Denture modeling preparation method and system

Abstract

The present application discloses a denture modeling and preparation method and system. The method includes: generating a patient's oral cavity model based on dental image data, and identifying the teeth to be implanted, normal teeth, and abnormal teeth in the oral cavity model; searching for a target standard oral cavity model that matches the patient based on the identification data of normal teeth, the patient's personal data, and a standard oral cavity model library; preliminarily optimizing the abnormal tooth model and the tooth model to be implanted in the target standard oral cavity model based on first model difference data between the normal tooth model in the target standard oral cavity model and the normal tooth model in the oral cavity model; if the second model difference data between the abnormal tooth model in the target standard oral cavity model after the preliminary optimization and the abnormal tooth model in the oral cavity model is greater than a set threshold, performing a secondary optimization on the tooth model to be implanted after the preliminary optimization to construct a dental implant model. In this way, the adaptability of the dental implant model is improved.

Description

Technical Field

[0001] The present application relates to the field of oral medicine technology, and in particular to a denture modeling and preparation method and system. Background Art

[0002] Dentures, commonly known as false teeth, are generally categorized as removable, fixed, and implants. A common dental implant method is "extraction-and-implantation," where a pre-prepared standard implant is placed directly into the tooth socket after the patient has had a bad tooth extracted.

[0003] Although the "immediate extraction and implantation" technology is simple and practical, it does not take into account that in most cases patients do not come for treatment in the early stages of dental problems, and often receive treatment after a long delay. In this case, the causes of tooth damage are more complicated than before, which means that bad teeth (i.e. teeth that need to be extracted) may affect other healthy teeth. The longer this impact is delayed, the more serious and irreversible it will be. The closer to the tooth to be extracted, the more serious the impact. Generally, the most seriously affected are the teeth that clash with it in the occlusal state. For example, if an incisor is broken due to a knock, but it is not treated for a long time, the other incisor that is in contact with this incisor will grow toward it, causing the other incisor to be too long. The teeth on both sides of this incisor will also tend to tilt toward the broken incisor.

[0004] Therefore, the traditional 'extraction and implantation' dental implant program uses a standard model, which is only suitable for patients with good oral health. However, for patients with damaged original teeth, it is not a good match, making it difficult to effectively solve their oral problems after implant treatment. Summary of the Invention

[0005] In view of this, an embodiment of the present application provides a denture modeling and preparation method and system, which aims to solve the problem of insufficient matching between the dental implant model and the patient's actual oral condition.

[0006] The technical solution of the embodiment of the present application is implemented as follows:

[0007] In a first aspect, an embodiment of the present application provides a denture modeling and preparation method, comprising:

[0008] Acquire dental image data in a patient's oral cavity and personal data of the patient, wherein the personal data includes at least one of the following: age data, gender data, and patient location data;

[0009] Generate an oral model of the patient based on the dental image data, and identify the teeth to be extracted in the oral model 、 Normal teeth and abnormal teeth;

[0010] searching for a target standard oral model that matches the patient based on the identification data of the normal teeth, the patient's personal data, and a standard oral model library; wherein the number of normal teeth in the oral model is consistent with the number of normal teeth in the target standard oral model;

[0011] Preliminarily optimizing the abnormal tooth model in the target standard oral model and the tooth model to be implanted corresponding to the tooth to be extracted based on first model difference data between the normal tooth model in the target standard oral model and the normal tooth model in the oral model;

[0012] If the second model difference data between the abnormal tooth model in the target standard oral model after the preliminary optimization and the abnormal tooth model of the oral model is greater than or equal to the set threshold, the tooth model to be implanted after the preliminary optimization is secondary optimized to construct a dental implant model;

[0013] Based on the dental implant model, the dental implant model is prepared.

[0014] In some embodiments, identifying teeth to be extracted, normal teeth, and abnormal teeth in the oral model includes:

[0015] Identifying the teeth to be extracted in the oral model;

[0016] Classifying the teeth other than the teeth to be extracted in the oral model of the target patient based on the trained neural network-like model, and determining normal teeth and abnormal teeth among the other teeth;

[0017] The normal teeth and the abnormal teeth are identified.

[0018] In some embodiments, generating the patient's oral cavity model based on the dental image data includes:

[0019] If the tooth image data includes wisdom tooth image data, and the type of the patient's tooth to be extracted is at least one of the following: a central incisor, an oblique incisor, or a canine, obtaining an initial oral model and generating instruction information;

[0020] In response to the instruction information, removing the wisdom tooth model from the initial oral cavity model;

[0021] The initial oral cavity model after removing the wisdom tooth model is adjusted to generate the oral cavity model.

[0022] In some embodiments, adjusting the initial oral cavity model after removing the wisdom tooth model includes:

[0023] Correcting the orientation data of the teeth to be adjusted in the initial oral cavity model after the wisdom tooth model is removed, wherein the teeth to be adjusted are adjacent teeth squeezed by the wisdom teeth.

[0024] In some embodiments, searching for a target standard oral model that matches the patient based on the identification data of the normal teeth, the patient's personal data, and a standard oral model library includes:

[0025] Screening the standard oral model library based on the patient's personal data to determine an initial oral model library;

[0026] The target standard oral cavity model is searched based on the identification data of the normal teeth and the initial oral cavity model library.

