Method and analysis system for generating digital 3D model of patient dentition

Abstract

The invention relates to a method for generating a digital 3D model of a patient's dentition. According to the invention, for a plurality of dentition variants, each comprising a combination of a digital 3D model of the patient's maxillary and a digital 3D model of the lower jaw, which 3D models differ from each other at the relative positioning of the maxillary and the lower jaw, each of the following steps being performed in a computing unit:-combining the digital 3D model of the patient's maxillary and the digital 3D model of the lower jaw, the upper jaw and the lower jaw are in contact with each other at a number of contact points, and sections of the upper jaw and the lower jaw do not have any spatial overlap, and determining a contact surface between the upper jaw and the lower jaw, taking into account said contact surface, selecting an optimized dentition variant as a 3D model of the dentition.

Description

[0001] The present invention relates to a method for generating a digital 3D model of a patient's dentition and an analysis system suitable for carrying out the method, in particular for planning dental prostheses.

[0002] When planning dental prostheses, for orthodontic planning or in other areas of modern dental technology, in particular in order to improve the basis for decisions in dentistry and dental technology or as a starting point for the use of CAD / CAM processes, the adjustment and analysis of the patient's initial dental condition or intermediate or final checks on treatment can be based on existing or digitally recorded data that accurately reflect the dental condition.

[0003] For example, in modern dental care concepts, prostheses (such as crowns and / or implant-supported dentures, bridges or similar devices) are usually made by reproducing the patient's oral condition as accurately as possible to achieve the best possible fit and, in addition to achieving the desired medical effect, provide the patient with the best possible wearing comfort. In traditional treatment, the patient's teeth are usually impressed using some kind of tool, impression material or other hardening substance to generate a negative mold that reflects the actual situation. For example, such a negative mold can be used to make a plaster model. The plaster model can be used as a basis for planning the production and insertion of dental prostheses. These models can then be digitized using, for example, an extraoral 3D scanner so that the finished dental product can then be produced using digital technology (CAD / CAM).

[0004] In more modern concepts, the patient's oral condition is digitally recorded, for example using an intraoral scanner to capture three-dimensional patient data reflecting the patient's oral condition. This three-dimensional data can then be used to generate a 3D model of the patient's teeth (e.g., 3D printing), and treatment strategies and dentures can then be planned for the patient using digital methods, significantly faster and more cost-effectively than before. In particular, this digital planning allows the automated manufacture of the desired dental prosthesis using the transferable 3D data.

[0005] However, these digitization methods currently have serious limitations. Due to the nature of the technology, as well as the technical capabilities and limitations of the scanners used to acquire 3D patient data from within the patient's mouth, only the patient's upper and lower jaws can be acquired separately. Consequently, after scanning the oral cavity (e.g., using an intraoral scanner), the data is only available in the form of a digital 3D model of the patient's upper jaw on the one hand and a digital 3D model of the patient's lower jaw on the other. In order to accurately reproduce the patient's entire oral cavity, these two partial models must be combined so that they are as close to the actual oral condition as possible.

[0006] This combination of digital 3D models of the patient's upper jaw and lower jaw is called an "articulation." Articulation is a crucial starting point for all subsequent steps in dentistry to proceed at a reasonable level and with a quality acceptable to the patient. Until now, technical devices used for this purpose, such as intraoral and extraoral 3D scanners for acquiring digital dental models, have been unable to produce sufficiently accurate articulations.

[0007] The current technology starts with the digitization of individual jaws, followed by manual alignment of the occlusion. The individual jaw scan is then compared (matched) with the occlusion scan to align them accordingly. Z-axis offsets are often used to eliminate any intersections or overlaps between the two jaws. However, this approach is generally unsatisfactory, as the jaws can be offset not only along the Z axis but also along the condylar path, making the method incomplete. This leads to high error rates in the subsequent process chain from CAD (design) to CAM (production).

