Oral cavity malocclusion invisible correction diagnosis and treatment auxiliary system and method thereof

Abstract

The invention discloses an invisible orthodontic diagnosis and treatment auxiliary system for oral malocclusion and a method thereof, and relates to the technical field of orthodontic digitization. The system can realize whole-process management of patient information acquisition, image processing, treatment suggestion generation, correction animation playback, intelligent appointment scheduling and accurate distribution of the correction appliance; the clinical diagnosis and treatment auxiliary module is integrated with a treatment progress abnormity identification model and is used for identifying a treatment deviation risk and providing an intervention prompt; the 3D animation scheme module supports visual playing and step number positioning in the correction process, the intelligent reservation module provides a scheduling mechanism of key node driving and date backstepping, and the issuing module realizes rapid correction appliance positioning by adopting hierarchical coding and hash index technologies. The system has the characteristics of high information integration level, controllable treatment path, high operation efficiency and the like, and is suitable for an invisible orthodontic whole-cycle diagnosis and treatment scene.

Description

Technical Field

[0001] The present invention relates to the technical field of digital orthodontics, and particularly to an auxiliary system and method for the diagnosis and treatment of oral malocclusion with invisible orthodontics. Background Art

[0002] With the continuous development of digital medical technology, invisible orthodontics has gradually become an important means in the treatment of dental malocclusion. This treatment method relies on digital modeling and three-dimensional forming technologies, and has the characteristics of beauty, comfort and customization. It is widely used in the daily treatment of various orthodontic patients. Its typical process includes initial diagnosis and filing of patients, image acquisition and analysis, formulation of treatment plans, production and distribution of orthodontic appliances, and periodic review and treatment adjustment. To meet this process, clinics usually need to use multiple information systems such as doctor workstations, oral imaging systems, electronic medical record systems, invisible orthodontic clients, etc. in cooperation.

[0003] However, under the existing technical conditions, there are still many deficiencies in the clinical application of invisible orthodontics. First of all, the review process highly depends on manual operations by doctors, and there is a lack of integration between different systems, resulting in doctors frequently switching between multiple platforms, discontinuous information acquisition, easy omission or misjudgment, prolonging the operation time and affecting the treatment efficiency. Secondly, the modification space of the treatment plan for invisible orthodontic appliances is limited after generation. Once the tooth movement effect deviates from the original design path, if it is not discovered and intervened in time, the risk of treatment failure will increase. But currently, there is a lack of effective technical means to automatically identify abnormal progress and give early warnings. Thirdly, due to the large number of invisible orthodontic companies and their doctor-side software being independent of each other, the system compatibility is poor and information sharing is difficult. At the same time, there are a variety of orthodontic appliances with scattered packaging, making it difficult to locate the required orthodontic appliances in a timely manner during patient reviews, further increasing the doctor's workload.

[0004] Therefore, there are still obvious technical bottlenecks in the existing invisible orthodontic technology in aspects such as "treatment progress monitoring", "system integration and interconnection", "dynamic adjustment of treatment plans", and "management efficiency of orthodontic appliances". There is an urgent need to propose a new type of auxiliary diagnosis and treatment technology with high integration, intelligent processing ability and full-process support ability to improve the clinical quality and operation efficiency of invisible orthodontics. Summary of the Invention

[0005] The purpose of the present invention is to provide an auxiliary system and method for the diagnosis and treatment of oral malocclusion with invisible orthodontics, and to construct an orthodontic intelligent auxiliary platform including an abnormal progress recognition model, animation synchronization control and intelligent appointment logic, so as to solve the key technical bottlenecks such as the inability to automatically identify treatment deviations, complex manual intervention, and broken information linkage in the current system.

[0006] The present invention achieves the above purpose through the following technical solutions:

[0007] On the one hand, the present invention provides an invisible orthodontic diagnosis and treatment assistance system for oral malocclusion, comprising:

[0008] A basic case information module, which is used to connect to the hospital system after obtaining the patient's authorization, collect the patient's basic information, medical records, and oral imaging data, and establish a primary diagnosis file to form patient file information;

[0009] An image information module, which is used to integrate the oral imaging data and perform automatic analysis to generate image analysis data, including performing multi-period image comparison on the lateral cephalogram to generate cephalometric change curves and overlapping maps;

[0010] A clinical diagnosis and treatment assistance module, which is used to integrate the patient file information and the image analysis data, automatically generate treatment suggestions, and call the data in the system during follow-up visits to update the content displayed on the doctor's interface in real time, and an abnormal progress recognition model for identifying the state where the treatment effect deviates from the expected target is integrated therein;

[0011] A 3D animation scheme module, which is used to construct an orthodontic treatment scheme animation according to the treatment suggestions, play it automatically, and position to the current orthodontic treatment step and pause the display after the playback is completed;

[0012] An intelligent appointment module, which is used to receive the current orthodontic treatment step and support two appointment modes: generating a review date based on key operation steps, or inversely inferring the number of orthodontic appliances to be worn based on the expected review date;

[0013] An orthodontic appliance distribution module, which is used to identify, store, and locate orthodontic appliances through a hierarchical coding rule, receive the distribution instruction from the intelligent appointment module, and quickly retrieve the storage location of the orthodontic appliances through a database indexing algorithm to complete the precise distribution of orthodontic appliances.

[0014] A further improvement of the present invention lies in that the basic case information module includes:

[0015] A follow-up visit information retrieval unit, which is used to automatically retrieve the patient's historical disease course records and the visit information of other departments during the patient's follow-up visit, and summarize them to form a multi-source diagnosis and treatment file;

[0016] A treatment stage management unit, which is used to generate structured follow-up visit reminder information based on the historical file and the current treatment stage, including recommended examination items, key clinical concerns, and pending operation suggestions.

