes explaining to users how location information and facial recognition are used, stored, and protected.

[0043] In summary, by legally and compliantly collecting user location information, importing and controlling this information, determining facial space based on location detection, and implementing dynamic location detection and precise facial spatial positioning, accurate facial spatial positioning can be achieved while ensuring privacy protection. However, this requires strict compliance with laws and regulations throughout the entire process and the implementation of necessary privacy protection measures.

[0044] Furthermore, based on facial operation prompts, dynamic changes in the user's facial space are triggered, and multiple change images are collected according to the dynamic changes in the user's facial space. Facial operation prompts are introduced to realize the dynamic changes in the user's facial space, so as to monitor the dynamic changes in the user's facial space, thereby collecting multiple change images, and then managing the multiple change images.

[0045] Specifically, design a series of facial manipulation prompts. These prompts can be simple changes in expression (such as smiling or blinking), head movements, or specific facial movements. Ensure that these prompts are both engaging and easy for users to understand and execute. Provide clear guidance and educational materials during system startup or when users first use the system, explaining the purpose of these facial manipulation prompts, how to execute them, and the security and privacy protection measures for their data.

[0046] The system provides real-time facial manipulation prompts to the user through the interface or audio, requiring the user to perform specific facial movements. Ensure the clarity and accuracy of the prompts so that the user can correctly understand and execute them. Use high-precision cameras and sensors to capture the dynamic changes in the user's facial movements. Ensure that camera parameters such as resolution, frame rate, and viewing angle meet capture requirements.

[0047] As the user performs facial manipulation, the system captures multiple changing images in real time. These images are pre-processed, such as through noise reduction and contrast enhancement, to improve the accuracy of subsequent analysis. These images are securely stored on a server, ensuring access only by authorized personnel or systems. Strict access controls and encryption are implemented to protect the privacy and security of user data.

[0048] The system monitors multiple captured images in real time, analyzing the user's facial spatial dynamics. It uses advanced image processing and machine learning algorithms to identify and track facial features, ensuring accurate and reliable analysis. The system is capable of detecting unusual facial spatial dynamics, such as sudden changes in facial expression or head movement. Upon detecting anomalies, the system can trigger an alarm or take other necessary responsive measures to ensure user safety and privacy.

[0049] Throughout the entire process, we strictly adhere to data protection and privacy regulations, ensuring user data is anonymized, encrypted, and stored with limited access to protect user privacy and security.

[0050] Based on the dynamic spatial changes of the user's face, the system can provide a more personalized interactive experience. For example, it can adjust interface color, brightness, or animation effects based on the user's facial expressions. We collect user feedback and suggestions to continuously optimize facial operation prompts and image acquisition processes. Through iterative updates and improvements to the system, we enhance user experience and satisfaction.

[0051] In summary, by introducing facial manipulation prompts, triggering dynamic spatial changes in the user's face, collecting multiple images of the changes, and monitoring and controlling these images, we can provide users with a more personalized interactive experience while ensuring data security and privacy. However, this requires strict compliance with laws and regulations throughout the entire process and the implementation of necessary privacy protection measures.

[0052] Therefore, the user's mouth space is defined based on the first-layer recognition of multiple changing images. At the same time, the user's tooth space is defined based on the second-layer recognition of multiple changing images. At this time, the user's mouth space and the user's tooth space are detected synchronously; the oral detection space is defined based on the user's mouth space and tooth space, which is compatible with the overall consideration of the user's mouth space and tooth space, realizes the precise control of the user's mouth space and tooth space, ensures the construction of the oral detection space, and determines the oral detection space based on the user's mouth space and tooth space to facilitate further control of the oral detection space.

[0053] Specifically, a high-precision camera or intraoral camera is used to capture multiple images of the user in different states. This ensures clear images that accurately reflect the user's oral features and dental alignment. The captured images are pre-processed, including denoising, contrast enhancement, and color correction. Image enhancement techniques are used to improve the visibility of the mouth and dental areas in the images.

[0054] Image processing algorithms, such as edge detection and contour extraction, are used to identify the mouth region in the image. Based on the shape, size, and other characteristics of the mouth region, the user's mouth space is defined. Based on the mouth space, image processing techniques, such as segmentation and feature extraction, are further used to identify and extract the tooth region in the image. The user's tooth space is defined based on characteristics such as tooth arrangement, shape, and color.

[0055] A synchronous detection mechanism is designed to process the mouth space and tooth space in multiple changing images simultaneously. By comparing and analyzing the mouth and tooth features in different images, the synchronous detection of the mouth space and tooth space is achieved.

[0056] When the user performs specific actions or expressions, the mouth and teeth images are captured and updated in real time. Based on the real-time images, the definition of the mouth space and tooth space is dynamically adjusted to ensure the accuracy of the detection results.

[0057] The oral detection space is defined by combining the recognition results of the mouth and tooth spaces. This space should include key information such as the overall shape of the mouth, tooth arrangement, and health status. When constructing the oral detection space, individual differences in users, such as mouth size and tooth shape, should be fully considered. Ensure that the oral detection space is compatible with the mouth and tooth characteristics of different users. Through precise image processing algorithms and data analysis techniques, precise control of the oral and tooth spaces is achieved. Ensure that the constructed oral detection space accurately reflects the user's oral health status.

[0058] Conduct further data analysis and evaluation of the oral testing space. Leverage machine learning algorithms to identify potential oral health issues, such as caries and periodontal disease. Gather user feedback and suggestions to continuously optimize the oral testing space construction process. Adjust testing parameters and algorithms based on user needs to improve accuracy and reliability. Throughout the entire process, strictly adhere to data protection and privacy regulations. Ensure user data is anonymized, encrypted, and stored with limited access to protect user privacy and security.

[0059] refer to Figure 3 In step S12, the spatial layout of the oral detection space is defined according to the traversal of the oral detection space, and the detection direction of the oral detection space is defined according to the spatial layout of the oral detection space, the shape of the oral detection space, and the arrangement of the teeth;

[0060] In the specific implementation process of the present invention, the specific steps may be:

[0061] S121: freeze the oral cavity detection space;

[0062] S122: defining a corresponding traversal mode based on the oral detection space and the user's previous oral data;

[0063] S123: triggering traversal of the oral cavity detection space according to the oral cavity detection space and the corresponding traversal mode;

[0064] S124: defining a spatial layout of the oral cavity detection space based on the traversal of the oral cavity detection space;

[0065] S125: collecting the shape of the oral detection space and the arrangement of the teeth, and correlating the spatial layout of the oral detection space, the shape of the oral detection space, and the arrangement of the teeth;

[0066] S126: defining a first direction parameter according to the spatial layout of the oral detection space and the shape of the oral detection space, and defining a second direction parameter according to the spatial layout of the oral detection space and the arrangement of teeth;

[0067] S127: Define a detection direction of the oral detection space according to the first direction parameter, the second direction parameter, and the oral detection space.

