Methods, devices, electronic equipment and storage media for evaluating dental implant materials

Abstract

The application provides an oral implant material evaluation method and device, electronic equipment and storage medium, and relates to the technical field of medical data processing. The method comprises the following steps: obtaining target information, wherein the target information comprises first attribute information and second attribute information, the first attribute information belongs to a to-be-evaluated implant, and the second attribute information belongs to target implant tissue; generating a first target model and a second target model according to the target information; generating a target artifact analysis result according to the first target model and the second target model; and generating a material evaluation result of the to-be-evaluated implant according to the target artifact analysis result. In this way, the automation level of the implant evaluation process is improved, and the output accuracy of the implant evaluation result is improved. During clinical treatment, the bone mass and density around the implant can be accurately evaluated, the judgment of the tooth movement direction and the relationship between the tooth root and the implant is not disturbed, and the clinical treatment is facilitated.

Description

Technical Field

[0001] Embodiments of this application relate to medical data processing, and more particularly to a method, apparatus, electronic device, and storage medium for evaluating dental implant materials. Background Technology

[0002] Implant evaluation aims to assess the performance, safety, and biocompatibility of the implant to ensure it can stably support the prosthesis long-term without adverse effects on surrounding tissues. Currently, related technologies for implant evaluation suffer from low levels of automation and poor accuracy of evaluation results.

[0003] Therefore, a new technical solution is urgently needed to solve the above-mentioned technical problems. Summary of the Invention

[0004] According to embodiments of this application, a method, apparatus, electronic device, and storage medium for evaluating dental implant materials are provided, which are beneficial to improving the automation level of the implant evaluation process and increasing the output accuracy of implant evaluation results.

[0005] In a first aspect of this application, a method for evaluating dental implant materials is provided, comprising:

[0006] Obtain target information, which includes: first attribute information and second attribute information, wherein the first attribute information belongs to the implant to be evaluated, and the second attribute information belongs to the target implant tissue;

[0007] Based on the target information, generate a first target model and a second target model;

[0008] Based on the first target model and the second target model, generate target artifact analysis results;

[0009] Based on the target artifact analysis results, the material evaluation results of the implant to be evaluated are generated.

[0010] In some feasible implementations, the generation of target artifact analysis results based on the first target model and the second target model includes:

[0011] A target γ-photon beam is applied to the first target model to obtain the first signal distribution information;

[0012] A target γ-photon beam is applied to the second target model to obtain second signal distribution information;

[0013] Based on the first signal distribution information and the second signal distribution information, the target artifact analysis results are generated.

[0014] In some feasible implementations, generating target artifact analysis results based on the first signal distribution information and the second signal distribution information includes:

[0015] Based on the first signal distribution information and the second signal distribution information, determine the intensity attenuation information and / or scattering information of the target γ photon beam;

[0016] Based on intensity attenuation information and / or scattering information, target artifact analysis results are generated.

[0017] In some feasible implementations, the determination of the intensity attenuation information of the target γ-photon beam and / or the scattering information based on the first signal distribution information and the second signal distribution information includes:

[0018] The intensity attenuation information is determined using the following formula:

[0019] I = I0 × e -μx

[0020] Where I is the intensity of γ photons penetrating a thickness of x, I0 is the initial intensity of γ photons, μ is the linear attenuation coefficient, x is the penetration thickness, and e is the base of the natural logarithm;

[0021] The scattering information is determined using the following formula:

[0022]

[0023] Where λ is the wavelength of the γ photon before scattering, λ′ is the wavelength of the γ photon after scattering, and m e Let c be the electron's rest mass, c be the speed of light, and θ be the scattering angle.

[0024] In some feasible implementations, the target artifact analysis results, as described in any of the preceding embodiments, include:

[0025] Gray-scale distribution information, shape information, and / or area information of the target artifact.

[0026] In some feasible implementations, the above method further includes:

[0027] Determine the boundaries of the target artifacts based on the grayscale distribution information;

[0028] Perform target operations on the boundary to determine the target boundary;

[0029] Determine the area information based on the target boundary.