[0017] A further improvement of the present invention lies in that the image information module includes:

[0018] An image data acquisition unit, which is used to connect to the hospital PACS system to obtain and standardize the patient's oral imaging data, including X-ray films, CT images, and intraoral scan images, for doctors to view and analyze;

[0019] An image classification unit for classifying image data according to image type and shooting time, and providing an image selection interface. Doctors can select data according to image type or shooting time for vertical or horizontal comparison to observe the changes in the condition or understand the image data at different time nodes;

[0020] A cephalometric analysis unit. If a doctor selects a lateral cephalogram, it automatically calls the cephalometric function in the clinical diagnosis and treatment assistance module to calculate and display cephalometric values at different time points, automatically mark the changed data beyond the normal range, and generate change curves and overlay graphs;

[0021] A CT image analysis unit. If a doctor selects a CT scan, it automatically intercepts and displays panoramic tomograms, cross-sections of the relationship between the roots and alveolar bone, joint cross-sections, etc., generates an analysis report, and provides key information to assist doctors in treatment evaluation.

[0022] A further improvement of the present invention is that the clinical diagnosis and treatment assistance module includes:

[0023] An expert opinion database unit for summarizing and classifying the classic design ideas reached by orthodontic experts through consensus, and providing treatment reference suggestions according to the type of malocclusion and clinical manifestations;

[0024] A case information management unit for collecting the patient's basic information, medical records, and image data at the first diagnosis, and retrieving historical diagnosis and treatment information at the follow-up visit to form a patient file;

[0025] An automatic image analysis unit for processing the patient's image data, calling the cephalometric function for multi-phase comparison, abnormal marking, change curve generation, and overlay graph analysis;

[0026] A personalized treatment plan design unit for automatically generating a preliminary treatment plan by combining the analysis results with expert opinions, and supporting the adjustment and optimization of the plan;

[0027] A follow-up visit information integration and display unit for uniformly displaying multi-source data of case information, analysis results, and treatment plans;

[0028] A treatment progress monitoring unit for stage-by-stage monitoring of the wearing status of the appliance and the treatment effect, and outputting a progress evaluation result;

[0029] A key and difficult operation guidance unit for guiding the operation steps in a standardized process, and assisting the operation execution with video demonstrations;

[0030] A retainer review reminder unit for pushing reminders for retainer wearing management and periodic reviews after the treatment ends.

[0031] A further improvement of the present invention lies in that the treatment progress monitoring unit includes a treatment progress abnormality recognition model, and the construction process of the treatment progress abnormality recognition model includes:

[0032] A stage error calculation unit for calculating, based on the actual three-dimensional coordinates of the tooth positions of the patient in the current orthodontic stage and the planned three-dimensional coordinates generated by the system to calculate the average position error of this stage , and the calculation formula is:

[0033] ;

[0034] Where: is the total number of tooth positions monitored in the current stage, is the tooth position number;

[0035] A pass rate evaluation unit for calculating the pass rate under a set error tolerance , and the calculation formula is:

[0036] ;

[0037] A label deviation detection unit for calculating the stage label deviation loss , and the calculation formula is:

[0038] ;

[0039] Where: represents the status identifier of the current orthodontic stage, is the label vector generated by the system according to the patient's historical data, is the label value manually input by the doctor in the current stage, and the three are used as inputs to calculate the cross-entropy loss function to measure the consistency of label recognition;

[0040] An abnormality determination unit for outputting an abnormality marking signal when any of the following conditions is met:

[0041] ;

[0042] Where: , , are the threshold parameters set by the system.

[0043] A further improvement of the present invention lies in that the 3D animation scheme module includes:

[0044] A data interface unit for data interaction with different invisible orthodontic brand workstations through a standardized interface, automatically obtaining orthodontic data from the workstations, parsing, and storing orthodontic animation information;

[0045] An animation generation unit for generating an orthodontic treatment plan animation for a patient based on the orthodontic data, displaying each animation step, and positioning to the current orthodontic step after playback is completed, pausing the display;

[0046] An animation optimization unit for compressing and formatting the generated orthodontic animation data, adjusting the size of the animation data to adapt to the terminal playback resources, and unifying the animation frame rate and rendering configuration;

[0047] A playback control unit for controlling the playback state of the orthodontic animation, supporting automatic playback and pause control, and providing interfaces for adjusting the playback speed and the number of steps to meet the doctor's control requirements for the playback rhythm;

[0048] A compatibility unit for supporting the animation data formats and coding methods of multiple orthodontic brands, ensuring that the module can be uniformly called in different brand environments;

[0049] A display customization unit for providing a personalized display item configuration interface, allowing doctors to adjust the playback parameters and progress display method according to treatment needs to achieve customized review of the orthodontic treatment plan and treatment evaluation.

[0050] A further improvement of the present invention is that the intelligent appointment module includes:

[0051] A review date generation unit for receiving the wearing cycle of each orthodontic appliance and the expected number of steps input by the doctor for the patient, and automatically generating corresponding review dates based on the parameters when there are key operation steps;

[0052] A step calculation unit for receiving the wearing cycle of each orthodontic appliance and the expected review date input by the doctor, and calculating the number of steps of the orthodontic appliance to be worn in the scenario where there are no key operation steps;

[0053] A review record unit for recording the appointment time of each review and the actual number of steps worn by the patient, for the clinical diagnosis and treatment assistance module to call for animation synchronization and treatment data management.

