Method, device and storage medium for determining indications for distal femoral plate fixation

Abstract

The present application discloses a method, device and storage medium for determining the indications of distal femoral plate fixation. The present application relates to the fields of data processing technology, medical device technology and other related technical fields. The method comprises: performing three-dimensional reconstruction based on multiple image data of the distal femur of the first object to obtain a target three-dimensional model one; performing fracture simulation on the target three-dimensional model one based on multiple fracture defect values ​​to obtain multiple target three-dimensional models two, and performing fracture fixation on each target three-dimensional model two through multiple plate fixation methods to obtain multiple target three-dimensional models three; determining the target indication corresponding to each plate fixation method based on the multiple target three-dimensional models three, wherein the target indication is used to characterize the scope of application of each plate fixation method. The present application solves the problem that the indications of the plate fixation method at the distal femoral fracture are determined based on artificial experience in the related art, resulting in a relatively low accuracy in determining the indications.

Description

Technical Field

[0001] The present application relates to the fields of data processing technology, medical device technology and other related technical fields, and in particular to a method, device and storage medium for determining indications for distal femoral plate fixation. Background Art

[0002] The incidence of distal femoral fractures is bimodal, with high-energy injuries in young people and low-energy injuries in the elderly. Its incidence accounts for 3-6% of femoral fractures, but the incidence of complications is as high as 15-20%. According to statistics, the mortality rate of distal femoral fractures in the elderly is similar to that of proximal femoral fractures, which has brought a heavy burden to public health. The lateral single plate fixation method and double plate internal fixation method for the treatment of distal femoral fractures have solved some problems in treatment due to their excellent biomechanical characteristics, but the plate fixation method suitable for the patient is usually determined based on manual experience, making the application indications of the two plate fixation methods unclear, such as: mismatched stability of the internal fixation system, severe soft tissue irritation and knee stiffness, resulting in no significant improvement in the incidence and treatment effect.

[0003] With regard to the problem that the indications of the plate fixation method for distal femoral fractures are determined based on manual experience in the related art, which leads to a relatively low accuracy in determining the indications, no effective solution has been proposed so far. Summary of the invention

[0004] The main purpose of the present application is to provide a method, device and storage medium for determining the indications of distal femoral plate fixation, so as to solve the problem that the indications of the plate fixation method for distal femoral fractures are determined based on manual experience in the related art, resulting in relatively low accuracy in determining the indications.

[0005] In order to achieve the above-mentioned purpose, according to one aspect of the present application, a method for determining the indications of distal femoral plate fixation is provided. The method comprises: performing three-dimensional reconstruction based on multiple image data of the distal femur of the first object to obtain a target three-dimensional model 1; performing fracture simulation on the target three-dimensional model 1 based on multiple fracture defect values ​​to obtain multiple target three-dimensional models 2, and performing fracture fixation on each target three-dimensional model 2 through multiple plate fixation methods to obtain multiple target three-dimensional models 3; determining the target indication corresponding to each plate fixation method based on the multiple target three-dimensional models 3, wherein the target indication is used to characterize the scope of application of each plate fixation method.

[0006] Furthermore, based on the multiple target three-dimensional models three, determining the target indication corresponding to each steel plate fixation method includes: performing axial loading analysis on each target three-dimensional model three to obtain multiple first analysis results; performing torsional analysis on each target three-dimensional model three to obtain multiple second analysis results; determining multiple target analysis results based on the multiple first analysis results and the multiple second analysis results; and determining the target indication corresponding to each steel plate fixation method based on the multiple target analysis results through a fuzzy comprehensive evaluation model.

[0007] Furthermore, determining the target indication corresponding to each plate fixation method based on the multiple target analysis results through a fuzzy comprehensive evaluation model includes: calculating according to the weight values ​​corresponding to the multiple target analysis results to obtain a target weight vector; determining the target membership function corresponding to each target analysis result according to a first preset threshold corresponding to each target analysis result; fitting the multiple target analysis results to obtain a target fitting function corresponding to each target analysis result under the multiple fracture defect values; and calculating according to the target weight vector, the target membership function and the target fitting function to obtain the target indication.

[0008] Furthermore, calculating according to the weight values ​​corresponding to the multiple target analysis results to obtain the target weight vector includes: calculating according to the weight value corresponding to each target analysis result and the weight values ​​corresponding to the remaining target analysis results to obtain multiple weight ratios; constructing a matrix according to the multiple weight ratios to obtain a pairwise comparison matrix corresponding to the multiple target analysis results; and when the pairwise comparison matrix meets preset conditions, calculating the pairwise comparison matrix to obtain the target weight vector.

[0009] Furthermore, calculating according to the target weight vector, the target membership function and the target fitting function to obtain the target indication includes: calculating according to the target fitting function and the target membership function to obtain a target membership matrix; calculating according to the target weight vector and the target membership matrix to obtain a target fuzzy decision matrix; calculating according to the target fuzzy decision matrix to obtain a target maximum value corresponding to the target fuzzy decision matrix; calculating according to the target maximum value to obtain the target indication.

[0010] Furthermore, before calculating the pairwise comparison matrix to obtain the target weight vector, the method also includes: calculating based on the pairwise comparison matrix to obtain the eigenvector corresponding to the pairwise comparison matrix; calculating based on the number of columns of the pairwise comparison matrix and the eigenvector to obtain the maximum eigenvalue corresponding to the pairwise comparison matrix; calculating based on the maximum eigenvalue and the matrix order of the pairwise comparison matrix to obtain the consistency index value corresponding to the pairwise comparison matrix; calculating based on the average random consistency index value corresponding to the matrix order and the consistency index value to obtain the consistency ratio value corresponding to the pairwise comparison matrix; if the consistency ratio value is less than a second preset threshold value, it is determined that the pairwise comparison matrix meets the preset conditions.

[0011] Furthermore, based on the first preset threshold corresponding to each target analysis result, determining the target membership function corresponding to each target analysis result includes: calculating based on the z-shaped membership function tool and the first preset threshold to obtain the first membership function; calculating based on the π-shaped membership function tool and the first preset threshold to obtain the second membership function; determining the target membership function based on the first membership function and the second membership function.

[0012] Furthermore, after determining the target indication corresponding to each plate fixation method based on the multiple target three-dimensional models, the method also includes: obtaining a target fracture defect value corresponding to a second object; determining a target plate fixation method from the multiple plate fixation methods based on the target fracture defect value and the target indication; and performing fracture fixation on the distal femur fracture of the second object based on the target plate fixation method.

[0013] In order to achieve the above-mentioned purpose, according to another aspect of the present application, a device for determining the indications of distal femoral plate fixation is provided. The device comprises: a reconstruction unit, which is used to perform three-dimensional reconstruction based on multiple image data of the distal femur of the first object to obtain a target three-dimensional model one; a simulation unit, which is used to perform fracture simulation on the target three-dimensional model one based on multiple fracture defect values ​​to obtain multiple target three-dimensional models two, and perform fracture fixation on each target three-dimensional model two through multiple plate fixation methods to obtain multiple target three-dimensional models three; a first determination unit, which is used to determine the target indication corresponding to each plate fixation method based on the multiple target three-dimensional models three, wherein the target indication is used to characterize the scope of application of each plate fixation method.

[0014] Furthermore, the first determination unit includes: a first analysis subunit, used to perform axial loading analysis on each target three-dimensional model three to obtain multiple first analysis results; a second analysis subunit, used to perform torsional analysis on each target three-dimensional model three to obtain multiple second analysis results; a first determination subunit, used to determine multiple target analysis results based on the multiple first analysis results and the multiple second analysis results; and a second determination subunit, used to determine the target indication corresponding to each steel plate fixation method based on the multiple target analysis results through a fuzzy comprehensive evaluation model.

[0015] Furthermore, the second determination subunit includes: a first calculation module, used to calculate according to the weight values ​​corresponding to the multiple target analysis results to obtain a target weight vector; a determination module, used to determine the target membership function corresponding to each target analysis result according to a first preset threshold corresponding to each target analysis result; a fitting module, used to fit the multiple target analysis results to obtain a target fitting function corresponding to each target analysis result under the multiple fracture defect values; a second calculation module, used to calculate according to the target weight vector, the target membership function and the target fitting function to obtain the target indication.