[0030] In some feasible implementations, the above method further includes:

[0031] Based on the coverage information of the target artifacts on the target planted tissue, the coverage rate information of the target artifacts on key points is determined; based on the coverage rate information, the evaluation results are generated.

[0032] In a second aspect of this application, an implant material evaluation device is provided, comprising:

[0033] The acquisition unit is used to acquire target information, wherein the target information includes: first attribute information and second attribute information, wherein the first attribute information belongs to the implant to be evaluated and the second attribute information belongs to the target implant tissue;

[0034] The first generation unit is used to generate a first target model and a second target model based on the target information.

[0035] The second generation unit is used to generate target artifact analysis results based on the first target model and the second target model;

[0036] The third generation unit is used to generate material evaluation results for the implant to be evaluated based on the target artifact analysis results.

[0037] In a third aspect of this application, an electronic device is provided, comprising: a processor and a memory, wherein the memory stores computer program instructions, which, when executed by the processor, are used to perform the oral implant material evaluation method as described in any of the preceding claims.

[0038] In a fourth aspect of this application, a computer storage medium is provided, on which program instructions are stored, which, when executed, are used to perform the oral implant material evaluation method as described in any of the preceding claims.

[0039] The oral implant material evaluation method, apparatus, and electronic device provided in this application include: acquiring target information, wherein the target information includes: first attribute information and second attribute information, wherein the first attribute information belongs to the implant to be evaluated, and the second attribute information belongs to the target implant tissue; generating a first target model and a second target model based on the target information; generating target artifact analysis results based on the first target model and the second target model; and generating material evaluation results for the implant to be evaluated based on the target artifact analysis results. This application is beneficial for improving the automation level of the implant evaluation process and increasing the output accuracy of implant evaluation results; enabling precise assessment of bone volume and density around the implant during clinical treatment, reducing interference in judging the direction of tooth movement and the relationship between the tooth root and the implant, thereby providing convenience for clinical treatment.

[0040] It should be understood that the description in the Summary Section is not intended to limit the key or essential features of the embodiments of this application, nor is it intended to restrict the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0041] The above and other features, advantages, and aspects of the embodiments of this application will become more apparent from the accompanying drawings and the following detailed description. In the drawings, the same or similar reference numerals denote the same or similar elements, wherein:

[0042] Figure 1 A flowchart illustrating a method for evaluating dental implant materials provided in an embodiment of this application;

[0043] Figure 2 This is a structural schematic diagram of an implant material evaluation device provided in an embodiment of this application;

[0044] Figure 3 This is a structural schematic diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0045] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0046] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0047] Implant evaluation aims to assess the performance, safety, and biocompatibility of the implant to ensure it can stably support the restoration long-term without adverse effects on surrounding tissues. Currently, artifacts created by metal implants can lead to missed or misdiagnosed lesions, making it difficult to accurately assess bone volume and density around the implant during clinical treatment. This interferes with determining the direction of tooth movement and the relationship between the root and implant, resulting in low automation and poor accuracy in implant evaluation results.

[0048] In view of this, the first aspect of the embodiments of this application proposes a method for evaluating dental implant materials. Figure 1This is a flowchart illustrating a method 100 for evaluating dental implant materials provided in an embodiment of this application. Figure 1 As shown, method 100 includes:

[0049] Step S110: Obtain target information, wherein the target information includes: first attribute information and second attribute information, wherein the first attribute information belongs to the implant to be evaluated, and the second attribute information belongs to the target implant tissue.

[0050] For example, the aforementioned first attribute information may include: material attribute information and size attribute information of the implant to be evaluated. It should be noted that the aforementioned first attribute information may also include: the shape, cross-sectional area, and / or, implantation location of the implant to be evaluated, etc.

[0051] For example, the above material property information may include: atomic number, and / or, density parameters, etc.

