Oral implant material evaluation method and device, electronic equipment and storage medium

Abstract

The invention provides an oral implant material evaluation method and device, electronic equipment and a storage medium, and relates to the technical field of medical data processing.The method comprises the steps that target information is obtained, 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 a to-be-evaluated implant; the second attribute information belongs to the target planting 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 implant to be evaluated according to the target artifact analysis result. In this way, the automation level of the implant evaluation process is improved, and the output precision of the implant evaluation result is improved; in the clinical treatment process, the bone mass and density around the implant are accurately evaluated, interference on judgment of the tooth moving direction and the relation between the tooth root and the implant is reduced, and convenience is provided for clinical treatment.

Description

Technical Field

[0001] Embodiments of the present application relate to medical data processing, and in particular to a method, device, electronic device, and storage medium for evaluating oral implant materials. Background Art

[0002] Implant evaluation aims to evaluate the performance, safety, and biocompatibility of the implant to be evaluated to ensure that the implant can stably support the prosthesis for a long time without causing adverse effects on the surrounding tissues. Currently, in related technologies, there are problems such as low automation level and poor accuracy of implant evaluation results in the implant evaluation process.

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

[0004] According to an embodiment of the present application, there is provided a method, device, electronic device, and storage medium for evaluating oral implant materials, which is beneficial to improving the automation level of the implant evaluation process and the output accuracy of the implant evaluation results.

[0005] In a first aspect of the present application, there is provided a method for evaluating oral implant materials, including:

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

[0007] Generate a first target model and a second target model according to the target information;

[0008] Generate a target artifact analysis result according to the first target model and the second target model;

[0009] Generate a material evaluation result of the implant to be evaluated according to the target artifact analysis result.

[0010] In some feasible embodiments, the generating a target artifact analysis result according to the first target model and the second target model includes:

[0011] Apply a target γ photon beam to the first target model to obtain first signal distribution information;

[0012] Apply a target γ photon beam to the second target model to obtain second signal distribution information;

[0013] Generate a target artifact analysis result according to the first signal distribution information and the second signal distribution information.

[0014] In some feasible embodiments, generating the target artifact analysis result according to the first signal distribution information and the second signal distribution information includes:

[0015] Determining the intensity attenuation information and / or scattering information of the target γ photon beam according to the first signal distribution information and the second signal distribution information;

[0016] Generating the target artifact analysis result according to the intensity attenuation information and / or scattering information.

[0017] In some feasible embodiments, determining the intensity attenuation information and / or scattering information of the target γ photon beam according to the first signal distribution information and the second signal distribution information includes:

[0018] Determining the intensity attenuation information according to the following formula:

[0019] I = I 0 × e -μx

[0020] where I is the intensity of γ photons with a penetration thickness of x, I 0 is the initial γ photon intensity, μ is the linear attenuation coefficient, x is the penetration thickness, and e is the base of the natural logarithm;

[0021] Determining the scattering information according to 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, m e is the electron rest mass, c is the speed of light, and θ is the scattering angle.

[0024] In some feasible embodiments, the target artifact analysis result as described in any one of the above includes:

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

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

[0027] Determining the boundary of the target artifact according to the gray-scale distribution information;

[0028] Performing a target operation on the boundary to determine the target boundary;

[0029] Determining the area information according to the target boundary.

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

[0031] Determine the coverage rate information of the target artifact for the key points according to the coverage point information of the target artifact for the target implant tissue; generate an evaluation result according to the coverage rate information.

[0032] In a second aspect of the present application, there is provided an implant material evaluation device, including:

[0033] An acquisition unit, configured to acquire target information, where the target information includes: first attribute information and second attribute information, where the first attribute information belongs to the implant to be evaluated, and the second attribute information belongs to the target implant tissue;

[0034] A first generation unit, configured to generate a first target model and a second target model according to the target information;

[0035] A second generation unit, configured to generate a target artifact analysis result according to the first target model and the second target model;

[0036] A third generation unit, configured to generate a material evaluation result of the implant to be evaluated according to the target artifact analysis result.

[0037] In a third aspect of the present application, there is provided an electronic device, including: a processor and a memory, where computer program instructions are stored in the memory, and when the computer program instructions are run by the processor, they are used to execute the oral implant material evaluation method described in any one of the above.

[0038] In a fourth aspect of the present application, there is provided a computer storage medium, on which program instructions are stored, and when the program instructions are run, they are used to execute the oral implant material evaluation method described in any one of the above.