[0016] Furthermore, the first calculation module includes: a first calculation sub-module, used to calculate according to the weight value corresponding to each target analysis result and the weight values ​​corresponding to the remaining target analysis results, to obtain multiple weight ratios; a construction sub-module, used to construct a matrix according to the multiple weight ratios, to obtain a pairwise comparison matrix corresponding to the multiple target analysis results; a second calculation sub-module, used to calculate the pairwise comparison matrix when the pairwise comparison matrix meets preset conditions, to obtain the target weight vector.

[0017] Furthermore, the second calculation module includes: a third calculation submodule, used to calculate based on the target fitting function and the target membership function to obtain a target membership matrix; a fourth calculation submodule, used to calculate based on the target weight vector and the target membership matrix to obtain a target fuzzy decision matrix; a fifth calculation submodule, used to calculate based on the target fuzzy decision matrix to obtain a target maximum value corresponding to the target fuzzy decision matrix; and a sixth calculation submodule, used to calculate based on the target maximum value to obtain the target indication.

[0018] Furthermore, the device also includes: a first calculation unit, which is used to calculate according to the paired comparison matrix to obtain the eigenvector corresponding to the paired comparison matrix before calculating the paired comparison matrix to obtain the target weight vector; a second calculation unit, which is used to calculate according to the number of columns of the paired comparison matrix and the eigenvector to obtain the maximum eigenvalue corresponding to the paired comparison matrix; a third calculation unit, which is used to calculate according to the maximum eigenvalue and the matrix order of the paired comparison matrix to obtain the consistency index value corresponding to the paired comparison matrix; a fourth calculation unit, which is used to calculate according to the average random consistency index value corresponding to the matrix order and the consistency index value to obtain the consistency ratio value corresponding to the paired comparison matrix; a second determination unit, which is used to determine that the paired comparison matrix meets the preset condition if the consistency ratio value is less than a second preset threshold.

[0019] Furthermore, the determination module includes: a seventh calculation submodule, used to calculate based on the z-shaped membership function tool and the first preset threshold to obtain a first membership function; an eighth calculation submodule, used to calculate based on the π-shaped membership function tool and the first preset threshold to obtain a second membership function; and a determination submodule, used to determine the target membership function based on the first membership function and the second membership function.

[0020] Furthermore, the device also includes: an acquisition unit, used to obtain a target fracture defect value corresponding to the second object after determining the target indication corresponding to each steel plate fixation method based on the multiple target three-dimensional models; a third determination unit, used to determine a target steel plate fixation method from the multiple steel plate fixation methods based on the target fracture defect value and the target indication; and a fixing unit, used to perform fracture fixation on the distal femur fracture of the second object based on the target steel plate fixation method.

[0021] In order to achieve the above-mentioned purpose, according to one aspect of the present application, a computer-readable storage medium is provided, wherein the storage medium stores a program, wherein when the program is running, the device where the storage medium is located is controlled to execute any one of the above-mentioned methods for determining the indications for distal femoral plate fixation.

[0022] In order to achieve the above-mentioned purpose, according to another aspect of the present application, an electronic device is also provided, the electronic device includes one or more processors and a memory, and the memory is used to store a method for determining an indication for distal femoral plate fixation as described above by one or more processors.

[0023] Through this application, the following steps are adopted: three-dimensional reconstruction is performed based on the image data of the distal femur of multiple first objects to obtain a target three-dimensional model one; fracture simulation is performed on the target three-dimensional model one based on multiple fracture defect values ​​to obtain multiple target three-dimensional models two, and fracture fixation is performed on each target three-dimensional model two through multiple steel plate fixation methods to obtain multiple target three-dimensional models three; based on multiple target three-dimensional models three, the target indication corresponding to each steel plate fixation method is determined, wherein the target indication is used to characterize the applicable scope of each steel plate fixation method. Through this application, the problem that the indication of the steel plate fixation method at the distal femur fracture is determined based on artificial experience in the related art, resulting in a relatively low accuracy in determining the indication. In this scheme, first, reverse modeling is performed based on the image data of the distal femur of multiple first objects in the normal population to generate a conventional classical model (i.e., the target three-dimensional model one). Then, fracture simulation is performed on the target three-dimensional model one based on multiple fracture defect values ​​to generate multiple distal femur fracture defect models (i.e., the target three-dimensional model two), and fracture fixation is performed on each target three-dimensional model two through multiple steel plate fixation methods to generate multiple target three-dimensional models three. Finally, the applicable interval of each plate fixation method is determined based on multiple target 3D models. Through 3D reconstruction and simulation technology, a variety of fracture conditions and plate fixation effects are accurately simulated, and the applicable interval of each plate fixation method is quickly determined, which improves the success rate of fracture recovery surgery and the patient's rehabilitation effect, and also reduces the risks and complications during the operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0025] Figure 1 is a flow chart of a method for determining an indication for distal femoral plate fixation according to an embodiment of the present application;

[0026] Figure 2 is a schematic diagram of a second three-dimensional model of multiple targets provided according to an embodiment of the present application;

[0027] Figure 3 Schematic diagram of a plurality of target three-dimensional models provided according to an embodiment of the present application Figure 1 ;

[0028] Figure 4 Schematic diagram of a plurality of target three-dimensional models provided according to an embodiment of the present application Figure 2 ;

[0029] Figure 5 is a schematic diagram of axial loading analysis provided according to an embodiment of the present application;

[0030] Figure 6 is a schematic diagram of a torsion analysis provided according to an embodiment of the present application;

[0031] Figure 7 is a schematic diagram of a target fitting function provided according to an embodiment of the present application Figure 1 ;

[0032] Figure 8 is a schematic diagram of a target fitting function provided according to an embodiment of the present application Figure 2 ;

[0033] Fig. 9 is a schematic diagram of target indications provided according to an embodiment of the present application;

[0034] Fig.10 is a schematic diagram of a target membership function provided according to an embodiment of the present application Figure 1 ;

[0035] Fig.11 is a schematic diagram of a target membership function provided according to an embodiment of the present application Figure 2 ;

[0036] Fig.12 is a schematic diagram of a device for determining an indication for distal femoral plate fixation according to an embodiment of the present application;

[0037] Fig.13 is a schematic diagram of an electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0038] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0039] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0040] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0041] It should be noted that the relevant information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for display, data for analysis, etc.) involved in this disclosure are all information and data authorized by the user or fully authorized by all parties. For example, an interface is set up between this system and the relevant users or organizations. Before obtaining relevant information, it is necessary to send an acquisition request to the aforementioned user or organization through the interface, and obtain relevant information after receiving the consent information fed back by the aforementioned user or organization.

[0042] The present invention is described below in conjunction with preferred implementation steps. Figure 1 is a flow chart of a method for determining an indication for distal femoral plate fixation according to an embodiment of the present application, such as Figure 1 As shown, the method comprises the following steps:

[0043] Step S101, performing three-dimensional reconstruction based on multiple image data of the distal femur of the first object to obtain a target three-dimensional model one.

[0044] Optionally, DICOM data of the distal femur of a normal population (i.e., multiple first subjects) is obtained through imaging techniques such as high-precision computed tomography (e.g., CT, MRI), and the DICOM data contains cross-sectional image information of the bone. The DICOM data is preprocessed (including but not limited to: noise removal, image calibration, and slice reconstruction, etc.) to obtain high-quality image data. Then, the DICOM data slices are stacked using three-dimensional reconstruction algorithms such as voxel reconstruction and surface reconstruction to generate a three-dimensional model of the bone. The bones to be used are separated from other bones by manual segmentation or automatic segmentation algorithms. Finally, the bone model is repaired and post-processed (including but not limited to: filling holes, smoothing surfaces, removing abnormal structures, etc.) to obtain the target three-dimensional model one.

[0045] It should be noted that the three-dimensional reconstruction algorithm can convert slice images into continuous three-dimensional bone surfaces or voxels.

