A method and device for planning a per-acetabular osteotomy based on collision detection

Abstract

The application provides a kind of based on collision detection's periacetabular osteotomy planning method and device, the method comprises: obtaining hip medical image, constructs hip three-dimensional model;According to hip three-dimensional model, the initial adjustment position and initial osteotomy position of acetabulum are determined;Simulate the collision data of femoral head and acetabulum under different motion states;Based on the collision data, the adjustment position and osteotomy position of acetabulum are optimized, and the best adjustment position and best osteotomy position of acetabulum are determined.In the application, the collision data of femoral head and acetabulum under different motion states is simulated, and the adjustment position and osteotomy position of acetabulum are optimized, so as to greatly increase the accuracy of acetabulum position and osteotomy position planning.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of medical image processing, in particular to a periacetabular osteotomy planning method and device based on collision detection. BACKGROUND

[0002] Periacetabular Osteotomy (PAO) is a surgical method for treating hip dysplasia, which repositions the acetabulum to improve the coverage of the hip joint, thereby reducing pain and delaying or preventing the development of hip degenerative diseases.

[0003] At present, only the acetabular coverage is used to plan the acetabular position and the osteotomy position, which is insufficient in accuracy. SUMMARY

[0004] The problem solved by the present application is the insufficient accuracy of current acetabular position and osteotomy position planning.

[0005] To solve the above problems, the first aspect of the present application provides a periacetabular osteotomy planning method based on collision detection, comprising:

[0006] Obtaining a medical image of the hip joint and constructing a three-dimensional model of the hip joint;

[0007] Determining the initial adjustment position and the initial osteotomy position of the acetabulum according to the three-dimensional model of the hip joint;

[0008] Simulating collision data of the femoral head and the acetabulum in different motion states;

[0009] Optimizing the adjustment position and the osteotomy position of the acetabulum based on the collision data to determine the best adjustment position and the best osteotomy position of the acetabulum.

[0010] The second aspect of the present application provides a periacetabular osteotomy planning device based on collision detection, comprising:

[0011] A model construction module for obtaining a medical image of the hip joint and constructing a three-dimensional model of the hip joint;

[0012] A position determination module for determining the initial adjustment position and the initial osteotomy position of the acetabulum according to the three-dimensional model of the hip joint;

[0013] A collision detection module for simulating collision data of the femoral head and the acetabulum in different motion states;

[0014] A position optimization module for optimizing the adjustment position and the osteotomy position of the acetabulum based on the collision data to determine the best adjustment position and the best osteotomy position of the acetabulum.

[0015] The third aspect of the present application provides an electronic device, comprising a memory and a processor;

[0016] The memory is configured to store a program;

[0017] The processor is coupled to the memory and configured to execute the program, so as to:

[0018] Obtaining a medical image of a hip joint and constructing a three-dimensional model of the hip joint;

[0019] According to the three-dimensional model of the hip joint, determining an initial adjustment position and an initial bone cutting position of the acetabulum;

[0020] Simulating collision data of the femoral head and the acetabulum under different motion states;

[0021] Based on the collision data, the adjustment position and the bone cutting position of the acetabulum are optimized to determine the optimal adjustment position and the optimal bone cutting position of the acetabulum.

[0022] The fourth aspect of the present application provides a computer readable storage medium, which stores a computer program, and the program is executed by a processor to realize the above-mentioned acetabular periacetabular osteotomy planning method based on collision detection.

[0023] In the present application, the collision data of the femoral head and the acetabulum under different motion states is simulated to optimize the position of the acetabulum and the bone cutting position, thereby greatly increasing the accuracy of the planning of the position of the acetabulum and the bone cutting position. BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 The flowchart of the acetabular periacetabular osteotomy planning method according to the embodiment of the present application is shown;

[0025] Figure 2 The flowchart of the collision detection of the acetabular periacetabular osteotomy planning method according to the embodiment of the present application is shown;

[0026] Figure 3 The structural block diagram of the acetabular periacetabular osteotomy planning device according to the embodiment of the present application is shown;

[0027] Figure 4 The structural block diagram of the electronic device according to the embodiment of the present application is shown. DETAILED DESCRIPTION

[0028] To make the above-mentioned objects, features, and advantages of the present application more clearly understood, specific embodiments of the present application are described in detail below with reference to the accompanying drawings. Although the accompanying drawings show exemplary embodiments of the present application, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments described herein. Instead, these embodiments are provided to enable a more thorough understanding of the present application and to fully convey the scope of the present application to those skilled in the art.

[0029] It should be noted that, unless otherwise specified, the technical or scientific terms used in this application should have the common meanings understood by those skilled in the art to which this application belongs.