[0039] The oral implant material evaluation method, device and electronic device provided by the embodiments of the present application, where the method includes: acquiring target information, where the target information includes: first attribute information and second attribute information, where 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 according to the target information; generating a target artifact analysis result according to the first target model and the second target model; generating a material evaluation result of the implant to be evaluated according to the target artifact analysis result. The present application is beneficial to improving the automation level of the implant evaluation process and improving the output accuracy of the implant evaluation result; enabling accurate evaluation of the bone mass and density around the implant during the clinical treatment process, reducing the interference in the judgment of the tooth movement direction and the relationship between the tooth root and the implant, thereby facilitating the clinical treatment.

[0040] It should be understood that the content described in the summary of the invention section is not intended to limit the key or important features of the embodiments of the present application, nor to limit the scope of the present application. Other features of the present application will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In conjunction with the accompanying drawings and with reference to the following detailed description, the above and other features, advantages, and aspects of the embodiments of the present application will become more apparent. In the drawings, the same or similar reference numerals denote the same or similar elements, where:

[0042] Figure 1 is a flowchart schematic diagram of a method for evaluating an oral implant material provided by an embodiment of the present application;

[0043] Figure 2 is a structural schematic diagram of an implant material evaluation device provided by an embodiment of the present application;

[0044] Figure 3 is a structural schematic diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0045] To make the objectives, technical solutions, and advantages of the embodiments of the present disclosure clearer, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present disclosure. Apparently, the described embodiments are some, but not all, of the embodiments of the present disclosure. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present disclosure without making creative efforts fall within the scope of protection of the present disclosure.

[0046] In addition, the term "and / or" in this article is merely a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this article generally represents an "or" relationship between the associated objects before and after.

[0047] Implant evaluation aims to evaluate the performance, safety, and biocompatibility of the implant to be evaluated to ensure that the implant can stably support the prosthesis for a long time without causing adverse effects on the surrounding tissues. Currently, in the related art, the artifacts formed by metal implants can lead to missed or misjudged lesions, making it impossible to accurately evaluate the bone mass and density around the implant during the clinical treatment process, interfering with the judgment of the tooth movement direction and the relationship between the tooth root and the implant, resulting in a low level of automation in the implant evaluation process and poor accuracy of the implant evaluation results.

[0048] In view of this, in the first aspect of the embodiments of the present application, a method for evaluating an oral implant material is proposed. Figure 1A flowchart of an oral implant material evaluation method 100 provided by an embodiment of the present application is shown as follows. Figure 1 As shown, method 100 includes:

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

[0050] Exemplarily, the above first attribute information may include: material attribute information and dimension attribute information of the implant to be evaluated. It should be noted that the above first attribute information may also include: the shape, cross-sectional area, and / or implantation position of the implant to be evaluated, etc.

[0051] Exemplarily, the above material attribute information may include: atomic number, and / or density parameter, etc.

[0052] Specifically, when the material corresponding to the implant to be evaluated includes materials such as titanium alloy and cobalt-chromium alloy, the material attribute information corresponding to the implant to be evaluated may include: the atomic number corresponding to titanium alloy, and / or density parameter, etc., and the atomic number corresponding to cobalt-chromium alloy, and / or density parameter, etc.

[0053] Exemplarily, the above dimension attribute information may include: the length, diameter, volume, etc. of the implant to be evaluated. Specifically, the above length may include: the total length of the implant to be evaluated, and / or the length of the part of the implant to be evaluated implanted in the alveolar bone. The above diameter may correspond to the maximum width of the implant to be evaluated.

[0054] In some feasible embodiments, the above second attribute information includes: attribute information of the target implant tissue.

[0055] Exemplarily, the above target implant tissue may include: target alveolar bone tissue, target soft tissue, etc. The attribute information of the above target implant tissue may include: material attribute information and dimension attribute information of the target implant tissue.

[0056] Exemplarily, the above material attribute information of the target implant tissue may include: the atomic number corresponding to the target implant tissue, and / or density parameter, etc.

[0057] Exemplarily, the above dimension attribute information of the target implant tissue may include: the volume of the target implant tissue, the height of the target implant tissue, and / or the thickness of the target implant tissue, etc.

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

[0059] Step S120: Generate a first target model and a second target model according to the target information.

[0060] Exemplarily, a first target model including the implant to be evaluated and the target implant tissue can be generated according to the above first attribute information.

[0061] Exemplarily, a second target model including only the target implant tissue but not the implant to be evaluated can be generated according to the above second attribute information.