[0054] A further improvement of the present invention is that the orthodontic appliance distribution module includes:

[0055] An identification coding unit for generating a unique hierarchical code according to the invisible orthodontic appliance brand, series, malocclusion type, and identification information of the patient. The code includes three segments: a brand code, a series serial number, and a patient identification number, and is bound and stored with the information of the first storage location of the orthodontic appliance;

[0056] A reservation instruction receiving unit, configured to receive a release request sent by the intelligent reservation module, and extract patient identification information and the required reservation steps;

[0057] An identity matching unit, configured to receive identification data transmitted by the case basic information module during the patient's follow-up visit, and perform matching verification with the reservation information.

[0058] A further improvement of the present invention lies in that the orthodontic appliance release module further includes:

[0059] A coding retrieval unit, configured to establish a mapping relationship between the coding and the storage location information based on the hierarchical coding and the hash index algorithm. When receiving a release request, locate the required orthodontic appliance through the combination of the patient identification number and the number of steps, and return its storage location information;

[0060] A release execution unit, configured to guide the doctor to complete the physical release operation of the orthodontic appliance according to the storage location information;

[0061] Wherein, the hash index algorithm establishes an index table with the complete coding as the primary key, adopts a conflict resolution strategy and supports an index reconstruction mechanism to ensure retrieval efficiency and consistency maintenance.

[0062] On the other hand, the present invention provides an auxiliary method for the diagnosis and treatment of oral malocclusion with invisible orthodontics, which is applied to the auxiliary system for the diagnosis and treatment of oral malocclusion with invisible orthodontics as described above. The method includes the following steps:

[0063] S1: Collect the basic information, medical record materials and oral imaging data of the patient, establish a primary diagnosis file, and form patient file information;

[0064] S2: Process the oral imaging data to generate image analysis data. The processing includes performing multi-period image comparison on the lateral cephalogram to generate a cephalometric change curve and an overlay map;

[0065] S3: Input the patient file information and the image analysis data into the clinical diagnosis and treatment assistance module to generate personalized treatment suggestions, and run an abnormal progress recognition model based on the data to determine whether the current treatment status deviates from the preset target status;

[0066] S4: Generate a corresponding 3D orthodontic treatment plan animation according to the treatment suggestions, play the animation, and automatically locate to the current orthodontic step and pause the display after the playback is completed;

[0067] S5: Input the current orthodontic step into the intelligent reservation module. If there are key operation steps, generate corresponding review dates according to the wearing cycle of each orthodontic appliance input by the doctor and the target number of steps; if there are no key operation steps, reverse-infer the required number of orthodontic appliance steps according to the wearing cycle and the expected review date input by the doctor;

[0068] S6: Combine the patient identification with the calculated orthodontic appliance steps to generate a hierarchical code, which is used as a retrieval key to locate the storage location of the corresponding orthodontic appliance through the database indexing algorithm, and guide the completion of the orthodontic appliance distribution operation.

[0069] The beneficial effects of the present invention are as follows: Through the cooperation of multiple modules, the present invention realizes the data integration and intelligent management of the diagnosis and treatment process. The system can automatically collect the basic information and imaging data of patients and establish a structured electronic file; the image module supports multi-period comparison and automatic measurement, facilitating the dynamic observation of structural changes; the diagnosis and treatment assistance module integrates an abnormal recognition model, which can intelligently identify treatment deviation situations and assist in decision-making; the animation module automatically generates an animation of the orthodontic process and accurately locates it to the current step, facilitating a quick assessment of the progress; the intelligent appointment module supports a dual-mode scheduling driven by key nodes or date backtracking, simplifying the operation; the distribution module realizes the rapid location and distribution of orthodontic appliances based on hierarchical coding and hash indexing. The modules are interconnected through standard interfaces, constructing a closed-loop intelligent diagnosis and treatment system throughout the initial diagnosis, review, treatment, and end, significantly improving the treatment efficiency and management level, and having good clinical practicability and promotion value. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings. Among them: Figure 1 is the system modular diagram of the present invention; Figure 2 is the method flow chart of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0071] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions of the embodiments of the present invention in conjunction with the drawings of the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Based on the described embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art belong to the scope of protection of the present invention.

[0072] As Figure 1 shown, it is an embodiment of the present invention. This embodiment provides an invisible orthodontic diagnosis and treatment assistance system for oral malocclusion, including:

[0073] (1) Case basic information module

[0074] It is used to connect to the hospital system, collect the basic information, medical records, and oral imaging data of patients, and establish a preliminary diagnosis file to form patient file information;

[0075] In a specific embodiment of the present invention, the basic case information module includes:

[0076] A follow-up visit information retrieval unit, which is used to automatically retrieve the historical medical records and the medical visit information of other departments when the patient has a follow-up visit, and summarize them to form a multi-source diagnosis and treatment file;

[0077] In this embodiment, when the patient has a follow-up visit, the historical medical record information recorded in the system can be automatically called, including the previous follow-up visit records, doctor's diagnosis and operation records, and the implementation of the treatment plan of the patient in the orthodontics department, etc. At the same time, it supports calling the medical visit records of the patient in other relevant departments (such as periodontics, implantology, prosthetics, etc.). The system unifies the formats of all data and sorts them according to the time axis, and summarizes and generates a structured multi-source diagnosis and treatment file for doctors' reference.

[0078] A treatment stage management unit, which is used to generate structured follow-up visit reminder information based on the historical file and the current treatment stage, including recommended examination items, key clinical concerns, and pending operation suggestions.