[0008] The object of the present invention is therefore to provide a method for generating a digital 3D model of a patient's dentition, in particular for planning dental prostheses, which method allows the generation of a complete digital 3D model of the patient's dentition in an extremely reliable and high-quality manner using existing digital 3D models of the patient's upper and lower jaws. Furthermore, an automated analysis system particularly suitable for carrying out this method is to be specified.

[0009] With regard to the method, the object is achieved according to the invention by combining in a computing unit a plurality of dental variants, each comprising a combination of a digital 3D model of the patient's upper jaw with a digital 3D model of the lower jaw, which differ from one another with regard to the relative positioning of the upper and lower jaws, in each case:

[0010] - combining the digital 3D model of the upper jaw with the digital 3D model of the patient's lower jaw so that the upper and lower jaws fit together at many contact points without any spatial overlap (commonly referred to in practice as "penetration"); and

[0011] - determine the contact surface between the maxillary and mandibular parts,

[0012] In this process, the optimized denture variant is selected as the 3D model of the denture, taking the contact surfaces into account.

[0013] The present invention is based on the consideration that a dental model consisting of two parts, the upper and lower jaw, can be considered to have a very high "fitting accuracy" if the two parts fit together as closely as possible, thereby reproducing the patient's actual oral condition as realistically as possible. Therefore, according to one aspect of the present invention, the contact surfaces where these parts touch each other are considered to be a particularly suitable criterion for fitting accuracy and are therefore taken into account.

[0014] According to one aspect of the present invention, which is considered to be independently inventive, the static friction generated by the planned displacement of the maxillary and mandibular components relative to each other can also be used as a basis for determining the accuracy of the fit. This is primarily described in terms of the contact surfaces, but for a more comprehensive evaluation, the contribution of each surface element to the static friction can be individually weighted based on its angle of inclination relative to the planned displacement direction of the components relative to each other. For example, surface elements with a relatively strong inclination relative to the displacement direction can be weighted with an increased contribution to the static friction because their shape alone means they offer a greater resistance to the planned displacement than relatively flat surface elements.

[0015] According to one aspect of the present invention, which is considered to have an independent inventive step, multiple dentition variants corresponding to temporal sequences during mastication can be taken into account when selecting a 3D model of the dentition. This is particularly intended to ensure that not only static aspects but also dynamic aspects—those occurring during mastication—are considered when selecting the 3D model. Surprisingly, it has been found that these aspects can be particularly important for the patient's care and comfort when wearing a custom prosthesis.

[0016] According to further aspects of the present invention, different contributions to the friction between teeth can be appropriately considered. For example, the friction contributions can include contact friction (tooth enamel), fluid friction (saliva), and morphology-related interlocking effects.

[0017] Advantageously, the evaluation of dentition variants also takes into account those dentition variants in which the inclination of the maxilla relative to the mandible is different. This allows six degrees of freedom to be taken into account when combining the two elements, the maxilla and the mandible.

[0018] According to an aspect of the present invention, a tooth variant in which the contact surface between the upper jaw and the lower jaw has a maximum value may be selected as the 3D model of the dentition.

[0019] Artificial intelligence is particularly preferred for generating dentition variants and / or determining the dentition variant to be selected. This is based on the consideration that due to the complex frictional relationships between teeth (static friction, fluid friction, interlocking effects, etc.), determining the optimal locking point or optimal combination of the maxillary and mandibular models is difficult using traditional modeling. Therefore, according to one aspect of the present invention, a neural network is used to learn the required friction conditions based on examples.

[0020] According to aspects of the present invention that are considered to be independently inventive, the articulation algorithm utilizes artificial intelligence to apply various modern computer graphics techniques to the 3D model of the tooth structure in a preliminary analysis step. To this end, filters can be used to detect extreme points and edges, and selective smoothing with the aid of partial differential equations can be employed to detect relevant tooth regions. Furthermore, principal component analysis and pattern recognition can be used to identify relevant geometric structures. The primary goal of the preliminary analysis is to extract as much information as possible about patterns, edges, and geometric structures from the 3D model.