[0052] Specifically, when the materials corresponding to the implants to be evaluated include materials such as titanium alloys and cobalt-chromium alloys, the material property information corresponding to the implants to be evaluated may include: the atomic number and / or density parameters of titanium alloys, and the atomic number and / or density parameters of cobalt-chromium alloys.

[0053] For example, the aforementioned dimensional attribute information may include: the length, diameter, and volume of the implant to be evaluated. Specifically, the aforementioned length may include: the total length of the implant to be evaluated, and / or, the length of the portion of the implant to be evaluated corresponding to the alveolar bone. The aforementioned diameter may correspond to the maximum width of the implant to be evaluated.

[0054] In some feasible implementations, the aforementioned second attribute information includes: attribute information of the target implanted tissue.

[0055] For example, the target implant tissue may include: target alveolar bone tissue, target soft tissue, etc. The attribute information of the target implant tissue may include: material attribute information and dimensional attribute information of the target implant tissue.

[0056] For example, the material property information of the target implanted tissue may include: the atomic number of the target implanted tissue, and / or, density parameters, etc.

[0057] For example, the size attribute information of the target implanted tissue may include: the volume of the target implanted tissue, the height of the target implanted tissue, and / or the thickness of the target implanted tissue, etc.

[0058] It should be noted that the aforementioned first attribute information and the aforementioned second attribute information can be determined by manual input.

[0059] Step S120: Generate the first target model and the second target model based on the target information.

[0060] For example, a first target model containing the implant to be evaluated and the target implant tissue can be generated based on the first attribute information mentioned above.

[0061] For example, a second target model can be generated based on the second attribute information described above, which contains only the target implant tissue but not the implant to be evaluated.

[0062] The first and second target models mentioned above can be generated based on MCNP software.

[0063] Based on this, by accurately generating the first target model and the second target model according to the attribute information of the implant to be evaluated and the target implant tissue, the simulation accuracy of the physical structure of the implant to be evaluated and the target implant tissue is improved, the simulation accuracy of the fit relationship and / or structural correlation between the implant to be evaluated and the target implant tissue is improved, and the experimental cost and risk caused by physical entity experiments are reduced.

[0064] Step S130: Generate target artifact analysis results based on the first target model and the second target model.

[0065] In some feasible implementations, generating target artifact analysis results based on the first target model and the second target model includes: applying a target γ-photon beam to the first target model to obtain first signal distribution information; applying a target γ-photon beam to the second target model to obtain second signal distribution information; and generating target artifact analysis results based on the first signal distribution information and the second signal distribution information.

[0066] For example, by setting the energy, intensity, incident angle, detector resolution, collimator parameters, and / or detector efficiency parameters of the X-ray source (i.e., the target gamma photon beam), the application of an X-ray (i.e., the target gamma photon beam) to a first target model can be simulated to obtain first signal distribution information, and the application of an X-ray (i.e., the target gamma photon beam) to a second target model can be simulated to obtain second signal distribution information. The parameters of the X-ray (i.e., the target gamma photon beam) applied to the first target model are the same as those of the X-ray (i.e., the target gamma photon beam) applied to the second target model. These parameters include the energy, intensity, incident angle, detector resolution, collimator parameters, and / or detector efficiency parameters of the X-ray source (i.e., the target gamma photon beam).

[0067] Based on this, by applying the target γ-photon beam to the first target model and the second target model, it is beneficial to accurately simulate the physical interaction process between the target γ-photon beam and the implant to be evaluated, so as to obtain the first signal distribution information. By accurately simulating the physical interaction process between the target γ-photon beam and the target implant tissue, the second signal distribution information can be obtained. Thus, by comparing the first signal distribution information and the second signal distribution information, the target artifact analysis results can be accurately generated, providing accurate data support for accurately generating the material evaluation results of the implant to be evaluated based on the target artifact analysis results.

