Implant position planning method, auxiliary planting system, medium and product

Abstract

The invention discloses an implant position planning method, an auxiliary planting system, a medium and a product. The method comprises the following steps: generating a three-dimensional oral cavity segmentation result based on tooth image data, and determining soft and hard tissue associated information corresponding to each target tooth position based on the tooth image data; inputting the three-dimensional oral cavity segmentation result, the form data of the tail end of the mechanical arm, the target tooth positions, and the attribute information and soft and hard tissue association information of the to-be-implanted body corresponding to each target tooth position to a preset planning model to obtain predicted planning positions corresponding to each target tooth position; on the basis of the predicted planning positions corresponding to the target tooth positions, a feasibility analysis result is obtained, under the condition that the feasibility analysis result meets a preset feasible judgment condition, a planning display result is generated, and the feasibility analysis result comprises the operation range of the tail end of the mechanical arm and / or the stress analysis result of each target tooth position. And the reliability of predicting the planned position is improved.

Description

Technical Field

[0001] The present invention relates to the field of image processing technology, and in particular to an implant position planning method, an auxiliary implant system, a medium and a product. Background Art

[0002] Implant restoration is one of the most commonly used methods to solve tooth loss and edentulous restoration, and is widely used by doctors and patients. Implant position planning is an important step in implant restoration.

[0003] At present, the existing technology is usually based on computer-assisted planning of implant positions. Specifically, the patient's oral CBCT data and intraoral three-dimensional scanning data are automatically analyzed based on the spatial constraint algorithm to obtain the predicted planned position of the implant, and the occlusal force of the implant is estimated based on the predicted planned position of the implant to ensure that the predicted planned position of the implant meets the mechanical requirements of the implant.

[0004] However, during the implant restoration process, the doctor needs to place the robotic arm in the patient's mouth, and the implant position planning in the existing technology only considers the spatial constraints between the implant and the tooth, so that the predicted planned position of the implant may not meet the operating requirements of the robotic arm, resulting in the failure of the implant restoration. Summary of the invention

[0005] The present invention provides an implant position planning method, an auxiliary implant system, a medium and a product to solve the problem that the prior art cannot ensure that the predicted planned position supports the end operation of a robotic arm, thereby improving the reliability of the predicted planned position.

[0006] According to one aspect of the present invention, there is provided an implant position planning method, comprising:

[0007] Acquire the tooth image data of the target object and the morphological data of the end of the robot arm, and determine at least one target tooth position and the attribute information of the implant to be implanted corresponding to each target tooth position;

[0008] Generate a three-dimensional oral cavity segmentation result based on the dental image data, and determine the soft and hard tissue association information corresponding to each target tooth position based on the dental image data;

[0009] The three-dimensional oral segmentation results, the morphological data of the end of the robotic arm, the target tooth positions, and the attribute information of the implants to be implanted corresponding to each target tooth position and the soft and hard tissue association information are input into the preset planning model to obtain the predicted planning positions corresponding to each target tooth position;

[0010] Performing a feasibility analysis based on the predicted planning positions corresponding to each target tooth position, and obtaining a feasibility analysis result, wherein the feasibility analysis includes one or more of a feasibility analysis of the robot arm operation and a stress analysis of each target tooth position, and correspondingly, the feasibility analysis result includes an operating range of the robot arm end and / or a stress analysis result of each target tooth position;

[0011] When the feasibility analysis results meet the preset feasibility judgment conditions, the planning display results are generated based on the three-dimensional oral segmentation results, the predicted planning positions corresponding to each target tooth position, and the attribute information of the implants corresponding to each target tooth position.

[0012] According to another aspect of the present invention, there is provided an auxiliary planting system, comprising:

[0013] An interactive module, used for receiving at least one target tooth position and attribute information of at least one implant corresponding to each of the target tooth positions input by a user;

[0014] A processing module, used to obtain the tooth image data of the target object and the morphological data of the end of the robotic arm, and determine at least one target tooth position and the attribute information of the implant to be implanted corresponding to each target tooth position; generate a three-dimensional oral segmentation result based on the tooth image data, and determine the soft and hard tissue association information corresponding to each target tooth position based on the tooth image data; input the three-dimensional oral segmentation result, the morphological data of the end of the robotic arm, the target tooth position, and the attribute information and soft and hard tissue association information of the implant to be implanted corresponding to each target tooth position into a preset planning model to obtain the predicted planning position corresponding to each target tooth position; perform a feasibility analysis based on the predicted planning position corresponding to each target tooth position to obtain a feasibility analysis result, wherein the feasibility analysis includes one or more of the feasibility analysis of the robotic arm operation and the stress analysis of each target tooth position, and accordingly, the feasibility analysis result includes the operating range of the end of the robotic arm and / or the stress analysis result of each target tooth position; when the feasibility analysis result meets the preset feasible judgment condition, generate a planning display result based on the three-dimensional oral segmentation result, the predicted planning position corresponding to each target tooth position, and the attribute information of the implant to be implanted corresponding to each target tooth position;

[0015] The interactive module is also used to display the three-dimensional oral segmentation results and planning display results.

[0016] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0017] at least one processor; and

[0018] a memory communicatively connected to at least one processor; wherein,

[0019] The memory stores a computer program that can be executed by at least one processor. The computer program is executed by at least one processor so that the at least one processor can execute the implant position planning method according to any embodiment of the present invention.

[0020] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to implement the implant position planning method of any embodiment of the present invention when executed by a processor.

[0021] According to another aspect of the present invention, a computer program product is provided. The computer program product comprises a computer program. When the computer program is executed by a processor, the computer program implements the implant position planning method according to any embodiment of the present invention.

[0022] The technical solution of the embodiment of the present invention obtains the predicted planning positions corresponding to each target tooth position by inputting the three-dimensional oral segmentation results, the morphological data of the end of the robotic arm, the target tooth position and the attribute information of the implant corresponding to each target tooth position, and the soft and hard tissue association information into a preset planning model. Instead of only predicting the predicted planning positions corresponding to each target tooth position based on the three-dimensional oral segmentation results, the target tooth position and the attribute information of the implant corresponding to each target tooth position, the problem that the prior art cannot ensure that the predicted planning positions support the operation of the end of the robotic arm is solved, and the reliability of the predicted planning positions is improved.

[0023] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0025] Figure 1 is a flow chart of an implant position planning method provided in Embodiment 1 of the present invention;

[0026] Figure 2 is a flow chart of an implant position planning method provided in Embodiment 2 of the present invention;

[0027] Figure 3 is a structural schematic diagram of an auxiliary planting system provided by Embodiment 3 of the present invention;

[0028] Figure 4It is a schematic diagram of the structure of an electronic device for implementing the implant position planning method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0031] Embodiment 1

[0032] Figure 1 This is a flowchart of an implant position planning method provided by the first embodiment of the present invention. This embodiment is applicable to computer-assisted implantation. The method can be executed by a processing module. The processing module can be implemented in the form of hardware and / or software. The processing module can be configured in an assisted implantation system. Optionally, it can be implemented by an electronic device, which can be a mobile terminal, a PC or a server. Figure 1 As shown, the method includes:

[0033] S110, acquiring tooth image data of the target object and morphological data of the end of the robotic arm, and determining at least one target tooth position and attribute information of the implant corresponding to each target tooth position.