[0021] According to one aspect of the present invention, a hypercube-based neural evolution algorithm for topology enhancement can be trained in a second step based on the information obtained during the initial analysis. For example, 1,875 training examples are used to teach the algorithm how to accurately calculate occlusion. According to one aspect of the present invention, the key concept of this second step is to train the neural network to determine the correct occlusion. Throughout the learning process, the neural network is advantageously extended to allow it to adapt its topology. This flexibility enables it to effectively use and combine the information obtained during the initial analysis, thereby increasing the neural network's freedom in learning and calculating the correct occlusion.

[0022] According to aspects of the present invention, various filters and techniques in the field of computer graphics can be used to extract relevant information from the 3D model. Subsequently, a special neural network can be advantageously trained to calculate the occlusion based on the extracted information.

[0023] In addition to AI-driven static occlusion evaluation, dynamic occlusion can also be determined by AI-supported tooth surface shape analysis. Here, hypercube-based algorithms are also advantageously used to enhance the neural evolution of topology. In addition, possible jaw joint movements can be described by a system of differential-algebraic inequalities. From the perspective of Bayesian statistics, the system of differential-algebraic inequalities forms a priority distribution. According to one aspect of the present invention, this distribution is continuously improved by AI using information derived from the tooth shape, thereby gradually approaching the limits that can be achieved from the information-theoretic perspective.

[0024] With regard to an automatic analysis system for planning dental prostheses, the aforementioned task is solved by comprising:

[0025] A first computing device comprising a memory storing non-transitory instructions that, when executed by one or more processors of the first computing device, cause the first computing device to:

[0026] reading the digital 3D models of the upper jaw and the lower jaw from a second computing device, wherein the second computing device includes a mass storage device in which the digital 3D model of the upper jaw of the patient and the digital 3D model of the lower jaw of the patient are stored,

[0027] For a plurality of dental variants, each comprising a combination of a digital 3D model of the patient's upper jaw and a digital 3D model of the lower jaw, which differ from each other in terms of the relative positioning of the upper and lower jaws, in each case:

[0028] - combining the digital 3D model of the upper jaw with the digital 3D model of the patient's lower jaw so that the upper and lower jaws fit together at many contact points without any spatial overlap, and

[0029] - determine the contact surface between the maxillary and mandibular parts,

[0030] And, taking the contact surfaces into account, an optimized dentition variant is selected as the 3D model of the dentition.

[0031] Preferably, the non-transitory commands, when executed by the one or more processors of the first computing device, cause the first computing device to take into account dentition variants having different inclinations of the upper jaw relative to the lower jaw.

[0032] Preferably, when executed by one or more processors of the first computing device, according to an aspect of the invention, the non-transitory command causes the first computing device to select as the 3D model of the dentition the dentition variant in which the contact surfaces of the maxillary and mandibular teeth have a maximum value.

[0033] In particular, according to one aspect of the present invention, a concept is provided for fully automated simulated occlusal determination and finding the most perfect occlusion between two digital dental models. The underlying algorithm preferably processes two digital models (for the maxillary and mandibular in any orientation) and determines the perfect occlusion by simulating jaw movement. For alignment, according to one aspect of the present invention, a self-learning algorithm is used that finds a basic alignment based on a number of digital models.

[0034] In one aspect of the invention, it is possible to provide for positioning the model in a patient-specific 3D image (DVT, MRI, CT) and for calculating the joint positioning based on the results calculated by the aforementioned static articulation algorithm.

[0035] According to one aspect, which is considered to be independently inventive, a 3D model of the dentition determined and selected according to the above concept can be used to make a basis for a dental prosthesis.

[0036] In an advantageous embodiment, further algorithms can be used individually or in combination with one another as required:

[0037] -Repair model

[0038] - Close holes and remove or reduce artifacts

[0039] - Reduce file size with virtually no loss using proprietary compression algorithms (faster CAD processing, storage efficiency, etc.)