[0068] In some feasible implementations, generating target artifact analysis results based on the first signal distribution information and the second signal distribution information includes: determining the intensity attenuation information and / or scattering information of the target γ-photon beam based on the first signal distribution information and the second signal distribution information; and generating target artifact analysis results based on the intensity attenuation information and / or scattering information.

[0069] For example, the first signal distribution information and the second signal distribution information mentioned above can be determined based on the corresponding CBCT images.

[0070] It should be noted that after the target gamma photon beam passes through the first or second target model, the target gamma photons will interact with the implant to be evaluated or the target implant tissue, causing energy loss in the target gamma photon beam and thus changing the signal distribution. These interactions can include the photoelectric effect, Compton scattering, and / or pair effects, and the changes in signal distribution can include changes in intensity and / or changes in transmission direction.

[0071] It should be noted that when the atomic number and density of the material corresponding to the implant to be evaluated are high, the target gamma photon beam will have a strong photoelectric effect with the implant to be evaluated. A large number of electrons in the inner shell of the metal atoms corresponding to the implant to be evaluated will undergo transitions, resulting in the absorption of a large number of gamma photons in the target gamma photon beam. The number of gamma photons at the corresponding position of the implant to be evaluated will be greatly reduced, resulting in a strong intensity attenuation of the target gamma photon beam. As a result, the signal change at the corresponding position of the implant to be evaluated will be high, and bright white stripes will form at the corresponding position of the implant to be evaluated, thus obscuring the structure of the target implant tissue. The aforementioned structure may include fine structures such as microvessels and periodontal ligament. Conversely, when the atomic number and density of the material corresponding to the implant to be evaluated are small, the target γ-photon beam will have a weak photoelectric effect with the implant to be evaluated. A small number of electrons in the inner shell of the metal atoms corresponding to the implant to be evaluated will undergo transitions, resulting in the absorption of a small number of γ-photons in the target γ-photon beam. The number of γ-photons at the corresponding position of the implant to be evaluated will decrease slightly, resulting in a weak intensity attenuation of the target γ-photon beam. As a result, the signal change at the corresponding position of the implant to be evaluated will be small, the contrast with the target implant tissue will be small, and dark stripes or blurry shadows will form at the corresponding position of the implant to be evaluated.

[0072] In some feasible implementations, determining the intensity attenuation information and / or scattering information of the target γ-photon beam based on the first signal distribution information and the second signal distribution information includes determining the intensity attenuation information according to the following formula:

[0073] I = I0 × e -μx (1)

[0074] Where I is the intensity of γ photons penetrating a thickness of x, I0 is the initial intensity of γ photons, μ is the linear attenuation coefficient, x is the penetration thickness, and e is the base of the natural logarithm.

[0075] It should be noted that the linear attenuation coefficient μ is positively correlated with the atomic number Z, density ρ, and energy E of the γ photon of the implant to be evaluated. That is, the larger the atomic number Z, the larger the density ρ, and the higher the energy E of the γ photon of the implant to be evaluated, the larger the linear attenuation coefficient μ and the faster the intensity of the γ photon attenuates.

[0076] It should be noted that, due to the low atomic number of the target implant tissue, the target gamma photon beam will undergo strong Compton scattering with the implant to be evaluated, which will cause a significant change in the direction of the target gamma photon beam and a loss of some energy.

[0077] For example, the scattering information mentioned above may include scattering angle information and / or scattering cross section information.

[0078] In some feasible implementations, the determination of the intensity attenuation information of the target γ-photon beam based on the first signal distribution information and the second signal distribution information, and / or the scattering information further includes: determining the scattering information according to the following formula:

[0079]

[0080] Where λ is the wavelength of the γ photon before scattering, λ′ is the wavelength of the γ photon after scattering, and m e Let c be the electron's rest mass, c be the speed of light, and θ be the scattering angle.

[0081] It should be noted that the scattering cross section σ c It is positively correlated with the atomic number Z. The aforementioned scattering cross section σ c Within a preset range, it is negatively correlated with the energy E of the γ photon.