[0027] In some embodiments, the method further comprises:

[0028] If the second model difference data between the abnormal tooth model in the target standard oral model after preliminary optimization and the abnormal tooth model of the oral model is less than the set threshold, a dental implant model is constructed based on the tooth model to be implanted in the target standard oral model after preliminary optimization.

[0029] In some embodiments, the abnormal tooth includes a positively interfering tooth that interferes with the tooth to be extracted in the height direction when the mouth is closed. The secondary optimization of the initially optimized model of the tooth to be implanted to construct the implant model includes:

[0030] Acquire tooth height difference data of the positive conflicting tooth model in the second model difference data;

[0031] Based on the tooth height difference data, adjusting the tooth height of the preliminarily optimized tooth model to be implanted, so as to perform secondary optimization on the preliminarily optimized tooth model to be implanted in the target standard oral cavity model;

[0032] Based on the secondary optimized tooth model to be implanted, the dental implant model is constructed.

[0033] In some embodiments, the abnormal tooth includes a positively interfering tooth that interferes with the tooth to be extracted in the height direction when the mouth is closed. The secondary optimization of the initially optimized model of the tooth to be implanted to construct the implant model includes:

[0034] Acquiring the conflicting surface morphology difference data of the positive conflicting tooth model in the second model difference data;

[0035] Based on the interference surface morphology difference data, adjusting the interference surface curvature of the preliminarily optimized tooth model to be implanted, so as to perform secondary optimization on the preliminarily optimized tooth model to be implanted in the target standard oral model;

[0036] Based on the secondary optimized tooth model to be implanted, the dental implant model is constructed.

[0037] In some embodiments, the abnormal tooth includes a lateral interfering tooth that interferes with the tooth to be extracted in a horizontal direction, and the preliminarily optimized model of the tooth to be implanted is subjected to secondary optimization to construct a dental implant model, including:

[0038] Acquire the crown morphology difference data of the lateral conflicting tooth model in the second model difference data;

[0039] Based on the crown morphology difference data, adjusting the crown width and crown contour morphology data of the preliminarily optimized tooth model to be implanted, so as to perform secondary optimization on the preliminarily optimized tooth model to be implanted in the target standard oral model;

[0040] Based on the secondary optimized tooth model to be implanted, the dental implant model is constructed.

[0041] In a second aspect, an embodiment of the present application provides a denture modeling and preparation system, the system comprising an image acquisition module and an electronic device; wherein the image acquisition module is used to acquire and send the patient's dental image data; the electronic device comprises: a processor and a memory for storing a computer program that can be run on the processor, wherein the processor, when running the computer program, executes the steps of the method described in the first aspect above.

[0042] The technical solution provided in the embodiment of the present application is a denture modeling and preparation method, comprising: obtaining dental image data of a patient's oral cavity and personal data of the patient, the personal data including at least one of the following: age data, gender data, and data on the patient's region; generating an oral model of the patient based on the dental image data, and identifying the teeth to be extracted in the oral model; 、Normal teeth and abnormal teeth; based on the identification data of normal teeth, the patient's personal data and the standard oral model library, searching for a target standard oral model that matches the patient; wherein the number of normal teeth in the oral model is consistent with the number of normal teeth in the target standard oral model; based on the first model difference data between the normal tooth model in the target standard oral model and the normal tooth model of the oral model, preliminarily optimizing the abnormal tooth model in the target standard oral model and the tooth model to be implanted corresponding to the tooth to be extracted; if the second model difference data between the abnormal tooth model in the target standard oral model after preliminarily optimization and the abnormal tooth model of the oral model is greater than or equal to the set threshold, performing a secondary optimization on the tooth model to be implanted after preliminarily optimization to construct a dental implant model; preparing a dental implant model based on the dental implant model.

[0043] In this way, the embodiment of the present application preliminarily optimizes the model of the teeth to be implanted in the target standard oral model by taking the first model error between the normal tooth model of the patient's normal teeth in the oral model and the tooth model in the standard oral model, and then further improves the model of the teeth to be implanted through secondary optimization. The final generated dental implant model is highly matched with the patient's current tooth structure. This method effectively solves the problem of poor adaptability of dental implants in traditional modeling methods, ensuring that dental implants can better adapt to the actual situation of the patient's oral cavity, especially when bad teeth affect other teeth. At the same time, by improving the adaptability of the dental implant model, it promotes the recovery of the patient's oral function and provides a more personalized and comfortable dental implant solution, significantly improving the patient's treatment experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 A schematic diagram of the process of the denture modeling and preparation method provided in an embodiment of the present application;

[0045] Figure 2 A schematic flow chart of a denture modeling and preparation method provided for an application example of this application;

[0046] Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0047] The present application will be described in further detail below with reference to the accompanying drawings and embodiments.

[0048] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application pertains. The terms used herein in the specification of this application are for the purpose of describing specific embodiments only and are not intended to limit this application.

[0049] The present invention provides a method for preparing denture modeling. Figure 1 As shown, the method includes the following steps:

[0050] Step 110: Acquire dental image data of the patient's oral cavity and the patient's personal data, where the personal data includes at least one of the following: age data, gender data, and patient location data.

[0051] In this embodiment, the tooth image data sent by the image acquisition device can be obtained. The image acquisition device includes but is not limited to an intraoral scanner or a three-dimensional photography device, which is used to acquire multi-angle tooth images in the patient's oral cavity.

