Method and device for determining final occlusion position, terminal and storage medium

Abstract

The invention provides a method and device for determining a final occlusion position, a terminal and a storage medium. The method for determining the final occlusion position comprises the following steps: acquiring stereolithography data of a three-dimensional image of a dentition and / or a dentale segment of a patient; carrying out preprocessing on the stereolithography data; marking mark points of the dentition based on the preprocessed stereolithography data; acquiring predicted mark points of the dentition based on the mark points of the dentition by using an occlusion model; on the basis of the prediction mark points, matching the three-dimensional images of the dentitions corresponding to the prediction mark points to the final occlusion position, and detecting tooth surface collision between the dentitions of different blocks or between the upper and lower jaw dentitions; and when collision occurs, adjusting the position of the predicted mark point of the dentition, and determining the adjusted position of the mark point of the dentition as the final occlusion position. According to the method and the device, the final occlusion position can be automatically and intelligently determined and predicted, and the manual operation cost is greatly reduced while the accuracy is ensured.

Description

Technical Field

[0001] The present disclosure relates to the field of information technology, and in particular to a method and device, a terminal and a storage medium for determining a terminal occlusal position. Background Art

[0002] Skeletal maxillofacial deformity is a disease caused by abnormal jaw growth and development, which leads to abnormal jaw volume and shape, thus affecting the occlusal function and appearance. Orthognathic surgery can treat occlusal disorders, improve facial contours, and correct deformities by changing the position of the upper and lower jaws. Among them, determining the final occlusal position is an important step in the design of orthognathic surgery, which can ensure a good postoperative occlusal relationship and determine the relative position relationship between the upper and lower jaws.

[0003] With the development of digital technology, the application of digital surgical simulation design is becoming more and more extensive. The method of establishing the final occlusal position has also progressed from matching the occlusion on the dental model and then scanning and matching to matching the occlusal relationship in a virtual environment. The final occlusal position can be obtained by moving the upper and lower jaw bone segments to the desired relative position on the digital platform and checking that there is no overlapping between the tooth surfaces of each tooth bone segment. With the advancement of technology, the research on automatic prediction of orthognathic surgery plans is increasing. However, these studies are limited to the changes in jaw morphology and appearance, and there is no precise matching of the postoperative occlusal relationship of the patient. Therefore, the main treatment goal of orthognathic surgery, "restoring occlusal function", cannot be achieved. This has limited the clinical application of the above studies and they are only at the technical level. Therefore, it is very necessary to establish a method for automatic terminal occlusal position establishment in orthognathic surgery, which can not only supplement the limitations of the existing automatic prediction of orthognathic surgery plans, but also save labor costs in the current conventional orthognathic surgery design.

[0004] There are currently two main methods for determining the final occlusal position of orthognathic surgery. The most common method is to obtain the dental model in the patient's mouth, match the plaster model to determine the final occlusal position, and then scan it to the digital platform and obtain it through registration; the other is to directly move the positions of different tooth-bone segments on the digital platform and match the final occlusal position according to the needs of orthognathic surgeons and orthodontists. The first method is relatively time-consuming and requires the patient to cooperate with a series of processes such as taking dental models, preparing plaster casting, polishing and correction, model truncation and matching, scanning, and matching. It takes about 1 hour and will introduce errors in multiple steps. The second method is to directly use the original data to segment and move the dentition and / or tooth-bone segments, which can quickly adjust the tooth position and the relative relationship between the upper and lower tooth-bone segments. It is faster than the first method and introduces less errors. However, this method requires the operator to have proficient software operation skills and the ability to abstractly match the digital platform and actual occlusion, and requires high experience. Summary of the invention

[0005] In order to solve the existing problems, the present disclosure provides a method and device, a terminal and a storage medium for determining a terminal occlusal position.

[0006] The present disclosure adopts the following technical solutions.

