Oral diagnosis system based on analog data support

Abstract

The invention relates to the field of oral diagnosis, in particular to an oral diagnosis system based on simulation data support, which comprises a simulation generation module, an analysis module, a diagnosis evaluation module and a diagnosis feedback module. By constructing the personalized tooth simulation model of the patient, the oral cavity function abnormity area can be accurately recognized, treatment simulation is performed in a targeted mode, compared with a traditional diagnosis method, the problems of tooth dislocation and function abnormity can be more accurately positioned, a more accurate diagnosis basis is provided for doctors, and the diagnosis efficiency is improved. By calculating the treatment gap correction rate and the treatment gradient correction rate, the accuracy of the treatment scheme can be dynamically judged, when the treatment scheme is invalid, abnormal conditions can be quickly recognized, correction suggestions can be provided, when the treatment scheme is effective, optimal treatment parameters can be further found, continuous optimization of the treatment scheme is achieved, and the treatment effect is improved. Diagnosis and treatment reference is provided for doctors, and the accuracy, the intelligent level and the diagnosis and treatment efficiency of oral diagnosis are improved.

Description

Technical Field

[0001] The present invention relates to the field of oral cavity diagnosis, and in particular to an oral cavity diagnosis system based on simulation data support. Background Art

[0002] With the rapid development of medical technology, oral diagnosis and treatment have become an important branch of modern medicine. Traditional oral diagnosis methods have many limitations, mainly manifested in insufficient diagnostic accuracy, lack of personalized evaluation of treatment plans, and lack of effective data simulation and verification mechanisms.

[0003] Traditional oral diagnosis mainly relies on the doctor's experience and visual observation, which is subject to significant subjectivity and uncertainty. It is difficult for doctors to accurately quantify subtle changes between teeth, and there is often a lack of comprehensive evaluation methods for complex oral deformities and functional abnormalities.

[0004] The patent document with publication number CN118866386A discloses an auxiliary diagnosis system for oral orthodontic diseases based on deep learning, including: an image processing module, used to detect image quality reference coefficients and perform image segmentation; a data processing module, used to determine a preliminary file set and determine the characteristic state of each preliminary file set; a data screening module, used to determine the corresponding processing method of each preliminary file set according to the characteristic state of each preliminary file set; a first analysis module, used to determine the matching method between the target patient information and the initial file set according to the target patient category; a second analysis module, used to determine the matching method between the target patient information and the initial file set according to the abnormal dental state of the target patient; a report recommendation module, used to generate a recommendation report from the matching historical file and send it to the client; a data storage module, used to store patient files.

[0005] This shows the following problem: In the prior art, it is impossible to judge and evaluate the treatment plan diagnosed by the doctor, resulting in deviations in the treatment effect of the patient. Summary of the invention

[0006] To this end, the present invention provides an oral diagnosis system based on simulation data support, which is used to dynamically evaluate the treatment plan according to the simulation data analysis of the treatment process to overcome the problem in the prior art that the treatment plan diagnosed by the doctor cannot be judged and evaluated, resulting in deviations in the patient's treatment effect.

[0007] To achieve the above object, the present invention provides an oral diagnosis system based on simulation data support, comprising:

[0008] A simulation generation module, used to simulate the patient's oral cavity based on the patient's oral dental image and point cloud data to obtain a dental simulation model;

[0009] an analysis module connected to the simulation generation module, for determining a functional abnormality area according to the tooth simulation model;

[0010] a diagnostic evaluation module connected to the analysis module, configured to perform a treatment simulation on the functionally abnormal region based on the received initial treatment method, and determine the accuracy of the initial treatment method according to the abnormal data changes of the functionally abnormal region during the treatment simulation;

[0011] A diagnostic feedback module is connected to the simulation production module and the diagnostic evaluation module to provide different diagnostic feedbacks according to the determination result of the effectiveness of the initial treatment method, wherein:

[0012] When it is determined that the initial treatment is ineffective, determining the abnormal situation and providing feedback, and receiving the revised treatment to perform a re-treatment simulation on the tooth simulation model;

[0013] When it is determined that the initial treatment method is effective, the optimal data reached by the abnormal data during the correction process is determined, and whether diagnostic optimization is required is determined based on the size of the optimal data and the treatment time to reach the optimal data.

[0014] Furthermore, the analysis module includes:

[0015] A tooth analysis unit, used to determine the actual gaps between the teeth and the actual inclinations between the teeth in the tooth simulation model;

[0016] An abnormality determination unit is connected to the tooth analysis unit and is used to determine whether the teeth are misaligned according to the actual gap and the actual inclination, and to determine the area where the misaligned teeth are located as a functional abnormality area.