[0040] -Alveolar socket / direct printing

[0041] - Models are sealed and waterproof, and file names are engraved (+ aligned) so that they can be sent directly to a 3D printer for production space models

[0042] -Dynamic occlusion

[0043] All possible mandibular movements are simulated based on the Bennett angle, condylar trajectory, and wear surface. According to one aspect of the invention, motion ("ISS" - immediate lateral shift) can also be taken into account. The output can advantageously be in XML file format, enabling further processing in CAD software to design the denture taking individual movements into account.

[0044] - The VDO can be calculated taking into account the jaw movement. This can be an important component in the design of bite plates, occlusal surfaces or other restorations / appliances that require / actively influence the VDO.

[0045] The advantages achieved by the present invention are as follows:

[0046] - Significantly improve efficiency in laboratories and dental clinics (= reduce time losses)

[0047] - Significantly reduced scrap rates, leading to lower production costs and lower material consumption

[0048] - Improve automation (reducing costs and speeding up delivery)

[0049] -Addresses skilled labor shortages as the software is easy to use and provides automated quality control

[0050] - Significantly improved quality (patients no longer need to visit the doctor or receive follow-up treatment due to inaccurate denture fit)

[0051] -Fills a gap in the complete digital workflow (currently labs still have analog intermediate steps that require manual adjustments)

[0052] According to further aspects, each of which is considered to be independently inventive, the described concepts may be supplemented by:

[0053] - Integration of 2D and / or 3D X-ray images of the patient's dental condition. This allows to specifically enrich and supplement the information intended for artificial intelligence in order to further improve the results.

[0054] - Integrate clinical photographs or 3D facial scans to determine joint positions with sufficient accuracy

[0055] - Check final CAD designs using static and dynamic data as automatic quality control and assign them an evaluation grade, which then triggers further automatic or manual steps.

[0056] - Automatic docking to the physical (articulator) by adjusting the 3D base through dynamics and statics.

[0057] -Simulate further chewing movements

[0058] - Use algorithm to calculate bite force

[0059] - Automatic integration of additional patient-related data or documents (new scans, scanned body scans, ...)

[0060] -Generate bite reports with contact point comparison (preferably before / after)

[0061] - Specifications / instructions for subsequent design

[0062] -Automatically optimize crown position based on contact and dynamics

[0063] -Simulate the movement and span of the mandibular crown through dynamics

[0064] - "4D Jaw Movement Over Time". Simulates jaw movement over several years to visualize the effects on tooth substance (this can show patients the effects of molar changes over time and motivate them to take further treatment steps, such as using a molar bite splint).

[0065] - Generate the desired intercuspation / contact point distribution and based on this generate a molar plan (2D or 3D file for production) to eliminate the early contacts that would prevent this situation from becoming the current one.

[0066] -Use habitual jaw movements from dental or prosthetic conditions to develop customized subsequent prostheses

[0067] -Automatic occlusal design based on the situation and jaw movement to define the new bite position.

[0068] -Model quality control (scanning 3D models and automatically comparing and scoring them with 3D CAD models)

[0069] - Monitoring (comparison and action recommendations over time based on model changes, e.g. during annual dental check-ups. Indication of changes, wear surface, etc.)

[0070] Further advantageous aspects of the present invention may include, for example, embodied in the form of corresponding modules or integrated functions:

[0071] "Transformation Preservation" module: This module provides the option of reading only the vertices from a 3D format and manipulating them using rotation matrices. In practice, rotation matrices are precisely the transformations required to achieve occlusion. The idea considered to be independently innovative here is that the 3D format does not need to be completely resaved, as additional information, such as color, may be lost in the process. It is also possible to transform "additional" models (such as bridges) into occlusal models.

[0072] - Provide a marking function in the GUI (Graphical User Interface): This allows the user to specify whether certain areas should be engaged or ignored. This gives the user the opportunity to influence the occlusion calculation; for example, they can mark the gingiva and thereby allow for greater penetration in the gingival area (the gingiva retracts when occluding).

[0073] - Option to adjust penetration depth: This allows the user to set a maximum penetration depth and thereby generate more / larger or fewer / smaller contacts.

[0074] - Option for bite raise based on dynamic occlusal data.