[0034] In this embodiment, the target object is a human body or other animal body that needs to undergo dental implantation, and the dental image data is cone beam computed tomography (CBCT) image data of the oral and maxillofacial region of the target object.

[0035] The robotic arm is a robotic arm used to perform or assist in performing the implantation operation during the implantation process. The end of the robotic arm is the part of the robotic arm that can move inside the oral cavity of the target object. For example, the end of the robotic arm is a drill bit used to drill holes in the target tooth position to obtain holes for implanting the implant. The morphological data of the end of the robotic arm is data that characterizes the morphology of the end of the robotic arm, including but not limited to the shape and size of the end of the robotic arm.

[0036] Specifically, the dental image data of the target object is obtained by reading the CBCT image data of the oral and maxillofacial region of the target object collected in real time, or calling the pre-stored CBCT image data of the oral and maxillofacial region of the target object. Based on the end model of the robotic arm, the pre-stored morphological data of the end of the robotic arm is called. It should be noted that the morphological data of the end of the robotic arm corresponding to different end models are different.

[0037] The target tooth position is the tooth position where the implant needs to be implanted, wherein the tooth position is a number representing the position of the tooth. The implant to be implanted corresponding to the target tooth position is the implant to be implanted in the target tooth position, and the attribute information of the implant to be implanted includes but is not limited to the shape information, density information and size information of the implant to be implanted, wherein the size information includes length and diameter.

[0038] Optionally, one or more target tooth positions are obtained by parsing the target tooth position determination instruction, wherein the target tooth position determination instruction is an instruction generated based on the user's target tooth position configuration operation, and the target tooth position determination instruction may include the identification of the target tooth position. Exemplarily, the dental image data of the target object may be displayed on an interactive page, and the target tooth position is determined in response to the target tooth position configuration operation. The target tooth position configuration operation may be a click operation on the dental image data of the target object in the interactive page, wherein the identification of the target tooth position is determined based on the tooth position where the click position is located, and the target tooth position determination instruction is generated based on the identification of the target tooth position. Alternatively, the target tooth position configuration operation may also be an input operation of the target tooth position identification, and the identification of each tooth position may be marked on the dental image data of the target object displayed on the interactive page, and the user inputs the target tooth position identification through an input device, and the target tooth position determination instruction is generated based on the target tooth position identification.

[0039] In the above embodiment, the attribute information of the implant corresponding to each target tooth position is obtained by parsing the instruction for determining the implant corresponding to each target tooth position; the instruction for determining the implant may include the information of the implant corresponding to the target tooth position, for example, the information of the implant may be the model of the implant. The attribute information of the implant stored in advance is called based on the model of the implant to obtain the attribute information of the implant corresponding to the target tooth position.

[0040] Exemplarily, it is assumed that the tooth position is represented by a digital identifier, which includes a digital identifier representing the area where the tooth is located and a digital identifier representing the tooth type, wherein the digital identifier representing the area where the tooth is located is 1, 2, 3, and 4 in the order of the upper right area, the upper left area, the lower right area, and the lower left area, and the digital identifier representing the tooth type is a number from 1 to 8 in the order from the central incisor to the third molar. Assuming that the target subject needs to implant the third molar in the upper left area, the target tooth position is represented as "28".

[0041] It should be noted that each tooth position corresponds to one or more selectable implants, and the implant to be implanted corresponding to the target tooth position is one of the one or more selectable implants corresponding to the target tooth position. Exemplarily, each selectable implant has a unique identifier (for example, a model identifier), and the unique identifier is obtained by parsing the instruction to determine the implant to be implanted, and the selectable implant represented by the unique identifier is determined as the implant to be implanted corresponding to the target tooth position; and the attribute information corresponding to the unique identifier is called to obtain the attribute information of the implant to be implanted corresponding to the target tooth position. Among them, the model of the implant to be implanted corresponding to the target tooth position can be selected by the user.

[0042] S120, generating a three-dimensional oral cavity segmentation result based on the dental image data, and determining the soft and hard tissue association information corresponding to each target tooth position based on the dental image data.

[0043] In this embodiment, the 3D oral segmentation result is a 3D model that characterizes the soft and hard tissue structures of the oral and maxillofacial region of the target object. The 3D oral segmentation result can intuitively display the position of the target tooth in the oral cavity of the target object, as well as the relative position relationship between the target tooth and the soft and hard tissues. The soft and hard tissues include but are not limited to the left maxillary sinus, the right maxillary sinus, the maxillary complex, the mandible, the left mandibular canal, the right mandibular canal, the teeth and the gums.

[0044] Specifically, a three-dimensional reconstruction process is performed on the dental image data by calling a three-dimensional reconstruction model or a three-dimensional reconstruction toolkit to obtain a three-dimensional oral model. The three-dimensional reconstruction model is a neural network model trained based on sample dental image data and a sample three-dimensional oral model corresponding to the sample dental image data; the three-dimensional reconstruction toolkit is a toolkit for automatically performing three-dimensional rendering on dental image data. The three-dimensional oral model is segmented by calling a segmentation model to obtain a three-dimensional oral segmentation result. The segmentation model is a neural network model trained based on a sample three-dimensional oral model and a sample three-dimensional oral segmentation result corresponding to the sample three-dimensional oral model. Exemplarily, the segmentation model is a 3D-Unet model.

[0045] In some embodiments, after generating the three-dimensional oral segmentation result, the teeth in the three-dimensional oral segmentation result are arranged based on a preset dental arch curve, wherein the preset dental arch curve is a curve established based on the tooth arrangement in the three-dimensional oral segmentation result. Exemplarily, by calling a virtual tooth arrangement model, the position and angle of the teeth in the three-dimensional oral segmentation result are adjusted so that the teeth in the three-dimensional oral segmentation result are parallel to the preset dental arch curve.

[0046] The soft and hard tissue association information is information about the soft and hard tissues around the target tooth position that is associated with the implant position planning, wherein the soft and hard tissue association information at least includes the bone density of the alveolar bone where the target tooth position is located. By calling the soft and hard tissue association information measurement toolkit, the soft and hard tissues around each target tooth position in the dental image data are analyzed to obtain the soft and hard tissue association information corresponding to each target tooth position.

[0047] Exemplarily, assuming that the soft and hard tissue association information includes the bone density and thickness of the alveolar bone where the target tooth is located and the thickness of the gums where the target tooth is located, the soft and hard tissue association information measurement tool kit includes a bone density measurement tool kit, an alveolar bone thickness measurement tool kit and a gum thickness measurement tool kit.

[0048] In some embodiments, the property information of the implant to be implanted corresponding to the target tooth position is verified based on the soft and hard tissue association information corresponding to the target tooth position. The soft and hard tissue association information may include one or more of the width, thickness and bone density of the alveolar bone. The soft and hard tissue association information may be extracted from the tooth image data.