[0079] In this embodiment, based on the orthodontic stage progress (such as the number of the current orthodontic appliance worn and the corresponding steps) and the previous treatment situation recognized in the current system, structured follow-up visit reminder information is automatically generated, specifically including but not limited to: recommended examination items (such as panoramic oral radiograph, lateral cephalogram), tooth positions or dentition relationships that should be focused on monitoring at the current stage, expected treatment goals, and pending key clinical operation suggestions (such as whether to perform attachment bonding, interproximal reduction, re-radiograph evaluation, etc.), which are used to assist doctors in making quick and accurate follow-up visit decisions.

[0080] (2) Image information module

[0081] It is used to integrate the oral imaging data and perform automatic analysis to generate image analysis data, including performing multi-period image comparison on the lateral cephalogram to generate cephalometric change curves and overlap maps;

[0082] In a specific embodiment, the image information module includes:

[0083] An image data acquisition unit, which is used to connect to the hospital PACS system to obtain and standardize the oral imaging data of patients, including X-ray films, CT images, and intraoral scan images, for doctors to view and analyze;

[0084] The image classification unit is used to classify the image data according to the image type and shooting time, and provide an image selection interface. Doctors select data according to the image type or shooting time for longitudinal or transverse comparison to observe the changes in the disease or understand the image data of different time nodes;

[0085] The cephalometric analysis unit, if the doctor selects the lateral head radiograph, automatically calls the cephalometric function in the clinical diagnosis and treatment auxiliary module, calculates and displays the cephalometric values at different time points, automatically marks the change data that exceeds the normal range, and generates a change curve and overlapping graph;

[0086] The CT image analysis unit, if the doctor selects a CT film, will automatically capture and display the curved surface slice, the cross section of the relationship between the tooth root and the alveolar bone, the joint cross section, etc., generate an analysis report, and provide key information to assist the doctor in treatment evaluation.

[0087] In this embodiment, through the collaborative work of the above units, the image information module can realize the standardized collection, structured classification and multi-time period comparative analysis of different types of oral image data of patients. Compared with the existing image management method that relies on manual operation, this module has the following improvements:

[0088] First, by integrating with the hospital's PACS system, the image data acquisition unit can automatically extract and standardize multi-source image data including X-rays, CT images, and intraoral scans without the need for manual uploading or naming, thereby improving data consistency and call efficiency.

[0089] Secondly, the image classification unit automatically classifies and generates image indexes according to the image type and shooting timeline. Doctors can quickly realize longitudinal comparison at different time nodes, or horizontal comparison of different types of images at the same time in the image selection interface, which significantly improves the efficiency of image retrieval.

[0090] In terms of cephalometric analysis, the system supports automatic identification of key bony landmarks, performs multi-index measurement, outputs change curves and overlap graphs, and automatically marks values that deviate from the normal range. Compared with traditional manual measurement and image overlay methods, the operating efficiency and accuracy are significantly improved.

[0091] For CT images, the system can automatically extract key sections such as tooth roots, alveolar bones, and joints and generate graphic analysis reports, providing structured decision support for subsequent plan evaluation, bone mass judgment, and complex case handling, solving the inefficient problem of doctors having to manually take screenshots and make judgments in existing technologies.

[0092] In addition, this module can synchronously transmit the analysis results to the diagnosis and treatment assistance module and the 3D animation module, realizing the automated data flow from image acquisition-diagnosis and treatment decision-animation display, breaking through the pain points of the existing system separation, and forming an image-driven intelligent diagnosis and treatment closed loop.

[0093] (3)Clinical diagnosis and treatment assistance module

[0094] It is used to integrate the patient file information and the image analysis data, automatically generate treatment suggestions, and call the data in the system during follow-up visits to update the content displayed on the doctor's interface in real time. An abnormal progress recognition model for identifying the state where the treatment effect deviates from the expected target is integrated therein;

[0095] The clinical diagnosis and treatment assistance module includes:

[0096] The expert opinion library unit is used to summarize and classify the classic design ideas reached by orthodontic experts, and provide treatment reference suggestions according to the malocclusion type and clinical manifestations;

[0097] The case information management unit is used to collect the patient's basic information, medical record materials and image data during the initial diagnosis, and retrieve the historical diagnosis and treatment information to form a patient file during follow-up visits;

[0098] The automatic image analysis unit is used to process the patient's image data, call the cephalometric function for multi-phase comparison, abnormal marking, generation of change curves and overlay map analysis;

[0099] The personalized treatment plan design unit is used to automatically generate a preliminary treatment plan by combining the analysis results and expert opinions, and support the adjustment and optimization of the plan;

[0100] The follow-up visit information integration and display unit is used to uniformly display the multi-source data of case information, analysis results and treatment plans;

[0101] The treatment progress monitoring unit is used to conduct phased monitoring of the wearing status of the appliance and the treatment effect, and output the progress evaluation results;

[0102] The key and difficult operation guidance unit is used to provide a standardized process guide for the operation steps and assist the operation execution in combination with video demonstrations;

[0103] The retainer review reminder unit is used to push reminders for retainer wearing management and periodic reviews after the treatment ends.

[0104] Specifically, the treatment progress monitoring unit includes a treatment progress abnormal recognition model. The construction process of the treatment progress abnormal recognition model includes:

[0105] The stage error calculation unit is used to calculate the average position error of this stage based on the actual three-dimensional coordinates of the tooth sites of the patient in the current orthodontic stage and the planned three-dimensional coordinates generated by the system for comparison. The calculation formula is:

[0106] ​​;

[0107] Wherein: is the total number of tooth sites monitored in the current stage, is the tooth site number;

[0108] The pass rate evaluation unit is used to calculate the pass rate under the set error tolerance The calculation formula is: ;

[0109] ;

[0110] The label deviation detection unit is used to calculate the stage label deviation loss The calculation formula is:

[0111] ;

[0112] Wherein: represents the current orthodontic stage status identifier, is the label vector generated by the system according to the patient's historical data, is the label value manually input by the doctor in the current stage. The three are used as inputs to calculate the cross-entropy loss function to measure the consistency of label recognition;

[0113] The abnormal determination unit is used to output an abnormal marking signal when any of the following conditions is met:

[0114] ;

[0115] Wherein: , , are the threshold parameters set by the system.