[0062] Among them, the above first target model and second target model 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 attribute information of the target implant tissue, the simulation accuracy of the physical structure of the implant to be evaluated and the target implant tissue can be improved, and the simulation accuracy of the matching relationship and / or the structural association relationship between the implant to be evaluated and the target implant tissue can be improved, and the experimental cost and risk caused by physical entity experiments can be reduced.

[0064] Step S130: Generate a target artifact analysis result according to the first target model and the second target model.

[0065] In some feasible embodiments, generating a target artifact analysis result according to 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; generating a target artifact analysis result according to the first signal distribution information and the second signal distribution information.

[0066] Exemplarily, by setting the energy parameter, intensity parameter, incident angle parameter, detector resolution parameter, collimator parameter, and / or detector detection efficiency parameter of the X-ray, that is, the target γ photon beam, it can be simulated to apply the X-ray, that is, the target γ photon beam, to the first target model to obtain first signal distribution information, and it can be simulated to apply the X-ray, that is, the target γ photon beam, to the second target model to obtain second signal distribution information. Among them, the parameters of the X-ray, that is, the target γ photon beam, applied to the first target model are the same as those of the X-ray, that is, the target γ photon beam, applied to the second target model. Among them, the above parameters include: the energy parameter, intensity parameter, incident angle parameter, detector resolution parameter, collimator parameter, and / or detector detection efficiency and other parameters of the X-ray source, that is, the target γ 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, and accurately simulate the physical interaction process between the target γ photon beam and the target implant tissue, so as to obtain the second signal distribution information. Thus, by comparing the first signal distribution information and the second signal distribution information, the target artifact analysis result can be accurately generated, providing accurate data support for accurately generating the material evaluation result of the implant to be evaluated according to the target artifact analysis result.

[0068] In some feasible embodiments, the generating of the target artifact analysis result according to 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 according to the first signal distribution information and the second signal distribution information; generating the target artifact analysis result according to the intensity attenuation information and / or scattering information.

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

[0070] It should be noted that after the target γ photon beam passes through the first target model or the second target model, the target γ photons will interact with the implant to be evaluated or the target implant tissue, causing the energy of the target γ photon beam to be lost, thereby causing the signal distribution to change. Among them, the above interactions can include: photoelectric effect, Compton scattering, and / or pair production effect, etc. The above signal distribution changes can include: intensity change and / or propagation direction change.

[0071] It should be noted that when the atomic number of the material corresponding to the implant to be evaluated is relatively high and the density is relatively large, the target γ photon beam will have a strong photoelectric effect with the implant to be evaluated. A large number of inner shell electrons of the metal atoms corresponding to the implant to be evaluated will undergo transitions, causing a large number of γ photons in the target γ photon beam to be absorbed. The number of γ photons at the position corresponding to the implant to be evaluated will be significantly reduced, resulting in a strong attenuation of the intensity of the target γ photon beam. Then, the degree of signal change at the position corresponding to the implant to be evaluated is relatively high, and bright white stripes will be formed at the position corresponding to the implant to be evaluated, masking the structure of the target implant tissue. Among them, the above structures may include fine structures such as tiny blood vessels and periodontal membranes. Conversely, when the atomic number of the material corresponding to the implant to be evaluated is relatively small and the density is relatively small, the target γ photon beam will have a weak photoelectric effect with the implant to be evaluated. A small number of inner shell electrons of the metal atoms corresponding to the implant to be evaluated will undergo transitions, causing a small number of γ photons in the target γ photon beam to be absorbed. The number of γ photons at the position corresponding to the implant to be evaluated will be slightly reduced, resulting in a weak attenuation of the intensity of the target γ photon beam. Then, the degree of signal change at the position corresponding to the implant to be evaluated is relatively small, and the contrast with the target implant tissue is relatively small. Dark stripes or blurred images will be formed at the position corresponding to the implant to be evaluated.

[0072] In some feasible embodiments, 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 = I 0 ×e -μx (1)

[0074] where I is the intensity of γ photons penetrating through a thickness of x, I 0 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 above linear attenuation coefficient μ is positively correlated with the atomic number Z, density ρ of the implant to be evaluated, and the energy E of γ photons. That is, the larger the atomic number Z, density ρ of the implant to be evaluated, and the higher the energy E of γ photons, the larger the linear attenuation coefficient μ, and the faster the intensity attenuation of γ photons.

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

[0077] Exemplarily, the above scattering information may include scattering angle information and / or scattering cross-section information.