[0049] Match the soft and hard tissue association information corresponding to the target tooth position with the attribute information of the implant to be implanted corresponding to the target tooth position. Specifically, match the width and thickness in the soft and hard tissue association information with the size information in the attribute information of the implant to be implanted. If the difference between the width and thickness of the alveolar bone and the size information of the implant to be implanted is greater than a preset threshold, it indicates that the soft and hard tissue association information corresponding to the target tooth position does not match the attribute information of the implant to be implanted corresponding to the target tooth position, and generate update prompt information of the implant to be implanted, which is used to reselect the model of the implant to be implanted at the same time. If the difference between the width and thickness of the alveolar bone and the size information of the implant to be implanted is less than a preset threshold, it indicates that the soft and hard tissue association information corresponding to the target tooth position matches the attribute information of the implant to be implanted corresponding to the target tooth position, generate a successful match information, and continue to execute the position planning of the implant to be implanted.

[0050] For example, the bone density in the soft and hard tissue association information may be matched with the density information of the implant. If the bone density in the soft and hard tissue association information and the density information of the implant meet the preset matching conditions, the density matching is determined to be successful.

[0051] S130, input the three-dimensional oral segmentation results, the morphological data of the end of the robotic arm, the target tooth position, and the attribute information of the implant to be implanted corresponding to each target tooth position and the soft and hard tissue association information into the preset planning model to obtain the predicted planning position corresponding to each target tooth position.

[0052] In this embodiment, the preset planning model is a pre-trained model for automatically planning the implant position. Exemplarily, the preset planning model is a traditional machine learning model or a deep learning model.

[0053] Specifically, by calling the preset planning model, the three-dimensional oral segmentation result, the morphological data of the end of the robotic arm, at least one target tooth position, and the attribute information and soft and hard tissue association information of the implant to be respectively corresponding to at least one target tooth position are analyzed, and the predicted planning position corresponding to at least one target tooth position is output. The predicted planning position is the implantation position corresponding to the implant to be respectively predicted by the preset planning model.

[0054] In the case where the preset planning model outputs a predicted planning position corresponding to a target tooth position at a time, the input information corresponding to each target tooth position is input into the preset planning model, so that the preset planning model predicts the predicted planning position corresponding to the target tooth position separately, wherein the input information corresponding to each target tooth position includes the three-dimensional oral segmentation result, the morphological data of the end of the robot arm, the target tooth position and the attribute information and soft and hard tissue association information of the implant to be implanted corresponding to the target tooth position. Exemplarily, assuming that there are multiple target tooth positions, the planning order of the multiple target tooth positions is determined, and the predicted planning positions corresponding to the multiple target tooth positions are determined in sequence according to the planning order.

[0055] In the case where the preset planning model outputs the predicted planning positions corresponding to all target tooth positions at a time, the three-dimensional oral segmentation result, the morphological data of the end of the robotic arm, all target tooth positions, and the attribute information of the implants to be implanted corresponding to all target tooth positions and the soft and hard tissue association information are simultaneously input into the preset planning model, so that the preset planning model jointly predicts the predicted planning positions corresponding to all target tooth positions. For example, assuming that there are multiple target tooth positions, the predicted planning positions corresponding to the multiple target tooth positions can be obtained simultaneously.

[0056] S140, performing a feasibility analysis based on the predicted planning positions corresponding to each target tooth position, and obtaining a feasibility analysis result.

[0057] The feasibility analysis includes one or more of the feasibility analysis of the robot arm operation and the stress analysis of each target tooth position. Correspondingly, the feasibility analysis result includes the operating range of the robot arm end and / or the stress analysis result of each target tooth position.

[0058] In this embodiment, the feasibility analysis result is used to characterize the feasibility of the predicted planning position corresponding to each target tooth position in the actual implantation process. The operating range of the end of the robotic arm is the movable space range of the end of the robotic arm inside the oral cavity of the target object, and the stress analysis result of each target tooth position is used to characterize the stress of the implant corresponding to the target tooth position when it is implanted to the predicted planning position corresponding to the target tooth position.

[0059] In some embodiments, the feasibility analysis of the robot arm operation is performed based on the predicted planning positions corresponding to each target tooth position, and the operating range of the end of the robot arm is obtained. Optionally, the oral safety range is determined based on the preset safety distance, the three-dimensional oral segmentation result, the attribute information of the implant to be implanted corresponding to each target tooth position, and the predicted planning position; the operating range of the end of the robot arm is determined based on the oral safety range and the morphological data of the end of the robot arm.

[0060] In this embodiment, the preset safety distance is the minimum distance between the end of the robotic arm and the soft and hard tissues. The oral safety range is the local space range inside the oral cavity of the target subject when the implant corresponding to each target tooth position is implanted at the predicted planned position corresponding to each target tooth position. It can be understood that when the end of the robotic arm moves within the oral safety range, the end of the robotic arm will not cause damage to the soft and hard tissues and implants.

[0061] Specifically, based on the three-dimensional oral segmentation results, the attribute information and predicted planning position of the implant corresponding to each target tooth position, the spatial range inside the oral cavity of the target object is determined when the implant corresponding to each target tooth position is implanted at the predicted planning position corresponding to each target tooth position; based on the preset safety distance, the spatial range inside the oral cavity of the target object is reduced to obtain the oral safety range; based on the morphological data of the end of the robotic arm, the activity of the end of the robotic arm in the oral safety range is simulated, and the operating range of the end of the robotic arm is determined by at least the partial oral safety range that the end of the robotic arm can reach. Among them, the preset safety distance is the default distance or the distance obtained by parsing the safety distance configuration instruction. For example, the preset safety distance is 0.5 mm.

[0062] The technical solution of this embodiment determines the oral safety range based on the preset safety distance, the three-dimensional oral segmentation result, the attribute information of the implant to be implanted corresponding to each target tooth position and the predicted planned position; determines the operating range of the robotic arm end based on the oral safety range and the morphological data of the robotic arm end, which can ensure that the operating range of the robotic arm end does not include soft and hard tissues and implants, and helps to improve the reliability of the operating range of the robotic arm end.

[0063] In some embodiments, stress analysis is performed on each target tooth position based on the predicted planning position corresponding to each target tooth position, and a stress analysis result of each target tooth position is obtained. Optionally, based on each current target tooth position and the three-dimensional oral segmentation result, at least one adjacent tooth corresponding to the current target tooth position is determined; the soft and hard tissue association information corresponding to the current target tooth position, the predicted planning position and the attribute information of the implant to be implanted, and the relative distances corresponding to at least one adjacent tooth corresponding to the current target tooth position are input into the stress analysis model corresponding to the current target tooth position, and the stress analysis result corresponding to the current target tooth position is obtained.