[0007] An embodiment of the present disclosure provides a method for determining a terminal occlusal position, the method for determining a terminal occlusal position comprising: obtaining stereolithography data of a three-dimensional image of a patient's dentition and / or tooth bone segment; preprocessing the stereolithography data; marking landmark points of the dentition based on the preprocessed stereolithography data; using an occlusal model to obtain predicted landmark points of the dentition based on the landmark points of the dentition, wherein the occlusal model is obtained by: constructing a neural network model; taking the landmark points of the upper and lower dentition before surgery and the block labels of each landmark point as input, taking the landmark points of the upper and lower dentition in terminal occlusion after surgery as output, minimizing the landmark point displacement error and synchronizing the landmark points; The neural network model is trained with the displacement consistency of the landmark points of a block as a constraint condition to obtain the occlusion model; based on the predicted landmark points, the three-dimensional image of the dentition corresponding to the predicted landmark points is matched to the terminal occlusal position, and the collision of the tooth surfaces between the dentitions of different blocks or between the upper and lower dentitions is detected; when the tooth surfaces between the dentitions of different blocks or between the upper and lower dentitions collide, the preset vectors of the positions of all blocks are changed, and the positions of the predicted landmark points of the dentition are adjusted by iterative optimization until there is no collision of the tooth surfaces between the dentitions of different blocks or between the upper and lower dentitions, and the positions of the adjusted dentition landmark points are determined as the final terminal occlusal position.

[0008] Another embodiment of the present disclosure provides a device for determining a terminal occlusal position, the device comprising: a data acquisition module configured to acquire stereolithography data of a three-dimensional image of a patient's dentition and / or tooth bone segment; a preprocessing module configured to preprocess the stereolithography data; a marking module configured to mark the landmark points of the dentition based on the preprocessed stereolithography data; a prediction module configured to acquire predicted landmark points of the dentition based on the landmark points of the dentition using an occlusal model, wherein the occlusal model is obtained by: constructing a neural network model; taking the landmark points of the upper and lower dentition before surgery and the block labels of each landmark point as input, taking the landmark points of the upper and lower dentition in terminal occlusion after surgery as output, and taking the landmark points displacement error as output; The neural network model is trained with the minimization of the difference and the consistency of the displacement of the landmark points in the same block as constraints to obtain the occlusion model; a detection module is configured to match the three-dimensional image of the dentition corresponding to the predicted landmark points to the terminal occlusal position based on the predicted landmark points, and detect the collision of the tooth surfaces between the dentitions of different blocks or between the upper and lower dentitions; an adjustment module is configured to change the preset vectors for the positions of all blocks when a collision occurs between the tooth surfaces of the dentitions of different blocks or between the upper and lower dentitions, and adjust the positions of the predicted landmark points of the dentition by iterative optimization until there is no collision between the tooth surfaces of the dentitions of different blocks or between the upper and lower dentitions, and determine the positions of the adjusted dentition landmark points as the final terminal occlusal position.

[0009] In some embodiments, the present disclosure provides a terminal, comprising: at least one memory and at least one processor; wherein the memory is used to store program codes, and the processor is used to call the program codes stored in the memory to execute the above-mentioned method for determining the terminal occlusal position.

[0010] In some embodiments, the present disclosure provides a storage medium for storing program code, wherein the program code is used to execute the above method for determining a terminal occlusal position.

[0011] The method disclosed in the present invention can determine and predict the terminal occlusal position in an automatic and intelligent manner, thereby greatly reducing the cost of manual operation while ensuring accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that components and elements are not necessarily drawn to scale.

[0013] Figure 1 is a flow chart of a method for determining a terminal occlusal position according to an embodiment of the present disclosure.

[0014] Figure 2 Schematic diagram of landmark points for marking dentition according to an embodiment of the present disclosure.

[0015] Figure 3 It is a partial module of the device for determining the terminal occlusal position according to another embodiment of the present disclosure.

[0016] Figure 4 It is a schematic diagram of the structure of an electronic device according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0017] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0018] It should be understood that the various steps described in the method embodiments of the present disclosure can be performed in sequence and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this respect.

[0019] The term "including" and its variations used herein are open inclusions, i.e., "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description.

[0020] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0021] It should be noted that the modification of “one” mentioned in the present disclosure is illustrative rather than restrictive, and those skilled in the art should understand that it should be understood as “one or more” unless otherwise clearly indicated in the context.