[0068] In an embodiment of the present application, the oral detection space is frozen; a corresponding traversal pattern is defined based on the oral detection space and the user's previous oral data, the oral detection space and the user's previous oral data are introduced, and the oral detection space and the user's previous oral data are managed and controlled to ensure the accuracy of the traversal pattern, thereby triggering the traversal of the oral detection space according to the oral detection space and the corresponding traversal pattern, thereby realizing the traversal of the oral detection space.

[0069] Specifically, based on the acquisition and preprocessing of the user's oral images, the oral area to be inspected is determined, including the overall oral morphology, tooth arrangement, and gum condition. Using 3D reconstruction technology, the 2D oral image is converted into a 3D model to more accurately reflect the oral structure and characteristics. The frozen oral inspection space should contain sufficient detail to facilitate subsequent analysis and inspection. The constructed 3D model is calibrated to ensure its consistency with the actual oral structure. The accuracy of the model is ensured by comparing it with known oral structures or verifying it using professional tools.

[0070] Collect and integrate the user's previous oral data, including oral health status, treatment records, regular examination results, etc. Ensure the integrity and accuracy of the data for subsequent analysis. Use data analysis technology to extract key features from previous oral data, such as the degree of tooth wear, gum health, etc. Based on these features, define the traversal pattern related to the current oral detection space. Based on the analyzed features and data, set the rules and paths of the traversal pattern. The traversal rules should be able to fully cover the oral detection space while avoiding repeated detection or missing important areas. Optimize the set traversal pattern to ensure that it can traverse the oral detection space efficiently and accurately. Verify the feasibility and accuracy of the traversal pattern through simulation tests or actual tests.

[0071] After the oral detection space is frozen and the traversal pattern is defined, the traversal program is started. Ensure that the program can automatically or manually trigger the traversal of the oral detection space according to the set traversal rules and paths. During the traversal process, high-precision sensors or image recognition technology are used to detect each area in the oral detection space in real time. The detected data is analyzed to extract key information such as tooth wear and gingival inflammation. The test results are recorded and compared with previous oral data to assess changes in oral health status. Based on the test results, personalized health advice or treatment recommendations are provided to users. Throughout the traversal process, data protection and privacy regulations are strictly observed. Ensure the anonymization, encrypted storage and limited access of user data to protect user privacy and security.

[0072] Furthermore, the spatial layout of the oral detection space is defined based on the traversal of the oral detection space, the traversal of the oral detection space is realized, and the spatial layout of the oral detection space is output during the traversal process, ensuring the precise control of the spatial layout of the oral detection space. At this time, multiple spatial features are collected during the traversal process, and the spatial layout of the oral detection space is defined based on the multiple spatial features.

[0073] Specifically, load the fixed-frame model of the oral inspection space, including its 3D structure and related parameters. Initialize the traversal program and set the traversal starting point, path, and end conditions. Based on the characteristics of the oral inspection space, set the traversal resolution, speed, direction, and other parameters. Ensure that the traversal fully covers the oral inspection space while avoiding duplicate inspections or missing important areas.

[0074] During the traversal process, high-precision sensors or image recognition technology are used to detect each area of the oral examination space in real time. Spatial characteristics such as the location, shape, and size of each detection point are recorded. Based on the real-time detection data, a spatial layout diagram of the oral examination space is constructed. This spatial layout diagram should clearly reflect the shape, structure, and relationships between the various areas of the oral examination space. The constructed spatial layout diagram is optimized to ensure that it accurately reflects the actual layout of the oral examination space. The accuracy of the spatial layout diagram is ensured by comparing it with known oral structures or verifying it using specialized tools.

[0075] The constructed spatial layout diagram is output in a visual format, allowing users or doctors to intuitively understand the layout of the oral examination space. The output format can be a 2D image, a 3D model, or an interactive interface. During the traversal process, the spatial layout diagram is compared and verified in real time with the actual oral examination space. Any errors are corrected to ensure precise control of the spatial layout.

[0076] During the traversal process, multiple spatial features related to the oral examination space are collected, such as tooth arrangement, gum morphology, and oral cavity volume. This ensures that the collected features fully reflect the characteristics of the oral examination space. Based on the collected spatial features, the spatial layout of the oral examination space is further defined. The spatial layout should clearly reflect the position and relationships of each feature within the oral examination space. The spatial layout is updated and adjusted based on new test results or user feedback, ensuring that the spatial layout continuously reflects the latest state of the oral examination space.

[0077] Therefore, the shape of the oral detection space and the arrangement of the teeth are collected, and the spatial layout of the oral detection space, the shape of the oral detection space and the arrangement of the teeth are associated; the first direction parameter is defined according to the spatial layout of the oral detection space and the shape of the oral detection space, and the second direction parameter is defined according to the spatial layout of the oral detection space and the arrangement of the teeth; the detection direction of the oral detection space is defined according to the first direction parameter, the second direction parameter and the oral detection space, which is compatible with the overall consideration of the spatial layout of the oral detection space, the shape of the oral detection space and the arrangement of the teeth, and realizes multi-dimensional control of the spatial layout of the oral detection space, the shape of the oral detection space and the arrangement of the teeth, and ensures the detection direction of the oral detection space, so as to facilitate further processing of the detection direction of the oral detection space.

[0078] Specifically, high-precision scanning equipment or image acquisition technology is used to obtain three-dimensional morphological data of the oral cavity. This data should include detailed information such as the overall shape, size, and internal structure of the oral cavity. Using image recognition or oral scanning technology, the position, shape, size, and relative arrangement of each tooth are precisely recorded. This ensures that the collected tooth arrangement data is accurate and reflects the actual oral condition.

[0079] Combined with the collected morphological and tooth arrangement data, the spatial layout of the oral examination space is analyzed in depth. Key areas and feature points, such as the occlusal surfaces of the teeth and the gingival contour, are identified. The resulting spatial layout information is then correlated with the morphological and tooth arrangement data of the oral examination space. A mapping relationship is established between the three to ensure data accuracy and consistency.

[0080] Based on the spatial layout and morphology of the oral cavity, define the first direction parameter. This parameter should reflect the main direction or characteristic axis of the oral cavity, such as the depth and width of the oral cavity. Based on the tooth arrangement information, define the second direction parameter. This parameter should reflect key characteristics such as the tooth arrangement direction and inclination angle.