[0082] It should be noted that, in some feasible implementations, the accuracy of determining the first signal distribution information and the second signal distribution information can be improved by adjusting the energy, intensity, and / or incident angle of the γ photons, thereby improving the accuracy of determining the target artifact analysis results.

[0083] Therefore, the above method can accurately determine the intensity attenuation information and / or scattering information according to the above formulas (1)-(2).

[0084] Based on this, the above method can accurately determine the target γ-photon beam passing through the implant to be evaluated, and / or the intensity attenuation information and / or scattering information of the target implant tissue by comparing the first signal distribution information and the second signal distribution information, thereby accurately generating target artifact analysis results and providing data support for objectively and quantitatively evaluating the performance of the implant to be evaluated.

[0085] Step S140: Based on the target artifact analysis results, generate the material evaluation results for the implant to be evaluated.

[0086] In some feasible implementations, the above-mentioned target artifact analysis results include: grayscale distribution information, shape information, and / or area information of the target artifact.

[0087] For example, the grayscale distribution information, shape information, and / or area information of the target artifact can be determined by comparing the first signal distribution information and the second signal distribution information.

[0088] It should be noted that before determining the grayscale distribution information, shape information, and / or area information of the target artifact based on the first and second signal distribution information, filtering operations can be performed on the first and second signal distribution information to achieve accurate noise reduction. Specifically, target filtering parameters can be set based on methods such as Gaussian filtering to perform filtering operations on the first and second signal distribution information.

[0089] Specifically, the difference between the grayscale histograms corresponding to the first signal distribution information and the second signal distribution information can be determined by comparing their grayscale histograms. Based on this difference, the grayscale distribution information of the target artifact can be determined.

[0090] Specifically, the boundary of the target artifact can be determined based on the edge detection algorithm and the first and second signal distribution information, thereby determining the shape information.

[0091] It should be noted that when the structure and shape of the implant to be evaluated are complex, the artifacts corresponding to the implant will be distorted and curved, and the artifacts will cover a large area of ​​the target implant tissue, affecting the observation of the target implant tissue. The target implant tissue includes the teeth surrounding the implant site and / or the alveolar bone. When the structure and shape of the implant to be evaluated are relatively regular, the artifacts corresponding to the implant will be more regular in shape, and the artifacts will cover a smaller area of ​​the target implant tissue, appearing concentrated at the implant site in a concentric ring or radial distribution.

[0092] In some feasible implementations, the above method further includes: determining the boundary of the target artifact based on grayscale distribution information; performing a target operation on the boundary to determine the target boundary; and determining the area information based on the target boundary.

[0093] For example, the boundary of the target artifact can be determined based on a target grayscale threshold, wherein the target grayscale threshold can be 200.

[0094] Specifically, if the gray value of the corresponding point is greater than 200 according to the gray histogram, then the above point is determined as the target point. Based on multiple target points, the boundary of the target artifact is determined.

[0095] It should be noted that the above target operations may include: corrosion operations, and / or, expansion operations.

[0096] For example, an erosion operation can be performed on the aforementioned boundary to eliminate isolated points and / or irregular line segments composed of multiple points in the boundary, and then an expansion operation can be performed to compensate for the eliminated isolated points and / or irregular line segments, thereby determining the aforementioned target boundary.

[0097] Specifically, the erosion operation and / or dilation operation described above can be performed based on the target structuring element. The target structuring element can be set according to the actual situation. For example, the target structuring element can be a 3×3 structuring element.

[0098] For example, the area information can be determined based on the number of pixels contained in the target boundary and the size of a single pixel. The artifact area is the product of the number of pixels contained in the target boundary and the area of ​​a single pixel.

[0099] Therefore, the above method can accurately determine the boundary of the target artifact based on the grayscale distribution information, perform target operations on the above boundary to determine the target boundary, and accurately determine the area information based on the above target boundary.

[0100] Alternatively, the area information can be determined based on the Region of Interest (ROI) set by the target user.