[0078] In some feasible embodiments, 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 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, m e is the electron rest mass, c is the speed of light, and θ is the scattering angle.

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

[0082] It should be noted that in some feasible embodiments, the determination accuracy of the above 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 photon, so as to improve the determination accuracy of the target artifact analysis result.

[0083] Thus, 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, by comparing the first signal distribution information and the second signal distribution information, the above method can accurately determine the intensity attenuation information and / or scattering information of the target γ photon beam passing through the implant to be evaluated and / or the target implant tissue, so as to accurately generate the target artifact analysis result, providing data support for objectively quantifying and evaluating the performance of the implant to be evaluated.

[0085] Step S140; generating a material evaluation result of the implant to be evaluated according to the target artifact analysis result.

[0086] In some feasible embodiments, the above target artifact analysis result includes: the gray-scale distribution information, shape information, and / or area information of the target artifact.

[0087] Exemplarily, the gray-scale 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 gray-scale distribution information, shape information, and / or area information of the target artifact based on the above-mentioned first signal distribution information and second signal distribution information, a filtering operation can be performed on the first signal distribution information and the second signal distribution information to achieve precise noise reduction of the first signal distribution information and the second signal distribution information. Specifically, the target filtering parameters can be set based on methods such as Gaussian filtering to perform the filtering operation on the first signal distribution information and the second signal distribution information.

[0089] Specifically, by comparing the gray-scale histograms of the first signal distribution information and the second signal distribution information, the difference between the gray-scale histogram corresponding to the first signal distribution information and the gray-scale histogram corresponding to the second signal distribution information can be determined, and based on the above difference, the gray-scale distribution information of the target artifact can be determined.

[0090] Specifically, based on an edge detection algorithm, according to the above-mentioned first signal distribution information and second signal distribution information, the boundary of the target artifact can be determined to determine the above-mentioned shape information.

[0091] It should be noted that in the case where the structure and shape of the implant to be evaluated are relatively complex, the shape of the artifact corresponding to the implant to be evaluated will be distorted and bent, and the masking range of the artifact on the target implant tissue is relatively large, which will affect the observation of the target implant tissue. Among them, the above-mentioned target implant tissue includes: teeth around the implant position corresponding to the implant to be evaluated, and / or alveolar bone, etc. In the case where the structure and shape of the implant to be evaluated are relatively regular, the shape of the artifact corresponding to the implant to be evaluated is relatively regular, and the masking range of the artifact on the target implant tissue is relatively small, and it appears concentrated at the position corresponding to the implant to be evaluated, showing a concentric ring distribution or a radial distribution.

[0092] In some feasible embodiments, the above method further includes: determining the boundary of the target artifact according to the gray-scale distribution information; performing a target operation on the boundary to determine the target boundary; and determining the above area information according to the target boundary.

[0093] Exemplarily, the boundary of the target artifact can be determined based on a target gray-scale threshold, where the above-mentioned target gray-scale threshold can be 200.

[0094] Specifically, in the case where it is determined according to the gray-scale histogram that the gray-scale value of the corresponding point is greater than 200, then the above-mentioned point is determined as the target point, and based on multiple above-mentioned target points, the boundary of the target artifact is determined.

[0095] It should be noted that the above-mentioned target operation can include: an erosion operation, and / or a dilation operation.

[0096] Exemplarily, an erosion operation can be performed on the above-mentioned boundary to eliminate isolated points and / or irregular line segments composed of multiple points in the above-mentioned boundary, and then a dilation operation is performed to compensate for the eliminated isolated points and / or irregular line segments, thereby determining the above-mentioned target boundary.

[0097] Specifically, the above-mentioned erosion operation and / or dilation operation can be performed based on a target structuring element. Among them, the above-mentioned target structuring element can be set by itself according to the actual situation. For example: the above-mentioned target structuring element can be a structuring element with a size of 3×3.

[0098] Exemplarily, the above-mentioned area information can be determined according to the number of pixels included in the above-mentioned target boundary and the size of a single pixel. Among them, the artifact area is the product of the number of pixels included in the target boundary and the area of a single pixel.

[0099] Thus, the above method can accurately determine the boundary of the target artifact according to the gray-scale distribution information, perform a target operation on the above boundary to determine the target boundary, and accurately determine the area information according to the above target boundary.

[0100] Alternatively, the above-mentioned area information can also be determined based on a region of interest (ROI) set by the target user himself.