[0116] In this example, the image information module obtains the latest orthodontic stage image data of the current return visit patient and registers it with the treatment plan stored in the system. The system extracts the three-dimensional coordinate data of the actual tooth sites and compares them with the expected coordinates according to the current step number to complete the calculation of the basic position error.

[0117] Subsequently, the system statistically analyzes the overall compliance of the tooth sites according to the set deviation tolerance and makes a warning judgment based on whether the pass rate is lower than the lower threshold. At the same time, if the doctor makes a manual annotation of the treatment progress on the interface (such as judging that the teeth do not move as expected or the attachments are lost), the system will compare this label information with the historical prediction label and the system's automatic status recognition result to analyze the degree of cognitive deviation.

[0118] If any of the above detection dimensions exceeds the system threshold setting, an abnormal recognition event will be triggered. The system will automatically pop up a prompt panel to inform the doctor of possible treatment problems at the current stage (such as excessive tooth position deviation, lag in movement progress, deviation in treatment plan execution, etc.), and recommend subsequent operation suggestions (such as extending the wearing period of the current step, redesigning the animation path for the next stage, considering periodic radiographic reexamination, etc.).

[0119] Compared with the existing monitoring methods that rely on manual experience judgment or static radiographic evaluation, this model has the following outstanding improvements:

[0120] Improved real-time performance: The system completes data retrieval and error judgment while the doctor calls the patient for a follow-up visit, reducing waiting and operation time;

[0121] Multi-dimensional joint determination: Introduce three joint criteria of displacement error, compliance rate, and label consistency to improve the recognition accuracy and avoid misjudgment caused by fluctuations in single indicators;

[0122] Intelligent prompt and operation association: The output result of the model can directly drive clinical operation prompts and treatment path adjustment, forming a complete "recognition - feedback - adjustment" closed loop;

[0123] Highly adaptable structure: The model parameters can be customized and adjusted according to case characteristics, adapting to different malocclusion types and doctors' treatment styles, with good generality.

[0124] The introduction of the above abnormal recognition model enables this system to break through the traditional passive follow-up visit mode that relies on manual intervention, constructs a dynamic, quantitative, and traceable treatment monitoring mechanism, significantly enhances the doctor's perception and control capabilities of treatment risks, and has significant clinical value in ensuring treatment effects and improving operation efficiency.

[0125] (4)3D Animation Scheme Module

[0126] Used to construct an animation of the orthodontic treatment plan according to the treatment recommendation, play it automatically, and pause and display at the current orthodontic treatment step after the playback is completed;

[0127] The 3D animation scheme module includes:

[0128] A data interface unit for data interaction with workstations of different invisible orthodontic brands through a standardized interface, automatically obtaining orthodontic treatment data from the workstation, parsing and storing orthodontic animation information;

[0129] An animation generation unit for generating an orthodontic treatment plan animation for the patient according to the orthodontic treatment data, displaying each animation step, and positioning to the current orthodontic treatment step and pausing for display after the playback is completed;

[0130] An animation optimization unit for compressing and formatting the generated orthodontic animation data, adjusting the size of the animation data to adapt to the terminal playback resources, and unifying the animation frame rate and rendering configuration;

[0131] A playback control unit for controlling the playback state of the orthodontic animation, supporting automatic playback and pause control, and providing interfaces for adjusting the playback speed and number of steps to meet the doctor's control requirements for the playback rhythm;

[0132] A compatibility unit for supporting the animation data formats and encoding methods of multiple orthodontic brands to ensure that the module can be uniformly called in different brand environments;

[0133] A display customization unit for providing a personalized display item configuration interface, allowing doctors to adjust the playback parameters and progress display methods according to treatment needs to achieve customized review of orthodontic treatment plans and treatment evaluation.

[0134] In practical applications, the 3D animation solution module receives treatment suggestions output by the clinical diagnosis and treatment assistance module through a standard data interface, and combines the data of the patient's corresponding orthodontic brand workstation to automatically analyze the tooth movement paths and animation frame structures at each stage.

[0135] The system can call the required animation solution according to the doctor's current follow-up operation and locate to the corresponding orthodontic step as needed; at the same time, during the playback process, the buffer preloading mechanism is used to reduce the risk of playback stuttering, and based on preset rules, it pauses at the specified step after the animation playback is completed, facilitating the doctor to quickly review and evaluate the current treatment stage.

[0136] Different from the existing technology where animation playback only supports linear browsing and the playback process is disconnected from clinical data, the module of the present invention can achieve a one-to-one mapping between orthodontic step data and animation frame positions, support doctors to accurately visit a certain key treatment point, and significantly improve the clinical guidance value of the animation.

[0137] In addition, the module has the ability of unified coding and parsing, which can uniformly convert the proprietary formats adopted by multiple invisible orthodontic brands into a controllable playback structure, solve the cumbersome problem that doctors need to switch between multiple brand clients to view animations in the current market, and improve the operation fluency and system integration.