[0017] Furthermore, the abnormality determination unit includes:

[0018] a misalignment inspection subunit, used for comparing the actual gap and the actual inclination with the corresponding standard gap and standard inclination to obtain a comparison result;

[0019] a misalignment determination subunit connected to the misalignment detection subunit, for determining whether the teeth are misaligned based on the comparison result, wherein the teeth are misaligned when the comparison result satisfies any one of the actual gap between the two teeth being larger than the standard gap or the actual inclination between the two teeth being larger than the standard inclination;

[0020] The area determination subunit is connected to the misalignment determination subunit and is used to determine the area of ​​the tooth simulation model where the misaligned tooth is located as the functional abnormality area.

[0021] Furthermore, the diagnostic assessment module includes:

[0022] A diagnosis receiving unit for obtaining the received initial treatment for the patient;

[0023] a treatment simulation unit connected to the diagnosis receiving unit and used to perform treatment simulation of the dysfunctional area according to the initial treatment method;

[0024] a treatment analysis unit connected to the treatment simulation unit, for acquiring a treatment gap and a treatment inclination after a certain treatment cycle in the treatment simulation based on a preset acquisition frequency, and calculating a treatment gap correction rate and a treatment inclination correction rate according to the treatment gap, the treatment inclination and the corresponding actual gap and actual inclination;

[0025] A treatment determination unit is connected to the treatment analysis unit and is used to determine the accuracy of the initial treatment method according to the treatment gap correction rate and the treatment inclination correction rate.

[0026] Furthermore, the treatment determination unit comprises:

[0027] The first determination subunit is used to determine whether the treatment gap correction rate and the treatment inclination correction rate are both positive values. If either the treatment gap correction rate or the treatment inclination correction rate is not a positive value, it is determined that the initial treatment method is inaccurate.

[0028] Furthermore, the treatment determination unit includes a second determination subunit connected to the first determination subunit, which is used to calculate the treatment change index of the treatment gap correction rate and the treatment inclination correction rate between each acquisition cycle when the treatment gap correction rate and the treatment inclination correction rate are both positive values; if the treatment change index is greater than the index change threshold, it is determined that the initial treatment method is inaccurate.

[0029] Furthermore, the diagnostic feedback module includes:

[0030] a treatment receiving unit, used to receive the accuracy of the initial treatment method determined by the treatment determining unit;

[0031] A first processing unit connected to the treatment receiving unit is used to determine that the initial treatment method determined by the first determination subunit is inaccurate or the initial treatment method determined by the second determination subunit is inaccurate when the initial treatment method is determined to be invalid;

[0032] a second processing unit connected to the feedback receiving unit, for determining optimal data based on the treatment change index of the treatment gap correction rate and the treatment inclination correction rate when determining that the initial treatment method is effective, including an optimal gap correction rate and an optimal inclination correction rate;

[0033] A treatment verification unit is connected to the second processing unit and is used to obtain the treatment time to achieve the best data, and determine whether diagnosis optimization is needed based on the best data and the treatment time.

[0034] Furthermore, the second processing unit includes:

[0035] An index comparison subunit, used to compare the treatment change index with the minimum change index to obtain a comparison result;

[0036] The data determination subunit is connected to the index comparison subunit and is used to determine that the treatment gap correction rate and treatment inclination correction rate at this time are the corresponding optimal gap correction rate and optimal inclination correction rate when the comparison result during the treatment process is that the treatment change index is less than the minimum change index.

[0037] Further, the treatment verification unit comprises:

[0038] A data verification subunit, used to compare the optimal data with preset standard data to obtain a data comparison result;

[0039] A time verification subunit, used to compare the treatment time with a preset treatment time threshold to obtain a time comparison result;

[0040] The diagnosis determination subunit is connected to the data verification subunit and the time verification subunit respectively, and is used to determine whether diagnosis optimization is needed according to the data comparison result and the time comparison result.

[0041] Furthermore, the simulation production module includes:

[0042] An image acquisition unit, used to acquire a patient's dental image;

[0043] An image enhancement unit, connected to the image acquisition unit, for preprocessing the tooth image to obtain an optimized tooth image;

[0044] The simulation unit is connected to the image enhancement unit and is used to scan the patient's oral cavity to obtain point cloud data, and perform tooth simulation based on the optimized tooth image and the point cloud data to obtain a tooth simulation model.