[0081] Comprehensively consider the first and second direction parameters, as well as the overall situation of the oral examination space. Ensure that the defined examination directions fully cover the oral examination space, while also taking into account the complexity of tooth arrangement. Based on these comprehensive considerations, define the examination directions for the oral examination space. The examination directions should ensure comprehensiveness and accuracy, while also balancing efficiency and comfort.

[0082] Optimize oral examination strategies and processes based on defined examination directions. Ensure accurate capture of key information during the examination process while minimizing unnecessary interference and errors. During the actual examination process, monitor the accuracy and effectiveness of the examination directions in real time. Make necessary adjustments and optimizations based on actual conditions to ensure a smooth examination process. Throughout the entire process, strictly adhere to data protection and privacy regulations. Ensure user data is anonymized, encrypted, and stored with limited access to protect user privacy and security.

[0083] refer to Figure 4 In step S13, a detection route of the oral detection space is defined according to the detection direction of the oral detection space, the shape of the oral detection member, and the movable range of the oral detection member;

[0084] In the specific implementation process of the present invention, the specific steps may be:

[0085] S131: fixing the detection direction of the oral detection space; collecting oral detection parts matching the oral detection space, and defining the shape of the oral detection parts based on online detection of the oral detection parts;

[0086] S132: defining a movement range of the oral cavity detection component based on the shape of the oral cavity detection component and movement information of the oral cavity detection component;

[0087] S133: Correlating the detection direction of the oral detection space, the shape of the oral detection component, and the movable range of the oral detection component; defining first system data based on the detection direction of the oral detection space and the shape of the oral detection component, and defining second system data based on the detection direction of the oral detection space and the movable range of the oral detection component;

[0088] S134: defining a detection route of the oral detection space according to the first system data, the second system data, and the system learning model matched with the oral detection space.

[0089] In an embodiment of the present application, the detection direction of the oral detection space is fixed; oral detection parts matching the oral detection space are collected, and the shape of the oral detection parts is defined based on the online detection of the oral detection parts, thereby realizing the online detection of the oral detection parts and introducing the shape of the oral detection parts, fully considering the influence of the shape of the oral detection parts.

[0090] Specifically, 3D scanning or image recognition technology is used to accurately measure and analyze the oral inspection space. Key inspection areas and feature points, such as the occlusal surfaces of teeth and the contours of the gums, are identified. Based on the analysis results, the inspection direction within the oral inspection space is defined. The inspection direction should ensure that the scanning or inspection equipment fully covers the critical area while avoiding unnecessary duplication of inspections. The defined inspection direction is calibrated to ensure its accuracy. The feasibility and effectiveness of the inspection direction are verified through simulation testing or actual inspections.

[0091] Select an oral inspection component that matches the inspection direction and characteristics of the oral inspection space. Ensure that the component adapts to the structure and morphology of the oral inspection space and meets the inspection requirements. Use high-precision sensors or image recognition technology to perform online inspection of the oral inspection component. Record the component's position and morphology in the oral inspection space in real time. Based on the results of online inspection, define the component's morphology. This morphological information should include key parameters such as the component's shape, size, and surface features.

[0092] Conduct in-depth analysis of the defined oral test part morphology. Identify factors within the morphology that may impact test results, such as edge sharpness and surface roughness. Optimize oral testing strategies and processes based on the results of the morphological analysis. Ensure that the impact of oral test part morphology is fully considered during the testing process, improving test accuracy and reliability. During the actual testing process, monitor changes in the oral test part morphology in real time. Based on the test results and morphological changes, make necessary adjustments and optimizations to ensure a smooth testing process.

[0093] Furthermore, the activity range of the oral detection part is defined based on the shape of the oral detection part and the activity information of the oral detection part, which is compatible with the overall consideration of the shape of the oral detection part and the activity information of the oral detection part, realizes the multi-dimensional control of the shape of the oral detection part and the activity information of the oral detection part, and ensures the accuracy of the activity range of the oral detection part.

[0094] Specifically, high-precision scanning or 3D modeling technology is used to obtain accurate 3D morphological data of the oral examination component. This data should include key information such as the component's shape, dimensions, and surface features. In-depth analysis of this acquired morphological data is then performed to identify the component's key morphological features. These features may include the component's edge shape, surface roughness, and overall dimensions.

[0095] Using sensors or image recognition technology, the movement of oral inspection components within the oral cavity is monitored in real time. Key activity information, such as the position, movement trajectory, and speed of the inspection component, is recorded. In-depth analysis of the collected activity data identifies patterns and trends in the inspection component's movement. This helps understand the actual movement of the inspection component within the oral cavity and any abnormal activity.

[0096] Comprehensively consider the morphological characteristics and movement information of the oral test piece. Ensure that the defined range of motion not only conforms to the test piece's morphological characteristics but also meets its intraoral movement requirements. Based on these comprehensive considerations, set the range of motion for the oral test piece. This range should clearly define the test piece's permitted movement areas and restrictions within the oral cavity. Verify the accuracy and feasibility of the set range of motion through simulation testing or actual use. Make necessary adjustments and optimizations based on the test results to ensure the accuracy of the range of motion.

[0097] During the use of oral test pieces, their activity information is monitored in real time. This helps to promptly detect and correct any abnormal activity, ensuring the safety and effectiveness of the test piece. Activity data of the oral test piece is collected and analyzed to understand its actual use in the oral cavity. Based on this data feedback, the range of motion is adjusted and optimized as necessary to adapt to different oral environments and testing needs. Education and training are provided to users on the use of oral test pieces and precautions. This ensures that users can use the test piece correctly and understand its range of motion and limitations in the mouth.

[0098] Therefore, the detection direction of the oral detection space, the shape of the oral detection part, and the activity range of the oral detection part are associated; the first system data is defined based on the detection direction of the oral detection space and the shape of the oral detection part, and the second system data is defined according to the detection direction of the oral detection space and the activity range of the oral detection part; the detection route of the oral detection space is defined according to the first system data, the second system data and the system learning model matching the oral detection space, which is compatible with the overall consideration of the first system data, the second system data and the system learning model matching the oral detection space, and multiple interactions are performed on the first system data, the second system data and the system learning model matching the oral detection space, thereby ensuring multi-dimensional control of the first system data, the second system data and the system learning model matching the oral detection space, and improving the accuracy of the detection route of the oral detection space.