[0052] In this embodiment, the patient's personal data can be extracted from the patient medical record system, including but not limited to age, gender, and region (this information is helpful for analyzing the impact of regional eating habits on tooth morphology).

[0053] Step 120: Generate an oral model of the patient based on the dental image data, and identify the teeth to be extracted, normal teeth, and abnormal teeth in the oral model.

[0054] In this embodiment, the dental image data can be converted into a digital oral model based on the dental image data, thereby constructing the patient's oral model. The patient's oral model represents the geometric shape, position and occlusal relationship of all teeth, and the patient's oral model includes the dental models of all teeth.

[0055] It can be understood that the teeth in the patient's mouth are divided into: the patient's teeth to be extracted, that is, bad teeth (the bad teeth need to be extracted and the teeth to be implanted are implanted), normal teeth affected by the bad teeth or less affected, and abnormal teeth that are severely affected.

[0056] For example, normal teeth should be symmetrical, neatly arranged, naturally colored, and have an aesthetically pleasing shape. Their tooth morphology parameters, such as crown width and height, should be within preset thresholds, and there should be no significant positional offset between the teeth and adjacent teeth. Abnormal teeth are those with abnormal shape or position (e.g., high front teeth or tilted lateral teeth) due to bad teeth.

[0057] In this embodiment, before constructing the model of the teeth to be implanted, it is necessary to classify all the teeth in the oral model and identify the teeth to be implanted, normal teeth, and abnormal teeth in the oral model.

[0058] Step 130: Based on the identification data of normal teeth, the patient's personal data and the standard oral model library, a target standard oral model matching the patient is searched; wherein the number of normal teeth in the oral model is consistent with the number of normal teeth in the target standard oral model.

[0059] In this embodiment, based on the identification data of normal teeth in the oral model and the patient's personal data (such as age data, gender data, patient's region data, etc.), a target standard oral model that matches the patient is searched from the standard oral model library.

[0060] In this embodiment, in order to ensure that the differences between the teeth at the same position in the oral model and the target standard oral model can be accurately compared later and the model of the teeth to be implanted can be optimized, it is necessary to ensure that the number of normal teeth in the two models is consistent.

[0061] Step 140: Preliminarily optimize the abnormal tooth model in the target standard oral model and the tooth model to be implanted corresponding to the tooth to be extracted based on the first model difference data between the normal tooth model in the target standard oral model and the normal tooth model of the oral model.

[0062] In this embodiment, the target standard oral model in the standard oral model library and the patient's oral model may not be completely consistent, and some differences between the two can also be understood as model errors.

[0063] In this embodiment, the normal tooth model of normal teeth in the target standard oral model and the standard tooth model at the same position in the target standard oral model (the normal tooth model of the oral model) can be compared to obtain the model difference between the two, generate first model difference data, and based on the first model difference data, preliminarily optimize the abnormal tooth model in the target standard oral model and the tooth model to be implanted corresponding to the tooth to be extracted.

[0064] For example, we can extract normal tooth models from the patient's oral model, such as the left canine and right first molar. We then compare these models point-by-point with the corresponding teeth in the target standard model, generating first-model difference data, including height difference ΔH, width difference ΔW, and inclination angle difference Δθ. We then map these difference data onto the abnormal teeth in the target standard model, proportionally adjusting their crown heights and inclination angles. Based on the adjustments to the abnormal teeth, we also modify the morphology of the implanted tooth.

[0065] In this way, by adjusting the model error of normal teeth, the tooth models of the "abnormal teeth" and "bad teeth" in the same position in the standard oral model are adjusted synchronously. In this way, the adjusted tooth models in the same position can be closer to the model shape of the patient's teeth when they are not affected by bad teeth.

[0066] Step 150: If the second model difference data between the abnormal tooth model in the target standard oral model after preliminary optimization and the abnormal tooth model in the oral model is greater than or equal to the set threshold, the tooth model to be implanted after preliminary optimization is secondary optimized to construct a dental implant model.

[0067] In this embodiment, under normal circumstances, the model of the tooth to be implanted after preliminary optimization will be infinitely close to the normal model shape when it is not affected by bad teeth. However, due to the influence of bad teeth, the teeth after preliminary optimization will still be different from the tooth model in the same position in the actual constructed oral model. This difference can be considered as the influence of bad teeth.

[0068] Therefore, the embodiment of the present application compares the abnormal tooth model after preliminary optimization with the actual abnormal tooth model of the patient, and calculates the second model difference data. If the second model difference data exceeds the set threshold (for example, ΔH>0.5mm), it indicates that the model difference is significant. At this time, a secondary optimization process will be triggered, that is, the tooth model to be implanted in the target standard oral model after preliminary optimization is secondary optimized to construct a dental implant model, which is used to prepare the tooth to be implanted.

[0069] Step 160: Prepare a dental implant model based on the dental implant model.

[0070] In this way, the embodiment of the present application performs a preliminary optimization of the tooth model to be implanted in the target standard oral model by taking the first model error between the normal tooth model of the patient's normal teeth in the oral model and the tooth model in the standard oral model, and then further improves the tooth model to be implanted through secondary optimization. Ultimately, a dental implant model that accurately matches the patient's current tooth structure is generated. This method effectively solves the problem of poor adaptability of dental implants in traditional modeling methods, ensuring that dental implants can better adapt to the actual conditions of the patient's oral cavity, especially when bad teeth affect other teeth. At the same time, by improving the adaptability of the dental implant model, it promotes the recovery of the patient's oral function and provides a more personalized and comfortable dental implant solution, significantly improving the patient's treatment experience.