[0075] - Provide reports (e.g., in the form of videos) comparing before and after situations based on touchpoints and evaluating them using metrics.

[0076] In particular, different articulation algorithms are available from which the user can choose:

[0077] - If the model is already close to occlusion, a local algorithm can be used to restrict the allowed movement of the mandible to the occlusal position.

[0078] -If the model is far from occlusion, a global algorithm can be used that does not restrict the allowed motion.

[0079] The "Bite-Finder" concept described above thus enables the use of an intraoral scanner to scan both the maxillary and mandibular surfaces with their corresponding dentition, eliminating the need for a third bite scan that would otherwise be necessary. The "Bite-Finder" concept is therefore an innovative concept that simplifies the creation of digital 3D models of a patient's bite, transforming dental clinics and laboratories. This technology is revolutionizing the dental industry by providing more efficient, accurate, and cost-effective methods for bite analysis, adjustment, and treatment planning. According to aspects of the present invention, it comprises the following key components:

[0080] Occlusal data acquisition:

[0081] The Bite Finder loads a digital 3D model of the patient's upper and lower jaws. This data can be acquired using various methods, such as an intraoral scanner or 3D dental imaging.

[0082] AI-Powered Alignment:

[0083] A unique and innovative aspect of the BiteFinder is its AI-powered alignment feature. Once digital models of the maxilla and mandible are acquired, the system uses sophisticated algorithms to align them with unparalleled precision. Unlike traditional methods that rely solely on Z-axis adjustments, the BiteFinder considers all degrees of freedom, including translation and rotation, ensuring a seamless fit between the maxilla and mandible.

[0084] Bite and penetration analysis:

[0085] According to one aspect of the present invention, the Bite Finder performs a detailed analysis of the aligned models to identify occlusion and penetration issues. Through comprehensive simulation and calculations, the system determines the optimal bite position by adjusting the contact points between the teeth. This process ensures a perfectly harmonious bite for the patient, resulting in improved comfort and better treatment outcomes.

[0086] Dynamic occlusion simulation:

[0087] In addition to static occlusal adjustments, one aspect of the present invention provides the possibility of dynamic occlusal simulation. This can replicate patient-specific jaw movements, allowing dentists and dental technicians to assess how the occlusal function works during real-life activities such as chewing and speaking. This feature improves the accuracy of restorative treatment and appliance design.

[0088] Automation model improvements:

[0089] The Occlusion Finder does much more than just occlusion correction. It can repair models, close holes, remove artifacts, reduce file size using a proprietary compression algorithm, and even prepare models for 3D printing. These features contribute to a streamlined and efficient workflow.

[0090] Quality Control and Assurance:

[0091] To maintain high quality standards, the Bite Finder features automatic quality control. This ensures that bite adjustments and models comply with industry and clinical standards.

[0092] Additionally, predictions can be made regarding the development of the wearing surface or wear.

[0093] Specific benefits and advantages of the present invention can be seen in particular in:

[0094] Accuracy: AI-driven alignment and analysis enable highly precise bite correction and reduce the risk of rework and errors.

[0095] Efficiency: By automating complex processes, Occlusion Finder significantly reduces the time required for occlusal analysis and treatment planning.

[0096] Cost-effectiveness: Fewer manual adjustments, lower material waste, and more efficient workflows save money for dental offices and laboratories.

[0097] Patient comfort: Due to precise occlusal adjustment, patients feel more comfortable during treatment.

[0098] Versatility: The bite finder can be used in a variety of dental specialties, from general dentistry to orthodontics and prosthodontics.

[0099] As described in one aspect of the present invention, the BiteFinder concept is a groundbreaking innovation that brings efficiency, accuracy, and affordability to the dental industry. By combining digital technology, AI algorithms, and 3D modeling, it simplifies the process of generating accurate 3D occlusal models, ultimately improving patient care and the quality of dental treatment. With the BiteFinder, dentists and dental technicians can work more efficiently and provide superior dental solutions for their patients.