[0046] Step S102, performing fracture simulation on target three-dimensional model one according to multiple fracture defect values ​​to obtain multiple target three-dimensional models two, and performing fracture fixation on each target three-dimensional model two by multiple steel plate fixation methods to obtain multiple target three-dimensional models three.

[0047] Optionally, Figure 2 Schematic diagram of multiple target three-dimensional models 2 provided according to an embodiment of the present application. Figure 2 As shown, a fracture defect was constructed at a distance of 6.5 cm from the joint line in the target three-dimensional model 1, and the size of the fracture defect value of each model was set to 0 mm, 5 mm, 10 mm, 15 mm, 20 mm, 25 mm and 30 mm, respectively, to obtain multiple distal femoral fracture models (i.e., target three-dimensional model 2).

[0048] Among them, model A is the target three-dimensional model 2 corresponding to the fracture defect value of 0mm, model B is the target three-dimensional model 2 corresponding to the fracture defect value of 5mm, model C is the target three-dimensional model 2 corresponding to the fracture defect value of 10mm, model D is the target three-dimensional model 2 corresponding to the fracture defect value of 15mm, model E is the target three-dimensional model 2 corresponding to the fracture defect value of 20mm, model F is the target three-dimensional model 2 corresponding to the fracture defect value of 25mm, and model G is the target three-dimensional model 2 corresponding to the fracture defect value of 30mm.

[0049] It should be noted that Figure 3 Schematic diagram of a plurality of target three-dimensional models provided according to an embodiment of the present application Figure 1 , Figure 4 Schematic diagram of a plurality of target three-dimensional models provided according to an embodiment of the present application Figure 2 .like Figure 3 and Figure 4 As shown, on each distal femoral fracture model, modeling and fracture fixation were performed using a lateral single plate fixation method and a double plate fixation method, respectively, to obtain multiple target three-dimensional models.

[0050] in, Figure 3 Model A in the figure is the target three-dimensional model 2 corresponding to the fracture defect value of 0 mm and the lateral single plate fixation method. Figure 3 Model B in the figure is the target three-dimensional model 2 corresponding to the fracture defect value of 5 mm and the lateral single steel plate fixation method. Figure 3 Model C in the figure is the target three-dimensional model 2 corresponding to the fracture defect value of 10 mm and the lateral single steel plate fixation method. Figure 3 The D model in the figure is the target three-dimensional model 2 corresponding to the fracture defect value of 15 mm and the lateral single steel plate fixation method. Figure 3 Model E in the figure is the target three-dimensional model 2 corresponding to the fracture defect value of 20 mm and the lateral single steel plate fixation method. Figure 3The F model in the figure is the target three-dimensional model 2 corresponding to the fracture defect value of 25 mm and the lateral single steel plate fixation method. Figure 3 The G model in the figure is the target three-dimensional model 2 corresponding to the fracture defect value of 30 mm and the lateral single steel plate fixation method.

[0051] Figure 4 Model A in the figure is the target three-dimensional model 2 corresponding to the fracture defect value of 0 mm and the double plate fixation method. Figure 4 Model B in the figure is the target three-dimensional model 2 corresponding to the fracture defect value of 5 mm and the double plate fixation method. Figure 4 Model C in the figure is the target three-dimensional model 2 corresponding to the fracture defect value of 10 mm and the double plate fixation method. Figure 4 The D model in the figure is the target 3D model 2 corresponding to the fracture defect value of 15 mm and the double plate fixation method. Figure 4 Model E in the figure is the target three-dimensional model 2 corresponding to the fracture defect value of 20 mm and the double plate fixation method. Figure 4 The F model in the figure is the target three-dimensional model 2 corresponding to the fracture defect value of 25 mm and the double plate fixation method. Figure 4 The G model in the figure is the target three-dimensional model 2 corresponding to the fracture defect value of 30 mm and the double plate fixation method.

[0052] It should be noted that the outer steel plates were modeled based on the LISS steel plate (422.345, 9 holes, 236 mm), while the inner support steel plate of the double steel plate group was modeled based on the PHILOS steel plate (441.921, 8 holes, 196 mm).

[0053] Step S103, determining the target indication corresponding to each steel plate fixation method based on the plurality of target three-dimensional models three, wherein the target indication is used to characterize the applicable scope of each steel plate fixation method.

[0054] Optionally, finite element analysis experiments are performed on multiple target three-dimensional models, and relevant data indicators are extracted to perform function fitting analysis, mine data change trends, and obtain function expressions. At the same time, the effective range of each mechanical indicator of the two steel plate fixation methods is comprehensively analyzed using the hierarchical analysis method and the fuzzy comprehensive evaluation algorithm, and then the applicable range (i.e., target indication) corresponding to each steel plate fixation method is obtained.

[0055] In summary, first, reverse modeling is performed based on the imaging data of the distal femur of multiple first subjects in the normal population to generate a conventional classical model (i.e., target three-dimensional model one). Then, fracture simulation is performed on target three-dimensional model one according to multiple fracture defect values ​​to generate multiple distal femur fracture defect models (i.e., target three-dimensional model two), and fracture fixation is performed on each target three-dimensional model two through multiple steel plate fixation methods to generate multiple target three-dimensional models three. Finally, based on multiple target three-dimensional models three, the applicable range corresponding to each steel plate fixation method is determined. Through three-dimensional reconstruction and simulation technology, a variety of fracture conditions and steel plate fixation effects are accurately simulated, and the applicable range corresponding to each steel plate fixation method is quickly determined, which improves the success rate of fracture recovery surgery and the patient's rehabilitation effect, and also reduces the risks and complications during the operation.

[0056] Optionally, in the method for determining the indications for distal femoral plate fixation provided in an embodiment of the present application, determining the target indication corresponding to each plate fixation method based on multiple target three-dimensional models three includes: performing axial loading analysis on each target three-dimensional model three to obtain multiple first analysis results; performing torsional analysis on each target three-dimensional model three to obtain multiple second analysis results; determining multiple target analysis results based on the multiple first analysis results and the multiple second analysis results; and determining the target indication corresponding to each plate fixation method based on the multiple target analysis results through a fuzzy comprehensive evaluation model.

[0057] In an optional embodiment, a finite element analysis is performed on each target three-dimensional model, including: axial loading analysis and torsion analysis. Figure 5 Schematic diagram of axial loading analysis provided according to an embodiment of the present application. Figure 5 As shown in the figure, to simulate the force conditions of the corresponding adult when standing, all nodes on the distal femoral surface are constrained to 0 degrees of freedom, while the proximal femur is not restricted to simulate the physiological state of the human body to the greatest extent. A downward load of 100% body weight is introduced at the center of the femoral head. The load direction is 8° with the axis of the femoral shaft in the sagittal plane and 13° with the axis of the femoral shaft in the coronal plane. After performing axial loading analysis on each target three-dimensional model, multiple axial loading analysis results (i.e., multiple first analysis results) are obtained, including: axial displacement at the fracture defect, maximum displacement of the femur, equivalent stress of the medial steel plate, and equivalent stress of the lateral steel plate. The axial stiffness (N / mm) of the internal fixation system can be calculated by the ratio of the load and the maximum displacement of the femur.

[0058] Figure 6 Schematic diagram of torsion analysis according to an embodiment of the present application. Figure 6As shown in the figure, the torsional moment of the femur when the human body walks is about 1.5-2.0%×body weight (Nm). The force is applied to the femoral head, and the direction is clockwise torsion in the horizontal plane. After performing torsion analysis on each target three-dimensional model, multiple torsion analysis results (i.e., multiple second analysis results) are obtained, including: the maximum torsion angle of the femoral head, the torsional displacement at the fracture defect, the equivalent stress of the medial steel plate, and the equivalent stress of the lateral steel plate. The torsional stiffness (Nm / deg) of the internal fixation model can be calculated based on the ratio of the torsional moment and the maximum torsion angle of the femoral head.

[0059] Function fitting, hierarchical analysis method and fuzzy comprehensive evaluation were combined to perform analysis and calculation based on the above axial loading analysis results and torsion analysis results (i.e., multiple target analysis results) to obtain the target indications corresponding to different internal fixation methods at different fracture defect values.