[0099] Specifically, high-precision scanning or image recognition technology is used to determine the primary inspection directions within the oral testing space. These directions are typically determined based on the oral anatomy and functional requirements. Based on the inspection directions, an oral testing component is selected that matches the inspection direction. Ensure that the component's form (e.g., shape, size, and material) is suitable for effective inspection in the specified direction. Based on the component's form and the characteristics of the oral testing space, the permissible range of movement within the oral cavity is determined. Parameters such as the component's trajectory, velocity, and acceleration during the inspection process are considered.

[0100] Based on the inspection direction of the oral inspection space and the shape of the inspection component, a preliminary inspection path outline is defined. This includes parameters such as the starting point, end point, turning points, and path smoothness and continuity. Based on the inspection direction and the range of motion of the inspection component, the dynamic characteristics of the inspection path are defined. These include the velocity and acceleration of the inspection component at different positions, as well as possible adjustments to the inspection strategy.

[0101] Based on the characteristics and requirements of the oral examination space, an appropriate system learning model is selected. These models may include machine learning algorithms, deep learning networks, or expert systems. Data from the first and second systems are input into the system learning model. Through model learning and optimization, an inspection route that meets the characteristics of the oral examination space is generated. The generated inspection route is controlled across multiple dimensions, including path accuracy, efficiency, safety, and comfort. Necessary adjustments and optimizations are made to the inspection route based on actual inspection results and feedback.

[0102] During the actual testing process, the execution of the test route is monitored in real time. The test route is dynamically adjusted based on test results and changes in the oral testing space. User feedback is collected to understand the actual effectiveness and potential issues of the test route. Through iterative optimization, the accuracy of the test route and user satisfaction are continuously improved.

[0103] refer to Figure 5 , S14: defining an oral inspection system according to the inspection direction of the oral inspection space, the inspection route of the oral inspection space and the inspection speed of the oral inspection part;

[0104] In the specific implementation process of the present invention, the specific steps may be:

[0105] S141: freeze the detection direction of the oral detection space;

[0106] S142: monitoring the detection of the oral detection part in real time and collecting the detection speed of the oral detection part;

[0107] S143: Correlating the detection direction of the oral detection space, the detection route of the oral detection space, and the detection speed of the oral detection component;

[0108] S144: performing multiple interactions on a detection direction of the oral detection space, a detection route of the oral detection space, and a detection speed of the oral detection component;

[0109] S145: defining an oral detection system based on multiple interactions of a detection direction of the oral detection space, a detection route of the oral detection space, and a detection speed of the oral detection component.

[0110] At this time, the detection direction of the oral detection space is fixed, and the detection direction of the oral detection space is introduced to control the detection direction of the oral detection space. At the same time, the detection of the oral detection parts is monitored in real time, and the detection speed of the oral detection parts is collected; the detection direction of the oral detection space, the detection route of the oral detection space and the detection speed of the oral detection parts are associated, which is compatible with the overall consideration of the detection direction of the oral detection space, the detection route of the oral detection space and the detection speed of the oral detection parts.

[0111] Specifically, high-precision scanning technology is used to acquire three-dimensional structural data of the oral cavity. This data is analyzed to identify key inspection areas and potential inspection challenges. Based on the analysis, the inspection direction of the oral inspection space is determined to ensure comprehensive and efficient inspection path coverage. A strategy for inspection direction control is developed to ensure that the inspection part moves in the intended direction. Software algorithms or mechanical guidance systems are used to adjust the inspection part's direction in real time to maintain consistency with the intended path.

[0112] High-precision sensors are used to monitor the speed of oral test pieces in real time. The data acquisition system should be able to record and process this speed data in real time for subsequent analysis and optimization. This speed data is combined with other relevant parameters (such as position and acceleration) to assess the condition of the test piece. Any anomalies or deviations from the planned path can be identified and corrective measures implemented.

[0113] Consider the inspection direction, inspection route, and inspection speed of the oral inspection space as a whole. Ensure synergy between these three factors to achieve an efficient oral inspection process. Optimize the inspection direction, inspection route, and inspection speed based on real-time monitoring data and evaluation results. For example, the inspection speed can be adjusted to match the inspection needs of different areas, or the inspection route can be optimized to reduce unnecessary duplication or omissions. Collect user feedback to understand the actual effectiveness and potential problems of the inspection process. Through iterative optimization, continuously improve the accuracy of the inspection direction, the rationality of the inspection route, and the adaptability of the inspection speed.

[0114] Therefore, multiple interactions are performed on the detection direction of the oral detection space, the detection route of the oral detection space, and the detection speed of the oral detection parts; the oral detection system is defined based on the multiple interactions of the detection direction of the oral detection space, the detection route of the oral detection space, and the detection speed of the oral detection parts, thereby realizing the multiple interactions of the detection direction of the oral detection space, the detection route of the oral detection space, and the detection speed of the oral detection parts, ensuring the accuracy of the oral detection system, and fully considering the detection direction of the oral detection space, the detection route of the oral detection space, and the detection speed of the oral detection parts.

[0115] Specifically, high-precision scanning technology is used to acquire three-dimensional oral structural data and determine the inspection direction based on this data. Software algorithms or a mechanical guidance system enable real-time interaction between the inspection direction and the oral inspection component. This means the inspection component can dynamically adjust its direction based on the actual oral structure to ensure comprehensive coverage of the inspection area. A reasonable inspection route is planned based on the inspection direction and the configuration of the oral inspection component. An intelligent optimization algorithm is introduced to adjust and optimize the inspection route in real time. This takes into account factors such as the inspection component's movement path, inspection blind spots, and possible variations in tooth alignment. Through real-time feedback and interaction with the user, the inspection route is further fine-tuned to enhance inspection comfort and accuracy. High-precision sensors are equipped to monitor the movement speed of the oral inspection component in real time. The inspection speed is dynamically adjusted based on the specific characteristics and requirements of the inspection area. For example, the speed may need to be reduced in sensitive areas or complex structures to ensure inspection accuracy, while it can be increased in open areas to improve inspection efficiency. Inspection speed is optimized through the synergy between the inspection direction and inspection route.

[0116] Integrate the aforementioned multiple, interacting inspection directions, routes, and speeds into a unified oral inspection system. Ensure synergy between these elements to achieve an efficient and accurate oral inspection process. Continuously optimize and iterate the oral inspection system based on actual inspection results and user feedback. Introduce new technologies and algorithms to improve inspection accuracy and efficiency. Regularly evaluate system performance and make adjustments and improvements as needed.

[0117] Before constructing the oral testing system, the acquired 3D structural data is verified and calibrated. This ensures data accuracy and completeness to reduce errors and uncertainties. During the testing process, parameters such as the movement, position, and speed of the oral testing component are monitored in real time. Based on this real-time monitoring data, the testing direction, route, and speed are dynamically adjusted and optimized. Users are encouraged to provide feedback and suggestions regarding the testing process. Based on this feedback, necessary adjustments and improvements are made to the oral testing system to enhance user experience and satisfaction.