[0064] In this embodiment, the current target tooth position is the target tooth position currently undergoing stress analysis. The adjacent teeth corresponding to the current target tooth position include horizontally adjacent teeth and vertically adjacent teeth, wherein the horizontally adjacent teeth are teeth at the horizontally adjacent tooth position in the same alveolar bone as the current target tooth position, and the vertically adjacent teeth are teeth at the vertically adjacent tooth position in different alveolar bones than the current target tooth position. The relative distance corresponding to each adjacent tooth corresponding to each target tooth position is the distance between the adjacent tooth and the implant corresponding to the target tooth position when the implant corresponding to the target tooth position is implanted in the predicted planned position corresponding to the target tooth position.

[0065] Specifically, any target tooth position is determined as the current target tooth position; each tooth in the horizontally adjacent tooth position in the same alveolar bone as the current target tooth position in the three-dimensional oral segmentation result is determined as a horizontally adjacent tooth, and the teeth in the vertically adjacent tooth position in different alveolar bones as the current target tooth position in the three-dimensional oral segmentation result are determined as vertically adjacent teeth. For example, assuming that the current target tooth position is "28", the tooth positions corresponding to the adjacent teeth corresponding to the current target tooth position include "17" and "48".

[0066] Based on the current target tooth position, a pre-stored stress analysis model is called to obtain a stress analysis model corresponding to the current target tooth position. It should be noted that different tooth positions have different corresponding stress analysis models. Based on the stress analysis model corresponding to the current target tooth position, the input soft and hard tissue association information corresponding to the current target tooth position, the attribute information of the predicted planning position and the implant to be implanted, and the relative distances corresponding to at least one adjacent tooth corresponding to the current target tooth position are analyzed to obtain a stress analysis result corresponding to the current target tooth position when the implant to be implanted is implanted in the current target tooth position. Among them, the stress analysis result corresponding to the current target tooth position includes the stress analysis result of the surface of the implant to be implanted corresponding to the current target tooth position and the stress analysis result of the bone around the predicted planning position. Exemplarily, the stress analysis model corresponding to each tooth position can be used to determine the stress analysis result corresponding to the tooth position when a vertical load and / or an inclined load is applied to the implant to be implanted in the tooth position.

[0067] The technical solution of this embodiment is to input the soft and hard tissue association information corresponding to the current target tooth position, the attribute information of the predicted planning position and the implant to be implanted, and the relative distance corresponding to at least one adjacent tooth corresponding to the current target tooth position into the stress analysis model corresponding to the current target tooth position, so as to obtain the stress analysis result corresponding to the current target tooth position, so that the stress analysis result can characterize the durability of the implant to be implanted in the predicted planning position, which helps to improve the reliability of implant position planning.

[0068] In some embodiments, a feasibility analysis of the robot arm operation is performed based on the predicted planned positions corresponding to each target tooth position to obtain the operating range of the end of the robot arm. At the same time, a stress analysis is performed on each target tooth position based on the predicted planned positions corresponding to each target tooth position to obtain a stress analysis result for each target tooth position, which can ensure the safety and reliability of the robot arm operation and improve the effectiveness of implant position planning.

[0069] S150. When the feasibility analysis result meets the preset feasibility judgment conditions, a planning display result is generated based on the three-dimensional oral segmentation result, the predicted planning position corresponding to each target tooth position, and the attribute information of the implant corresponding to each target tooth position.

[0070] In this embodiment, the preset feasible determination condition is a condition for determining whether the predicted planned position is feasible. The preset feasible determination condition includes the feasible determination condition of the end of the robot arm and / or the feasible determination condition corresponding to each target tooth position.

[0071] Specifically, the feasibility analysis result is used to determine whether the preset feasibility determination condition is satisfied. Optionally, when the operating range of the end of the robot arm satisfies the preset operating range, and / or when the stress analysis result of each target tooth position satisfies the tooth position stress condition, it is determined that the feasibility analysis result satisfies the preset feasibility determination condition.

[0072] In the present embodiment, the preset operating range includes the operating range of the end of the robotic arm required for the predicted planning position corresponding to each target tooth position, and the preset operating range can be determined based on the morphological data of the end of the robotic arm and the predicted planning position corresponding to each target tooth position. Exemplarily, assuming that the end of the robotic arm is a drill bit, the preset operating range is determined based on the angle required for the drill bit to perform drilling operations on the predicted planning position corresponding to each target tooth position. The tooth position stress condition is a condition for determining whether the implant to be implanted in the predicted planning position corresponding to the target tooth position can be permanently stable. Exemplarily, the tooth position stress condition includes the result of the surface stress analysis of the implant, which indicates that the stress on the implanted tooth is less than the preset implant stress threshold, and the result of the bone stress analysis around the predicted planning position, which indicates that the stress on the bone around the predicted planning position is less than the preset bone stress threshold.

[0073] Specifically, when the feasibility analysis results only include the operating range of the robotic arm end, if the operating range of the robotic arm end includes a preset operating range, it can be determined that the operating range of the robotic arm end meets the preset operating range; if the operating range of the robotic arm end does not include the preset operating range or includes a partial preset operating range, it can be determined that the operating range of the robotic arm end does not meet the preset operating range.

[0074] When the feasibility analysis results only include the stress analysis results of each target tooth position, if the stress analysis results of each target tooth position meet the stress conditions corresponding to the target tooth position, it can be determined that the feasibility analysis results meet the preset feasibility determination conditions; if the stress analysis results of any target tooth position do not meet the stress conditions corresponding to the target tooth position, it can be determined that the feasibility analysis results do not meet the preset feasibility determination conditions.

[0075] In the case where the feasibility analysis result only includes the operating range of the robotic arm end and the stress analysis result of each target tooth position, if the operating range of the robotic arm end includes the preset operating range, and the stress analysis result of each target tooth position satisfies the stress condition corresponding to the target tooth position, it can be determined that the feasibility analysis result satisfies the preset feasible judgment condition; if the operating range of the robotic arm end does not include the preset operating range or includes a local preset operating range, or the stress analysis result of any target tooth position does not satisfy the stress condition corresponding to the target tooth position, it can be determined that the feasibility analysis result does not meet the preset feasible judgment condition.

[0076] The technical solution of the present embodiment ensures the feasibility of implanting the implant at the predicted planned position corresponding to the target tooth position and / or the durability of the implant implanted at the predicted planned position corresponding to the target tooth position by determining that the feasibility analysis result meets the preset feasibility judgment condition when the operating range of the end of the robotic arm meets the preset operating range and / or the stress analysis result of each target tooth position meets the tooth position stress condition.

[0077] When the feasibility analysis result meets the preset feasibility judgment conditions, based on the attribute information of the implant corresponding to each target tooth position, the morphological structure of the implant corresponding to the target tooth position is drawn at the predicted planning position corresponding to the target tooth position in the three-dimensional oral segmentation result to obtain the planning display result. Among them, the planning display result is used to characterize the effect of implanting the implant corresponding to each target tooth position at the predicted planning position.