[0101] Exemplarily, the target user can select a corresponding shape selection tool according to the shape information of the above-mentioned target artifact to determine the above-mentioned area information. Among them, the above-mentioned corresponding shape selection tool can include: a rectangular selection tool, a circular selection tool, and / or an irregular shape selection tool.

[0102] Specifically, when the shape of the target artifact is circular, the above-mentioned region of interest can be selected based on the circular selection tool to determine the above-mentioned area information.

[0103] In some feasible embodiments, after the above-mentioned selection operation is completed, the scale information of the target artifact can be determined based on a preset calibration tool.

[0104] Exemplarily, the above-mentioned scale information can be determined based on a preset calibration tool according to a reference object with a known standard size.

[0105] Specifically, based on a preset calibration tool, the size value of a single pixel can be determined according to a metal sphere with a known diameter of 5 mm. According to the number of pixels included in the above-mentioned region of interest and the size value of the above-mentioned single pixel, the above-mentioned area information is determined.

[0106] Thus, the above method can generate a material evaluation result of the implant to be evaluated in multiple dimensions according to the gray-scale distribution information, shape information, and / or area information of the target artifact, thereby improving the generation accuracy of the material evaluation result of the implant to be evaluated.

[0107] In some feasible embodiments, the above method further includes: determining the coverage rate information of the target artifact on the key points according to the coverage position information of the target artifact on the target implant tissue; generating an evaluation result according to the coverage rate information.

[0108] Exemplarily, the above key points can be determined according to the anatomical information and / or atlas information of the target implant tissue. Specifically, the above key points may include: nerve canals, vascular bundles, adjacent tooth roots, maxillary sinus floor, and / or bone margins, etc.

[0109] Exemplarily, the above coverage rate can be determined as the ratio of the number of pixels of the key points covered by the above target artifact to the total number of pixels of the key points.

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

[0111]

[0112] In some feasible embodiments, weights can be set for multiple key points to generate the above evaluation result according to the weights of each key point and the coverage rate of each key point.

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

[0114] Specifically, when the total coverage rate of the above target artifact on multiple above key points is less than or equal to the preset total coverage rate threshold, and moreover, when the coverage rate of the above target artifact on a single above key point is less than or equal to the corresponding coverage rate threshold, the above evaluation result is output as qualified.

[0115] Among them, the above total coverage rate can be determined according to the following formula:

[0116]

[0117] Among them, the above n is the number of key points, the coverage rate i is the coverage rate of the i-th key point, and the weight i is the weight of the i-th key point.

[0118] Based on this, the above method can accurately determine the coverage rate information of the target artifact on the key points according to the coverage position information of the target artifact on the target implant tissue, and generate the above evaluation result accurately and objectively according to the above coverage rate information.

[0119] It should be noted that when the total coverage rate of the target artifact on multiple key points is greater than the preset total coverage rate threshold, and / or when the coverage rate of the target artifact on a single key point is greater than the corresponding coverage rate threshold, that is, when the above evaluation result is unqualified, the component ratio of the implant to be evaluated can be adjusted so that the total coverage rate of the target artifact on multiple key points is less than or equal to the preset total coverage rate threshold, and the coverage rate of the target artifact on a single key point is less than or equal to the corresponding coverage rate threshold, that is, the evaluation result is qualified, so as to realize the automatic adjustment of the component ratio of the implant to be evaluated, avoid the omission or misjudgment of lesions caused by the artifact formed by the metal implant, and enable accurate evaluation of the bone mass and density around the implant during the clinical treatment process, reduce the interference in the judgment of the tooth movement direction and the relationship between the tooth root and the implant, thus providing convenience for clinical treatment.

[0120] Based on this, the method for evaluating oral implant materials provided in this application includes: obtaining target information, where the target information includes: first attribute information and second attribute information, where 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 according to the target information; generating a target artifact analysis result according to the first target model and the second target model; generating a material evaluation result of the implant to be evaluated according to the target artifact analysis result. This application is conducive to accurately simulating the physical structure of the implant to be evaluated, the target implant tissue, and the cooperation relationship, and / or the structural association relationship between the implant to be evaluated and the target implant tissue according to the first attribute information and the second attribute information. According to the physical structure of the implant to be evaluated, the target implant tissue, and the cooperation relationship, and / or the structural association relationship between the implant to be evaluated and the target implant tissue, the target artifact analysis result can be accurately determined while saving experimental costs, and the material evaluation result of the implant to be evaluated can be accurately output according to the target artifact analysis result, thereby improving the automation level of the implant evaluation process and the accuracy of the implant evaluation result.