[0071] In some embodiments, identifying teeth to be extracted, normal teeth, and abnormal teeth in the oral model includes:

[0072] Identify the teeth to be extracted in the oral model;

[0073] Based on the trained neural network model, the teeth other than the teeth to be extracted in the oral model of the target patient are classified to determine the normal teeth and abnormal teeth among the other teeth;

[0074] Identify normal and abnormal teeth.

[0075] In this embodiment, for the teeth to be extracted, the physician may manually mark the position of the bad tooth (eg, a broken central incisor) in the model, thereby identifying the teeth to be extracted in the oral model.

[0076] For the identification of normal / abnormal teeth, firstly, the teeth other than the teeth to be implanted in the oral model of the target patient can be classified based on the pre-trained neural network model, and the other teeth can be classified into normal teeth and abnormal teeth, and the normal teeth and abnormal teeth among the other teeth can be determined; and the normal teeth and abnormal teeth can be identified.

[0077] In this way, by using specially trained neural network-like systems, normal teeth and abnormal teeth can be accurately distinguished, so as to facilitate the primary and secondary optimization of the teeth to be implanted.

[0078] In some embodiments, generating a patient's oral cavity model based on the dental image data includes:

[0079] If the tooth image data includes wisdom tooth image data, and the type of the patient's tooth to be extracted is at least one of the following: a central incisor, an oblique incisor, or a canine, obtaining an initial oral model and generating instruction information;

[0080] In response to the instruction information, removing the wisdom tooth model from the initial oral cavity model;

[0081] The initial oral cavity model after removing the wisdom tooth model is adjusted to generate an oral cavity model.

[0082] In this embodiment, if the patient's oral model contains wisdom teeth, and the teeth to be extracted are central incisors, bevel incisors or canines, the standard oral model library in this embodiment does not take into account the special case of wisdom teeth, which will result in the number of normal teeth in the constructed oral model being greater than the number of teeth in the oral model in the model library, resulting in a phenomenon that the target standard oral model cannot be matched.

[0083] Therefore, if the dental image data includes wisdom tooth image data, and the patient's dental implant type is at least one of the following: central incisor, bevel incisor, or canine, an initial oral model is acquired and instruction information is generated. This instruction information can be manually issued by the physician. In response to the instruction information, the wisdom tooth model is removed from the initial oral model to ensure that the target standard oral model can be successfully matched in the standard oral model library. Furthermore, after removing the wisdom tooth model, the initial oral model after removing the wisdom tooth model can be adjusted, and the adjusted new initial model is used as the oral model of the patient.

[0084] In some embodiments, adjusting the initial oral cavity model after removing the wisdom tooth model includes:

[0085] Correct the orientation data of the teeth to be adjusted in the initial oral model after the wisdom tooth model is removed. The teeth to be adjusted are the adjacent teeth squeezed by the wisdom teeth.

[0086] In this embodiment, adjusting the initial oral cavity model after removing the wisdom tooth model may include correcting the orientation of the adjacent teeth squeezed by the wisdom teeth (eg, resetting the tilted second molar to a vertical position).

[0087] For example, in actual application, if wisdom teeth are present and the damaged teeth are central incisors, bevel incisors or canines, the doctor will manually remove the wisdom tooth tooth model from the constructed initial oral model and adjust the orientation of the teeth affected by the wisdom teeth (usually only the orientation is changed and the tooth morphology remains normal), and then use the adjusted tooth model to perform subsequent steps.

[0088] In some embodiments, based on the identification data of normal teeth, the patient's personal data, and a standard oral model library, searching for a target standard oral model that matches the patient includes:

[0089] Screen the standard oral model library based on the patient's personal data to determine the initial oral model library;

[0090] Based on the identification data of normal teeth and the initial oral model library, the target standard oral model is found.

[0091] In this embodiment, in order to ensure that the standard oral model selected from the standard oral model library has a higher degree of fit with the patient, the standard model library needs to be double-screened.

[0092] Specifically, the first screening is to start from the basic situation of the patient, and conduct a preliminary screening based on the patient's personal data (age data, gender data, and regional data), generate a preliminary screening result, and thus screen out a standard oral model (initial oral model library) that meets the conditions. For example, a preliminary screening can be conducted based on the patient's personal data (such as age ≥ 50 years old, gender female, and region of high sugar diet), and oral models that meet the typical characteristics of this group can be screened out from the standard oral model library to form a candidate set, that is, the initial oral model library, which contains standard oral models that meet objective factors.

[0093] After the screening is completed, the most similar standard oral model (target standard oral model) is further screened out from the initial screening results based on the identification data of the normal teeth used to construct the model.

[0094] Because abnormal teeth have already been affected and are therefore not suitable for selecting the target standard oral model, we only use normal teeth as the screening criteria. Based on the identification data of normal teeth, we search for the target standard oral model in the initial oral model library. This can improve the accuracy of the screening results and the matching degree with the patient.

[0095] In some embodiments, the method further comprises:

[0096] If the second model difference data between the abnormal tooth model in the target standard oral model after preliminary optimization and the abnormal tooth model of the oral model is less than the set threshold, a dental implant model is constructed based on the tooth model to be implanted in the target standard oral model after preliminary optimization.