[0078] In some embodiments, optionally, when the feasibility analysis result does not meet the preset feasibility judgment condition, the attribute information of the implant to be implanted corresponding to at least one target tooth position is updated; based on the updated attribute information of the implant to be implanted, the predicted planned position corresponding to each target tooth position is re-determined; and the feasibility analysis is performed again on the predicted planned position corresponding to each target tooth position until the feasibility analysis result corresponding to the updated attribute information of the implant to be implanted meets the preset feasibility judgment condition.

[0079] Specifically, if the feasibility analysis result does not meet the preset feasible judgment conditions, it can be considered that it is not feasible to implant the implant at the predicted planning position corresponding to the target tooth position. For example, the implant cannot last, or the bone around the predicted planning position is difficult to recover and grow, so the attribute information of the implant corresponding to at least one target tooth position is re-determined. By inputting the three-dimensional oral segmentation result, the morphological data of the end of the robotic arm, the target tooth position, and the updated attribute information of the implant corresponding to each target tooth position and the soft and hard tissue association information into the preset planning model, the updated predicted planning position corresponding to each target tooth position is obtained. A feasibility analysis is performed based on the updated predicted planning position corresponding to each target tooth position to obtain a feasibility analysis result. When the feasibility analysis result meets the preset feasible judgment conditions, a planning display result is generated based on the three-dimensional oral segmentation result, the predicted planning position corresponding to each target tooth position, and the updated attribute information of the implant corresponding to each target tooth position. When the feasibility analysis result does not meet the preset feasibility judgment conditions, the attribute information of the implant corresponding to at least one target tooth position is updated again, and the predicted planning positions corresponding to each target tooth position are re-determined based on the updated attribute information of the implant, and the feasibility analysis of the predicted planning positions corresponding to each target tooth position is performed again.

[0080] Exemplarily, assuming that the stress analysis result of a target tooth position does not meet the tooth position stress condition, the updated attribute information of the implant to be implanted corresponding to the target tooth position has a smaller diameter and / or shorter length than the attribute information of the implant to be implanted before the update.

[0081] On the basis of the above embodiment, the retention prediction of the implant to be implanted in the target tooth position in the planning display result is performed based on the retention prediction model, and the retention information of each implant to be implanted is determined, and the retention information includes the retention time and the retention probability corresponding to the retention time. Among them, the retention prediction model is a machine learning model that is pre-trained and used to predict the retention information of the implant to be implanted. The retention prediction model can be trained based on the planning display results and actual retention information of the sample implant.

[0082] On the basis of the above embodiment, the planning display result is displayed on the interactive page, and in response to the user's adjustment operation on the position of the implant to be implanted in the planning display result on the interactive page, the predicted planning position of the implant to be implanted is updated to obtain the updated planning display result. Based on the retention prediction model, the retention prediction of the implant to be implanted in the target tooth position in the updated planning display result is performed to determine the retention information of each implant to be implanted.

[0083] In the case of any of the above retention predictions, the retention time and retention probability of each implant to be implanted are displayed. The retention time may be multiple, for example, including but not limited to half a year, one year, two years, five years, etc. If the retention probability corresponding to any retention time is less than the probability threshold, a first mark is set for the retention time. A second mark is set for the maximum retention time greater than the probability threshold, and when the maximum retention time greater than the probability threshold is less than the retention time threshold, a prompt message is generated, which is used to prompt the implant to be replanned.

[0084] The technical solution of this embodiment obtains the predicted planning positions corresponding to each target tooth position by inputting the three-dimensional oral segmentation results, the morphological data of the end of the robotic arm, the target tooth position and the attribute information of the implants corresponding to each target tooth position, and the soft and hard tissue association information into a preset planning model. Instead of only predicting the predicted planning positions corresponding to each target tooth position based on the three-dimensional oral segmentation results, the target tooth position and the attribute information of the implants corresponding to each target tooth position, the problem that the prior art cannot ensure that the predicted planning positions support the operation of the end of the robotic arm is solved, and the reliability of the predicted planning positions is improved.

[0085] Embodiment 2

[0086] Figure 2 1 is a flowchart of an implant position planning method provided by Embodiment 2 of the present invention. The technical solution of the embodiment of the present invention is improved on the basis of the above embodiment. The explanations of the terms that are the same or corresponding to the above embodiments are not repeated here. Figure 2 As shown, the method includes:

[0087] S210, acquiring tooth image data of the target object and morphological data of the end of the robotic arm, and determining at least one target tooth position and attribute information of the implant corresponding to each target tooth position.

[0088] S220, generating a three-dimensional oral cavity segmentation result based on the dental image data, and determining the soft and hard tissue association information corresponding to each target tooth position based on the dental image data.

[0089] S230, input the three-dimensional oral segmentation results, the morphological data of the end of the robotic arm, the target tooth position, and the attribute information of the implant to be implanted corresponding to each target tooth position and the soft and hard tissue association information into the preset planning model to obtain the predicted planning position corresponding to each target tooth position.

[0090] S240. Perform a feasibility analysis based on the predicted planned positions corresponding to each target tooth position to obtain a feasibility analysis result, wherein the feasibility analysis includes one or more of a robot arm operation feasibility analysis and a stress analysis of each target tooth position. Accordingly, the feasibility analysis result includes the operating range of the robot arm end and / or the stress analysis result of each target tooth position.

[0091] S250. When the feasibility analysis result meets the preset feasibility judgment conditions, call the pre-trained expert solution model, perform tooth position planning processing on the tooth image data based on the expert solution model, and obtain the expert planning position corresponding to each target tooth position.

[0092] In this embodiment, the expert solution model is a machine learning model. In some embodiments, optionally, the expert solution model is trained based on sample tooth image data corresponding to a set expert and implant position planning labels corresponding to the sample tooth image data; there is at least one expert solution model.

[0093] In this embodiment, the set experts are experts in the field of dental implants. It is understandable that each set expert corresponds to an expert solution model. The sample dental image data corresponding to the set expert is the dental image data diagnosed by the set expert. The sample dental image data can be obtained by transmission through internal or external storage systems such as storage systems such as Picture Archiving and Communication Systems (PACS), or can be obtained by calling an electronic medical record system. This embodiment does not limit this. The implant position planning label is the sample dental image data including the implant mark. The implant mark is a mark that characterizes the position of the implant in the sample dental image data. For example, the implant mark is a color mark.

[0094] Specifically, during the training process of the expert solution model, the sample tooth image data corresponding to the set expert is input into the expert solution model to obtain the implant position planning prediction result corresponding to the sample tooth image data. The target loss function is determined based on the implant position planning prediction result corresponding to the sample tooth image data and the implant position planning label, and the model parameters of the expert solution model corresponding to the set expert are optimized based on the target loss function. For example, the expert solution model is a random forest model or a decision tree model. Among them, the implant position planning prediction result is the sample tooth image data including the predicted implant marker. The predicted implant marker is a marker characterizing the implant predicted by the expert solution model.

[0095] The technical solution of this embodiment is to obtain an expert solution model based on sample tooth image data corresponding to the set expert and implant position planning labels corresponding to the sample tooth image data, so that each expert solution model corresponds to a set expert, which helps to subsequently determine the expert planning position that meets the implant position planning habits of the set expert based on the expert solution model.