[0118] At the same time, the oral detection system is defined according to the detection direction of the oral detection space, the detection route of the oral detection space, and the detection speed of the oral detection parts, which is compatible with the overall consideration of the detection direction of the oral detection space, the detection route of the oral detection space, and the detection speed of the oral detection parts, and realizes multi-dimensional control of the detection direction of the oral detection space, the detection route of the oral detection space, and the detection speed of the oral detection parts, thereby ensuring the accuracy of the oral detection system.

[0119] Specifically, high-precision scanning technology (such as an oral scanner or CT scan) is used to acquire three-dimensional structural data of the oral cavity. Based on this data, and taking into account the oral anatomy and dental arrangement, the inspection direction is precisely determined. This ensures that the inspection direction comprehensively covers all critical areas within the oral cavity while avoiding unnecessary damage to the teeth and surrounding tissues. Based on the determined inspection direction and the shape and size of the oral inspection component, an optimal inspection route is planned. This inspection route should ensure that the inspection component can move along the predetermined path within the oral cavity while avoiding collisions with the teeth and surrounding tissues. An optimization algorithm is used to adjust the inspection route in real time to accommodate changes in oral structure and inspection requirements. The inspection speed is appropriately set based on the characteristics of the inspection area and the performance of the inspection component. This ensures that the inspection speed meets inspection efficiency requirements while not causing excessive pressure or discomfort in the oral cavity. Changes in the inspection speed are monitored in real time and adjusted as needed to maintain inspection continuity and stability.

[0120] When defining the oral testing system, consider the testing direction, route, and speed as a whole. Ensure synergy between these three elements to achieve comprehensive and accurate oral testing. Introduce real-time monitoring technology to monitor various parameters during the testing process. Based on the monitoring results, dynamically adjust and optimize the testing direction, route, and speed. Ensure the flexibility and adaptability of the testing system to cope with changes in different oral structures and testing needs. Establish a user feedback mechanism to collect user opinions and suggestions on the testing process. Continuously improve and optimize the oral testing system based on user feedback. Ensure that the testing system can better meet user needs and expectations, and enhance user satisfaction and trust.

[0121] Ensure the accuracy and completeness of acquired 3D structural data. Perform rigorous data processing and analysis to reduce errors and uncertainties. Develop standardized testing procedures and operating specifications. Train and assess testing personnel to ensure they are familiar with and master these procedures and specifications. Reduce the impact of human factors on test results through standardization and regularization, thereby improving test accuracy and reliability. Regularly evaluate and maintain the oral testing system. Check the performance and status of testing equipment to ensure proper operation and accurate testing. Make necessary adjustments and improvements to the testing system based on evaluation results and maintenance records.

[0122] refer to Figure 6 S15: In the oral detection system, multiple detection areas are defined based on the oral detection system and the oral detection space, and corresponding sub-oral images are collected according to the directional shooting of the multiple detection areas;

[0123] In the specific implementation process of the present invention, the specific steps may be:

[0124] S151: Fixed-frame oral testing system;

[0125] S152: In the oral detection system, multiple interactions are performed on the oral detection system and the oral detection space;

[0126] S153: Defining multiple detection areas based on multiple interactions of the oral detection system and the oral detection space;

[0127] S154: Freeze multiple detection areas, and define a detection order for the multiple detection areas according to the locations of the multiple detection areas, the corresponding area sizes, and the corresponding weight coefficients;

[0128] S155: performing directional photography of the multiple detection areas according to the detection order of the multiple detection areas and the orientation of the multiple detection areas;

[0129] S156: Acquire corresponding sub-oral cavity images based on the directional shooting of multiple detection areas.

[0130] In an embodiment of the present application, an oral detection system is fixed; in the oral detection system, multiple interactions are performed on the oral detection system and the oral detection space, thereby defining multiple detection areas based on the multiple interactions of the oral detection system and the oral detection space, realizing multiple interactions of the oral detection system and the oral detection space, ensuring the rationality of the division of multiple detection areas, and then accurately controlling the multiple detection areas.

[0131] Specifically, establish the basic framework of the oral testing system, including core elements such as testing objectives, testing methods, and testing processes. Ensure that the system framework is flexible and scalable enough to adapt to different oral structures and changing testing needs. Integrate advanced technologies such as high-precision scanning, image recognition, and data analysis algorithms to provide strong technical support for oral testing. Ensure that these technologies are seamlessly integrated into the testing system to improve testing accuracy and efficiency.

[0132] High-precision scanning technology is used to acquire three-dimensional oral structural data, including key information such as tooth arrangement, gum shape, and oral depth. This data is then analyzed in depth to identify potential inspection challenges and critical areas. Based on the results of this spatial data analysis, an interaction mechanism is established between the oral inspection system and the inspection space. This includes matching the inspection direction with the oral structure, coordinating the inspection route with the tooth arrangement, and balancing inspection speed with oral sensitivity.

[0133] Based on the multiple interactions between the oral inspection system and the inspection space, establish principles for dividing inspection areas. Ensure that each inspection area fully covers key structures while avoiding unnecessary duplication of inspections. Use image recognition technology or manual annotation methods to clearly define and identify inspection areas. Ensure that each area has clear boundaries and well-defined inspection targets.

[0134] During the testing process, the interaction between the testing system and the testing space is monitored in real time. Based on the monitoring results, the interaction mechanism is dynamically optimized and adjusted to ensure precise control of the testing area. Detailed testing strategies and methods are developed for each testing area. This ensures that the testing strategy fully considers factors such as regional characteristics, testing difficulty, and testing objectives to improve testing accuracy and efficiency. User feedback and suggestions on the testing process are collected. Based on user feedback, necessary iterative optimization of the testing system, testing space, and testing area is performed. This ensures that the testing system can continuously adapt to changes in oral structure and testing needs, providing users with higher-quality and more efficient oral testing services.

[0135] Therefore, multiple detection areas are frozen, and the detection order of the multiple detection areas is defined according to the positions of the multiple detection areas, the corresponding area areas and the corresponding weight coefficients; directional shooting of the multiple detection areas is performed along the detection order of the multiple detection areas and the directions of the multiple detection areas; based on the directional shooting of the multiple detection areas, the corresponding sub-oral cavity images are collected, thereby realizing directional shooting of the multiple detection areas and ensuring the accuracy of the sub-oral cavity images.