[0022] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0023] The present invention discloses a model for automatically establishing the terminal occlusal position of orthognathic surgery based on the surgical plan requirements of orthognathic surgery patients, such as tooth extraction and block segmentation. The model preprocesses the dentition data based on the surgical plan, and then automatically identifies and matches the tooth landmarks to preliminarily obtain the terminal occlusal position. Through collision detection, it eliminates the overlap of teeth between different block dentitions or between the upper and lower jaw dentitions, so as to achieve the purpose of automatically and quickly matching the terminal occlusal position of orthognathic surgery.

[0024] Figure 1 A flow chart of a method for determining a terminal occlusal position according to an embodiment of the present disclosure is provided. The method for determining a terminal occlusal position according to the present disclosure may include step S101, obtaining STL (stereolithography) data of a three-dimensional image of a patient's dentition and / or tooth bone segment. In some embodiments, obtaining the stereolithography data of a three-dimensional image of a patient's dentition and / or tooth bone segment includes: scanning the patient's dentition and a dental cast with an intraoral scanner to obtain the stereolithography data of a three-dimensional image of the patient's dentition, or obtaining the dentition data by cone beam computed tomography (CBCT) / computed tomography (CT) scanning and an intraoral scanner, and obtaining the stereolithography data of a three-dimensional image of a tooth bone segment after registration and replacement.

[0025] In some embodiments, the method of the present disclosure may further include step S102, pre-processing the stereolithography data. In some embodiments, pre-processing the stereolithography data includes: using the anatomical information and geometric features of the dentition, dividing the dentition and / or the tooth bone segment into multiple blocks through manual annotation or regular segmentation; for areas where tooth extraction is required, deleting the stereolithography data of the corresponding area. In some embodiments, according to the needs of the surgical plan, such as tooth extraction, segmentation, etc., using the anatomical information and geometric features of the dentition and / or the tooth bone segment, dividing the dentition and / or the tooth bone segment into multiple structural blocks through manual annotation or regular segmentation; for areas where tooth extraction is required, deleting the corresponding three-dimensional image data.

[0026] In some embodiments, the method of the present disclosure may further include step S103, marking the landmarks of the dentition based on the preprocessed stereolithography data. In some embodiments, according to the general rules of normal dentition occlusion, the landmarks of the upper and lower dentition may be automatically marked by manual or existing automatic marking models. In some embodiments, the landmarks of the dentition are automatically marked by the key point detection neural network model of the present disclosure. For example, Figure 2 As shown, the central incisor is marked with one landmark, the lateral incisor, canine and premolar are marked with two landmarks, and the molar is marked with four landmarks. Figure 2Only some of the landmark points are marked. In some embodiments, the key point detection neural network model is obtained by: constructing a neural network model; taking the stereolithography data of the three-dimensional image of the dentition as input and the landmark points of the dentition as output to train the neural network model, and obtaining the key point detection neural network model. In some embodiments, the neural network model can adopt a graph convolutional neural network, and the processing grid can be appropriately simplified to reduce the overall number of vertices. Therefore, in some embodiments, the three-dimensional image of the dentition and the landmark point labels of the image vertices can be used as training data, and the key point detection neural network model can be established based on topological information and local global features.

[0027] In some embodiments, the method disclosed herein may further include step S104, using the occlusal model, based on the landmark points of the dentition, to obtain the predicted landmark points of the dentition, that is, by predicting the displacement vector of the landmark points, the deformation of the dentition from the original position to the ideal target position is achieved. In some embodiments, there are currently a lot of data on the landmark points of the dentition before and after surgery, and the occlusal model is obtained in the following manner: construct another neural network model; using the landmark points of the upper and lower dentition before surgery (for example, the coordinates of the landmark points are P1, P2, P3, etc.) and the block labels of each landmark point (usually, each block of the dentition and / or tooth bone segment corresponds to 3-7 teeth) as input, using the landmark points of the upper and lower dentition in terminal occlusion after surgery (for example, the coordinates are P1', P2', P3', etc.) as output, and training the other neural network model with the minimization of the landmark point displacement error and the consistency of the landmark point displacement of the same block as constraints to obtain the occlusal model. The prediction of landmark points by the occlusal model disclosed herein reduces the requirements for doctor experience, and can achieve automatic prediction, greatly reducing the workload of doctors and reducing labor costs.