[0101] For example, the target user can select the corresponding shape selection tool based on the shape information of the target artifact to determine the area information. The corresponding shape selection tool may include: a rectangular selection tool, a circular selection tool, and / or an irregular shape selection tool.

[0102] Specifically, if the target artifact is circular in shape, the area of ​​interest can be selected using a circular selection tool to determine the area information.

[0103] In some feasible implementations, after completing the above selection operation, the scale information of the target artifact can be determined based on a preset calibration tool.

[0104] For example, the above-mentioned scale information can be determined based on a preset calibration tool and a reference object known to be of standard size.

[0105] Specifically, the size of a single pixel can be determined based on a preset calibration tool and a known metal sphere with a diameter of 5mm. The area information is then determined based on the number of pixels contained in the region of interest and the size of each individual pixel.

[0106] Therefore, the above method can generate material evaluation results for the implant to be evaluated from multiple dimensions based on the grayscale distribution information, shape information, and / or area information of the target artifact, thereby improving the accuracy of the generated material evaluation results for the implant to be evaluated.

[0107] In some feasible implementations, the above method further includes: determining the coverage information of key points of the target artifact based on the coverage point information of the target planted tissue; and generating evaluation results based on the coverage information.

[0108] For example, the aforementioned key locations can be determined based on the anatomical information and / or atlas information of the target implant tissue. Specifically, the aforementioned key locations may include: neural canals, vascular bundles, adjacent tooth roots, maxillary sinus floor, and / or bone margins, etc.

[0109] For example, the coverage rate can be determined by the ratio of the number of pixels at key points covered by the target artifacts to the total number of pixels at the key points.

[0110] Specifically, the above coverage rate can be determined according to the following formula:

[0111]

[0112] In some feasible implementations, weights can be set for multiple key points to generate the above evaluation results based on the weights and coverage of each key point.

[0113] Specifically, if the total coverage of the target artifacts on multiple key points is greater than a preset total coverage threshold, and / or if the coverage of the target artifacts on a single key point is greater than the corresponding coverage threshold, then the evaluation result is output as unqualified.

[0114] Specifically, if the total coverage of the target artifacts for multiple key points is less than or equal to a preset total coverage threshold, and if the coverage of the target artifacts for a single key point is less than or equal to the corresponding coverage threshold, then the evaluation result is output as qualified.

[0115] The total coverage rate mentioned above can be determined according to the following formula:

[0116]

[0117] Where n represents the number of key locations and the coverage rate. i The weight is the coverage of the i-th key point. i Let be the weight of the i-th key point.

[0118] Based on this, the above method can accurately determine the coverage information of key points of the target artifact based on the coverage point information of the target planting tissue, and generate the above evaluation results accurately, objectively and quantitatively based on the coverage information.

[0119] It should be noted that when the total coverage of the target artifact over multiple key points exceeds a preset total coverage threshold, and / or when the coverage of the target artifact over a single key point exceeds the corresponding coverage threshold (i.e., the evaluation result is unqualified), the component ratio of the implant to be evaluated can be adjusted so that the total coverage of the target artifact over multiple key points is less than or equal to the preset total coverage threshold, and the coverage of the target artifact over a single key point is less than or equal to the corresponding coverage threshold (i.e., the evaluation result is qualified). This achieves automated control of the component ratio of the implant to be evaluated, reducing the omission or misjudgment of lesions caused by artifacts formed by metal implants. It also allows for accurate assessment of bone mass and density around the implant during clinical treatment, reducing interference in judging the direction of tooth movement and the relationship between the root and the implant, thus facilitating clinical treatment.