[0060] By performing finite element analysis on each target three-dimensional model, the effects of different plate fixation methods on the fracture defect value can be simulated and evaluated quickly and accurately.

[0061] Optionally, in the method for determining the indications for distal femoral plate fixation provided in an embodiment of the present application, the target indication corresponding to each plate fixation method is determined based on multiple target analysis results through a fuzzy comprehensive evaluation model, including: calculating according to the weight values ​​corresponding to the multiple target analysis results to obtain a target weight vector; determining the target membership function corresponding to each target analysis result according to the first preset threshold corresponding to each target analysis result; fitting the multiple target analysis results to obtain the target fitting function corresponding to each target analysis result under multiple fracture defect values; and calculating according to the target weight vector, the target membership function and the target fitting function to obtain the target indication.

[0062] In an optional embodiment, each target analysis result in the axial loading analysis result and the torsion analysis result has a corresponding weight value and a limiting condition (i.e., a first preset threshold value). A comparison matrix is ​​constructed based on the weight value corresponding to each target analysis result, and the comparison matrix is ​​solved to obtain a target weight vector. Based on the limiting condition and the membership function tool corresponding to each target analysis result, a target membership function corresponding to each target analysis result can be obtained.

[0063] It should be noted that the multiple target analysis results are fitted by a nonlinear function model to obtain a target fitting function corresponding to each target analysis result under multiple fracture defect values. Figure 7 is a schematic diagram of a target fitting function provided according to an embodiment of the present application Figure 1 .like Figure 7As shown, taking the finite element analysis axial loading data of a 70KG patient as an example, this figure is a double Y-axis graph of the axial loading experimental parameter function fitting of the single plate and double plate fixation models. Figure 7 Figure A in the figure is the axial stiffness function fitting diagram. Figure 7 Figure B is the maximum equivalent stress function fitting diagram of the outer steel plate. Figure 7 Figure C is a fitting diagram of the axial displacement function of the fracture defect area, and the shaded area of ​​the fitting curve represents the 95% confidence interval. Figure 8 is a schematic diagram of a target fitting function provided according to an embodiment of the present application Figure 2 .like Figure 8 As shown, taking the finite element analysis torsional loading data of a 70KG patient as an example, this figure is a double Y-axis graph of the parameter function fitting of the torsional loading experiment of the single plate and double plate fixation models. Figure 8 Figure A in the figure is the fitting diagram of the torsional stiffness function. Figure 8 Figure B is the maximum equivalent stress function fitting diagram of the outer steel plate. Figure 8 Figure C is the fitting diagram of the torsional displacement function in the fracture defect area, and the shaded area of ​​the fitting curve represents the 95% confidence interval.

[0064] The target fitting function was used to explore the relationship between different defect sizes in the distal femoral fracture metaphysis and various research parameter indicators, and to achieve effective prediction of the results.

[0065] The target indication corresponding to each plate fixation method can be obtained by calculating the target weight vector, the target membership function and the target fitting function.

[0066] It should be noted that nonlinear fitting function models include but are not limited to: exponential functions and polynomial functions, etc. Function fitting is performed based on such models, and the one with the best fitting effect is selected as the final function model (i.e., the target fitting function). The fitting effect is mainly evaluated by the following three factors: (1) R square value > 0.8; (2) whether the fitting function converges; (3) whether the function graph conforms to the image characteristics of the basic scatter plot. Among them, the R square value is used as the main evaluation indicator, while the convergence of the function and the image characteristics are used as auxiliary evaluation indicators to prevent overfitting and improve the efficiency of subsequent algorithm analysis.

[0067] It should be noted that the first preset threshold is a limiting condition and a limiting range for multiple axial loading analysis results and multiple torsion analysis results. For axial stiffness and torsion stiffness, it is necessary to avoid deformity and non-union caused by insufficient stiffness, and also to avoid stress barriers formed by excessive strength of the internal fixation system. Therefore, the appropriate range of axial steel stiffness is 50-400N / mm, and the appropriate range of torsion stiffness is 5-25N / deg. For micro-displacement, the axial movement between fracture fragments is mostly a positive stimulus to fracture healing, while shear displacement is mostly an inhibitory effect, and the limiting range of torsion displacement is more stringent. Therefore, the limiting range of axial displacement is 0.1-3mm, and the limiting range of torsion displacement is 0-1.5mm. For the maximum equivalent stress of the outer steel plate, different loading conditions cannot exceed the yield strength of the material. Therefore, the limiting range of the maximum equivalent stress of the outer steel plate under axial loading is 0-1014MPa, and the maximum equivalent stress of the outer steel plate under torsion loading is 0-455MPa.

[0068] Through the fuzzy comprehensive evaluation model, the impact of multiple target analysis results on the plate fixation method is comprehensively considered, and the target weight vector is calculated according to the weight value, so as to evaluate the indications of different fixation methods more objectively and scientifically.

[0069] Optionally, in the method for determining the indications for distal femoral plate fixation provided in an embodiment of the present application, calculation is performed based on weight values ​​corresponding to multiple target analysis results to obtain a target weight vector, including: calculation is performed based on the weight value corresponding to each target analysis result and the weight values ​​corresponding to the remaining target analysis results to obtain multiple weight ratios; a matrix is ​​constructed based on the multiple weight ratios to obtain a pairwise comparison matrix corresponding to the multiple target analysis results; when the pairwise comparison matrix meets preset conditions, the pairwise comparison matrix is ​​calculated to obtain the target weight vector.

[0070] In an optional embodiment, two or more attending physicians determine the weight value corresponding to each target analysis result based on the limiting conditions and clinical importance of each target analysis result, and independently compare each indicator (i.e., each target analysis result) with each other through a hierarchical analysis algorithm to determine the level (i.e., weight ratio). If the two researchers disagree, a third physician with higher qualifications will make the decision. The expression for determining the level is as follows:

[0071]

[0072] in, and is the weight value of indicator (i.e., analysis result) i to j, n represents the number of compared indicators (i.e., multiple analysis results), Represents the weight ratio of two indicators.

[0073] like Compare Important, then The ratio result is a positive number; if Compare Important, then The result of the ratio is a score, where the relative importance of each indicator relative to itself is 1.

[0074] By comparing each index pairwise, we can get the pairwise comparison matrix A, which is expressed as follows:

[0075]

[0076] When there is no logical problem in the pairwise comparison matrix (that is, the pairwise comparison matrix meets the preset conditions), the eigenvalue of the matrix is ​​solved, and the eigenvector corresponding to the eigenvalue is the weight coefficient vector W (that is, the target weight vector).

[0077] By calculating the weight values, we can objectively evaluate the importance of different analysis results and provide a more scientific and reasonable basis for decision-making.

[0078] Optionally, in the method for determining the indications for distal femoral plate fixation provided in an embodiment of the present application, calculations are performed based on the target weight vector, the target membership function and the target fitting function to obtain the target indication, including: calculating based on the target fitting function and the target membership function to obtain a target membership matrix; calculating based on the target weight vector and the target membership matrix to obtain a target fuzzy decision matrix; calculating based on the target fuzzy decision matrix to obtain a target maximum value corresponding to the target fuzzy decision matrix; calculating based on the target maximum value to obtain the target indication.

[0079] In an optional embodiment, as the interfemoral gap increases in the interval [0,30], the multiple evaluation indicators (i.e., multiple target analysis results) obtained by the axial loading analysis and the torsion analysis will change accordingly. Substitute them into their respective membership functions (i.e., target membership functions) to obtain the membership function matrix U (i.e., target membership matrix), and the expression of the membership function matrix U is as follows:

[0080]

[0081] in, represents the membership function of the ith indicator under the comment “suitable”; Represents the membership function of the i-th indicator under the comment “inappropriate”, i=1, 2, 3, 4, 5, 6.