[0097] In this embodiment, if the second model difference data is less than the set threshold, it indicates that the model difference is small, and there is no need to perform secondary optimization on the tooth model to be implanted in the target standard oral model after the preliminary optimization. Instead, the dental implant model can be directly constructed based on the tooth model to be implanted in the target standard oral model after the preliminary optimization, that is, the tooth model to be implanted in the target standard oral model after the preliminary optimization can be used as the dental implant model.

[0098] In some embodiments, the abnormal tooth includes a positively interfering tooth that interferes with the tooth to be extracted in the height direction when the mouth is closed. The primary optimized model of the tooth to be implanted is subjected to secondary optimization to construct a dental implant model, including:

[0099] Acquire tooth height difference data of the positive conflicting tooth model in the second model difference data;

[0100] Based on the tooth height difference data, the tooth height of the initially optimized tooth model to be implanted is adjusted to perform secondary optimization on the initially optimized tooth model to be implanted in the target standard oral model;

[0101] Based on the secondary optimized tooth model to be implanted, a dental implant model is constructed.

[0102] In this embodiment, the abnormal teeth include positively interfering teeth that conflict with the teeth to be implanted (bad teeth) in the height direction. If the second model difference data is greater than the set threshold, it indicates that the model difference is large, and it is necessary to perform secondary optimization on the model of the teeth to be implanted in the target standard oral model after the preliminary optimization, and construct a dental implant model based on the secondary optimized model of the teeth to be implanted.

[0103] Specifically, the tooth height of the tooth model to be implanted after preliminary optimization can be adjusted based on the tooth height difference data, so as to perform secondary optimization on the tooth model to be implanted in the target standard oral cavity model after preliminary optimization.

[0104] For example, the tooth height difference data includes the difference data of the height being too high or too low. Taking the excessive height of the interfering tooth as an example, in this case, it is usually caused by the low height of the bad tooth (the tooth to be extracted). Since the bad tooth itself is low, it is easy for the interfering tooth to grow too high without the teeth to interfere with it. In this case, it is necessary to adjust the tooth height of the initially optimized model of the tooth to be implanted according to the tooth height difference data of the interfering tooth, that is, to reduce the height of the standard tooth model in the same position as the tooth, so that the oral cavity can be closed healthily.

[0105] In some embodiments, the abnormal tooth includes a positively interfering tooth that interferes with the tooth to be extracted in the height direction when the mouth is closed. The primary optimized model of the tooth to be implanted is subjected to secondary optimization to construct a dental implant model, including:

[0106] Obtaining the conflicting surface morphology difference data of the positive conflicting tooth model in the second model difference data;

[0107] Based on the data of the difference in the interfering surface morphology, the curvature of the interfering surface of the tooth model to be implanted after the preliminary optimization is adjusted, so as to perform a secondary optimization on the tooth model to be implanted in the target standard oral model after the preliminary optimization;

[0108] Based on the secondary optimized tooth model to be implanted, a dental implant model is constructed.

[0109] In this embodiment, the contact surface of the interfering teeth may become non-standard due to the lack of interference of healthy teeth.

[0110] Assume that the abnormal teeth include interfering teeth that interfere with the tooth to be extracted in the height direction. If the difference data of the second model exceeds the threshold, the model difference is large, and the initially optimized model of the tooth to be implanted needs to be optimized again to construct the implant model.

[0111] In this embodiment, the model to be implanted can be adjusted according to the morphological data of the contact surface of the directly interfering tooth in the first model difference data.

[0112] Taking the above-mentioned excessive height of the interfering teeth as an example, since the bad teeth themselves are relatively low in height, it is not only easy for the interfering teeth to grow too high due to the lack of teeth to interfere with, but also the contact surface of the interfering teeth will become non-standard due to the lack of interference from healthy teeth. In this case, it is necessary to adjust the curvature of the interfering surface of the tooth model to be implanted after preliminary optimization based on the difference data of the interfering surface of the positive interfering teeth, so as to perform secondary optimization on the tooth model to be implanted in the target standard oral model after preliminary optimization.

[0113] In some embodiments, the abnormal tooth includes a lateral interfering tooth that interferes with the tooth to be extracted in the horizontal direction. The model of the tooth to be implanted after the initial optimization is subjected to secondary optimization to construct the implant model, including:

[0114] Acquire the crown morphology difference data of the lateral conflicting tooth model in the second model difference data;

[0115] Based on the crown morphology difference data, the crown width and crown contour morphology data of the initially optimized model of the tooth to be implanted are adjusted, and the model of the tooth to be implanted in the initially optimized target standard oral model is secondary optimized;

[0116] Based on the secondary optimized tooth model to be implanted, a dental implant model is constructed.

[0117] In this embodiment, we use the lateral impaction tooth crown morphology difference data in the second model difference data to perform secondary optimization on the to-be-implanted tooth model in the target standard oral model after preliminary optimization, and finally construct the dental implant model based on this optimization result.

[0118] Specifically, the crown width and crown contour morphology data of the initially optimized model of the tooth to be implanted can be adjusted based on the crown morphology difference data.

[0119] Exemplarily, the crown morphology difference data includes the lateral interfering teeth width difference data. For example, a bad tooth that has been missing for a long time will make the lateral interfering teeth too wide. At this time, the crown of the optimized tooth model to be implanted can be adjusted to be narrower, so that the overall shape of the crown can fit the interfering teeth on both sides.