[0136] Specifically, high-precision scanning technology is used to acquire three-dimensional structural data of the oral cavity. Based on this data, the oral cavity is divided into multiple inspection areas, each of which is assigned a unique identifier. The location, area, and possible morphological characteristics of each inspection area are recorded. These characteristics will serve as an important basis for subsequently defining the inspection sequence and imaging method.

[0137] A weight coefficient is assigned to each inspection area based on its importance, inspection difficulty, and relevance to other areas. Areas with higher weight coefficients receive higher priority in the inspection sequence. Combining the weight coefficients with the location of the areas, a reasonable inspection sequence is planned. This ensures efficient and orderly inspections while avoiding overlooking critical areas.

[0138] Determine the optimal shooting angle and position based on the orientation and morphological characteristics of each inspection area. Ensure that the camera accurately captures the key structures within the area. Follow the planned inspection sequence and perform directional photography of each inspection area. During the photography process, carefully adjust shooting parameters (such as focal length and exposure) to ensure image quality. Based on directional photography, capture sub-oral images of each inspection area. Ensure that the captured images are clear, complete, and accurately reflect the oral structures within the area.

[0139] Perform a quality check on the captured sub-oral images to ensure they are clear, free of blur or distortion. If necessary, perform post-processing (such as contrast enhancement and sharpening) to improve image quality. Verify that the captured sub-oral images match the original inspection area. Ensure that the structures in the images are consistent with those in the original data to avoid image misalignment or omissions. Integrate all sub-oral images into a unified database. Leverage image recognition and data analysis technologies to conduct in-depth image analysis and extract key information, providing strong support for subsequent oral health assessment and treatment.

[0140] refer to Figure 7 S16: Based on the interaction between the oral inspection component and the oral inspection system, a primary overall image is collected, and a high-level overall image is defined according to the primary overall image, the multiple sub-oral images, and the abnormal position of the oral cavity; and a final oral image is constructed according to the high-level overall image, the user's oral habits, and the primary overall image;

[0141] In the specific implementation process of the present invention, the specific steps may be:

[0142] S161: Freeze the oral inspection component and the oral inspection system, and interact with the oral inspection component and the oral inspection system;

[0143] S162: Collecting a primary overall image based on the interaction between the oral inspection component and the oral inspection system;

[0144] S163: defining an abnormal position of the oral cavity based on abnormality detection of the plurality of detection areas, and defining an advanced overall image based on the primary overall image, the plurality of sub-oral cavity images, and the abnormal position of the oral cavity;

[0145] S164: collecting high-level overall images, the user's oral habits, and the user's mouth shape layout;

[0146] S165: Perform multiple interactions on the advanced overall image, the user's oral habits, and the user's mouth shape layout, and define a review area based on the multiple interactions on the advanced overall image, the user's oral habits, and the user's mouth shape layout;

[0147] S166: Constructing a final oral cavity image based on the primary overall image, the advanced overall image, and the review area.

[0148] At this time, the oral inspection part and the oral inspection system are frozen, and the oral inspection part and the oral inspection system interact with each other; the primary overall image is collected based on the interaction between the oral inspection part and the oral inspection system, realizing the interaction between the oral inspection part and the oral inspection system and ensuring the accuracy of the primary overall image.

[0149] Specifically, select oral inspection devices that meet industry standards and undergo rigorous calibration, such as oral endoscopes and 3D scanners. Ensure that the device's resolution, color reproduction, focal length, and other parameters meet the requirements for capturing high-quality images. Establish an oral inspection system that includes data acquisition, image processing, data storage, and analysis. Ensure that the system can support data access from a variety of oral inspection devices and has the ability to process and analyze data in real time.

[0150] Connect oral testing devices to the oral testing system through standardized interface protocols. Ensure that data collected by the test devices is transmitted to the testing system in real time and accurately. Establish clear interaction logic within the testing system, including test device activation, image acquisition triggering, and real-time data processing. Ensure that the interaction between the test device and the system is smooth, stable, and in compliance with clinical operating standards.

[0151] Under the guidance of the oral inspection system, activate the oral inspection unit to capture images. Adjust the unit's shooting angle, focal length, and other parameters based on clinical needs to ensure comprehensive and clear images. Immediately after image acquisition, conduct a quality check, including image clarity, color reproduction, and integrity. If poor image quality is detected, recapture the image immediately until a satisfactory primary overall image is obtained.

[0152] Regularly calibrate oral testing components to ensure stable and accurate performance. Use known standard images for verification to ensure the testing system can accurately process and analyze acquired image data. Continuously optimize the performance of oral testing components and the testing system based on clinical feedback and technological developments. Regularly upgrade the testing system's software algorithms and hardware configuration to improve the accuracy and efficiency of image acquisition and processing.

[0153] Furthermore, the abnormal position of the oral cavity is defined based on the abnormality detection of multiple detection areas, and the advanced overall image is defined based on the primary overall image, multiple sub-oral images and the abnormal position of the oral cavity. At this time, abnormality detection of multiple detection areas is realized, so as to facilitate abnormality investigation of multiple detection areas, thereby introducing the abnormal position of the oral cavity, further controlling the abnormal position of the oral cavity, associating the primary overall image, multiple sub-oral images and the abnormal position of the oral cavity, and performing overall control of the primary overall image, multiple sub-oral images and the abnormal position of the oral cavity, thereby ensuring the accuracy of the advanced overall image.

[0154] Specifically, specialized oral inspection equipment and technology are used to perform detailed inspections of multiple predetermined inspection areas within the oral cavity. Based on the inspection data and analysis results, possible abnormalities in each inspection area, such as caries, periodontal disease, and missing teeth, are identified. Based on the abnormality detection results, the specific location of the abnormality within the oral cavity is determined. These abnormal locations are marked on the primary overall image or the corresponding sub-oral image to facilitate subsequent image analysis and processing.

[0155] The primary overall image is integrated with multiple sub-oral images to form a complete oral image dataset. Each sub-oral image is accurately mapped to the corresponding location in the primary overall image. The previously identified abnormality location information is incorporated into the integrated image dataset, ensuring that each abnormality location is accurately represented in the image dataset. Based on the integrated image dataset and abnormality location information, advanced image processing techniques and algorithms are used to generate a high-level overall image. This image should clearly reflect the overall structure, detailed features, and abnormality locations of the oral cavity.

[0156] Before generating the advanced overall image, a detailed abnormality check is performed on multiple inspection areas. Abnormalities in each inspection area are accurately identified and marked. Identified abnormal locations are further verified and confirmed. Professional oral inspection techniques and equipment are used to conduct more in-depth analysis and processing of abnormal locations. The primary overall image, multiple sub-oral images, and the location of oral abnormalities are closely correlated. This information is comprehensively controlled to ensure that it is accurately reflected and represented in the advanced overall image. The comprehensive application of these steps ensures the accuracy of the advanced overall image. Advanced image processing techniques and algorithms are used to further optimize and process the image to improve its clarity and accuracy.