[0045] Compared with the prior art, the beneficial effect of the present invention lies in that, by constructing a personalized tooth simulation model for the patient, the system can accurately identify areas of oral dysfunction and perform targeted treatment simulation. Compared with traditional diagnostic methods, the system can more accurately locate tooth misalignment and dysfunction problems, providing doctors with more accurate diagnostic basis. By calculating the treatment gap correction rate and the treatment inclination correction rate, the accuracy of the treatment plan can be dynamically judged. When the treatment plan is ineffective, the system can quickly identify abnormal conditions and provide correction suggestions. When the treatment plan is effective, it can further find the optimal treatment parameters to achieve continuous optimization of the treatment plan, provide doctors with diagnosis and treatment reference, and improve the accuracy, intelligence level and diagnosis and treatment efficiency of oral diagnosis.

[0046] Furthermore, by accurately measuring the actual gaps and actual inclinations between teeth in the tooth simulation model, the spatial relationship between teeth can be accurately quantified. By establishing standard gaps and standard inclinations as reference benchmarks, it is helpful to more accurately evaluate the degree of tooth abnormalities and significantly improve the accuracy and objectivity of abnormality identification. The abnormality determination unit can not only identify whether there is misalignment of teeth, but also accurately locate the specific area where the misaligned teeth are located. It can quickly lock in the oral area that needs special attention and treatment, thereby improving the efficiency of diagnosis and treatment.

[0047] Furthermore, by accurately comparing the actual gap between teeth and the actual inclination with the standard value to judge tooth misalignment, it is possible to comprehensively capture subtle abnormalities in tooth arrangement. By accurately locating the specific area where the misaligned teeth are located and marking it as an area of ​​functional abnormality, the accuracy and reliability of diagnosis can be significantly improved.

[0048] Furthermore, by dynamically acquiring the actual gap and actual inclination changes during the treatment simulation process based on a preset acquisition frequency, the system can simulate the actual treatment process, obtain detailed treatment data, and accurately calculate the treatment gap correction rate and treatment inclination correction rate, thereby achieving a comprehensive and objective evaluation of the initial treatment method, and measuring the effectiveness and accuracy of the initial treatment method.

[0049] Furthermore, through real-time monitoring of the treatment gap correction rate and the treatment inclination correction rate, the system can dynamically evaluate the effectiveness of the treatment plan. This dynamic optimization mechanism can help doctors adjust treatment strategies in a timely manner and improve the accuracy and pertinence of oral orthodontic treatment.

[0050] Furthermore, by introducing the treatment change index, the system can dynamically and real-time monitor the correction changes during the treatment process. By comparing the treatment gap correction rate and treatment tilt correction rate of different acquisition cycles, abnormal fluctuations in the treatment process can be discovered in time, and the treatment strategy can be adjusted in time to prevent the treatment from deviating from the expected goal. This is conducive to a more comprehensive and in-depth judgment of the effectiveness of the treatment plan, and significantly improves the accuracy and reliability of the diagnosis.

[0051] Furthermore, by accurately distinguishing the specific reasons for inaccurate initial treatment methods, it can help doctors more accurately locate and solve specific problems in treatment, improve the pertinence and effectiveness of diagnosis, and by analyzing the treatment change index, it can dynamically capture and extract the best data in the treatment process. By comprehensively analyzing the best treatment data and the corresponding treatment time, it can intelligently determine whether further diagnostic optimization is needed, which can effectively enhance the continuous improvement capabilities of oral diagnosis, realize dynamic optimization and iteration of diagnosis and treatment plans, and help improve the personalization level and treatment effects of oral treatment.

[0052] Furthermore, by dynamically tracking the changing index during the treatment process and accurately locating the moment when the treatment effect is best, the system can continuously monitor subtle changes during the treatment process and quickly capture key parameters when the optimal treatment state occurs, significantly improving the accuracy and effectiveness of the treatment plan.

[0053] Furthermore, through comprehensive analysis of data comparison results and time comparison results, it is possible to intelligently determine whether diagnostic optimization is needed, which can effectively improve the accuracy and personalization of oral diagnosis, provide doctors with more intelligent diagnosis and treatment suggestions, and improve diagnosis and treatment efficiency.