[0120] Below, the embodiment of the present application is described in detail with reference to an application example.

[0121] Based on the defects of the existing dental implant modeling logic, this application example designs a new dental implant modeling and preparation solution, so that dental implants that are extremely close to the patient's current dental overall condition can be prepared.

[0122] Below, as Figure 2 As shown, Figure 2 This is a flow chart of the denture modeling and preparation method, which explains the specific process of modeling and preparation of dental implant models.

[0123] Step 201: Constructing an oral cavity model.

[0124] Taking a certain number of photos of the patient's teeth is used to build a model of the patient's mouth. This step is the cornerstone of the entire modeling process and is crucial to the accuracy of subsequent analysis.

[0125] Step 202: Bad teeth identification and classification.

[0126] In this application example, bad teeth are identified in a patient's oral model, and the identification results are input into a trained recognition neural network model.

[0127] The model can identify "normal teeth" that are less affected by bad teeth and "abnormal teeth" that are more affected. In practice, bad teeth can be identified manually by a doctor or automatically using a neural network.

[0128] Furthermore, when wisdom teeth are present in the oral model and affect other teeth, special considerations are required. Wisdom teeth can alter the orientation of the central incisors, bevels, or canines, and oral models in standard model libraries typically do not consider their impact. This can result in the number of normal teeth in the constructed oral model exceeding the number of teeth in the oral model library. The number of teeth is also a key matching indicator in step 203, which can lead to a failure to match the standard oral model in step 203.

[0129] Therefore, when constructing an oral model, if wisdom teeth are present and the damaged teeth are central incisors, bevel incisors, or canines, the doctor needs to manually remove the wisdom tooth model and adjust the orientation of the teeth affected by the wisdom teeth (generally, the teeth affected by wisdom teeth will only change in orientation, and the tooth shape remains normal) to ensure the smooth progress of subsequent steps.

[0130] Step 203: Screening of standard oral cavity models (ie, the aforementioned target standard oral cavity models).

[0131] In this application example, the closest standard oral model (target standard oral model) can be selected from the standard model library based on the "normal teeth" in the oral model and patient information (such as age, gender, and region). Initial screening is performed based on the patient's objective factors (age, gender, and region), and further screening is performed based on normal tooth characteristics to obtain the closest standard oral model. This dual screening mechanism is designed to improve the matching between the screening results and the patient.

[0132] In actual applications, abnormal teeth are not suitable as the selection criteria for standard oral models because they have been affected. Therefore, this scheme only uses normal teeth as the screening criteria, and combines the patient's objective factors such as age, personality and region in the selection process to improve the matching degree between the screening results and the patient.

[0133] The standard model library is screened in two ways. The first level of screening is to select standard oral models that meet the patient's objective factors (age, gender, and region). After the first level of screening is completed, the most similar standard oral models are further screened from the first level of screening results based on the normal teeth used to construct the model, thus completing the second level of screening.

[0134] Step 204: Model difference calculation.

[0135] In this application example, the "normal teeth" in the target standard oral model selected in step 203 are compared with the "normal teeth" in the patient's oral model, and the model difference between the two is calculated (first model difference data). Because the standard model and the patient's actual model cannot be completely consistent, this difference can be regarded as a model error, and this error also exists for the teeth in other standard oral models.

[0136] Step 205: Optimize the standard tooth model.

[0137] In this application example, based on the first model difference data obtained in step 204, the standard tooth model in the standard oral model, which is located at the same position as the "abnormal tooth" and the damaged tooth, is adjusted and optimized to obtain an optimized standard tooth model. By synchronously applying the model error of the normal tooth to the tooth model at the corresponding position in the standard oral model, the tooth model is more similar to the model shape of the patient without the damaged tooth.

[0138] Step 206: Calculate the difference of the abnormal tooth model.

[0139] In this application example, the tooth model corresponding to the "abnormal tooth" in the optimized standard tooth model in step 205 is compared with the tooth model of the "abnormal tooth" in the patient's oral model to obtain the model difference between the two (second model difference data). This difference reflects the degree of impact of the bad tooth on the surrounding teeth.

[0140] In practice, the adjusted tooth models in step 205 typically closely resemble the normal model shape without the effects of bad teeth. However, due to the presence of bad teeth, these adjusted tooth models may still differ from the tooth models at the same location in the actual constructed oral model. This difference reflects the effects of bad teeth.

[0141] Step 207: Adjust the dental implant model.

[0142] According to the second model difference data obtained in step 206, decide whether to make further adjustments to the standard tooth model optimized in step 205 to obtain the final dental implant model. If the model difference is small, the optimized standard tooth model is used directly; if the difference is large, targeted adjustments are required. Specifically, the differences can be divided into two categories: positive interfering teeth (teeth that the bad teeth interfere with when the mouth is closed) and lateral interfering teeth (teeth on both sides of the bad teeth). The influence of positive interfering teeth is mainly reflected in the tooth height and tooth abutment surface. The height and abutment surface of the standard tooth model need to be adjusted according to the difference to ensure normal occlusion with the positive interfering teeth; the influence of lateral interfering teeth is mainly reflected in the crown shape. The crown shape of the standard tooth model needs to be adjusted according to the difference to make it fit the interfering teeth on both sides. For example, after the dental implant surgery, the doctor will perform initial adjustment, functional adjustment, fine adjustment of the occlusion, and adjustment based on patient feedback to ensure that the occlusal relationship between the implant and the adjacent teeth is correct.