[0100] process:

[0101] - View preview and send to lab for use (and payment)

[0102] According to one aspect of the present invention, the following may be considered to be inventive:

[0103] A method for generating a digital 3D model of a patient's occlusion, comprising:

[0104] a. Use one or more imaging devices to acquire digital 3D models of the patient's upper and lower jaws.

[0105] b. Use artificial intelligence algorithms to align the digital 3D models of the maxilla and mandible, taking into account translation, rotation, and degrees of freedom.

[0106] c. Perform bite and penetration analysis to determine the optimal bite position by adjusting the contact points between the teeth.

[0107] d. Generate dynamic occlusal simulations to replicate patient-specific jaw movements for bite analysis.

[0108] The following additional features may also be provided:

[0109] Repair digital models, close holes, and remove artifacts to improve model quality and / or

[0110] Use a proprietary compression algorithm to reduce file size while maintaining model integrity.

[0111] Some aspects wherein dynamic occlusal simulation includes replicating real-life activities, such as chewing and speaking, to evaluate occlusal function. And / or

[0112] Automated preparation of digital models for 3D printing and / or

[0113] Perform automated quality control checks to ensure that the occlusal adjustments and models meet pre-defined quality standards and / or

[0114] Computer program product comprising computer readable instructions stored on a non-transitory computer readable medium for executing the above method and / or

[0115] Artificial intelligence control system for generating a digital 3D model of the patient's bite, including

[0116] a. One or more imaging devices for acquiring digital 3D models of the patient's upper and lower jaws.

[0117] b. A processing unit configured to align the digital 3D models of the maxillary and mandibular jaws using an artificial intelligence algorithm, taking into account translations, rotations, and degrees of freedom.

[0118] c. Analysis module for performing occlusion and penetration analysis to determine the optimal occlusal alignment by adjusting the contact points between the teeth.

[0119] According to aspects of the present invention, it can be supplemented by:

[0120] Dynamic Simulation Module for generating dynamic occlusal simulations to replicate patient-specific jaw movements for occlusal analysis, and / or

[0121] A quality control module for automated quality control checks to ensure that the occlusal adjustments and models meet pre-defined quality standards, and / or

[0122] Modules for repairing digital models, closing holes, and removing artifacts to improve model quality, and / or

[0123] module to reduce file size using a proprietary compression algorithm while maintaining model integrity, and / or

[0124] In one aspect, the dynamic simulation module provides the ability to simulate real-life activities such as chewing and speaking to evaluate bite function and / or

[0125] Modules for automating the preparation of digital models for 3D printing, and / or

[0126] User interface for dental professionals to interact with the system.

[0127] Further advantages of the present invention can be seen in:

[0128] 1. Improved Precision: The Bite Finder uses advanced artificial intelligence (AI) algorithms to ensure highly accurate bite adjustments and reduce the risk of errors and re-dos.

[0129] 2. Improved efficiency: The system significantly reduces the time required for occlusal analysis and treatment planning, improving the efficiency of the entire workflow.

[0130] 3. Cost savings: Fewer manual adjustments, lower material waste, and improved workflow efficiency save costs for dental clinics and laboratories.

[0131] 4. Improve patient comfort: Precise occlusal adjustment improves patient comfort during surgery and treatment.

[0132] 5. Versatility: The bite finder can be used in a variety of dental specialties, from general dentistry to orthodontics and prosthodontics, making it a versatile tool for dentists.

[0133] 6. Streamlined workflow: The system automates complex processes such as model repair, cavity filling, artifact removal, and file size reduction, simplifying the workflow for dentists and dental technicians.

[0134] 7. Automated Model Preparation: Bite Finder automates the preparation of digital models for 3D printing, saving time and reducing the need for manual intervention.

[0135] 8. Quality Control: Automated quality control ensures that occlusal adjustments and models meet industry and clinical standards, reducing the possibility of suboptimal results.

[0136] 9. Reduced Errors: By minimizing manual intervention and reliance on human judgment, the Bite Finder reduces the potential for human error and achieves more consistent results.