[0054] Furthermore, by accurately capturing and intelligently preprocessing the patient's dental images, clearer and more detailed optimized dental images can be obtained, providing a high-quality data foundation for subsequent simulations. Based on the fusion of multi-source data, intelligent dental simulation reconstruction can be performed to accurately restore the actual morphology and structural characteristics of the patient's oral cavity, providing a more reliable simulation basis for subsequent diagnosis. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 This is a system framework diagram of an oral diagnosis system based on simulation data support according to an embodiment of the present invention;

[0056] Figure 2 It is a structural schematic diagram of an analysis module according to an embodiment of the present invention;

[0057] Figure 3 This is a schematic diagram of the structure of a diagnostic evaluation module according to an embodiment of the present invention;

[0058] Figure 4 It is a schematic diagram of the structure of the diagnosis feedback module according to an embodiment of the present invention. DETAILED DESCRIPTION

[0059] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0060] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0061] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0062] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0063] See also Figure 1 ,like Figure 1 As shown, it is a system framework diagram of an oral diagnosis system based on simulation data support according to an embodiment of the present invention;

[0064] Specifically, the oral diagnosis system based on simulation data support provided by the embodiment of the present invention includes:

[0065] A simulation generation module, used to simulate the patient's oral cavity based on the patient's oral dental image and point cloud data to obtain a dental simulation model;

[0066] an analysis module connected to the simulation generation module, for determining a functional abnormality area according to the tooth simulation model;

[0067] a diagnostic evaluation module connected to the analysis module, configured to perform a treatment simulation on the functionally abnormal region based on the received initial treatment method, and determine the accuracy of the initial treatment method according to the abnormal data changes of the functionally abnormal region during the treatment simulation;

[0068] A diagnostic feedback module is connected to the simulation production module and the diagnostic evaluation module to provide different diagnostic feedbacks according to the determination result of the effectiveness of the initial treatment method, wherein:

[0069] When it is determined that the initial treatment is ineffective, determining the abnormal situation and providing feedback, and receiving the revised treatment to perform a re-treatment simulation on the tooth simulation model;

[0070] When it is determined that the initial treatment method is effective, the optimal data reached by the abnormal data during the correction process is determined, and whether diagnostic optimization is required is determined based on the size of the optimal data and the treatment time to reach the optimal data.

[0071] Specifically, the functional abnormality area is an abnormal area composed of abnormal teeth with a large gap between two teeth and a large actual inclination between the two teeth. The initial treatment method is a treatment method determined by the doctor based on the acquired tooth simulation model and the functional abnormality area, which may be wearing corresponding braces and assisting recovery after surgery, etc. In the present embodiment, braces with corresponding data are worn. The revised treatment method is the initial treatment method initially diagnosed by the doctor. When the treatment is determined to be ineffective during the treatment simulation, the doctor determines that the new treatment method is accepted. It may be a modification and replacement of the braces worn or further surgical correction.

[0072] The abnormal data are abnormal actual gaps and abnormal actual inclinations. The abnormal data changes during the treatment simulation based on the tooth simulation model are used to determine whether there is a problem in the general direction of the diagnostic results of the treatment and correction. When the tooth data during the treatment process does not produce a benign correction change during periodic collection or the correction effect drops sharply after a period of time, it indicates that there is a problem with the treatment method. If there is a problem, that is, whether the initial treatment method is accurate, if the initial treatment method is ineffective, the situation will be fed back to the doctor, and the doctor will obtain a further diagnosed corrected treatment method. When the initial treatment method is effective, the simulated data of the treatment process is obtained based on the changes in the simulated tooth simulation model during the treatment to determine the optimal data and treatment time. The optimal data is the data when the abnormal data changes very little within a period of time during the treatment process. At this time, it indicates that the treatment and correction has reached its end. Whether the treatment needs to be optimized is determined based on the optimal data size and treatment time. When the treatment data and treatment time show poor treatment results, the doctor is required to further diagnose and optimize the initial treatment method to ensure the best treatment effect.

[0073] Specifically, by constructing a personalized tooth simulation model for the patient, the system can accurately identify areas of oral dysfunction and perform targeted treatment simulation. Compared with traditional diagnostic methods, this system can more accurately locate tooth misalignment and dysfunction problems, providing doctors with more accurate diagnostic basis. By calculating the treatment gap correction rate and the treatment inclination correction rate, it can dynamically judge the accuracy of the treatment plan. When the treatment plan is ineffective, the system can quickly identify abnormal conditions and provide correction suggestions. When the treatment plan is effective, it can further find the optimal treatment parameters to achieve continuous optimization of the treatment plan, provide doctors with diagnosis and treatment reference, and improve the accuracy, intelligence level and diagnosis and treatment efficiency of oral diagnosis.

[0074] Please continue reading Figure 2 ,like Figure 2 As shown, it is a schematic diagram of the structure of the analysis module of an embodiment of the present invention;

[0075] Specifically, the analysis module includes:

[0076] A tooth analysis unit, used to determine the actual gaps between the teeth and the actual inclinations between the teeth in the tooth simulation model;

[0077] An abnormality determination unit is connected to the tooth analysis unit and is used to determine whether the teeth are misaligned according to the actual gap and the actual inclination, and to determine the area where the misaligned teeth are located as a functional abnormality area.