[0120] Based on this, the oral implant material evaluation method provided in this application includes: acquiring target information, wherein the target information includes: first attribute information and second attribute information, wherein the first attribute information belongs to the implant to be evaluated, and the second attribute information belongs to the target implant tissue; generating a first target model and a second target model based on the target information; generating target artifact analysis results based on the first target model and the second target model; and generating material evaluation results for the implant to be evaluated based on the target artifact analysis results. This application is beneficial for accurately simulating the physical structure of the implant to be evaluated and the target implant tissue, as well as the fit relationship and / or structural correlation between the implant to be evaluated and the target implant tissue, based on the first attribute information and the second attribute information. Based on the aforementioned physical structure of the implant to be evaluated and the target implant tissue, as well as the fit relationship and / or structural correlation between the implant to be evaluated and the target implant tissue, the target artifact analysis results are accurately determined while saving experimental costs. Based on the target artifact analysis results, the material evaluation results for the implant to be evaluated are accurately output, thereby improving the automation level of the implant evaluation process and improving the accuracy of the implant evaluation results.

[0121] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0122] The above is an introduction to the method embodiments. The following describes the solution described in this application through device embodiments.

[0123] A second aspect of this application provides an implant material evaluation device. Figure 2 This is a structural schematic diagram of an implant material evaluation device 200 provided in an embodiment of this application. Figure 2 The apparatus 200 shown includes: an acquisition unit 210, a first generation unit 220, a second generation unit 230, and a third generation unit 240.

[0124] The acquisition unit 210 is used to acquire target information, wherein the target information includes: first attribute information and second attribute information, wherein the first attribute information belongs to the implant to be evaluated and the second attribute information belongs to the target implant tissue;

[0125] The first generation unit 220 is used to generate a first target model and a second target model based on the target information.

[0126] The second generation unit 230 is used to generate target artifact analysis results based on the first target model and the second target model;

[0127] The third generation unit 240 is used to generate material evaluation results for the implant to be evaluated based on the target artifact analysis results.

[0128] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the described method can be referred to the corresponding process in the foregoing system embodiments, and will not be repeated here.

[0129] Figure 3 This is a schematic diagram of the structure of an electronic device 300 provided in an embodiment of this application. Figure 3 As shown, the electronic device 300 includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage section 308 into a random access memory (RAM) 303. The RAM 303 also stores various programs and data required for the operation of the terminal device or server. The CPU 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0130] The following components are connected to I / O interface 305: an input section 306 including a keyboard, mouse, etc.; an output section 307 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN card, modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to I / O interface 305 as needed. A removable medium 311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on drive 310 as needed so that computer programs read from it can be installed into storage section 308 as needed.

[0131] Specifically, according to embodiments of this application, the above method flow steps can be implemented as a computer software program. For example, embodiments of this application include a computer program product comprising a computer program carried on a machine-readable medium, the computer program containing program code for performing the methods shown in the flowchart. In such embodiments, the computer program can be downloaded and installed from a network via communication section 309, and / or installed from removable medium 311. When the computer program is executed by central processing unit (CPU) 301, it performs the functions defined in the system of this application.

[0132] It should be noted that the computer-readable medium described in this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0133] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0134] The units or modules described in the embodiments of this application can be implemented in software or hardware. The described units or modules can also be located in a processor. The names of these units or modules do not, in certain circumstances, constitute a limitation on the unit or module itself.

[0135] The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the foregoing application concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions claimed in this application.

Claims

1. A method for evaluating an oral implant material, characterized by, The method comprises the following steps: obtaining target information, wherein the target information comprises first attribute information and second attribute information, the first attribute information comprises material attribute information of a to-be-evaluated implant, and the second attribute information comprises material attribute information of a target implant tissue; generating a first target model and a second target model according to the target information; generating a target artifact analysis result according to the first target model and the second target model; specifically, a target gamma photon beam is applied to the first target model to obtain first signal distribution information; a target gamma photon beam with the same parameters is applied to the second target model to obtain second signal distribution information; intensity attenuation information and scattering information of the target gamma photon beam are determined according to the first signal distribution information and the second signal distribution information; and a target artifact analysis result containing artifact gray distribution information, shape information and area information is generated according to the intensity attenuation information and the scattering information; generating a material evaluation result of the to-be-evaluated implant according to the target artifact analysis result; specifically, coverage rate information of a key point position of the target artifact is determined according to coverage point position information of the target artifact on the target implant tissue, and the evaluation result is generated according to the coverage rate information; the coverage rate information is determined according to a ratio of a pixel number of a key point position covered by the target artifact to a total pixel number of the key point position; if a total coverage rate of the target artifact on a plurality of key point positions is greater than a preset total coverage rate threshold, and / or if a coverage rate of the target artifact on a single key point position is greater than a corresponding coverage rate threshold, the evaluation result is output as unqualified; if the total coverage rate of the target artifact on the plurality of key point positions is less than or equal to the preset total coverage rate threshold, and the coverage rate of the target artifact on the single key point position is less than or equal to the corresponding coverage rate threshold, the evaluation result is output as qualified.