[0028] In some embodiments, the method disclosed herein may further include step S105, based on the predicted landmark points, matching the three-dimensional image of the dentition corresponding to the predicted landmark points to the terminal occlusal position, and detecting the collision of the tooth surfaces between the dentitions of different blocks or between the upper and lower jaws. In some embodiments, the predicted landmark points are used as a connecting bridge to match the three-dimensional image of the dentition to the terminal occlusal position, thereby facilitating the detection of the collision of the tooth surfaces between the dentitions of different blocks and between the upper and lower jaws.

[0029] In some embodiments, the method disclosed herein may further include step S106, when a collision occurs between the tooth surfaces of different blocks of dentition or between the upper and lower dentitions, the preset vectors are changed for the positions of all blocks, and the positions of the predicted landmarks of the dentition are adjusted by iterative optimization until no collision occurs between the tooth surfaces of different blocks of dentition and between the upper and lower dentitions, and the positions of the adjusted dentition landmarks are determined as the final terminal occlusal position. In some embodiments, the preset vectors include rotation matrix vectors and / or translation vectors. In some embodiments, if a collision and intersection of the tooth surfaces between the dentitions of the blocks and between the upper and lower dentitions occurs, a rigid change of the preset vector Ti (including the rotation matrix vector Ri and the translation vector ti) is performed on all blocks to minimize the coordinate error between the adjusted landmarks and the initial ideal landmarks, and to increase the distance between the blocks. The coordinates of the predicted landmarks are adjusted by iterative optimization, and all blocks are re-checked after each iteration to see if they meet the no-intersection (or intersection or collision) constraint; if no intersection occurs, the position is confirmed as the terminal occlusal position by detection.

[0030] The method disclosed in the present invention can determine and predict the terminal occlusal position in an automatic and intelligent manner, thereby greatly reducing the cost of manual operation while ensuring accuracy.

[0031] The embodiment of the present disclosure further provides a device 400 for determining a terminal occlusal position. Figure 3An apparatus 400 for determining a terminal occlusal position according to some embodiments is shown. The apparatus 400 for determining a terminal occlusal position includes a data acquisition module 401, a preprocessing module 402, a marking module 403, a prediction module 404, a detection module 405, and an adjustment module 406. In some embodiments, the data acquisition module 401 is configured to acquire stereolithography data of a three-dimensional image of a patient's dentition and / or tooth bone segment. In some embodiments, the preprocessing module 402 is configured to preprocess the stereolithography data. In some embodiments, the marking module 403 is configured to mark landmark points of the dentition based on the preprocessed stereolithography data. In some embodiments, the prediction module 404 is configured to use the occlusal model to obtain the predicted landmarks of the dentition based on the landmarks of the dentition, wherein the occlusal model is obtained by: constructing a neural network model; using the landmarks of the upper and lower dentition before surgery and the block labels of each landmark as input, using the landmarks of the upper and lower dentition in terminal occlusion after surgery as output, training the neural network model with the minimization of the landmark displacement error and the consistency of the landmark displacement of the same block as constraints to obtain the occlusal model. In some embodiments, the detection module 405 is configured to match the three-dimensional image of the dentition corresponding to the predicted landmark to the terminal occlusal position based on the predicted landmark, and detect the collision of the tooth surfaces between the dentitions of different blocks or between the upper and lower dentitions. In some embodiments, the adjustment module 406 is configured to change the preset vectors for the positions of all blocks when a collision occurs between the tooth surfaces of different blocks of dentition or between the upper and lower dentitions, and adjust the positions of the predicted landmark points of the dentition by iterative optimization until there is no collision between the tooth surfaces of different blocks of dentition or between the upper and lower dentitions, and determine the positions of the adjusted dentition landmark points as the final terminal occlusal position.

[0032] It should be understood that the contents described about the method for determining the terminal occlusal position are also applicable to the device 400 for determining the terminal occlusal position herein, and for the sake of simplicity, a detailed description is not given here.