[0078] Specifically, the maximum distance between adjacent teeth in the tooth simulation model is taken as the actual gap, and the angle between the closest points of two adjacent teeth close to the inner side of the oral cavity is taken as the actual inclination.

[0079] Specifically, by accurately measuring the actual gaps and actual inclinations between teeth in the tooth simulation model, the spatial relationship between teeth can be accurately quantified. By establishing standard gaps and standard inclinations as reference benchmarks, it is helpful to more accurately evaluate the degree of dental abnormalities and significantly improve the accuracy and objectivity of abnormality identification. The abnormality determination unit can not only identify whether there are misaligned teeth, but also accurately locate the specific areas where the misaligned teeth are located. It can quickly lock in the oral areas that need special attention and treatment, thereby improving the efficiency of diagnosis and treatment.

[0080] Specifically, the abnormality determination unit includes:

[0081] a misalignment inspection subunit, used for comparing the actual gap and the actual inclination with the corresponding standard gap and standard inclination to obtain a comparison result;

[0082] a misalignment determination subunit connected to the misalignment detection subunit, for determining whether the teeth are misaligned based on the comparison result, wherein the teeth are misaligned when the comparison result satisfies any one of the actual gap between the two teeth being larger than the standard gap or the actual inclination between the two teeth being larger than the standard inclination;

[0083] The area determination subunit is connected to the misalignment determination subunit and is used to determine the area of ​​the tooth simulation model where the misaligned tooth is located as the functional abnormality area.

[0084] In the specific implementation process, the standard gap is 0.5mm, the standard inclination is 1°, the actual gap between two teeth of the patient is 0.4mm, and the actual inclination is 20°, the actual inclination is greater than the standard inclination, and the actual gaps between the remaining teeth are less than or equal to the standard gap and the actual inclination is less than or equal to the standard inclination, then the area of ​​the two teeth where the actual inclination is greater than the standard inclination is determined as the functional abnormality area.

[0085] Specifically, tooth misalignment can be judged by accurately comparing the actual gap between teeth and the actual inclination with the standard value, which can comprehensively capture subtle abnormalities in tooth arrangement. By accurately locating the specific area where the misaligned teeth are located and marking it as an area of ​​functional abnormality, the accuracy and reliability of diagnosis can be significantly improved.

[0086] Please continue reading Figure 3 ,like Figure 3 As shown, it is a schematic diagram of the structure of the diagnosis and evaluation module of an embodiment of the present invention;

[0087] Specifically, the diagnostic assessment module includes:

[0088] A diagnosis receiving unit for obtaining the received initial treatment for the patient;

[0089] a treatment simulation unit connected to the diagnosis receiving unit and used to perform treatment simulation of the dysfunctional area according to the initial treatment method;

[0090] a treatment analysis unit connected to the treatment simulation unit, for acquiring a treatment gap and a treatment inclination after a certain treatment cycle in the treatment simulation based on a preset acquisition frequency, and calculating a treatment gap correction rate and a treatment inclination correction rate according to the treatment gap, the treatment inclination and the corresponding actual gap and actual inclination;

[0091] A treatment determination unit is connected to the treatment analysis unit and is used to determine the accuracy of the initial treatment method according to the treatment gap correction rate and the treatment inclination correction rate.

[0092] Specifically, the preset collection frequency is the frequency of treatment effect detection during dental treatment, which is generally set at 20-40 days / time, and in this embodiment is 30 days / time. The treatment gap correction rate is the ratio of the difference between the actual gap and the treatment gap to the actual gap, and the treatment inclination correction rate is the ratio of the difference between the actual inclination and the treatment inclination to the actual inclination.

[0093] Specifically, by dynamically acquiring the actual gap and actual inclination changes during the treatment simulation based on the preset acquisition frequency, the system can simulate the real treatment process, obtain detailed treatment data, and accurately calculate the treatment gap correction rate and treatment inclination correction rate, thereby achieving a comprehensive and objective evaluation of the initial treatment method, and measuring the effectiveness and accuracy of the initial treatment method.

[0094] Specifically, the treatment determination unit includes:

[0095] The first determination subunit is used to determine whether the treatment gap correction rate and the treatment inclination correction rate are both positive values. If either the treatment gap correction rate or the treatment inclination correction rate is not a positive value, it is determined that the initial treatment method is inaccurate.

[0096] Specifically, if the treatment gap correction rate and the treatment inclination correction rate are both positive values, it is determined that the initial treatment method is accurate.