2. The method for evaluating the dental implant material according to claim 1, wherein The determination of the intensity attenuation information and the scattering information of the target gamma photon beam according to the first signal distribution information and the second signal distribution information comprises: the intensity attenuation information is determined according to the following formula: wherein, is the intensity of gamma photons for a penetration thickness of is the intensity of gamma photons for a penetration thickness of is the initial intensity of gamma photons, is the linear attenuation coefficient, is the penetration thickness, is the base of the natural logarithm; the scattering information is determined according to the following formula: wherein, is the wavelength of the gamma photon before scattering, is the wavelength of the gamma photon after scattering, is the rest mass of the electron, is the speed of light, is the scattering angle.

3. The dental implant material evaluation method according to claim 1, characterized by, The generation of the target artifact analysis result containing the artifact gray distribution information, the shape information and the area information further comprises: a boundary of the target artifact is determined according to the gray distribution information; a target operation is performed on the boundary to determine a target boundary; the area information is determined according to the target boundary.

4. An oral implant material evaluation device, characterized by, The method comprises the following steps: an obtaining unit is configured to obtain target information, wherein the target information comprises first attribute information and second attribute information, the first attribute information comprises material attribute information of a to-be-evaluated implant, and the second attribute information comprises material attribute information of a target implant tissue; a first generating unit is configured to generate a first target model and a second target model according to the target information; The second generation unit is configured to generate a target artifact analysis result according to the first target model and the second target model. Specifically, a target gamma photon beam is applied to the first target model to obtain first signal distribution information; the same parameter target gamma photon beam is applied to the second target model to obtain second signal distribution information; the intensity attenuation information and the scattering information of the target gamma photon beam are determined according to the first signal distribution information and the second signal distribution information; and the target artifact analysis result including the artifact gray scale distribution information, the shape information and the area information is generated according to the intensity attenuation information and the scattering information. The third generation unit is configured to generate a material evaluation result of the target implant according to the target artifact analysis result. Specifically, the coverage rate information of the target artifact to the key point is determined according to the coverage point information of the target artifact to the target implant tissue, and the evaluation result is generated according to the coverage rate information. The coverage rate information is determined according to the ratio of the pixel number of the key point covered by the target artifact to the total pixel number of the key point. In a case where the total coverage rate of the target artifact to a plurality of key points is greater than a preset total coverage rate threshold and / or the coverage rate of the target artifact to a single key point is greater than a corresponding coverage rate threshold, the evaluation result is output as unqualified. In a case where the total coverage rate of the target artifact to a plurality of key points is less than or equal to the preset total coverage rate threshold and / or the coverage rate of the target artifact to a single key point is less than or equal to the corresponding coverage rate threshold, the evaluation result is output as qualified.

5. An electronic device, comprising: A processor and a memory are included, wherein the memory stores computer program instructions, and the computer program instructions are used to execute the dental implant material evaluation method according to any one of claims 1 to 3 when executed by the processor.

6. A computer storage medium, characterized in that A computer storage medium stores program instructions, and the program instructions are used to execute the dental implant material evaluation method according to any one of claims 1 to 3 when executed.

Images