[0033] In some embodiments, obtaining stereolithography data of a three-dimensional image of a patient's dentition and / or tooth bone segment includes: scanning the patient's dentition or dental model with an intraoral scanner to obtain stereolithography data of a three-dimensional image of the patient's dentition, or obtaining dentition data by cone beam computed tomography (CBCT) / computed tomography (CT) scanning and intraoral scanner scanning, and obtaining stereolithography data of a three-dimensional image of a tooth bone segment after registration and replacement. In some embodiments, preprocessing the stereolithography data includes: using the anatomical information and geometric features of the dentition, dividing the dentition or tooth bone segment into a plurality of blocks by manual annotation or regular segmentation; for an area where teeth need to be extracted, deleting the stereolithography data of the corresponding area. In some embodiments, based on the preprocessed stereolithography data, marking the landmark points of the dentition includes: automatically marking the landmark points of the dentition by a key point detection neural network model, wherein the key point detection neural network model is obtained by: constructing another neural network model; using the stereolithography data of the three-dimensional image of the dentition as input and the landmark points of the dentition as output to train another neural network model to obtain a key point detection neural network model. In some embodiments, the preset vector includes a rotation matrix vector and / or a translation vector.

[0034] In addition, the present disclosure also provides a terminal, including: at least one memory and at least one processor; wherein the memory is used to store program codes, and the processor is used to call the program codes stored in the memory to execute the above-mentioned method for determining the terminal occlusal position.

[0035] In addition, the present disclosure also provides a computer storage medium storing a program code, wherein the program code is used to execute the above method for determining a terminal occlusal position.

[0036] The above describes the method and device for determining the terminal occlusal position of the present disclosure based on the embodiments and application examples. In addition, the present disclosure also provides a terminal and a storage medium, which are described below.

[0037] Reference below Figure 4 , which shows a schematic diagram of the structure of an electronic device (such as a terminal device or a server) 500 suitable for implementing the embodiment of the present disclosure. The terminal device in the embodiment of the present disclosure may include but is not limited to mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 4 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0038] like Figure 4 As shown, the electronic device 500 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage device 508 into a random access memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the electronic device 500 are also stored. The processing device 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0039] Typically, the following devices may be connected to the I / O interface 505: an input device 506 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 507 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 508 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 509. The communication device 509 may allow the electronic device 500 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 4 The electronic device 500 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead.

[0040] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device 509, or installed from a storage device 508, or installed from a ROM 502. When the computer program is executed by the processing device 501, the above-mentioned functions defined in the method of the embodiment of the present disclosure are executed.

[0041] It should be noted that the computer-readable medium disclosed above may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device. In the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0042] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (HyperText Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0043] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0044] The computer-readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device executes the method of the present disclosure.

[0045] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0046] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0047] The units involved in the embodiments described in the present disclosure may be implemented by software or hardware, wherein the name of a unit does not, in some cases, limit the unit itself.

[0048] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0049] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0050] According to one or more embodiments of the present disclosure, a method for determining a terminal occlusal position is provided, the method for determining a terminal occlusal position comprising: obtaining stereolithography data of a three-dimensional image of a patient's dentition and / or tooth bone segment; preprocessing the stereolithography data; marking landmark points of the dentition based on the preprocessed stereolithography data; using an occlusal model to obtain predicted landmark points of the dentition based on the landmark points of the dentition, wherein the occlusal model is obtained by: constructing a neural network model; taking the landmark points of the upper and lower dentition before surgery and the block labels of each landmark point as input, taking the landmark points of the upper and lower dentition in terminal occlusion after surgery as output, and taking the landmark point displacement error as output. The neural network model is trained with minimization and the displacement consistency of the landmark points in the same block as constraints to obtain the occlusion model; based on the predicted landmark points, the three-dimensional image of the dentition corresponding to the predicted landmark points is matched to the terminal occlusal position, and the collision of the tooth surfaces between the dentitions of different blocks or between the upper and lower dentitions is detected; when the tooth surfaces between the dentitions of different blocks or between the upper and lower dentitions collide, the preset vectors of the positions of all blocks are changed, and the positions of the predicted landmark points of the dentition are adjusted by iterative optimization until there is no collision of the tooth surfaces between the dentitions of different blocks or between the upper and lower dentitions, and the positions of the adjusted dentition landmark points are determined as the final terminal occlusal position.