[0137] 10. Cost-effective CAD / CAM processing: Proprietary compression algorithms reduce file size without compromising model quality, enabling more cost-effective CAD / CAM processing.

[0138] 11. Addressing Industry Challenges: Bite Finder addresses existing challenges in the dental industry, such as the need for more accurate bite modeling and the demand for automation to offset labor shortages.

[0139] 12. Improved treatment planning: The dynamic bite simulation feature allows dentists to evaluate bite function during real-life activities such as chewing and speaking, thereby improving treatment planning.

[0140] 13. Patient Satisfaction: Precise occlusal adjustment improves the fit and comfort of the appliance, thereby increasing patient satisfaction and reducing post-treatment complaints.

[0141] 14. Real-time feedback: Dentists can receive real-time feedback on bite adjustments and treatment planning, enabling rapid adjustments and improvements.

[0142] 15. Versatile Applications: The bite finder can be used in a variety of dental procedures, including restorative treatments, orthodontics, implantology, and more, making it a valuable tool for a range of dental practices.

[0143] 16. Integration capabilities: The system can be integrated with other dental technologies (such as 2D and 3D imaging, clinical photos and facial scans) to enrich information and improve results.

[0144] 17. Potential for further innovation: The modular design of the BiteFinder allows for the integration of additional algorithms and features, which may pave the way for further innovations in the field of dentistry.

[0145] Preferred fields of application and areas of use can be found in:

[0146] 1. Restoration:

[0147] Precise bite correction for crowns, bridges and prostheses.

[0148] Evaluation and correction of occlusal deviations in prosthetic treatment.

[0149] 2. Orthodontics:

[0150] Evaluate occlusal relationships in orthodontic cases.

[0151] Simulate jaw movement to plan orthodontic treatment.

[0152] 3. Implantology:

[0153] Analyze the occlusal fit of implant-supported restorations.

[0154] Ensures optimal occlusion for implant planning.

[0155] 4. Restorative Dentistry:

[0156] Perform bite analysis for restorative procedures such as fillings and veneers.

[0157] Check the occlusal fit of the restorative material.

[0158] 5. Occlusion analysis:

[0159] Comprehensive occlusal analysis to identify occlusal deviations.

[0160] Identify and correct occlusal interferences.

[0161] 6. Temporomandibular joint disorder (TMJ):

[0162] To evaluate jaw movements and occlusal relationships in cases of temporomandibular joint disorders.

[0163] Plan treatment to address jaw joint problems.

[0164] 7. Treatment planning:

[0165] Simulate occlusal function during treatment planning.

[0166] Optimize treatment planning based on dynamic occlusal analysis.

[0167] 8. Post-treatment evaluation:

[0168] Check bite accuracy and comfort after dental treatment.

[0169] Adjustments and refinements are made based on post-treatment occlusal analysis.

[0170] 9. Prosthetic restorations:

[0171] The Bite Finder can be used to optimize the fit and comfort of a variety of prosthetic restorations, including full-arch reconstructions and partial dentures.

[0172] 10. Removable appliances:

[0173] Analyze occlusal relationships in removable appliances such as partial dentures.

[0174] Ensure a comfortable fit for patients wearing removable dentures.

[0175] 11.Quality Control:

[0176] Ongoing quality control is performed in the dental laboratory to verify the accuracy of the digital models.

[0177] Identify and correct problems in the digital model before they cause clinical problems.

[0178] 12. Dental Education:

[0179] To train and educate dental students and professionals in occlusal analysis and adjustment.

[0180] Simulate and teach occlusion-related concepts in a virtual environment.

[0181] 13. Integration with CAD / CAM:

[0182] Integrate with computer-aided design and computer-aided manufacturing (CAD / CAM) for a seamless digital workflow in the dental laboratory.

[0183] 14. Collaboration with other professionals:

[0184] Facilitates collaboration between dentists (e.g., orthodontists, prosthodontists, and oral surgeons) by providing a common digital platform for occlusal analysis.