[0096] The expert planning position is the planned position of the implant corresponding to the target tooth position determined based on the expert solution model. When the feasibility analysis result meets the preset feasible judgment conditions, the expert solution model call instruction is parsed to determine the expert solution model to be called. The expert solution model to be called is called and processed. In some embodiments, in the process of calling the expert solution model, one or more setting experts are obtained by parsing the expert solution model call instruction, and the corresponding expert solution model is called based on each setting expert obtained by the analysis.

[0097] By inputting the dental image data of the target object into the expert solution model, an expert solution result corresponding to the dental image data is obtained. The expert solution result is the dental image data including the predicted implant mark. The planned position of the implant corresponding to the predicted implant mark of each target tooth position in the expert solution result is determined as the expert planned position corresponding to each target tooth position. Exemplarily, assuming that the implant position planning habit of any set expert is closer to the lingual side than the labial side compared to the implant position planning habit of other set experts, then the expert planned position corresponding to each target tooth position determined by the expert solution model corresponding to the set expert is closer to the lingual side compared to each target tooth position determined by the expert solution model corresponding to other set experts.

[0098] S260: Determine the target planning position corresponding to each target tooth position based on the predicted planning position and the expert planning position corresponding to each target tooth position.

[0099] Optionally, a feasibility analysis is performed on the expert planning position to obtain the feasibility analysis result of the expert planning position. If the feasibility analysis result of the expert planning position meets the preset feasibility judgment condition, the expert planning position can be determined as the target planning position. If the feasibility analysis result of the expert planning position does not meet the preset feasibility judgment condition, the predicted planning position is adjusted at least once, and the predicted planning position is adjusted in the direction of the expert planning position. After each adjustment, a feasibility analysis is performed to obtain the planning position that meets the preset feasibility judgment condition and is closest to the expert planning position as the target planning position.

[0100] Optionally, the predicted planning position is manually or automatically corrected based on the expert planning position corresponding to each target tooth position, and the corrected predicted planning position is determined as the target planning position.

[0101] In some embodiments, the correction process is an automatic correction process, by calculating the distance between the predicted planning position and the expert planning position corresponding to each target tooth position, and obtaining the error distance. When the error distance is less than the first preset distance threshold, it can be considered that the predicted planning position conforms to the implant position planning habit set by the expert, and the predicted planning position is determined as the target planning position. When the error distance is greater than or equal to the first preset distance threshold, and less than the second preset distance threshold, it can be considered that there is a gap between the predicted planning position and the implant position planning habit set by the expert, and the predicted planning position is fine-tuned toward the target planning position. When the error distance is greater than the second preset distance threshold, it can be considered that the predicted planning position does not conform to the implant position planning habit set by the expert, and the expert planning position can be determined as the target planning position, or the predicted planning position corresponding to the target tooth position can be re-determined based on the attribute information of the implant to be implanted in each target tooth position in the expert solution result, and the target planning position corresponding to each target tooth position is determined based on the re-determined predicted planning position corresponding to the target tooth position and the expert planning position corresponding to the target tooth position.

[0102] In some embodiments, the correction process is a manual correction process, and optionally, the predicted planning position and expert planning position corresponding to each target tooth position are displayed; in response to the adjustment operation of the predicted planning position corresponding to the target tooth position, the predicted planning position corresponding to the target tooth position is adjusted, and the adjusted position of the predicted planning position corresponding to the target tooth position is determined as the target planning position.

[0103] Specifically, by drawing a first position mark corresponding to the predicted planning position and a second position mark corresponding to the expert planning position in the three-dimensional oral segmentation result, the predicted planning position and the expert planning position corresponding to each target tooth position can be displayed, wherein the first position mark and the second position label can be color marks or pattern marks. It should be noted that the first position mark is distinguished from the second position mark.

[0104] The predicted planning position adjustment operation is an operation of manually adjusting the predicted planning position. When the predicted planning position adjustment operation is identified, the predicted planning position corresponding to the target tooth position is adjusted according to the predicted planning position adjustment operation to obtain the target planning position.

[0105] For example, the predicted planning position adjustment operation is a dragging operation on the predicted planning position, and the position of the predicted planning position corresponding to the target tooth position after the dragging process is determined as the target planning position.

[0106] The technical solution of this embodiment determines the target planned position in response to the predicted planned position adjustment operation corresponding to the target tooth position, which can improve the interactivity of the target planned position determination and help improve the reliability of implant position planning.

[0107] S270 , generating a planning display result based on the three-dimensional oral cavity segmentation result, the target planning position corresponding to each target tooth position, and the attribute information of the implant to be implanted corresponding to each target tooth position.

[0108] Specifically, based on the attribute information of the implant corresponding to each target tooth position, the morphological structure of the implant corresponding to the target tooth position is drawn at the target planning position corresponding to the target tooth position in the three-dimensional oral segmentation result to obtain a planning display result.

[0109] Optionally, a retention prediction is performed on the implants to be implanted in the target tooth position in the planning display result based on a retention prediction model to determine the retention information of each implant to be implanted.

[0110] The technical solution of this embodiment determines the target planning position corresponding to each target tooth position based on the predicted planning position and the expert planning position corresponding to each target tooth position; generates a planning display result based on the three-dimensional oral segmentation result, the target planning position corresponding to each target tooth position, and the attribute information of the implant to be implanted corresponding to each target tooth position, which can make the planning display result more in line with the expert's implant position planning habits and help reduce the workload of experts in implant position planning.

[0111] Embodiment 3

[0112] Figure 3 Schematic diagram of the structure of an auxiliary planting system provided by the third embodiment of the present invention. Figure 3As shown, the system includes:

[0113] The interaction module 310 is used to receive at least one target tooth position and attribute information of at least one implant corresponding to the target tooth position input by a user;

[0114] The processing module 320 is used to obtain the tooth image data of the target object and the morphological data of the end of the robot arm, and determine at least one target tooth position and the attribute information of the implant to be implanted corresponding to each target tooth position; generate a three-dimensional oral segmentation result based on the tooth image data, and determine the soft and hard tissue association information corresponding to each target tooth position based on the tooth image data; input the three-dimensional oral segmentation result, the morphological data of the end of the robot arm, the target tooth position, and the attribute information and soft and hard tissue association information of the implant to be implanted corresponding to each target tooth position into a preset planning model to obtain the predicted planning position corresponding to each target tooth position; perform a feasibility analysis based on the predicted planning position corresponding to each target tooth position to obtain a feasibility analysis result, wherein the feasibility analysis includes one or more of the feasibility analysis of the robot arm operation and the stress analysis of each target tooth position, and accordingly, the feasibility analysis result includes the operating range of the end of the robot arm and / or the stress analysis result of each target tooth position; when the feasibility analysis result meets the preset feasible judgment condition, generate a planning display result based on the three-dimensional oral segmentation result, the predicted planning position corresponding to each target tooth position, and the attribute information of the implant to be implanted corresponding to each target tooth position;

[0115] The interactive module 310 is also used to display the three-dimensional oral cavity segmentation results and planning display results.