[0097] During the specific implementation process, the actual inclination of the two teeth is 20°, and the treatment inclination obtained in the first acquisition cycle of the treatment process is 15°. The treatment inclination correction rate is the ratio of the difference between the actual inclination and the treatment inclination to the actual inclination, which is 25%. The treatment inclination correction rate is a positive value, and the treatment inclination correction rates obtained in subsequent acquisition cycles are all positive values, then it is determined that the initial treatment method is accurate.

[0098] Specifically, through real-time monitoring of the treatment gap correction rate and the treatment inclination correction rate, the system can dynamically evaluate the effectiveness of the treatment plan. This dynamic optimization mechanism can help doctors adjust treatment strategies in a timely manner and improve the accuracy and pertinence of oral orthodontic treatment.

[0099] Specifically, the treatment determination unit includes a second determination subunit connected to the first determination subunit, which is used to calculate the treatment change index of the treatment gap correction rate and the treatment inclination correction rate between each acquisition cycle when the treatment gap correction rate and the treatment inclination correction rate are both positive values; if the treatment change index is greater than the index change threshold, it is determined that the initial treatment method is inaccurate.

[0100] Specifically, if during the treatment process, the treatment change index between cycles is greater than the index change threshold, it means that the treatment effect of this cycle changes suddenly, which means that there may be some potential problems with this initial treatment method. The treatment change index is the ratio of the absolute value of the difference between the treatment gap correction rate or the treatment inclination correction rate of the two cycles to the treatment gap correction rate or the treatment inclination correction rate corresponding to the earlier cycle collected in the two cycles.

[0101] During the specific implementation process, the index change threshold is 0.1, the treatment inclination correction rate obtained in the first acquisition cycle during the patient's treatment is 25%, and the treatment inclination correction rate obtained in the second cycle is 5%. The treatment change index is 0.8. The treatment change index is greater than the index change threshold, and it is determined that the initial treatment method is inaccurate.

[0102] Specifically, by introducing the treatment change index, the system can dynamically and in real time monitor the correction changes during the treatment process. By comparing the treatment gap correction rate and treatment tilt correction rate of different acquisition cycles, abnormal fluctuations in the treatment process can be discovered in time, and the treatment strategy can be adjusted in time to prevent the treatment from deviating from the expected goal. This is conducive to a more comprehensive and in-depth judgment of the effectiveness of the treatment plan, and significantly improves the accuracy and reliability of the diagnosis.

[0103] Please continue reading Figure 4 ,like Figure 4 As shown, it is a schematic diagram of the structure of the diagnostic feedback module of an embodiment of the present invention;

[0104] Specifically, the diagnostic feedback module includes:

[0105] a treatment receiving unit, used to receive the accuracy of the initial treatment method determined by the treatment determining unit;

[0106] A first processing unit connected to the treatment receiving unit is used to determine that the initial treatment method determined by the first determination subunit is inaccurate or the initial treatment method determined by the second determination subunit is inaccurate when the initial treatment method is determined to be invalid;

[0107] a second processing unit connected to the feedback receiving unit, for determining optimal data based on the treatment change index of the treatment gap correction rate and the treatment inclination correction rate when determining that the initial treatment method is effective, including an optimal gap correction rate and an optimal inclination correction rate;

[0108] A treatment verification unit is connected to the second processing unit and is used to obtain the treatment time to achieve the best data, and determine whether diagnosis optimization is needed based on the best data and the treatment time.

[0109] Specifically, when an initial treatment is determined to be ineffective, the basis for the inaccurate determination is determined so that the physician can further modify the initial treatment.

[0110] Specifically, by accurately distinguishing the specific reasons for inaccurate initial treatment methods, it can help doctors more accurately locate and solve specific problems in treatment, improve the pertinence and effectiveness of diagnosis, and by analyzing the treatment change index, it can dynamically capture and extract the best data in the treatment process. By comprehensively analyzing the best treatment data and the corresponding treatment time, it can intelligently determine whether further diagnostic optimization is needed, which can effectively enhance the continuous improvement capabilities of oral diagnosis, realize dynamic optimization and iteration of diagnosis and treatment plans, and help improve the personalization level and treatment effects of oral treatment.

[0111] Specifically, the second processing unit includes:

[0112] An index comparison subunit, used to compare the treatment change index with the minimum change index to obtain a comparison result;

[0113] The data determination subunit is connected to the index comparison subunit and is used to determine that the treatment gap correction rate and treatment inclination correction rate at this time are the corresponding optimal gap correction rate and optimal inclination correction rate when the comparison result during the treatment process is that the treatment change index is less than the minimum change index.