[0138] (5) Intelligent appointment module

[0139] For receiving the current orthodontic step, supporting two appointment modes: generating a review date based on key operation steps, or inversely inferring the number of orthodontic appliance steps to be worn based on the expected review date;

[0140] The intelligent appointment module includes:

[0141] A review date generation unit, configured to receive the wearing period and expected steps of each orthodontic appliance input by a doctor, and automatically generate corresponding review dates based on the parameters when there are key operation steps;

[0142] A step count calculation unit, configured to receive the wearing period of each orthodontic appliance and the expected review date input by a doctor, and calculate the steps that should be taken for the orthodontic appliance in the scenario where there are no key operation steps;

[0143] A review record unit, configured to record the appointment time of each review and the actual step information worn by the patient, for the clinical diagnosis and treatment assistance module to call for animation synchronization and treatment data management.

[0144] In the specific implementation process, this module forms a data closed-loop with the clinical diagnosis and treatment assistance module, the 3D animation scheme module, the orthodontic appliance distribution module, etc.:

[0145] The current step data is transmitted from the animation module;

[0146] The key operation prompt is output by the treatment advice generation logic;

[0147] The step count calculation and review time results are transmitted back to the orthodontic appliance distribution module in the reverse direction for controlling the distributed steps;

[0148] Meanwhile, it outputs the comparison information between the patient's review plan and the current treatment status to the doctor interface.

[0149] Different from the prior art where the appointment process mostly relies on manual entry and linear judgment by doctors, the present invention realizes an automated and highly flexible appointment scheduling mechanism by structuring the treatment plan data and introducing a key node recognition and time-step mapping algorithm.

[0150] This module significantly reduces the calculation and judgment burden on doctors, improves the accuracy of review arrangement and the system integration degree, and is particularly suitable for scenarios with a long invisible orthodontic treatment cycle, dense nodes, and a high degree of treatment personalization.

[0151] (6) Orthodontic appliance distribution module

[0152] It is configured to identify, store, and locate orthodontic appliances through a hierarchical coding rule, receive the distribution instruction of the intelligent appointment module, and quickly retrieve the storage location of the orthodontic appliances through a database indexing algorithm to complete the precise distribution of orthodontic appliances.

[0153] The orthodontic appliance distribution module includes:

[0154] An identification coding unit, configured to generate a unique hierarchical code according to the brand, series, malocclusion type, and identification information of the patient's invisible orthodontic appliance. This code includes three sections: a brand code, a series serial number, and a patient identification number, and is bound and stored with the information of the first storage location of the orthodontic appliance;

[0155] A reservation instruction receiving unit, which is used to receive the distribution request sent by the intelligent reservation module, and extract the patient identification information and the required reservation steps;

[0156] An identity matching unit, which is used to receive the identification data transmitted by the case basic information module when the patient returns for a follow-up visit, and perform matching verification with the reservation information.

[0157] A coding retrieval unit, which is used to establish a mapping relationship between the coding and the storage location information based on the hierarchical coding and the hash index algorithm. When receiving the distribution request, it locates the required orthodontic appliance through the combination of the patient identification number and the number of steps and returns its storage location information;

[0158] A distribution execution unit, which is used to guide the doctor to complete the physical distribution operation of the orthodontic appliance according to the storage location information;

[0159] Among them, the hash index algorithm establishes an index table with the complete coding as the primary key, adopts a conflict resolution strategy and supports an index reconstruction mechanism to ensure retrieval efficiency and consistency maintenance.

[0160] During the application process of the system, this module forms a real-time linkage with the case basic information module, the intelligent reservation module and the database management system. Its advantages include:

[0161] Reducing the doctor's memory burden and manual search time: Automatic coding and position binding replace paper numbering and experience-based search, improving efficiency;

[0162] Preventing misdistribution and omission: Through the dual verification mechanism of reservation verification and identity matching, improving security;

[0163] Improving the overall clinic management level: Having three functions of coding standardization, storage management and resume tracking, and supporting unified management of multiple clinics / multiple brands of orthodontic appliances.

[0164] Compared with the majority of the existing hospitals that rely on manual marking and paper distribution, this module realizes the digital, standardized and intelligent improvement of the distribution process, significantly improves the follow-up visit fluency and patient experience, and also reserves a data interface and scalability foundation for future automatic orthodontic appliance distribution equipment.

[0165] As Figure 2 shown, this is another embodiment of the present invention. This embodiment provides an auxiliary method for the diagnosis and treatment of oral malocclusion with invisible orthodontics, which applies the oral malocclusion with invisible orthodontics auxiliary system as described above, and includes the following steps:

[0166] S1: Collect the basic information, medical record materials and oral imaging data of the patient, establish a primary diagnosis file, and form patient file information;

[0167] S2: Process the oral imaging data to generate imaging analysis data. The processing includes performing multi - period image comparison on the lateral cephalogram to generate cephalometric change curves and overlapping diagrams;

[0168] S3: Input the patient file information and the imaging analysis data into the clinical diagnosis and treatment assistance module to generate personalized treatment suggestions, and run an abnormal progress recognition model based on the data to determine whether the current treatment status deviates from the preset target status;

[0169] S4: Generate a corresponding 3D orthodontic treatment plan animation according to the treatment suggestions, play the animation, and automatically locate to the current orthodontic treatment step and pause the display after the play is completed;

[0170] S5: Input the current orthodontic treatment step into the intelligent appointment module. If there are key operation steps, generate corresponding review dates according to the wearing cycle of each orthodontic appliance and the target steps input by the doctor; if there are no key operation steps, reverse - deduce the required orthodontic appliance steps according to the wearing cycle and the expected review date input by the doctor;

[0171] S6: Combine the patient identifier with the calculated orthodontic appliance steps to generate a hierarchical code, use it as a search key to locate the storage location of the corresponding orthodontic appliance through the database indexing algorithm, and guide the completion of the orthodontic appliance distribution operation.