[0116] In some embodiments, the interactive module 310 includes an interactive interface, wherein the interactive interface includes one or more of a display interface, a target tooth position determination interface, a to-be-implanted body determination interface, an expert plan surface model determination interface, and a feasibility analysis interface. The display interface includes but is not limited to a three-dimensional oral cavity segmentation result display interface, a planning position display interface, and a planning display result display interface. The three-dimensional oral cavity segmentation result display interface is used to display the three-dimensional oral cavity segmentation result, the planning position display interface is used to display the predicted planning position and the expert planning position, and the planning display result is used to display the planning display result.

[0117] The technical solution of this embodiment obtains the predicted planning positions corresponding to each target tooth position by inputting the three-dimensional oral segmentation results, the morphological data of the end of the robotic arm, the target tooth position and the attribute information of the implants corresponding to each target tooth position, and the soft and hard tissue association information into a preset planning model. Instead of only predicting the predicted planning positions corresponding to each target tooth position based on the three-dimensional oral segmentation results, the target tooth position and the attribute information of the implants corresponding to each target tooth position, the problem that the prior art cannot ensure that the predicted planning positions support the operation of the end of the robotic arm is solved, and the reliability of the predicted planning positions is improved.

[0118] On the basis of the above-mentioned embodiment, optionally, the processing module 320 is specifically used to: determine the oral safety range based on a preset safety distance, three-dimensional oral segmentation results, attribute information of the implant corresponding to each target tooth position and the predicted planned position; determine the operating range of the robotic arm end based on the oral safety range and the morphological data of the robotic arm end.

[0119] On the basis of the above embodiment, optionally, the processing module 320 is specifically used to: determine at least one adjacent tooth corresponding to the current target tooth position based on each current target tooth position and the three-dimensional oral segmentation result; input the soft and hard tissue association information corresponding to the current target tooth position, the predicted planning position and the attribute information of the implant to be implanted, and the relative distance corresponding to at least one adjacent tooth corresponding to the current target tooth position into the stress analysis model corresponding to the current target tooth position to obtain the stress analysis result corresponding to the current target tooth position.

[0120] Based on the above embodiment, optionally, the processing module 320 is specifically used to: when the operating range of the end of the robotic arm satisfies the preset operating range, and / or when the stress analysis result of each target tooth position satisfies the tooth position stress condition, determine that the feasibility analysis result satisfies the preset feasibility judgment condition.

[0121] On the basis of the above-mentioned embodiment, optionally, the processing module 320 is also used for: when the feasibility analysis result meets the preset feasibility judgment conditions, calling the pre-trained expert solution model, performing tooth position planning processing on the dental image data based on the expert solution model, and obtaining the expert planning position corresponding to each target tooth position; determining the target planning position corresponding to each target tooth position based on the predicted planning position and the expert planning position corresponding to each target tooth position; generating a planning display result based on the three-dimensional oral segmentation result, the target planning position corresponding to each target tooth position, and the attribute information of the implant corresponding to each target tooth position.

[0122] On the basis of the above embodiment, optionally, the expert solution model is obtained by training based on the sample tooth image data corresponding to the set expert and the implant position planning label corresponding to the sample tooth image data; there is at least one expert solution model; accordingly, the processing module 320 is specifically used to: display the predicted planning position and the expert planning position corresponding to each target tooth position; in response to the adjustment operation of the predicted planning position corresponding to the target tooth position, adjust the predicted planning position corresponding to the target tooth position, and determine the adjusted position of the predicted planning position corresponding to the target tooth position as the target planning position.

[0123] On the basis of the above embodiment, optionally, the processing module 320 is also used to: update the attribute information of the implant to be implanted corresponding to at least one target tooth position when the feasibility analysis result does not meet the preset feasibility judgment condition; re-determine the predicted planned position corresponding to each target tooth position based on the updated attribute information of the implant to be implanted; and re-perform a feasibility analysis on the predicted planned position corresponding to each target tooth position until the feasibility analysis result corresponding to the updated attribute information of the implant to be implanted meets the preset feasibility judgment condition.

[0124] On the basis of the above embodiment, optionally, the processing module 320 is also used to: verify the attribute information of the implant to be implanted corresponding to the target tooth position based on the soft and hard tissue association information corresponding to the target tooth position, wherein the attribute information of the implant to be implanted corresponding to the target tooth position includes the attribute information of the implant to be implanted selected by the user or the attribute information of the implant to be implanted predicted by the expert solution model; when the attribute information of the implant to be implanted corresponding to the target tooth position does not match the soft and hard tissue association information corresponding to the target tooth position, generate an attribute update prompt for the implant to be implanted.

[0125] On the basis of the above embodiment, optionally, the processing module 320 is also used to: perform retention prediction on the implants to be implanted in the target tooth position in the planning display result based on the retention prediction model, and determine the retention information of each implant to be implanted, wherein the retention information includes the retention time and the retention probability corresponding to the retention time.

[0126] The processing module in the auxiliary implant system provided in the embodiment of the present invention can execute the implant position planning method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0127] Embodiment 4

[0128] Figure 41 is a schematic diagram of the structure of an electronic device for implementing the implant position planning method of an embodiment of the present invention. The electronic device 10 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0129] like Figure 4 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0130] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0131] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as an implant position planning method.

[0132] In some embodiments, the implant position planning method can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the implant position planning method described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to perform the implant position planning method in any other appropriate manner (e.g., by means of firmware).

[0133] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0134] The computer program for implementing the implant position planning method of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program can be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0135] Embodiment 5

[0136] Embodiment 5 of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to execute an implant position planning method, the method comprising:

[0137] Acquire the tooth image data of the target object and the morphological data of the end of the robot arm, and determine at least one target tooth position and the attribute information of the implant to be implanted corresponding to each target tooth position; generate a three-dimensional oral segmentation result based on the tooth image data, and determine the soft and hard tissue association information corresponding to each target tooth position based on the tooth image data; input the three-dimensional oral segmentation result, the morphological data of the end of the robot arm, the target tooth position, and the attribute information and soft and hard tissue association information of the implant to be implanted corresponding to each target tooth position into a preset planning model to obtain the predicted planning position corresponding to each target tooth position; perform a feasibility analysis based on the predicted planning position corresponding to each target tooth position to obtain a feasibility analysis result, wherein the feasibility analysis includes one or more of the feasibility analysis of the robot arm operation and the stress analysis of each target tooth position, and accordingly, the feasibility analysis result includes the operating range of the end of the robot arm and / or the stress analysis result of each target tooth position; when the feasibility analysis result meets the preset feasible judgment condition, generate a planning display result based on the three-dimensional oral segmentation result, the predicted planning position corresponding to each target tooth position, and the attribute information of the implant to be implanted corresponding to each target tooth position.

[0138] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. 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.

[0139] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0140] The systems and techniques described herein may be implemented in a computing system that includes a backend (e.g., as a data server), or a computing system that includes middleware (e.g., an application server), or a computing system that includes a frontend (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backends, middleware, or frontends. The systems may be interconnected by 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), a blockchain network, and the Internet.