[0051] According to one or more embodiments of the present disclosure, obtaining stereolithography data of a three-dimensional image of a patient's dentition and / or tooth bone segment includes: scanning the patient's dentition or dental mold with an intraoral scanner to obtain stereolithography data of a three-dimensional image of the patient's dentition, or obtaining dentition data through cone beam computed tomography (CBCT) / computed tomography (CT) scanning and intraoral scanner scanning and obtaining stereolithography data of a three-dimensional image of a tooth bone segment after alignment and replacement.

[0052] According to one or more embodiments of the present disclosure, preprocessing the stereolithography data includes: using the anatomical information and geometric features of the dentition or tooth bone segment, dividing the dentition or tooth bone segment into multiple blocks through manual labeling or regularized segmentation; for the area where tooth extraction is required, deleting the stereolithography data of the corresponding area.

[0053] According to one or more embodiments of the present disclosure, marking the landmark points of the dentition based on preprocessed stereolithography data includes: automatically marking the landmark points of the dentition through a key point detection neural network model, wherein the key point detection neural network model is obtained by: constructing another neural network model; using the stereolithography data of the three-dimensional image of the dentition as input and the landmark points of the dentition as output to train the other neural network model to obtain the key point detection neural network model.

[0054] According to one or more embodiments of the present disclosure, the preset vector includes a rotation matrix vector and / or a translation vector.

[0055] According to one or more embodiments of the present disclosure, there is provided a device for determining a terminal occlusal position, the device for determining a terminal occlusal position comprising: a data acquisition module configured to acquire stereolithography data of a three-dimensional image of a patient's dentition and / or tooth bone segment; a preprocessing module configured to preprocess the stereolithography data; a marking module configured to mark the landmark points of the dentition based on the preprocessed stereolithography data; a prediction module configured to acquire predicted landmark points of the dentition based on the landmark points of the dentition using an occlusal model, wherein the occlusal model is obtained by: constructing a neural network model; taking the landmark points of the upper and lower dentition before surgery and the block label of each landmark point as input, and taking the landmark points of the upper and lower dentition in terminal occlusion after surgery as output , the neural network model is trained with the minimization of the marker point displacement error and the consistency of the marker point displacement of the same block as constraints to obtain the occlusion model; a detection module is configured to match the three-dimensional image of the dentition corresponding to the predicted marker point to the terminal occlusion position based on the predicted marker point, and detect the collision of the tooth surface between the dentition of different blocks or between the upper and lower dentitions; an adjustment module is configured to change the preset vector of the position of all blocks when the tooth surface collision occurs between the dentition of different blocks or between the upper and lower dentitions, and adjust the position of the predicted marker point of the dentition by iterative optimization until there is no collision between the tooth surface between the dentition of different blocks or between the upper and lower dentitions, and determine the position of the adjusted dentition marker point as the final terminal occlusion position.

[0056] According to one or more embodiments of the present disclosure, a terminal is provided, comprising: at least one memory and at least one processor; wherein the at least one memory is used to store program code, and the at least one processor is used to call the program code stored in the at least one memory to execute any one of the methods described above.

[0057] According to one or more embodiments of the present disclosure, a storage medium is provided, wherein the storage medium is used to store program code, and the program code is used to execute the above method.

[0058] The above description is only a preferred embodiment of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present disclosure is not limited to the technical solutions formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in the present disclosure (but not limited to) by each other to form a technical solution.

[0059] In addition, although each operation is described in a specific order, this should not be understood as requiring these operations to be performed in the specific order shown or in a sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous. Similarly, although some specific implementation details are included in the above discussion, these should not be interpreted as limiting the scope of the present disclosure. Some features described in the context of a separate embodiment can also be implemented in a single embodiment in combination. On the contrary, the various features described in the context of a single embodiment can also be implemented in multiple embodiments individually or in any suitable sub-combination mode.

[0060] Although the subject matter has been described in language specific to structural features and / or methodological logical actions, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. On the contrary, the specific features and actions described above are merely example forms of implementing the claims.