[0114] During the specific implementation process, the minimum transformation index is 0.02. During the treatment process, the patient suppresses the treatment tilt correction rate. The treatment change index of one acquisition cycle is 0.03, and the treatment change index of the next acquisition cycle is 0.01. At this time, the treatment tilt correction rate with a treatment change index of 0.01 is the optimal tilt correction rate, and the optimal tilt correction rate at this time is 95%.

[0115] Specifically, by dynamically tracking the changing index during the treatment process and accurately locating the moment when the treatment effect is best, the system can continuously monitor subtle changes during the treatment process and quickly capture key parameters when the optimal treatment state occurs, significantly improving the accuracy and effectiveness of the treatment plan.

[0116] Specifically, the treatment verification unit includes:

[0117] A data verification subunit, used to compare the optimal data with preset standard data to obtain a data comparison result;

[0118] A time verification subunit, used to compare the treatment time with a preset treatment time threshold to obtain a time comparison result;

[0119] The diagnosis determination subunit is connected to the data verification subunit and the time verification subunit respectively, and is used to determine whether diagnosis optimization is needed according to the data comparison result and the time comparison result.

[0120] Specifically, when the data comparison result is that the best data is greater than the standard data and the time comparison result is that the treatment time is less than the treatment time threshold, it is determined that diagnostic optimization is not required.

[0121] During the specific implementation process, the standard treatment inclination correction rate in the standard data is 92%, the treatment time threshold is 200 days, the optimal inclination correction rate for treatment simulation is 95%, and the treatment time is 180 days. The data comparison result is that the optimal data is greater than the standard data, and the time comparison result is that the treatment time is less than the treatment time threshold, determining that no diagnostic optimization is required.

[0122] Specifically, by comprehensively analyzing the data comparison results and the time comparison results, it is possible to intelligently determine whether diagnostic optimization is needed, which can effectively improve the accuracy and personalization of oral diagnosis, provide doctors with more intelligent diagnosis and treatment suggestions, and improve diagnosis and treatment efficiency.

[0123] Specifically, the simulation production module includes:

[0124] An image acquisition unit, used to acquire a patient's dental image;

[0125] An image enhancement unit, connected to the image acquisition unit, for preprocessing the tooth image to obtain an optimized tooth image;

[0126] The simulation unit is connected to the image enhancement unit and is used to scan the patient's oral cavity to obtain point cloud data, and perform tooth simulation based on the optimized tooth image and the point cloud data to obtain a tooth simulation model.

[0127] Specifically, the preprocessing includes denoising, clarity optimization, etc., which can make the image information more accurately processed. In this embodiment, it is denoising. The patient's tooth image is collected by an image collector, and the preprocessed optimized tooth image is combined with the point cloud data obtained by oral scanning to generate a tooth simulation model.

[0128] Specifically, by accurately capturing and intelligently preprocessing the patient's dental images, clearer and more detailed optimized dental images can be obtained, providing a high-quality data foundation for subsequent simulations. Based on the fusion of multi-source data, intelligent dental simulation reconstruction can be performed to accurately restore the actual morphology and structural characteristics of the patient's oral cavity, providing a more reliable simulation foundation for subsequent diagnosis.

[0129] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0130] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An oral diagnosis system based on simulation data support, characterized in that: include: A simulation generation module, used to simulate the patient's oral cavity based on the patient's oral dental image and point cloud data to obtain a dental simulation model; an analysis module connected to the simulation generation module, for determining a functional abnormality area according to the tooth simulation model; a diagnostic evaluation module connected to the analysis module, configured to perform a treatment simulation on the functionally abnormal region based on the received initial treatment method, and determine the accuracy of the initial treatment method according to the abnormal data changes of the functionally abnormal region during the treatment simulation; A diagnostic feedback module is connected to the simulation production module and the diagnostic evaluation module to provide different diagnostic feedbacks according to the determination result of the effectiveness of the initial treatment method, wherein: When it is determined that the initial treatment is ineffective, determining the abnormal situation and providing feedback, and receiving the revised treatment to perform a re-treatment simulation on the tooth simulation model; When it is determined that the initial treatment method is effective, the optimal data reached by the abnormal data during the correction process is determined, and whether diagnostic optimization is required is determined based on the size of the optimal data and the treatment time to reach the optimal data.

2. The oral diagnosis system based on simulation data support according to claim 1, characterized in that: The analysis module comprises: A tooth analysis unit, used to determine the actual gaps between the teeth and the actual inclinations between the teeth in the tooth simulation model; An abnormality determination unit is connected to the tooth analysis unit and is used to determine whether the teeth are misaligned according to the actual gap and the actual inclination, and to determine the area where the misaligned teeth are located as a functional abnormality area.