[0141] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0142] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0143] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for implant position planning, characterized in that: include: Acquire the tooth image data of the target object and the morphological data of the end of the robot arm, and determine at least one target tooth position and the attribute information of the implant to be implanted corresponding to each target tooth position; Generate a three-dimensional oral cavity segmentation result based on the tooth image data, and determine the soft and hard tissue association information corresponding to each target tooth position based on the tooth image data; Input the three-dimensional oral segmentation result, the morphological data of the end of the robotic arm, the target tooth position, and the attribute information of the implant to be implanted and the soft and hard tissue association information corresponding to each target tooth position into a preset planning model to obtain the predicted planning position corresponding to each target tooth position; Performing a feasibility analysis based on the predicted planning positions corresponding to each of the target tooth positions, and obtaining a feasibility analysis result, wherein the feasibility analysis includes one or more of a feasibility analysis of the robot arm operation and a stress analysis of each of the target tooth positions, and correspondingly, the feasibility analysis result includes an operating range of the robot arm end and / or a stress analysis result of each of the target tooth positions; When the feasibility analysis result meets the preset feasibility judgment conditions, a planning display result is generated based on the three-dimensional oral segmentation result, the predicted planning position corresponding to each target tooth position, and the attribute information of the implant corresponding to each target tooth position.

2. The method according to claim 1, characterized in that The feasibility analysis of the robot arm operation based on the predicted planning positions corresponding to the target tooth positions includes: Determine the oral safety range based on the preset safety distance, the three-dimensional oral segmentation result, the attribute information of the implant to be implanted corresponding to each target tooth position, and the predicted planned position; The operating range of the robot arm end is determined based on the oral safety range and the morphological data of the robot arm end.

3. The method according to claim 1, characterized in that: The stress analysis of each target tooth position based on the predicted planning position corresponding to each target tooth position includes: Based on each current target tooth position and the three-dimensional oral cavity segmentation result, determining at least one adjacent tooth corresponding to the current target tooth position; The soft and hard tissue association information corresponding to the current target tooth position, the predicted planned position and the attribute information of the implant to be implanted, and the relative distance corresponding to at least one adjacent tooth corresponding to the current target tooth position are input into the stress analysis model corresponding to the current target tooth position to obtain the stress analysis result corresponding to the current target tooth position.

4. The method according to claim 1, characterized in that: The method further comprises: When the operating range of the end of the robotic arm satisfies the preset operating range, and / or when the stress analysis result of each target tooth position satisfies the tooth position stress condition, it is determined that the feasibility analysis result satisfies the preset feasibility determination condition.

5. The method according to claim 1, characterized in that The method further comprises: When the feasibility analysis result meets the preset feasibility judgment condition, calling the pre-trained expert solution model, performing tooth position planning processing on the tooth image data based on the expert solution model, and obtaining the expert planning position corresponding to each target tooth position; Determine a target planning position corresponding to each target tooth position based on the predicted planning position and the expert planning position corresponding to each target tooth position; The planning display result is generated based on the three-dimensional oral segmentation result, the target planning positions corresponding to the target tooth positions, and the attribute information of the implants corresponding to the target tooth positions.

6. The method according to claim 5, characterized in that The expert solution model is obtained by training based on the sample tooth image data corresponding to the set expert and the implant position planning label corresponding to the sample tooth image data; the expert solution model is at least one; Determining the target planning position corresponding to each target tooth position based on the predicted planning position and the expert planning position corresponding to each target tooth position includes: Displaying the predicted planned position and the expert planned position corresponding to each target tooth position; In response to an adjustment operation on the predicted planned position corresponding to the target tooth position, the predicted planned position corresponding to the target tooth position is adjusted, and the adjusted position of the predicted planned position corresponding to the target tooth position is determined as the target planned position.

7. The method according to claim 1, characterized in that The method further comprises: When the feasibility analysis result does not satisfy the preset feasibility judgment condition, update the attribute information of the implant to be implanted corresponding to at least one of the target tooth positions; re-determine the predicted planned positions corresponding to each of the target tooth positions based on the updated attribute information of the implant to be implanted; and re-perform a feasibility analysis on the predicted planned positions corresponding to each of the target tooth positions until the feasibility analysis result corresponding to the updated attribute information of the implant to be implanted satisfies the preset feasibility judgment condition.

8. The method according to claim 5, characterized in that The method further comprises: Verifying the attribute information of the implant to be implanted corresponding to the target tooth position based on the soft and hard tissue association information corresponding to the target tooth position, wherein the attribute information of the implant to be implanted corresponding to the target tooth position includes the attribute information of the implant to be implanted selected by a user or the attribute information of the implant to be implanted predicted by the expert solution model; When the property information of the implant to be implanted corresponding to the target tooth position does not match the soft and hard tissue association information corresponding to the target tooth position, a prompt for updating the property of the implant to be implanted is generated.

9. The method according to any one of claims 1 to 8, characterized in that: The method further comprises: Based on the retention prediction model, a retention prediction is performed on the implants to be implanted in the target tooth position in the planning display result to determine the retention information of each implant to be implanted, wherein the retention information includes a retention duration and a retention probability corresponding to the retention duration.

10. An auxiliary planting system, characterized in that: include: An interactive module, used for receiving at least one target tooth position input by a user and attribute information of at least one to-be-implanted object respectively corresponding to the target tooth position; A processing module, used to obtain the tooth image data of the target object and the morphological data of the end of the robotic arm, and determine at least one target tooth position and the attribute information of the implant to be implanted corresponding to each of the target tooth positions; generate a three-dimensional oral segmentation result based on the tooth image data, and determine the soft and hard tissue association information corresponding to each of the target tooth positions based on the tooth image data; input the three-dimensional oral segmentation result, the morphological data of the end of the robotic arm, the target tooth position, and the attribute information and soft and hard tissue association information of the implant to be implanted corresponding to each of the target tooth positions into a preset planning model to obtain the predicted planning position corresponding to each of the target tooth positions; perform a feasibility analysis based on the predicted planning position corresponding to each of the target tooth positions to obtain a feasibility analysis result, wherein the feasibility analysis includes one or more of a feasibility analysis of the robotic arm operation and a stress analysis of each of the target tooth positions, and accordingly, the feasibility analysis result includes the operating range of the end of the robotic arm and / or the stress analysis result of each of the target tooth positions; when the feasibility analysis result meets the preset feasible judgment condition, generate a planning display result based on the three-dimensional oral segmentation result, the predicted planning position corresponding to each of the target tooth positions, and the attribute information of the implant to be implanted corresponding to each of the target tooth positions; The interactive module is also used to display the three-dimensional oral cavity segmentation result and the planning display result.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the implant position planning method according to any one of claims 1 to 9 when executed.

12. A computer program product, characterized in that The computer program product comprises a computer program, which, when executed by a processor, implements the implant position planning method according to any one of claims 1-9.

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