Claims

1. A method for determining a terminal occlusal position, characterized in that: The method for determining the terminal occlusal position comprises: acquiring stereolithography data of a three-dimensional image of a patient's dentition and / or tooth bone segment; Preprocessing the stereolithography data; Based on the pre-processed stereolithography data, mark the landmarks of the dentition; Using the occlusal model, based on the landmark points of the dentition, the predicted landmark points of the dentition are obtained, wherein the occlusal model is obtained by: constructing a neural network model; taking the landmark points of the upper and lower dentition before surgery and the block labels of each landmark point as input, taking the landmark points of the upper and lower dentition in terminal occlusion after surgery as output, and training the neural network model with minimization of landmark point displacement error and consistency of landmark point displacement in the same block as constraints to obtain the occlusal model; Based on the predicted landmark points, the three-dimensional image of the dentition corresponding to the predicted landmark points is matched to the terminal occlusal position, and the collision of the tooth surfaces between the dentitions of different blocks or between the upper and lower jaw dentitions is detected; When the tooth surfaces of different blocks of dentition or between the upper and lower teeth collide, the preset vectors of the positions of all blocks are changed, and the positions of the predicted landmark points of the dentition are adjusted by iterative optimization until there is no collision between the tooth surfaces of different blocks of dentition or between the upper and lower teeth. The positions of the adjusted landmark points of the dentition are determined as the final terminal occlusal position.

2. The method for determining the terminal occlusal position according to claim 1, characterized in that: Acquiring stereolithography data of a three-dimensional image of a patient's dentition includes: acquiring the patient's dentition data by scanning the patient's dentition or dental model with an intraoral scanner, or acquiring dentition data by cone beam computed tomography (CBCT) / computed tomography (CT) scanning and intraoral scanner scanning and acquiring stereolithography data of a three-dimensional image of a tooth bone segment after registration and replacement.

3. The method for determining the terminal occlusal position according to claim 1, characterized in that: Preprocessing the stereolithography data includes: using anatomical information and geometric features of the tooth surface to divide the dentition into multiple blocks through manual marking or regular segmentation; for areas where teeth need to be extracted, deleting the stereolithography data of the corresponding areas.

4. The method for determining the terminal occlusal position according to claim 1, characterized in that: Based on the pre-processed stereolithography data, the landmarks for marking the dentition include: The landmark points of the dentition are automatically marked by a key point detection neural network model, wherein the key point detection neural network model is obtained by: constructing another neural network model; using stereolithography data of a three-dimensional image of the dentition as input and using the landmark points of the dentition as output to train the other neural network model, thereby obtaining the key point detection neural network model.

5. The method for determining the terminal occlusal position according to claim 1, characterized in that: The preset vector includes a rotation matrix vector and / or a translation vector.

6. A device for determining a terminal occlusal position, characterized in that: The device for determining the terminal occlusal position comprises: a data acquisition module configured to acquire stereolithography data of a three-dimensional image of a patient's dentition and / or tooth bone segment; a preprocessing module configured to preprocess the stereolithography data; a marking module configured to mark landmarks of a dentition based on the preprocessed stereolithography data; A prediction module is configured to obtain predicted landmarks of the dentition based on the landmarks of the dentition using the occlusal model, wherein the occlusal model is obtained by: constructing a neural network model; taking the landmarks of the upper and lower dentition before surgery and the block labels of each landmark as input, taking the landmarks of the upper and lower dentition in terminal occlusion after surgery as output, and training the neural network model with minimization of landmark displacement error and consistency of landmark displacement of the same block as constraints to obtain the occlusal model; A detection module is configured to match the three-dimensional image of the dentition corresponding to the predicted landmark point to the terminal occlusal position based on the predicted landmark point, and detect the collision of the tooth surface between the dentitions of different blocks or between the upper and lower jaw dentitions; The adjustment module is configured to change the preset vectors for the positions of all blocks when a collision occurs between the tooth surfaces of different blocks of dentition or between the upper and lower teeth, and adjust the positions of the predicted landmark points of the dentition by iterative optimization until no collision occurs between the tooth surfaces of different blocks of dentition or between the upper and lower teeth, and determine the positions of the adjusted landmark points of the dentition as the final terminal occlusal position.

7. A terminal, comprising: at least one memory and at least one processor; The at least one memory is used to store program codes, and the at least one processor is used to call the program codes stored in the at least one memory to execute the method for determining the terminal occlusal position according to any one of claims 1 to 5.

8. A storage medium for storing a program code for executing the method for determining a terminal occlusal position according to any one of claims 1 to 5.

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