[0185] 15. Research and Development:

[0186] Support dental research and development by providing accurate occlusal modeling and analysis capabilities for research and experimentation.

[0187] 16. Post-traumatic cases:

[0188] Assess and correct bite problems caused by dental trauma.

[0189] Restoring occlusal function and esthetics in post-traumatic cases.

[0190] 17. Pediatric Dentistry:

[0191] Analyze and adjust the bite of pediatric patients undergoing various dental procedures.

[0192] Ensures accurate bite and alignment for growing children.

[0193] 18. Multidisciplinary Cases:

[0194] Participates in complex multidisciplinary cases where multiple dentists are involved in treatment planning and delivery.

[0195] 19. Continuous Monitoring:

[0196] Continuous occlusal monitoring of patients wearing dentures to ensure long-term comfort and effectiveness.

Claims

1. A method for generating a digital 3D model of a patient's dentition, wherein: In the computing unit, for a plurality of dentition variants, each of which comprises a combination of a digital 3D model of the patient's upper jaw and a digital 3D model of the lower jaw, and which differ from one another in terms of the relative positioning of the upper jaw and the lower jaw, the following is performed in each case: - combining the digital 3D model of the upper jaw with the digital 3D model of the patient's lower jaw so that the upper jaw and the lower jaw fit together at multiple contact points without any spatial overlap between the upper jaw and the lower jaw, and - determining the contact surface between the upper jaw and the lower jaw, Therein, taking the contact surfaces into account, an optimized dentition variant is selected as the 3D model of the dentition.

2. The method according to claim 1, wherein Dental variants in which the inclinations of the upper jaw relative to the lower jaw differ from one another are taken into account.

3. The method according to claim 1 or 2, wherein: The dentition variant is selected in which the contact surface between the upper jaw and the lower jaw has a maximum value.

4. The method according to any one of claims 1 to 3, wherein A plurality of dentition variants corresponding to time sequences in chewing movements are taken into account for selecting a 3D model of the dentition.

5. The method according to any one of claims 1 to 4, wherein Generating the dentition variant and / or determining the dentition variant to be selected is performed with the aid of artificial intelligence.

6. Automatic analysis system, in particular for carrying out the method according to any one of claims 1 to 5, comprising: A first computing device comprising a memory storing non-transitory instructions that, when executed by one or more processors of the first computing device, cause the first computing device to: The digital 3D models of the upper jaw and the lower jaw are read from a second computing device, wherein the second computing device includes a large-capacity storage device in which the digital 3D model of the upper jaw of the patient and the digital 3D model of the lower jaw of the patient are stored. For a plurality of dental variants, each dental variant comprises a combination of a digital 3D model of the upper jaw and a digital 3D model of the lower jaw of the patient, which differ from each other in terms of the relative positioning of the upper jaw and the lower jaw with respect to each other, in each case: - combining the digital 3D model of the upper jaw with the digital 3D model of the patient's lower jaw so that the upper jaw and the lower jaw fit together at a number of contact points without any spatial overlap between the upper jaw and the lower jaw, and - determining the contact surface between the upper jaw and the lower jaw, And, taking the contact surfaces into account, selecting an optimized dentition variant as the 3D model of the dentition.

7. The system according to claim 6, wherein: When executed by one or more processors of the first computing device, the non-transitory command causes the first computing device to select, as the 3D model of the dentition, a dentition variant in which the contact surface of the maxillary and mandibular contact surfaces has a maximum value.

8. The system according to claim 6 or 7, wherein: When executed by one or more processors of the first computing device, the non-transitory commands cause the first computing device to take into account dentition variants in which the inclinations of the upper jaw relative to the lower jaw differ from each other.

9. The system according to any one of claims 6 to 8, wherein: The non-transitory commands, when executed by one or more processors of the first computing device, cause the first computing device to take into account a plurality of dentition variants corresponding to a temporal sequence in a chewing motion to select a 3D model of the dentition.

10. Use of the 3D model of the dentition selected according to the method of any one of claims 1 to 5 as a basis for producing a dental prosthesis.