[0143] The differences found in step 206 are divided into two categories based on their positional relationship: direct contact teeth (teeth that contact the bad tooth) and lateral contact teeth (teeth on both sides of the bad tooth). Direct contact teeth affect the adjustment of crown height and contact surface, while lateral contact teeth affect the adjustment of crown peripheral shape.

[0144] In this application example, the two types of teeth are affected by bad teeth and the adjustment logic is as follows:

[0145] The influences of the interfering teeth compared in step 206 include the influence of tooth height and the influence of the tooth abutment surface. The influence of tooth height includes causing the height of the teeth to be too high or too low. Taking the excessive height of the interfering teeth as an example, it is usually caused by the low height of the bad teeth themselves. Since the bad teeth themselves are low in height, it is easy for the interfering teeth to be too high due to the lack of tooth abutment to restrict their growth. In addition, the contact surface of the interfering teeth will also become non-standard due to the lack of a healthy tooth's abutment. In this case, step 206 needs to adjust the height of the standard tooth model corresponding to the bad tooth according to the height of the interfering teeth to ensure that the adjusted tooth height allows the oral cavity to close healthily. At the same time, it is also necessary to adjust the abutment surface of the standard tooth model according to the contact surface of the abutment teeth to ensure that the adjusted abutment surface can normally occlude with the abutment teeth.

[0146] The same applies to the situation where the tooth height affects the ground too low, which will not be elaborated here.

[0147] The impact of the lateral interfering teeth compared in step 206 is primarily used to adjust the overall crown shape. For example, if a long-term missing tooth causes the lateral interfering teeth to be too wide, the crown of the standard tooth model can be adjusted to be narrower based on the difference in the lateral interfering teeth. The overall crown shape is adjusted to ensure that it fits the interfering teeth on both sides.

[0148] In addition, after the adjustment in step 205, the fit between the tooth model and the patient's actual teeth needs to be verified again; step 206 further confirms the fit. If the difference between the models is small or no, it means that the standard tooth model can be used directly as a dental implant model.

[0149] Step 208: Dental implant preparation.

[0150] The dental implant is prepared according to the dental implant model obtained in step 207 .

[0151] Thus, this application example, through the above denture modeling and preparation method, achieves (1) when the patient's bad teeth affect other teeth, a more suitable dental implant model can be obtained. (2) The selected standard oral model has a higher degree of fit with the patient. (3) The use of a specially trained neural network can accurately distinguish between normal teeth and abnormal teeth. (4) The influence of wisdom teeth on the selection of standard tooth models is eliminated.

[0152] In some embodiments, the embodiments of the present application further provide a denture modeling and preparation system, which includes: an image acquisition module and an electronic device 300; wherein the image acquisition module is used to acquire and send the patient's tooth image data.

[0153] Here, the image acquisition device includes but is not limited to: an intraoral scanner or a three-dimensional photography device, which is used to acquire multi-angle dental images in the patient's mouth, generate and send the patient's dental image data to the electronic device 300.

[0154] Based on the hardware implementation of the above program modules, and in order to implement the method of the embodiment of the present application, the embodiment of the present application also provides an electronic device. Figure 3 Only an exemplary structure of the electronic device is shown, not all structures, and it can be implemented as needed. Figure 3 Part or all of the structure shown. Figure 3 As shown, the electronic device 300 provided in the embodiment of the present application includes: at least one processor 301, a memory 302, a user interface 303 and at least one network interface 304. The various components in the electronic device 300 are coupled together through a bus system 305. It can be understood that the bus system 305 is used to realize the connection and communication between these components. In addition to the data bus, the bus system 305 also includes a power bus, a control bus and a status signal bus. However, for the sake of clarity, Figure 3 Various buses are labeled as bus system 305 .

[0155] The user interface 303 may include a display, a keyboard, a mouse, a trackball, a click wheel, keys, buttons, a touch pad or a touch screen.

[0156] The memory 302 in the embodiment of the present application is used to store various types of data to support the operation of the electronic device. Examples of such data include: any computer program used to operate on the electronic device.

[0157] The denture modeling and preparation method for an electronic device disclosed in the embodiments of the present application can be applied to or implemented by the processor 301. The processor 301 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the denture modeling and preparation method for an electronic device can be completed by hardware integrated logic circuits or software instructions in the processor 301. The processor 301 mentioned above can be a general-purpose processor, a digital signal processor (DSP), or other programmable logic device, discrete gate or transistor logic device, discrete hardware component, etc. The processor 301 can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the embodiments of the present application can be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium located in the memory 302. The processor 301 reads the information in the memory 302 and, in conjunction with its hardware, completes the steps of the denture modeling and preparation method for an electronic device provided in the embodiments of the present application.

[0158] In an exemplary embodiment, the electronic device may be implemented by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers (MCUs), microprocessors, or other electronic components to perform the aforementioned method.

[0159] It is understood that the memory 302 can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic random access memory (FRAM), a flash memory, a magnetic surface memory, an optical disc or a compact disc read-only memory (CD-ROM); the magnetic surface memory can be a magnetic disk or. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), synchronous static random access memory (SSRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct rambus random access memory (DRRAM). The memory described in the embodiments of the present application is intended to include, but is not limited to, these and any other suitable types of memory.