[0082] The target fuzzy decision matrix is ​​obtained by calculating the weight coefficient vector W (i.e., the target weight vector) and the membership function matrix U (i.e., the target membership matrix). The expression is as follows:

[0083]

[0084]

[0085] Among them, comment is a 2×1 evaluation vector, W is a 6×1 dimensional weight coefficient vector, and the final evaluation is the maximum value in the comment. Obviously, when the femoral defect size x changes, will also change accordingly, so is a function of x.

[0086] By calculating based on the target maximum value, the target indication can be obtained. Fig. 9 is a schematic diagram of target indications provided according to the embodiments of the present application. Fig. 9 As shown in the figure, taking the data of a 70KG patient as an example, the dotted line represents the single-plate fixation model, and the solid line represents the double-plate fixation model. The horizontal axis represents the size of the fracture defect (mm), and the vertical axis represents the degree of acceptability. The closer it is to "0", the higher the degree of unacceptability. On the contrary, "1" means completely acceptable. The range of 9.6mm-13.4mm is a fuzzy interval that needs to be handled in combination with actual factors.

[0087] The target indication corresponding to each plate fixation method can be obtained quickly and accurately through calculations using the target weight vector, the target membership function and the target fitting function.

[0088] Optionally, in the method for determining the indications for distal femoral plate fixation provided in an embodiment of the present application, before calculating the paired comparison matrix to obtain the target weight vector, the method also includes: calculating based on the paired comparison matrix to obtain the eigenvector corresponding to the paired comparison matrix; calculating based on the number of columns and the eigenvector of the paired comparison matrix to obtain the maximum eigenvalue corresponding to the paired comparison matrix; calculating based on the maximum eigenvalue and the matrix order of the paired comparison matrix to obtain the consistency index value corresponding to the paired comparison matrix; calculating based on the average random consistency index value and the consistency index value corresponding to the matrix order to obtain the consistency ratio value corresponding to the paired comparison matrix; if the consistency ratio value is less than the second preset threshold value, it is determined that the paired comparison matrix meets the preset conditions.

[0089] In an optional embodiment, whether the single sorting vector result of the weight coefficient is correct needs to be judged by a consistency check, and the purpose of the consistency check is to detect whether there is a logical problem in the pairwise comparison matrix, that is, whether the pairwise comparison matrix meets the preset conditions.

[0090] The maximum eigenvalue λ of the eigenvector in the consistency check depends on , the larger λ is than the matrix order n, the more serious the inconsistency of matrix A. The consistency index CI is a commonly used consistency test standard. The larger the value, the greater the degree of inconsistency, which will make the result error of the eigenvector larger. In order to calculate the consistency, the eigenvector must be defined first. , the eigenvector The expression is as follows:

[0091]

[0092] in, is the eigenvector, is the normalized sum of each row in the matrix, and n is the number of indicators (i.e., the number of multiple analysis results).

[0093] Then, by multiplying the number of columns by the eigenvector ( ) to obtain the maximum eigenvalue corresponding to the pairwise comparison matrix , the maximum eigenvalue The expression is as follows:

[0094]

[0095] Of course, the deviation from consistency may also be caused by random reasons. It is necessary to compare the consistency index value CI with the average random consistency index value RI (which can be obtained by referring to Table 1). The ratio can be expressed as the consistency ratio value CR. This ratio also depends on the order of the matrix (n). The expression of the consistency index value CI is as follows:

[0096]

[0097] in, is the maximum eigenvalue of the pairwise comparison matrix, n is the order of the pairwise comparison matrix, and CI is the consistency index value.

[0098] Among them, Table 1 shows the average random consistency index value RI.

[0099] Table 1 Average random consistency index value RI

[0100]

[0101] The expression of the consistency ratio value CR is as follows:

[0102]

[0103] Among them, CR is the consistency ratio value, CI is the consistency index value, and RI is the average random consistency index value. If CR < 0.1 (i.e., the second preset threshold), the pairwise comparison matrix passes the consistency test; otherwise, the comparison matrix needs to be readjusted, and the consistency test needs to be re-performed after eliminating the logical problems.

[0104] By performing consistency check on the pairwise comparison matrix, it is possible to quickly and accurately determine whether there are logical problems in the pairwise comparison matrix.

[0105] Optionally, in the method for determining the indications for distal femoral plate fixation provided in an embodiment of the present application, determining the target membership function corresponding to each target analysis result based on the first preset threshold corresponding to each target analysis result includes: calculating based on the z-shaped membership function tool and the first preset threshold to obtain the first membership function; calculating based on the π-shaped membership function tool and the first preset threshold to obtain the second membership function; determining the target membership function based on the first membership function and the second membership function.

[0106] In an optional embodiment, a basic evaluation is set for multiple evaluation indicators (i.e., multiple target analysis results) of the axial load analysis and the torsion analysis: "suitable" and "unsuitable". When the indicator meets the limited interval condition (i.e., the first preset threshold), it is "suitable", and when the indicator exceeds the limited interval condition, it is "unsuitable".

[0107] The first membership functions of "suitable" and "unsuitable" for each indicator are generated by using the Z-shaped and π-shaped membership function tools in the fuzzy toolbox. and the second membership function (It can also be expressed as ), the first membership function The expression is as follows:

[0108]

[0109] Among them, a, b, c, and d are four preset constants, which must be arranged from small to large, and x represents each indicator.

[0110] The second membership function The expression is as follows:

[0111]

[0112] Among them, a, b, c, and d are four preset constants, which must be arranged from small to large, and x represents each indicator.

[0113] It is not difficult to see from the function expression that It basically presents a "unidirectional" change characteristic, which is consistent with the maximum equivalent stress of the axial and torsional steel plate, that is, in order to avoid failure of the internal fixation system, the maximum stress value must be less than the yield strength of the material property. It exhibits a "bidirectional" characteristic, which is consistent with the changing characteristics of structural stiffness and micro-displacement under axial and torsional loading.

[0114] It should be noted that Fig.10 is a schematic diagram of a target membership function provided according to an embodiment of the present application Figure 1 .like Fig.10 As shown, taking the finite element analysis torsional loading data of a 70KG patient as an example, this figure is the membership function diagram of the axial loading index. Fig.10 Figure A in the figure represents the membership function diagram of axial stiffness (N / mm). Fig.10 Figure B in the figure represents the membership function diagram of the axial micro-displacement (mm). Fig.10 Figure C in the figure represents the membership function diagram of the maximum equivalent stress (MPa) of the outer steel plate. The dotted line indicates that the indicator is "unsuitable" and the solid line indicates "suitable". The horizontal axis of the coordinates is the data type and interval of each indicator, and the vertical axis is the "acceptance degree". The closer it is to "0", the higher the unacceptability. On the contrary, "1" means it is completely acceptable.

[0115] It should be noted that Fig.11 is a schematic diagram of a target membership function provided according to an embodiment of the present application Figure 2 .like Fig.11 As shown, taking the finite element analysis torsional loading data of a 70KG patient as an example, this figure is a membership function diagram of the torsional loading index. Fig.11 Figure A in the figure represents the membership function diagram of torsional stiffness (N / deg). Fig.11 Figure B in the figure represents the membership function diagram of the torsional displacement (mm) of the defect area. Fig.11 Figure C in the figure represents the membership function diagram of the maximum equivalent stress (MPa) of the outer steel plate. The dotted line indicates that the indicator is "unsuitable" and the solid line indicates "suitable". The horizontal axis of the coordinates is the data type and interval of each indicator, and the vertical axis is the "acceptance degree". The closer it is to "0", the higher the unacceptability. On the contrary, "1" means it is completely acceptable.

[0116] The target membership function can be obtained quickly and accurately through the z-shaped membership function tool and the π-shaped membership function tool.

[0117] Optionally, in the method for determining the indications for distal femoral plate fixation provided in an embodiment of the present application, after determining the target indication corresponding to each plate fixation method based on multiple target three-dimensional models, the method also includes: obtaining a target fracture defect value corresponding to a second object; determining a target plate fixation method from multiple plate fixation methods based on the target fracture defect value and the target indication; and performing fracture fixation on the distal femur fracture of the second object based on the target plate fixation method.