[0172] In summary, the oral malocclusion invisible orthodontic diagnosis and treatment assistance system and method provided by the present invention construct a structurally complete, process - closed - loop, and highly efficient digital diagnosis and treatment platform through systematic integration and intelligent processing of various links such as case information, oral imaging, treatment suggestions, orthodontic animation, appointment arrangement, and orthodontic appliance distribution. Data intercommunication is realized between modules through standardized interfaces, which not only improves the doctor's diagnosis and treatment efficiency and decision - making accuracy, but also improves the patient's treatment experience and compliance. Compared with the existing scattered invisible orthodontic treatment plans that rely on manual judgment, the present invention has the advantages of high information integration, strong monitoring ability, convenient operation, and wide adaptability. It is applicable to multi - brand and multi - type oral orthodontic clinical scenarios, has good practical value and promotion prospects, and provides practical technical support for promoting the development of digital orthodontics and intelligent medical services.

[0173] In the description of this specification, the descriptions referring to terms such as "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. Moreover, the specific features, structures, materials, or characteristics described may be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0174] Any process or method description shown in a flowchart or described in other ways herein can be understood as representing a module, segment, or part of code including one or more executable instructions for implementing a specific logical function or process. And the scope of the preferred embodiments of the present application includes additional implementations, where the functions may be executed in a substantially simultaneous manner or in a reverse order according to the functions involved, without being in the order shown or discussed.

[0175] As described above, this is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed in the present application can easily think of various changes or substitutions, and these should all be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. An invisible orthodontic diagnosis and treatment assistance system for oral malocclusion, characterized in that, Including: A basic case information module, which is used to connect to the hospital system after obtaining the patient's authorization, collect the patient's basic information, medical records, and oral imaging data, establish a preliminary diagnosis file, and form patient file information; An image information module, which is used to integrate the oral imaging data and automatically analyze it to generate imaging analysis data. The imaging analysis data includes performing multi-period image comparison on the lateral cephalogram to generate a cephalometric change curve and an overlap map; A clinical diagnosis and treatment assistance module, which is used to integrate the patient file information and the imaging analysis data, automatically generate treatment suggestions, and call the data in the system during a follow-up visit to update the content displayed on the doctor's interface in real time. Among them, an abnormal progress recognition model for identifying the state where the treatment effect deviates from the expected target is also integrated; A 3D animation plan module, which is used to construct an orthodontic treatment plan animation according to the treatment suggestions and play it automatically; after the playback is completed, it locates to the current orthodontic treatment step and pauses the display; An intelligent appointment module, which is used to receive the current orthodontic treatment step and support two appointment modes: generating a review date based on key operation steps, or inferring the number of orthodontic appliance steps to be worn based on the expected review date; An orthodontic appliance distribution module, which is used to identify, store, and locate orthodontic appliances according to a hierarchical coding rule, and receive the distribution instruction from the intelligent appointment module to quickly retrieve the storage location of orthodontic appliances through a database indexing algorithm.

2. The auxiliary system for invisible orthodontic diagnosis and treatment of oral malocclusion according to claim 1, characterized in that The basic case information module includes: A follow-up visit information retrieval unit, which is used to automatically retrieve the patient's historical medical records and the medical treatment information of other departments during the patient's follow-up visit, and summarize them to form a multi-source medical treatment file; A treatment stage management unit, which is used to generate structured follow-up visit reminder information based on the multi-source medical treatment file and the current treatment stage. The structured follow-up visit reminder information includes recommended examination items, key clinical concerns, and pending operation suggestions.

3. The auxiliary system for the diagnosis and treatment of oral malocclusion by invisible orthodontics according to claim 1, characterized in that, The image information module includes: An image data acquisition unit, which is used to connect to the hospital PACS system to obtain and standardize the patient's oral imaging data. The oral imaging data includes X-ray films, CT images, and intraoral scan images; An image classification unit, which is used to classify the oral imaging data according to the image type and shooting time, and provide an image selection interface. The doctor selects the data according to the image type or shooting time for vertical or horizontal comparison to observe the disease condition changes or understand the imaging data at different time nodes; A cephalometric analysis unit, when the image selection interface monitors that the selected image is a lateral cephalogram, automatically calls the cephalometric function in the clinical diagnosis and treatment assistance module, calculates and displays the cephalometric values at different time points, automatically marks the changed data beyond the normal range, and generates a change curve and an image overlap comparison map based on the cephalometric values; A CT image analysis unit, when the image selection interface monitors that the selected image is a CT film, automatically intercepts and displays the panoramic tomogram, the cross-section of the relationship between the tooth root and the alveolar bone, and the joint cross-section, automatically summarizes the image analysis results, and generates an analysis report containing key measurement data and image comparison information.

4. An orthodontic malocclusion invisible orthodontic diagnosis and treatment assistance system according to claim 1, characterized in that, The clinical diagnosis and treatment assistance module includes: Expert opinion library unit, which is used to summarize and classify the classic design ideas reached by orthodontic experts, and provide treatment reference suggestions based on the type of malocclusion and clinical manifestations; Case information management unit, used to collect basic patient information, medical records and oral imaging data during the initial visit, and retrieve historical diagnosis and treatment information to form patient files during follow-up visits; Automatic image analysis unit, used to process the patient's oral image data, call the cephalometric function to perform multi-period comparison, abnormality marking, change curve generation and overlap map analysis; Personalized treatment plan design unit, which is used to combine analysis results with expert opinions to generate preliminary treatment plans and support plan adjustment and optimization; The integrated display unit for follow-up information is used to display case information, analysis results and treatment plan data in a linked manner on the same interface; Treatment progress monitoring unit, used to monitor the appliance wearing status and treatment effect in stages and output progress evaluation results; The key and difficult operation guidance unit is used to provide standardized process guidance for operation steps, combined with video demonstrations to assist in operation execution; The retainer review reminder unit is used to push retainer wearing management and periodic review reminders after the treatment is completed.