[0157] Therefore, the advanced overall image, the user's oral habits and the user's mouth shape layout are collected; multiple interactions are performed on the advanced overall image, the user's oral habits and the user's mouth shape layout, and the review area is defined based on the multiple interactions of the advanced overall image, the user's oral habits and the user's mouth shape layout; the final oral image is constructed based on the primary overall image, the advanced overall image and the review area, realizing the multiple interactions of the advanced overall image, the user's oral habits and the primary overall image, and comprehensively considering the primary overall image, the abnormal position of the mouth, the user's oral habits and the advanced overall image, thereby ensuring multi-dimensional control of the final oral image and improving the modeling accuracy of the final oral image.

[0158] Specifically, advanced oral inspection technology and equipment are used to capture high-quality, full-body oral images, ensuring that the images clearly and accurately reflect the overall structure and details of the oral cavity. Information on users' oral habits, including brushing frequency, dietary habits, and daily oral care behaviors such as flossing, is collected through questionnaires, face-to-face interviews, or smart device monitoring. Information on the user's mouth layout is obtained through oral scanning or photography, analyzing the size and shape of the mouth and the alignment of the teeth.

[0159] The system integrates a high-level overall image with the user's oral habits and mouth shape. Advanced image processing techniques and algorithms analyze the correlations and influences between these factors. Based on these interactions, it identifies areas of the mouth that may contain abnormalities or require further examination. These areas may include the tooth surface, gums, and periodontal tissues.

[0160] Integrate the primary overall image with the advanced overall image to form a complete oral image dataset. Ensure the consistency of the two images in terms of details and structure. In the integrated image dataset, clearly mark the review areas. Ensure that these areas are highlighted and accurately reflected in the final oral image. In the process of constructing the final oral image, multiple factors such as the primary overall image, abnormal locations in the mouth, the user's oral habits, and the advanced overall image are comprehensively considered. These factors are controlled in multiple dimensions to ensure that they are accurately reflected and balanced in the final image. Through the comprehensive application of the above steps, the modeling accuracy of the final oral image is improved. Using advanced image processing and modeling technologies, the image is further optimized and processed to improve its clarity and accuracy.

[0161] The resulting oral image not only reflects the user's oral health status but also takes into account individual differences and oral habits. This provides dentists with a more comprehensive and accurate basis for diagnosis, helping to develop personalized treatment plans. Furthermore, this comprehensive image construction method offers new insights and technical support for oral health monitoring and disease prevention.

[0162] See also Figure 8 , Figure 8 Schematic diagram of the structure of the oral image modeling device in an embodiment of the present invention.

[0163] like Figure 8 As shown, a modeling device for an oral cavity image comprises:

[0164] An oral detection space module 21 is configured to define an oral detection space based on the user's oral space and tooth space;

[0165] A detection direction module 22 is used to define the spatial layout of the oral detection space according to the traversal of the oral detection space, and to define the detection direction of the oral detection space according to the spatial layout of the oral detection space, the shape of the oral detection space, and the arrangement of the teeth;

[0166] A detection route module 23 is used to define a detection route of the oral detection space according to the detection direction of the oral detection space, the shape of the oral detection component, and the range of movement of the oral detection component;

[0167] A protection path module 24 is used to define an oral inspection system according to an inspection direction of the oral inspection space, an inspection route of the oral inspection space, and an inspection speed of the oral inspection component;

[0168] The sub-oral imaging module 25 is used to define multiple detection areas in the oral detection system based on the oral detection system and the oral detection space, and to capture corresponding sub-oral images by directional shooting of the multiple detection areas;

[0169] The oral image module 26 is used to collect a primary overall image based on the interaction between the oral detection parts and the oral detection system, define an advanced overall image based on the primary overall image, multiple sub-oral images and abnormal positions of the oral cavity; and construct a final oral image based on the advanced overall image, the user's oral habits and the primary overall image.

[0170] The above is a detailed introduction to the oral image modeling method and device provided in the embodiments of the present invention. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core ideas. For those skilled in the art, according to the ideas of the present invention, there may be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A modeling method for oral images, characterized in that: Modeling scenarios applied to oral images; The oral image modeling method includes: Defining an oral detection space based on the user's oral space and tooth space; Defining the spatial layout of the oral detection space according to the traversal of the oral detection space, and defining the detection direction of the oral detection space according to the spatial layout of the oral detection space, the shape of the oral detection space, and the arrangement of teeth; Defining the detection route of the oral detection space according to the detection direction of the oral detection space, the shape of the oral detection part, and the range of movement of the oral detection part; An oral inspection system is defined based on the inspection direction of the oral inspection space, the inspection route of the oral inspection space, and the inspection speed of the oral inspection parts, including: freezing the inspection direction of the oral inspection space; real-time monitoring of the inspection of oral inspection parts, and collecting the inspection speed of the oral inspection parts; associating the inspection direction of the oral inspection space, the inspection route of the oral inspection space, and the inspection speed of the oral inspection parts; performing multiple interactions on the inspection direction of the oral inspection space, the inspection route of the oral inspection space, and the inspection speed of the oral inspection parts; defining an oral inspection system based on the multiple interactions of the inspection direction of the oral inspection space, the inspection route of the oral inspection space, and the inspection speed of the oral inspection parts; considering the inspection direction, inspection route, and inspection speed as a whole to ensure the synergy between the three elements, introducing real-time monitoring technology, performing real-time monitoring of various parameters in the inspection process, and dynamically adjusting and optimizing the inspection direction, inspection route, and inspection speed based on the monitoring results to cope with changes in different oral structures and inspection needs; In the oral detection system, multiple detection areas are defined based on the oral detection system and the oral detection space, and corresponding sub-oral images are collected according to the directional shooting of the multiple detection areas; Based on the interaction between the oral detection part and the oral detection system, a primary overall image is collected, and an advanced overall image is defined according to the primary overall image, multiple sub-oral images and abnormal positions of the oral cavity; a final oral image is constructed according to the advanced overall image, the user's oral habits and the primary overall image, including: freezing the oral detection part and the oral detection system, and interacting with the oral detection part and the oral detection system; collecting the primary overall image according to the interaction between the oral detection part and the oral detection system; defining the abnormal position of the oral cavity based on abnormal detection of multiple detection areas, and defining the advanced overall image according to the primary overall image, multiple sub-oral images and abnormal positions of the oral cavity; collecting the advanced overall image, the user's oral habits and the user's mouth shape layout; performing multiple interactions on the advanced overall image, the user's oral habits and the user's mouth shape layout, and defining a review area according to the multiple interactions of the advanced overall image, the user's oral habits and the user's mouth shape layout; and constructing the final oral image based on the primary overall image, the advanced overall image and the review area.