[0118] In an optional embodiment, a target fracture defect value corresponding to the patient (i.e., the second subject) is obtained through medical imaging technology, including but not limited to: X-rays, CT, etc., and the most suitable plate fixation method (i.e., the target plate fixation method) corresponding to the target fracture defect value is determined through the target indication. The fracture site of the distal femur of the patient is fixed by the target plate fixation method.

[0119] Based on the target indication and the patient's fracture defect value, the best plate fixation method for the patient can be quickly and accurately determined.

[0120] The method for determining the indications of distal femoral plate fixation provided in the embodiment of the present application is to perform three-dimensional reconstruction based on the image data of the distal femur of multiple first objects to obtain a target three-dimensional model one; perform fracture simulation on the target three-dimensional model one based on multiple fracture defect values ​​to obtain multiple target three-dimensional models two, and perform fracture fixation on each target three-dimensional model two through multiple plate fixation methods to obtain multiple target three-dimensional models three; based on the multiple target three-dimensional models three, determine the target indication corresponding to each plate fixation method, wherein the target indication is used to characterize the scope of application of each plate fixation method, which solves the problem that the indications of the plate fixation method at the distal femoral fracture are determined based on artificial experience in the related art, resulting in a relatively low accuracy in determining the indications. In summary, in this scheme, first, reverse modeling is performed based on the image data of the distal femur of multiple first objects in the normal population to generate a conventional classical model (i.e., target three-dimensional model one). Then, the target three-dimensional model 1 is simulated for fracture according to multiple fracture defect values ​​to generate multiple distal femoral fracture defect models (i.e., target three-dimensional model 2), and each target three-dimensional model 2 is fracture-fixed by multiple plate fixation methods to generate multiple target three-dimensional models 3. Finally, the applicable range corresponding to each plate fixation method is determined according to multiple target three-dimensional models 3. Through three-dimensional reconstruction and simulation technology, a variety of fracture conditions and plate fixation effects are accurately simulated, and the applicable range corresponding to each plate fixation method is quickly determined, which improves the success rate of fracture recovery surgery and the patient's rehabilitation effect, and also reduces the risks and complications during the operation.

[0121] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0122] The embodiment of the present application also provides a device for determining the indications for distal femoral plate fixation. It should be noted that the device for determining the indications for distal femoral plate fixation in the embodiment of the present application can be used to execute the method for determining the indications for distal femoral plate fixation provided in the embodiment of the present application. The device for determining the indications for distal femoral plate fixation provided in the embodiment of the present application is introduced below.

[0123] Fig.12 Schematic diagram of a device for determining an indication for distal femoral plate fixation according to an embodiment of the present application. Fig.12 As shown, the device includes: a reconstruction unit 1201, a simulation unit 1202, and a first determination unit 1203.

[0124] A reconstruction unit 1201 is used to perform three-dimensional reconstruction based on the image data of the distal end of the femur of the plurality of first objects to obtain a target three-dimensional model 1;

[0125] The simulation unit 1202 is used to perform fracture simulation on the target three-dimensional model 1 according to the multiple fracture defect values ​​to obtain multiple target three-dimensional models 2, and perform fracture fixation on each target three-dimensional model 2 by multiple steel plate fixation methods to obtain multiple target three-dimensional models 3;

[0126] The first determination unit 1203 is used to determine the target indication corresponding to each steel plate fixation method based on multiple target three-dimensional models 3, wherein the target indication is used to characterize the applicable scope of each steel plate fixation method.

[0127] The embodiment of the present application provides a device for determining the indications of distal femoral plate fixation, wherein the reconstruction unit 1201 performs three-dimensional reconstruction based on the image data of the distal femur of multiple first objects to obtain a target three-dimensional model 1; the simulation unit 1202 performs fracture simulation on the target three-dimensional model 1 based on multiple fracture defect values ​​to obtain multiple target three-dimensional models 2, and performs fracture fixation on each target three-dimensional model 2 through multiple plate fixation methods to obtain multiple target three-dimensional models 3; the first determination unit 1203 determines the target indication corresponding to each plate fixation method based on the multiple target three-dimensional models 3, wherein the target indication is used to characterize the applicable scope of each plate fixation method, and solves the problem that the indication of the plate fixation method at the distal femoral fracture is determined based on artificial experience in the related art, resulting in a relatively low accuracy in determining the indication. In this solution, first, reverse modeling is performed based on the image data of the distal femur of multiple first objects in the normal population to generate a conventional classical model (i.e., target three-dimensional model 1). Then, the target three-dimensional model 1 is simulated for fracture according to multiple fracture defect values ​​to generate multiple distal femoral fracture defect models (i.e., target three-dimensional model 2), and each target three-dimensional model 2 is fracture-fixed by multiple plate fixation methods to generate multiple target three-dimensional models 3. Finally, the applicable range corresponding to each plate fixation method is determined according to multiple target three-dimensional models 3. Through three-dimensional reconstruction and simulation technology, a variety of fracture conditions and plate fixation effects are accurately simulated, and the applicable range corresponding to each plate fixation method is quickly determined, which improves the success rate of fracture recovery surgery and the patient's rehabilitation effect, and also reduces the risks and complications during the operation.

[0128] Optionally, in the device for determining the indications for distal femoral plate fixation provided in an embodiment of the present application, the first determination unit includes: a first analysis subunit, used to perform axial loading analysis on each target three-dimensional model three to obtain multiple first analysis results; a second analysis subunit, used to perform torsional analysis on each target three-dimensional model three to obtain multiple second analysis results; the first determination subunit, used to determine multiple target analysis results based on the multiple first analysis results and the multiple second analysis results; the second determination subunit, used to determine the target indication corresponding to each plate fixation method based on the multiple target analysis results through a fuzzy comprehensive evaluation model.

[0129] Optionally, in the device for determining the indications for distal femoral plate fixation provided in an embodiment of the present application, the second determination subunit includes: a first calculation module, used to calculate according to weight values ​​corresponding to multiple target analysis results to obtain a target weight vector; a determination module, used to determine the target membership function corresponding to each target analysis result according to a first preset threshold corresponding to each target analysis result; a fitting module, used to fit multiple target analysis results to obtain a target fitting function corresponding to each target analysis result under multiple fracture defect values; a second calculation module, used to calculate according to the target weight vector, the target membership function and the target fitting function to obtain the target indication.

[0130] Optionally, in the device for determining the indications for distal femoral plate fixation provided in an embodiment of the present application, the first calculation module includes: a first calculation submodule, used to calculate according to the weight value corresponding to each target analysis result and the weight values ​​corresponding to the remaining target analysis results, to obtain multiple weight ratios; a construction submodule, used to construct a matrix according to the multiple weight ratios, to obtain a pairwise comparison matrix corresponding to the multiple target analysis results; a second calculation submodule, used to calculate the pairwise comparison matrix when the pairwise comparison matrix meets preset conditions, to obtain a target weight vector.

[0131] Optionally, in the device for determining the indications for distal femoral plate fixation provided in an embodiment of the present application, the second calculation module includes: a third calculation submodule, used to perform calculations based on a target fitting function and a target membership function to obtain a target membership matrix; a fourth calculation submodule, used to perform calculations based on a target weight vector and a target membership matrix to obtain a target fuzzy decision matrix; a fifth calculation submodule, used to perform calculations based on the target fuzzy decision matrix to obtain a target maximum value corresponding to the target fuzzy decision matrix; and a sixth calculation submodule, used to perform calculations based on the target maximum value to obtain a target indication.

[0132] Optionally, in the device for determining the indications for distal femoral plate fixation provided in an embodiment of the present application, the device also includes: a first calculation unit, which is used to calculate according to the paired comparison matrix to obtain the eigenvector corresponding to the paired comparison matrix before calculating the paired comparison matrix to obtain the target weight vector; a second calculation unit, which is used to calculate according to the number of columns and the eigenvector of the paired comparison matrix to obtain the maximum eigenvalue corresponding to the paired comparison matrix; a third calculation unit, which is used to calculate according to the maximum eigenvalue and the matrix order of the paired comparison matrix to obtain the consistency index value corresponding to the paired comparison matrix; a fourth calculation unit, which is used to calculate according to the average random consistency index value and the consistency index value corresponding to the matrix order to obtain the consistency ratio value corresponding to the paired comparison matrix; a second determination unit, which is used to determine that the paired comparison matrix meets the preset conditions if the consistency ratio value is less than a second preset threshold.