3. The oral diagnosis system based on simulation data support according to claim 2, characterized in that: The abnormality determination unit comprises: a misalignment inspection subunit, used for comparing the actual gap and the actual inclination with the corresponding standard gap and standard inclination to obtain a comparison result; a misalignment determination subunit connected to the misalignment detection subunit, for determining whether the teeth are misaligned based on the comparison result, wherein the teeth are misaligned when the comparison result satisfies any one of the actual gap between the two teeth being larger than the standard gap or the actual inclination between the two teeth being larger than the standard inclination; The area determination subunit is connected to the misalignment determination subunit and is used to determine the area of ​​the tooth simulation model where the misaligned tooth is located as the functional abnormality area.

4. The oral diagnosis system based on simulation data support according to claim 3, characterized in that: The diagnostic assessment module includes: A diagnosis receiving unit for obtaining the received initial treatment for the patient; a treatment simulation unit connected to the diagnosis receiving unit and used to perform treatment simulation of the dysfunctional area according to the initial treatment method; a treatment analysis unit connected to the treatment simulation unit, for acquiring a treatment gap and a treatment inclination after a certain treatment cycle in the treatment simulation based on a preset acquisition frequency, and calculating a treatment gap correction rate and a treatment inclination correction rate according to the treatment gap, the treatment inclination and the corresponding actual gap and actual inclination; A treatment determination unit is connected to the treatment analysis unit and is used to determine the accuracy of the initial treatment method according to the treatment gap correction rate and the treatment inclination correction rate.

5. The oral diagnosis system based on simulation data support according to claim 4, characterized in that: The treatment determination unit comprises: The first determination subunit is used to determine whether the treatment gap correction rate and the treatment inclination correction rate are both positive values. If either the treatment gap correction rate or the treatment inclination correction rate is not a positive value, it is determined that the initial treatment method is inaccurate.

6. The oral diagnosis system based on simulation data support according to claim 5, characterized in that: The treatment determination unit includes a second determination subunit connected to the first determination subunit, which is used to calculate the treatment change index of the treatment gap correction rate and the treatment inclination correction rate between each acquisition cycle when the treatment gap correction rate and the treatment inclination correction rate are both positive values; if the treatment change index is greater than the index change threshold, it is determined that the initial treatment method is inaccurate.

7. The oral diagnosis system based on simulation data support according to claim 6, characterized in that: The diagnostic feedback module comprises: a treatment receiving unit, used to receive the accuracy of the initial treatment method determined by the treatment determining unit; A first processing unit connected to the treatment receiving unit is used to determine that the initial treatment method determined by the first determination subunit is inaccurate or the initial treatment method determined by the second determination subunit is inaccurate when the initial treatment method is determined to be invalid; a second processing unit connected to the feedback receiving unit, for determining optimal data based on the treatment change index of the treatment gap correction rate and the treatment inclination correction rate when determining that the initial treatment method is effective, including an optimal gap correction rate and an optimal inclination correction rate; A treatment verification unit is connected to the second processing unit and is used to obtain the treatment time to achieve the best data, and determine whether diagnosis optimization is needed based on the best data and the treatment time.

8. The oral diagnosis system based on simulation data support according to claim 7, characterized in that: The second processing unit comprises: An index comparison subunit, used to compare the treatment change index with the minimum change index to obtain a comparison result; The data determination subunit is connected to the index comparison subunit and is used to determine that the treatment gap correction rate and treatment inclination correction rate at this time are the corresponding optimal gap correction rate and optimal inclination correction rate when the comparison result during the treatment process is that the treatment change index is less than the minimum change index.

9. The oral diagnosis system based on simulation data support according to claim 8, characterized in that: The treatment verification unit comprises: A data verification subunit, used to compare the optimal data with preset standard data to obtain a data comparison result; A time verification subunit, used to compare the treatment time with a preset treatment time threshold to obtain a time comparison result; The diagnosis determination subunit is connected to the data verification subunit and the time verification subunit respectively, and is used to determine whether diagnosis optimization is needed according to the data comparison result and the time comparison result.

10. The oral diagnosis system based on simulation data support according to claim 9, characterized in that: The simulation production module includes: An image acquisition unit, used to acquire a patient's dental image; An image enhancement unit, connected to the image acquisition unit, for preprocessing the tooth image to obtain an optimized tooth image; The simulation unit is connected to the image enhancement unit and is used to scan the patient's oral cavity to obtain point cloud data, and perform tooth simulation based on the optimized tooth image and the point cloud data to obtain a tooth simulation model.

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