5. An orthodontic malocclusion invisible orthodontic diagnosis and treatment assistance system according to claim 4, characterized in that, The treatment progress monitoring unit includes a treatment progress abnormality identification model, and the treatment progress abnormality identification model construction process includes: A stage error calculation unit for calculating, based on the actual three-dimensional coordinates of the tooth positions of a patient in the current orthodontic stage and the planned three-dimensional coordinates generated by the system for comparison to calculate the average position error of this stage , and the calculation formula is: , the calculation formula is: ； Wherein: is the total number of tooth sites monitored in the current stage, is the tooth site number; Compliance rate evaluation unit, used to calculate the compliance rate under the set error tolerance , and the calculation formula is: ； Label deviation detection unit, used to calculate the stage label deviation loss , and the calculation formula is: ； Wherein: represents the status identifier of the current orthodontic stage, is the label vector generated by the system based on the patient's historical data, is the label value manually input by the doctor at the current stage; The abnormality determination unit is used to output an abnormality flag signal when any of the following conditions is met: ； Wherein: , , are threshold parameters set by the system.

6. The auxiliary system for the diagnosis and treatment of oral malocclusion by invisible orthodontics according to claim 1, characterized in that, The 3D animation solution module includes: The data interface unit is used to exchange data with workstations of different invisible correction brands through a standardized interface, automatically obtain the correction data of the workstation, and analyze and store the correction animation information; An animation generation unit, used to generate a correction plan animation for the patient according to the correction data, display each animation step, and locate the current correction step after the playback is completed, and pause the display; Animation optimization unit, used to compress and format the generated correction animation data, adjust the size of the animation data to adapt to the terminal playback resources, and unify the animation frame rate and rendering configuration; The playback control unit is used to control the playback status of the correction animation and provide an interface for adjusting the playback speed and number of steps; Compatibility unit, used to support animation data formats and encoding methods of multiple correction brands; The display customization unit is used to provide a personalized display item configuration interface.

7. An auxiliary system for the diagnosis and treatment of oral malocclusion by invisible orthodontics according to claim 6, characterized in that, The intelligent reservation module includes: A review date generation unit is used to receive the patient's input of each pair of braces wearing period and expected number of steps, and automatically generate a corresponding review date when there are key operation steps; A step calculation unit, which is used to receive the wearing period of each pair of braces and the expected review date input by the doctor, and calculate the number of steps of the braces to be worn in the scenario where there are no key operation steps; The review recording unit is used to record the appointment time of each review and the actual number of steps the patient has taken.

8. An orthodontic malocclusion invisible orthodontic diagnosis and treatment assistance system according to claim 7, characterized in that, The appliance dispensing module comprises: An identification coding unit is used to generate a unique hierarchical code according to the brand, series, malocclusion type and identification information of the patient's invisible braces. The hierarchical code includes a three-segment structure of brand code, series serial number and patient identification number, and is bound and stored with the storage location information where the braces are first stored; A reservation instruction receiving unit, configured to receive the issuance request sent by the intelligent reservation module, and extract the patient identification information and the required reservation steps; An identity matching unit, configured to receive the identification data transmitted by the case basic information module during the patient's follow-up visit, and perform matching verification with the reservation information.

9. An orthodontic malocclusion invisible orthodontic diagnosis and treatment assistance system according to claim 8, characterized in that, The appliance issuance module further includes: A coding retrieval unit, configured to establish a mapping relationship between the coding and the storage location information based on the hierarchical coding and the hash index algorithm. When receiving the issuance request, locate the required appliance according to the combination of the patient identification number and the steps, and return its storage location information; An issuance execution unit, configured to guide the doctor to complete the physical issuance operation of the appliance according to the storage location information.

10. A method for assisting in the diagnosis and treatment of oral malocclusion with invisible orthodontics, applied to the oral malocclusion invisible orthodontics diagnosis and treatment assistance system according to any one of claims 1-9, characterized in that, The method includes the following steps: S1: Collect the basic information, medical record data, and oral imaging data of the patient, establish a first visit file, and form patient file information; S2: Process the oral imaging data to generate image analysis data. The processing includes performing multi-period image comparison on the lateral cephalogram to generate a cephalometric change curve and an overlap map; S3: Input the patient file information and the image analysis data into the clinical diagnosis and treatment assistance module to generate personalized treatment suggestions, and run an abnormal progress recognition model based on the data to determine whether the current treatment status deviates from the preset target status; S4: Generate a corresponding 3D orthodontic treatment plan animation according to the treatment suggestions, play the animation, and automatically locate to the current orthodontic step and pause the display after the playback is completed; S5: Input the current orthodontic step into the intelligent reservation module. If there are key operation steps, generate the corresponding review date according to the wearing period of each appliance and the target steps input by the doctor; if there are no key operation steps, reverse-deduce the required appliance steps according to the wearing period and the expected review date input by the doctor; S6: Combine the patient identification with the calculated appliance steps to generate a hierarchical coding, use it as a retrieval key to locate the storage location of the corresponding appliance through the database indexing algorithm, and guide the completion of the appliance issuance operation.

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