2. The oral image modeling method according to claim 1, characterized in that: Defining the oral detection space based on the user's oral space and tooth space includes: Collect the user's location; determining a user's face space based on detection of the user's location; triggering a dynamic change of the user's facial space based on a facial operation prompt, and collecting a plurality of change images according to the dynamic change of the user's facial space; The user's mouth space is defined based on the first layer recognition of the multiple change images, and the user's tooth space is defined based on the second layer recognition of the multiple change images. At this time, the user's mouth space and the user's tooth space are synchronously detected; The oral cavity detection space is defined according to the user's mouth space and teeth space.

3. The oral image modeling method according to claim 2, characterized in that: Defining the spatial layout of the oral detection space according to the traversal of the oral detection space, and defining the detection direction of the oral detection space according to the spatial layout of the oral detection space, the shape of the oral detection space, and the arrangement of teeth, includes: Freeze the oral testing space; Define the corresponding traversal mode based on the oral detection space and the user's previous oral data; Triggering the traversal of the oral detection space according to the oral detection space and the corresponding traversal mode; Defining a spatial layout of the oral detection space based on traversal of the oral detection space; Collecting the shape of the oral testing space and the arrangement of the teeth, and correlating the spatial layout of the oral testing space, the shape of the oral testing space and the arrangement of the teeth; A first direction parameter is defined according to the spatial layout of the oral detection space and the shape of the oral detection space, and a second direction parameter is defined according to the spatial layout of the oral detection space and the arrangement of teeth; The detection direction of the oral detection space is defined according to the first direction parameter, the second direction parameter and the oral detection space.

4. The oral image modeling method according to claim 3, characterized in that: Defining the detection route of the oral detection space according to the detection direction of the oral detection space, the shape of the oral detection piece, and the range of movement of the oral detection piece includes: Fixing the detection direction of the oral detection space; collecting oral detection parts that match the oral detection space, and defining the shape of the oral detection parts based on the online detection of the oral detection parts; defining a range of movement of the oral cavity detection component based on the shape of the oral cavity detection component and movement information of the oral cavity detection component; Associating the detection direction of the oral detection space, the shape of the oral detection part, and the range of movement of the oral detection part; defining first system data based on the detection direction of the oral detection space and the shape of the oral detection part, and defining second system data based on the detection direction of the oral detection space and the range of movement of the oral detection part; A detection route of the oral detection space is defined according to the first system data, the second system data, and a system learning model matched with the oral detection space.

5. The oral image modeling method according to claim 1, characterized in that: In the oral detection system, multiple detection areas are defined based on the oral detection system and the oral detection space, and corresponding sub-oral images are collected according to directional shooting of the multiple detection areas, including: Fixed-frame oral testing system; In the oral detection system, multiple interactions are performed on the oral detection system and the oral detection space; Multiple detection areas are defined based on multiple interactions of the oral detection system and the oral detection space.

6. The oral image modeling method according to claim 5, characterized in that: In the oral cavity detection system, multiple detection areas are defined based on the oral cavity detection system and the oral cavity detection space, and corresponding sub-oral cavity images are collected according to directional shooting of the multiple detection areas, further comprising: Freeze multiple detection areas and define the detection order of multiple detection areas according to their locations, corresponding area sizes and corresponding weight coefficients; Performing directional photography of the multiple detection areas along the detection order of the multiple detection areas and the orientations of the multiple detection areas; Based on the directional shooting of multiple detection areas, corresponding sub-oral images are collected.

7. A modeling device for oral images, characterized in that: The oral image modeling device is applied to the oral image modeling method according to any one of claims 1 to 6, and the oral image modeling device comprises: An oral detection space module, used to define an oral detection space based on the user's oral space and tooth space; A detection direction module, used to define the spatial layout of the oral detection space according to the traversal of the oral detection space, and to define the detection direction of the oral detection space according to the spatial layout of the oral detection space, the shape of the oral detection space, and the arrangement of the teeth; A detection route module is used to define a detection route of the oral detection space according to the detection direction of the oral detection space, the shape of the oral detection component, and the range of movement of the oral detection component; A protection path module is used to define an oral detection system based on the detection direction of the oral detection space, the detection route of the oral detection space, and the detection speed of the oral detection parts, including: freezing the detection direction of the oral detection space; real-time monitoring of the detection of oral detection parts and collecting the detection speed of oral detection parts; associating the detection direction of the oral detection space, the detection route of the oral detection space, and the detection speed of the oral detection parts; performing multiple interactions on the detection direction of the oral detection space, the detection route of the oral detection space, and the detection speed of the oral detection parts; defining the oral detection system based on the multiple interactions of the detection direction of the oral detection space, the detection route of the oral detection space, and the detection speed of the oral detection parts; considering the detection direction, detection route, and detection speed as a whole to ensure the synergy between the three elements, introducing real-time monitoring technology, performing real-time monitoring of various parameters in the detection process, and dynamically adjusting and optimizing the detection direction, detection route, and detection speed based on the monitoring results to cope with changes in different oral structures and detection needs; A sub-oral imaging module is used to define multiple detection areas in the oral detection system based on the oral detection system and the oral detection space, and to capture corresponding sub-oral images based on directional shooting of the multiple detection areas; An oral image module is used to collect a primary overall image based on the interaction between an oral detection piece and an oral detection system, define an advanced overall image based on the primary overall image, multiple sub-oral images and abnormal positions of the oral cavity; construct a final oral image based on the advanced overall image, the user's oral habits and the primary overall image, including: freezing the oral detection piece and the oral detection system, and interacting with the oral detection piece and the oral detection system; collecting a primary overall image based on the interaction between the oral detection piece and the oral detection system; defining abnormal positions of the oral cavity based on abnormal detection of multiple detection areas, and defining an advanced overall image based on the primary overall image, multiple sub-oral images and abnormal positions of the oral cavity; collecting an advanced overall image, the user's oral habits and the user's mouth shape layout; performing multiple interactions on the advanced overall image, the user's oral habits and the user's mouth shape layout, and defining a review area based on the multiple interactions of the advanced overall image, the user's oral habits and the user's mouth shape layout; and constructing a final oral image based on the primary overall image, the advanced overall image and the review area.

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