[0133] Optionally, in the device for determining the indications for distal femoral plate fixation provided in an embodiment of the present application, the determination module includes: a seventh calculation submodule, used to perform calculations based on a z-shaped membership function tool and a first preset threshold to obtain a first membership function; an eighth calculation submodule, used to perform calculations based on a π-shaped membership function tool and a first preset threshold to obtain a second membership function; and a determination submodule, used to determine a target membership function based on the first membership function and the second membership function.

[0134] Furthermore, the device also includes: an acquisition unit, which is used to obtain the target fracture defect value corresponding to the second object after determining the target indication corresponding to each steel plate fixation method based on multiple target three-dimensional models; a third determination unit, which is used to determine the target steel plate fixation method from multiple steel plate fixation methods based on the target fracture defect value and the target indication; and a fixing unit, which is used to fix the distal femur fracture of the second object based on the target steel plate fixation method.

[0135] The device for determining the indications for distal femoral plate fixation includes a processor and a memory. The above-mentioned reconstruction unit 1201, simulation unit 1202, first determination unit 1203, etc. are all stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to realize accurate processing of distal femoral fracture data.

[0136] The processor includes a kernel, which retrieves the corresponding program unit from the memory. One or more kernels can be set, and the accurate processing of distal femoral fracture data can be achieved by adjusting kernel parameters.

[0137] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0138] An embodiment of the present invention provides a computer-readable storage medium having a program stored thereon, and when the program is executed by a processor, a method for determining an indication for distal femoral plate fixation is implemented.

[0139] An embodiment of the present invention provides a processor, which is used to run a program, wherein the program executes a method for determining an indication for distal femoral plate fixation when the program is run.

[0140] like Fig.13As shown, an embodiment of the present invention provides an electronic device, the device includes a processor, a memory, and a program stored in the memory and executable on the processor, and the processor implements the following steps when executing the program: performing three-dimensional reconstruction based on multiple image data of the distal femur of a first object to obtain a target three-dimensional model one; performing fracture simulation on the target three-dimensional model one based on multiple fracture defect values ​​to obtain multiple target three-dimensional models two, and performing fracture fixation on each target three-dimensional model two using multiple steel plate fixation methods to obtain multiple target three-dimensional models three; determining the target indication corresponding to each steel plate fixation method based on the multiple target three-dimensional models three, wherein the target indication is used to characterize the scope of application of each steel plate fixation method.

[0141] Optionally, based on the target fracture defect values ​​corresponding to the multiple target three-dimensional models three and the second object, determining the target indication corresponding to each plate fixation method includes: performing axial loading analysis on each target three-dimensional model three to obtain multiple first analysis results; performing torsional analysis on each target three-dimensional model three to obtain multiple second analysis results; determining multiple target analysis results based on the multiple first analysis results and the multiple second analysis results; and determining the target indication corresponding to each plate fixation method based on the multiple target analysis results through a fuzzy comprehensive evaluation model.

[0142] Optionally, determining the target indication of the fracture defect value corresponding to each plate fixation method based on multiple target analysis results through a fuzzy comprehensive evaluation model includes: calculating according to the weight values ​​corresponding to the multiple target analysis results to obtain a target weight vector; determining the target membership function corresponding to each target analysis result according to the first preset threshold corresponding to each target analysis result; fitting the multiple target analysis results to obtain the target fitting function corresponding to each target analysis result under multiple fracture defect values; calculating according to the target weight vector, the target membership function and the target fitting function to obtain the target indication.

[0143] Optionally, calculating according to weight values ​​corresponding to multiple target analysis results to obtain a target weight vector includes: calculating according to the weight value corresponding to each target analysis result and the weight values ​​corresponding to the remaining target analysis results to obtain multiple weight ratios; constructing a matrix according to the multiple weight ratios to obtain a pairwise comparison matrix corresponding to the multiple target analysis results; when the pairwise comparison matrix meets preset conditions, calculating the pairwise comparison matrix to obtain the target weight vector.

[0144] Optionally, calculating according to the target weight vector, the target membership function and the target fitting function to obtain the target indication includes: calculating according to the target fitting function and the target membership function to obtain the target membership matrix; calculating according to the target weight vector and the target membership matrix to obtain the target fuzzy decision matrix; calculating according to the target fuzzy decision matrix to obtain the target maximum value corresponding to the target fuzzy decision matrix; calculating according to the target maximum value to obtain the target indication.

[0145] Optionally, before calculating the paired comparison matrix to obtain the target weight vector, the method also includes: calculating based on the paired comparison matrix to obtain the eigenvector corresponding to the paired comparison matrix; calculating based on the number of columns and the eigenvector of the paired comparison matrix to obtain the maximum eigenvalue corresponding to the paired comparison matrix; calculating based on the maximum eigenvalue and the matrix order of the paired comparison matrix to obtain the consistency index value corresponding to the paired comparison matrix; calculating based on the average random consistency index value and the consistency index value corresponding to the matrix order to obtain the consistency ratio value corresponding to the paired comparison matrix; if the consistency ratio value is less than the second preset threshold value, it is determined that the paired comparison matrix meets the preset conditions.

[0146] Optionally, based on the first preset threshold corresponding to each target analysis result, determining the target membership function corresponding to each target analysis result includes: calculating based on the z-shaped membership function tool and the first preset threshold to obtain the first membership function; calculating based on the π-shaped membership function tool and the first preset threshold to obtain the second membership function; determining the target membership function based on the first membership function and the second membership function.

[0147] Optionally, after determining the target indication corresponding to each plate fixation method based on multiple target three-dimensional models, the method also includes: obtaining a target fracture defect value corresponding to the second object; determining a target plate fixation method from multiple plate fixation methods based on the target fracture defect value and the target indication; and performing fracture fixation on the distal femur fracture of the second object based on the target plate fixation method.

[0148] The devices in this article can be servers, PCs, PADs, mobile phones, etc.

[0149] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program that initializes the following method steps: performing three-dimensional reconstruction based on multiple image data of the distal femur of a first object to obtain a target three-dimensional model one; performing fracture simulation on the target three-dimensional model one based on multiple fracture defect values ​​to obtain multiple target three-dimensional models two, and performing fracture fixation on each target three-dimensional model two using multiple steel plate fixation methods to obtain multiple target three-dimensional models three; based on the multiple target three-dimensional models three, determining the target indication corresponding to each steel plate fixation method, wherein the target indication is used to characterize the scope of application of each steel plate fixation method.

[0150] Optionally, based on the target fracture defect values ​​corresponding to the multiple target three-dimensional models three and the second object, determining the target indication corresponding to each plate fixation method includes: performing axial loading analysis on each target three-dimensional model three to obtain multiple first analysis results; performing torsional analysis on each target three-dimensional model three to obtain multiple second analysis results; determining multiple target analysis results based on the multiple first analysis results and the multiple second analysis results; and determining the target indication corresponding to each plate fixation method based on the multiple target analysis results using a fuzzy comprehensive evaluation model.

[0151] Optionally, determining the target indication corresponding to each plate fixation method based on multiple target analysis results through a fuzzy comprehensive evaluation model includes: calculating according to weight values ​​corresponding to multiple target analysis results to obtain a target weight vector; determining a target membership function corresponding to each target analysis result according to a first preset threshold corresponding to each target analysis result; fitting multiple target analysis results to obtain a target fitting function corresponding to each target analysis result under multiple fracture defect values; and calculating according to the target weight vector, the target membership function and the target fitting function to obtain the target indication.

[0152] Optionally, calculating according to weight values ​​corresponding to multiple target analysis results to obtain a target weight vector includes: calculating according to the weight value corresponding to each target analysis result and the weight values ​​corresponding to the remaining target analysis results to obtain multiple weight ratios; constructing a matrix according to the multiple weight ratios to obtain a pairwise comparison matrix corresponding to the multiple target analysis results; when the pairwise comparison matrix meets preset conditions, calculating the pairwise comparison matrix to obtain the target weight vector.