[0121] It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that this application is not limited by the described action sequence, because according to this application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know 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 the introduction of the method embodiments. The following further illustrates the solution of the present application through device embodiments.

[0123] In a second aspect of the embodiments of the present application, a device for evaluating implant materials is proposed. Figure 2 It is a structural schematic diagram of a device 200 for evaluating implant materials provided by the embodiments of the present application. As Figure 2 shown, the device 200 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 configured to acquire target information, where the target information includes: first attribute information and second attribute information, where 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 configured to generate a first target model and a second target model according to the target information;

[0126] The second generation unit 230 is configured to generate a target artifact analysis result according to the first target model and the second target model;

[0127] The third generation unit 240 is configured to generate a material evaluation result of the implant to be evaluated according to the target artifact analysis result.

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

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

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

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

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

[0133] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations 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 can represent a module, a program segment, or a part of code, and the aforementioned module, program segment, or part of code contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, as well as the combination of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0134] The units or modules involved in the embodiments described in this application can be implemented in software or in hardware. The described units or modules can also be provided in a processor. Among them, the names of these units or modules do not, in some cases, constitute a limitation on the units or modules themselves.

[0135] The above description is only a preferred embodiment of this application and an explanation of the technical principles applied. Those skilled in the art should understand that the scope of the application involved in this application is not limited to the technical solutions formed by the specific combination of the above technical features, and should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the foregoing application concept. For example, the technical solutions formed by mutually replacing the above features with the technical features (but not limited to) having similar functions applied in this application.

Claims

1. A method for evaluating oral implant materials, characterized in that: include: 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; 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; A material evaluation result of the implant to be evaluated is generated according to the target artifact analysis result.

2. The oral implant material evaluation method according to claim 1, characterized in that: Generating a target artifact analysis result according to the first target model and the second target model includes: applying a target gamma photon beam to the first target model to obtain first signal distribution information; applying the target gamma photon beam to the second target model to obtain second signal distribution information; A target artifact analysis result is generated according to the first signal distribution information and the second signal distribution information.

3. The oral implant material evaluation method according to claim 2, characterized in that: The generating a target artifact analysis result according to the first signal distribution information and the second signal distribution information comprises: Determining intensity attenuation information and / or scattering information of the target gamma photon beam according to the first signal distribution information and the second signal distribution information; The target artifact analysis result is generated according to the intensity attenuation information and / or the scattering information.

4. The oral implant material evaluation method according to claim 3, characterized in that: Determining the intensity attenuation information of the target gamma photon beam and / or the scattering information according to the first signal distribution information and the second signal distribution information includes: The intensity attenuation information is determined according to the following formula: I=I0×e -μx Where I is the gamma photon intensity with a penetration thickness of x, I0 is the initial gamma photon intensity, μ is the linear attenuation coefficient, x is the penetration thickness, and e is the base of the natural logarithm; The scattering information is determined according to the following formula: Where λ is the wavelength of the γ photon before scattering, λ′ is the wavelength of the γ photon after scattering, and m e is the electron rest mass, c is the speed of light, and θ is the scattering angle.

5. The oral implant material evaluation method according to any one of claims 1 to 4, characterized in that: The target artifact analysis results include: Grayscale distribution information, shape information, and / or area information of the target artifact.

6. The oral implant material evaluation method according to claim 5, characterized in that: Also includes: Determining a boundary of the target artifact according to the grayscale distribution information; performing a target operation on the boundary to determine a target boundary; The area information is determined according to the target boundary.

7. The oral implant material evaluation method according to claim 6, characterized in that: Also includes: Determining coverage information of the target artifact on key points according to coverage point information of the target artifact on the target implant tissue; The evaluation result is generated according to the coverage information.

8. An implant material evaluation device, characterized in that: include: An acquisition unit, configured 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; A first generating unit, configured to generate a first target model and a second target model according to the target information; A second generating unit, configured to generate a target artifact analysis result according to the first target model and the second target model; The third generating unit is used to generate a material evaluation result of the implant to be evaluated according to the target artifact analysis result.

9. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores computer program instructions, and the computer program instructions are used to execute the oral implant material evaluation method according to any one of claims 1 to 7 when the processor is running.

10. A computer storage medium, characterized in that: Program instructions are stored on the computer storage medium, and the program instructions are used to execute the oral implant material evaluation method according to any one of claims 1 to 7 when running.

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