[0160] It should be noted that: "first", "second", etc. are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0161] In addition, the technical solutions described in the embodiments of the present application can be arbitrarily combined without conflict.

[0162] The above are only specific embodiments of the present application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by any person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A denture modeling and preparation method, characterized in that: include: Acquire dental image data in a patient's oral cavity and personal data of the patient, wherein the personal data includes at least one of the following: age data, gender data, and patient location data; generating an oral model of the patient based on the tooth image data, and identifying teeth to be extracted, normal teeth, and abnormal teeth in the oral model; searching for a target standard oral model that matches the patient based on the identification data of the normal teeth, the patient's personal data, and a standard oral model library; wherein the number of normal teeth in the oral model is consistent with the number of normal teeth in the target standard oral model; Preliminarily optimizing the abnormal tooth model in the target standard oral model and the tooth model to be implanted corresponding to the tooth to be extracted based on first model difference data between the normal tooth model in the target standard oral model and the normal tooth model in the oral model; If the second model difference data between the abnormal tooth model in the target standard oral model after the preliminary optimization and the abnormal tooth model of the oral model is greater than or equal to the set threshold, then based on the second model difference data, the tooth model to be implanted after the preliminary optimization is secondary optimized to construct a dental implant model; Based on the dental implant model, the dental implant is prepared.

2. The method according to claim 1, characterized in that The step of identifying teeth to be extracted, normal teeth, and abnormal teeth in the oral model includes: Identifying the teeth to be extracted in the oral model; Classifying the teeth other than the teeth to be extracted in the patient's oral model based on the trained neural network-like model, and determining normal teeth and abnormal teeth among the other teeth; The normal teeth and the abnormal teeth are identified.

3. The method according to claim 1, characterized in that Generating the patient's oral cavity model based on the dental image data includes: If the tooth image data includes wisdom tooth image data, and the type of the patient's tooth to be extracted is at least one of the following: a central incisor, an oblique incisor, or a canine, obtaining an initial oral model and generating instruction information; In response to the instruction information, removing the wisdom tooth model from the initial oral cavity model; The initial oral cavity model after removing the wisdom tooth model is adjusted to generate the oral cavity model.

4. The method according to claim 3, characterized in that The adjusting of the initial oral cavity model after removing the wisdom tooth model includes: Correcting the orientation data of the teeth to be adjusted in the initial oral cavity model after the wisdom tooth model is removed, wherein the teeth to be adjusted are adjacent teeth squeezed by the wisdom teeth.

5. The method according to claim 1, wherein The step of searching for a target standard oral model that matches the patient based on the identification data of the normal teeth, the personal data of the patient, and a standard oral model library includes: Screening the standard oral model library based on the patient's personal data to determine an initial oral model library; The target standard oral cavity model is searched based on the identification data of the normal teeth and the initial oral cavity model library.

6. The method according to claim 1, characterized in that The method further comprises: If the second model difference data between the abnormal tooth model in the target standard oral model after preliminary optimization and the abnormal tooth model of the oral model is less than the set threshold, a dental implant model is constructed based on the tooth model to be implanted in the target standard oral model after preliminary optimization.

7. The method according to claim 1, characterized in that The abnormal teeth include teeth that interfere with the teeth to be extracted in the height direction when the mouth is closed. The secondary optimization of the initially optimized model of the teeth to be implanted to construct the implant model includes: Acquire tooth height difference data of the positive conflicting tooth model in the second model difference data; Based on the tooth height difference data, adjusting the tooth height of the preliminarily optimized tooth model to be implanted, so as to perform secondary optimization on the preliminarily optimized tooth model to be implanted in the target standard oral cavity model; Based on the secondary optimized tooth model to be implanted, the dental implant model is constructed.

8. The method according to claim 1, characterized in that The abnormal teeth include teeth that interfere with the teeth to be extracted in the height direction when the mouth is closed. The secondary optimization of the initially optimized model of the teeth to be implanted to construct the implant model includes: Acquiring the conflicting surface morphology difference data of the positive conflicting tooth model in the second model difference data; Based on the interference surface morphology difference data, adjusting the interference surface curvature of the preliminarily optimized tooth model to be implanted, so as to perform secondary optimization on the preliminarily optimized tooth model to be implanted in the target standard oral model; Based on the secondary optimized tooth model to be implanted, the dental implant model is constructed.

9. The method according to claim 1, characterized in that The abnormal teeth include lateral interfering teeth that interfere with the teeth to be extracted in the horizontal direction. The tooth model to be implanted after preliminary optimization is subjected to secondary optimization to construct an implant model, including: Acquire the crown morphology difference data of the lateral conflicting tooth model in the second model difference data; Based on the crown morphology difference data, adjusting the crown width and crown contour morphology data of the preliminarily optimized tooth model to be implanted, so as to perform secondary optimization on the preliminarily optimized tooth model to be implanted in the target standard oral model; Based on the secondary optimized tooth model to be implanted, the dental implant model is constructed.

10. A denture modeling and preparation system, characterized in that: The system includes an image acquisition module and an electronic device; wherein the image acquisition module is used to acquire and send the patient's dental image data; the electronic device includes: a processor and a memory for storing a computer program that can be run on the processor, wherein, The processor is configured to execute the steps of the method according to any one of claims 1 to 9 when running a computer program.

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