[0153] Optionally, calculating according to the target weight vector, the target membership function and the target fitting function to obtain the target indication includes: calculating according to the target fitting function and the target membership function to obtain the target membership matrix; calculating according to the target weight vector and the target membership matrix to obtain the target fuzzy decision matrix; calculating according to the target fuzzy decision matrix to obtain the target maximum value corresponding to the target fuzzy decision matrix; calculating according to the target maximum value to obtain the target indication.

[0154] Optionally, before calculating the paired comparison matrix to obtain the target weight vector, the method also includes: calculating based on the paired comparison matrix to obtain the eigenvector corresponding to the paired comparison matrix; calculating based on the number of columns and the eigenvector of the paired comparison matrix to obtain the maximum eigenvalue corresponding to the paired comparison matrix; calculating based on the maximum eigenvalue and the matrix order of the paired comparison matrix to obtain the consistency index value corresponding to the paired comparison matrix; calculating based on the average random consistency index value and the consistency index value corresponding to the matrix order to obtain the consistency ratio value corresponding to the paired comparison matrix; if the consistency ratio value is less than the second preset threshold value, it is determined that the paired comparison matrix meets the preset conditions.

[0155] Optionally, based on the first preset threshold corresponding to each target analysis result, determining the target membership function corresponding to each target analysis result includes: calculating based on the z-shaped membership function tool and the first preset threshold to obtain the first membership function; calculating based on the π-shaped membership function tool and the first preset threshold to obtain the second membership function; determining the target membership function based on the first membership function and the second membership function.

[0156] Optionally, after determining the target indication corresponding to each plate fixation method based on multiple target three-dimensional models, the method also includes: obtaining a target fracture defect value corresponding to the second object; determining a target plate fixation method from multiple plate fixation methods based on the target fracture defect value and the target indication; and performing fracture fixation on the distal femur fracture of the second object based on the target plate fixation method.

[0157] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0158] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0159] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0160] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0161] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0162] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0163] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0164] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0165] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0166] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for determining the indications for distal femoral plate fixation, characterized in that: include: Performing three-dimensional reconstruction based on the image data of the distal end of the femur of the plurality of first objects to obtain a target three-dimensional model 1; Performing fracture simulation on the target three-dimensional model one according to the multiple fracture defect values ​​to obtain multiple target three-dimensional models two, and performing fracture fixation on each target three-dimensional model two by multiple steel plate fixation methods to obtain multiple target three-dimensional models three; Determining the target indication corresponding to each steel plate fixation method according to the plurality of target three-dimensional models three, wherein the target indication is used to characterize the applicable scope of each steel plate fixation method; Wherein, the plurality of steel plate fixation methods include an outer single steel plate fixation method and a double steel plate fixation method, and the target indication is the effective range of each mechanical index corresponding to the plurality of steel plate fixation methods; Wherein, according to the plurality of target three-dimensional models 3, determining the target indication corresponding to each steel plate fixation method includes: Performing axial loading analysis on each target three-dimensional model to obtain a plurality of first analysis results; Performing a torsion analysis on each target three-dimensional model to obtain a plurality of second analysis results; Determining a plurality of target analysis results according to the plurality of first analysis results and the plurality of second analysis results; The target indication corresponding to each plate fixation method is determined based on the multiple target analysis results through a fuzzy comprehensive evaluation model.

2. The method according to claim 1, characterized in that Based on the multiple target analysis results through the fuzzy comprehensive evaluation model, the target indications corresponding to each plate fixation method are determined to include: Calculating according to the weight values ​​corresponding to the multiple target analysis results to obtain a target weight vector; Determine a target membership function corresponding to each target analysis result according to a first preset threshold corresponding to each target analysis result; Fitting the multiple target analysis results to obtain a target fitting function corresponding to each target analysis result under the multiple fracture defect values; The target indication is obtained by performing calculations based on the target weight vector, the target membership function and the target fitting function.

3. The method according to claim 2, characterized in that The target weight vector is obtained by calculating the weight values ​​corresponding to the multiple target analysis results, including: Calculate based on the weight value corresponding to each target analysis result and the weight values ​​corresponding to the remaining target analysis results to obtain multiple weight ratios; Constructing a matrix according to the multiple weight ratios to obtain a pairwise comparison matrix corresponding to the multiple target analysis results; When the pairwise comparison matrix meets a preset condition, the pairwise comparison matrix is ​​calculated to obtain the target weight vector.

4. The method according to claim 2, characterized in that: The target indications obtained by calculating according to the target weight vector, the target membership function and the target fitting function include: Calculating according to the target fitting function and the target membership function to obtain a target membership matrix; Calculating according to the target weight vector and the target membership matrix to obtain a target fuzzy decision matrix; Calculating according to the target fuzzy decision matrix to obtain the target maximum value corresponding to the target fuzzy decision matrix; The target indication is obtained by performing calculation according to the target maximum value.

5. The method according to claim 3, characterized in that: Before calculating the pairwise comparison matrix to obtain the target weight vector, the method further includes: Calculating according to the pairwise comparison matrix to obtain a eigenvector corresponding to the pairwise comparison matrix; Calculating according to the number of columns of the pairwise comparison matrix and the eigenvector to obtain the maximum eigenvalue corresponding to the pairwise comparison matrix; Calculating according to the maximum eigenvalue and the matrix order of the pairwise comparison matrix to obtain a consistency index value corresponding to the pairwise comparison matrix; Calculating according to the average random consistency index value corresponding to the matrix order and the consistency index value to obtain a consistency ratio value corresponding to the pairwise comparison matrix; If the consistency ratio value is less than a second preset threshold, it is determined that the pairwise comparison matrix meets the preset condition.

6. The method according to claim 2, characterized in that Determining the target membership function corresponding to each target analysis result according to the first preset threshold corresponding to each target analysis result includes: Calculating according to the z-shaped membership function tool and the first preset threshold to obtain a first membership function; Calculating according to the π-shaped membership function tool and the first preset threshold to obtain a second membership function; The target membership function is determined according to the first membership function and the second membership function.

7. The method according to claim 1, characterized in that After determining the target indication corresponding to each steel plate fixation method according to the plurality of target three-dimensional models, the method further includes: obtaining a target fracture defect value corresponding to the second object; A target plate fixation method is determined from among the multiple plate fixation methods according to the target fracture defect value and the target indication.

8. A device for determining indications for distal femoral plate fixation, characterized in that: include: A reconstruction unit, configured to perform three-dimensional reconstruction based on the image data of the distal end of the femur of the plurality of first objects to obtain a target three-dimensional model 1; A simulation unit, configured to perform fracture simulation on the target three-dimensional model one according to a plurality of fracture defect values ​​to obtain a plurality of target three-dimensional models two, and perform fracture fixation on each target three-dimensional model two by a plurality of steel plate fixation methods to obtain a plurality of target three-dimensional models three; A first determination unit is used to determine a target indication corresponding to each steel plate fixation method according to the plurality of target three-dimensional models three, wherein the target indication is used to characterize the applicable scope of each steel plate fixation method; Wherein, the plurality of steel plate fixation methods include an outer single steel plate fixation method and a double steel plate fixation method, and the target indication is the effective range of each mechanical index corresponding to the plurality of steel plate fixation methods; Among them, the first determination unit includes: a first analysis subunit, used to perform axial loading analysis on each target three-dimensional model three to obtain multiple first analysis results; a second analysis subunit, used to perform torsional analysis on each target three-dimensional model three to obtain multiple second analysis results; the first determination subunit, used to determine multiple target analysis results based on the multiple first analysis results and the multiple second analysis results; the second determination subunit, used to determine the target indication corresponding to each steel plate fixation method based on the multiple target analysis results through a fuzzy comprehensive evaluation model.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the storage medium is controlled to execute the method for determining the indication for distal femoral plate fixation according to any one of claims 1 to 7 on a device.

10. An electronic device, characterized in that: It includes one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method for determining the indications for distal femoral plate fixation as described in any one of claims 1 to 7.

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