[0030] To address the above problems, the present application provides a new collision detection-based periacetabular osteotomy planning scheme, which solves the problem of low accuracy of three-dimensional reconstruction results generated by current X-ray films by downsampling the anteroposterior and lateral two-dimensional images respectively, and upsampling the three-dimensional images obtained by conversion and fusion.

[0031] The embodiment of the present application provides a method for planning periacetabular osteotomy based on collision detection, the specific scheme of the method is as follows: Figures 1-2 As shown, the method can be performed by a periacetabular osteotomy planning device based on collision detection, and the periacetabular osteotomy planning device based on collision detection can be integrated into electronic devices such as computers, servers, computers, server clusters, and data centers. Figure 1 , which is a flow chart of a periacetabular osteotomy planning method based on collision detection according to one embodiment of the present application; wherein the periacetabular osteotomy planning method based on collision detection includes:

[0032] S101, acquiring medical images of the hip joint and constructing a three-dimensional model of the hip joint;

[0033] The hip joint medical image is a CT image or MRI image containing the hip joint.

[0034] In this application, based on the medical image of the hip joint, three-dimensional point cloud data of the hip joint can be generated; based on the three-dimensional point cloud data of the hip joint, the three-dimensional point cloud data can be converted into a three-dimensional model of the hip joint through image processing technology.

[0035] S102, determining an initial adjustment position and an initial osteotomy position of the acetabulum based on the three-dimensional model of the hip joint;

[0036] Among them, the initial adjustment position of the acetabulum can be obtained by: identifying the key points of the three-dimensional model of the hip joint; analyzing the three-dimensional model of the hip joint to evaluate the direction of the acetabulum opening, the location and degree of coverage of the defect; and determining the initial adjustment position of the acetabulum based on the evaluation results and the standard acetabulum inclination angle.

[0037] In the initial adjustment position of the acetabulum, the acetabular opening direction was evaluated by the lateral center edge angle (LCEA) and the acetabular inclination angle (AIA), and the location and degree of coverage of the defect were evaluated by the head and acetabulum coverage (HAI).

[0038] S103, simulated collision data between the femoral head and acetabulum in different motion states;

[0039] S104: Optimizing the adjustment position and osteotomy position of the acetabulum based on the collision data to determine the optimal adjustment position and optimal osteotomy position of the acetabulum.

[0040] In this application, the acetabulum position and osteotomy position are optimized by simulating the collision data of the femoral head and acetabulum in different motion states, thereby greatly increasing the accuracy of the acetabulum position and osteotomy position planning.

[0041] In one embodiment, combined Figure 2 As shown,

[0042] The step S103 simulates collision data between the femoral head and the acetabulum in different motion states, including:

[0043] S301, obtaining the current acetabulum adjustment position and osteotomy position;

[0044] S302, representing the femoral head and acetabulum as a polygonal mesh, wherein the polygonal mesh is composed of a plurality of triangular facets;

[0045] In the present application, after obtaining the three-dimensional model of the femoral head, the surface point cloud of the femoral head is determined, and the surface point cloud is converted into a polygonal mesh consisting of triangular facets. The surface point cloud can be converted into triangular facets by a triangulation algorithm.

[0046] Preferably, the generated polygonal mesh is optimized using a mesh optimization algorithm to reduce the number of triangles in the polygonal mesh and remove irregular shapes or noise in the mesh while preserving the geometric features of the original model as much as possible.

[0047] Similarly, in this application, the polygonal mesh of the acetabulum is generated using the same method.

[0048] S303, simulating the motion state of the femoral head;

[0049] In the present application, the movement state of the femoral head can include flexion / extension, internal / external rotation, abduction / adduction, wherein the range of motion of the femoral head is: flexion / extension: -10° to 120°; internal / external rotation: -45° to 45°; abduction / adduction: about -30° to 45°.

[0050] S304, determining the collision position of the femoral head and the acetabulum in the movement state;

[0051] In the present application, the collision position of the femoral head and the acetabulum in the movement state is determined according to the limit movement state of the femoral head. For example, the collision position of the femoral head and the acetabulum corresponding to the movement state of the femoral head flexion -10° is determined.

[0052] S305, traversing all movement states of the femoral head to determine the collision position in each movement state as the collision data.

[0053] In the present application, the movement state of the femoral head is infinite, and the movement state in several limit conditions is set to represent all movement states of the femoral head.

[0054] The movement state in several limit conditions includes flexion / extension state, internal / external rotation state, and abduction / adduction state.

[0055] The range of motion of the femoral head is: flexion / extension: -10° to 120°; internal / external rotation: -45° to 45°; abduction / adduction: about -30° to 45°, based on which the range of motion of the femoral head forms a closed area, and the movement state of the boundary of the range of motion is set as the movement state in the limit condition of the femoral head.

[0056] In the present application, a plurality of discrete points are selected on the boundary of the closed area as the movement state in the limit condition.

[0057] The movement state in the limit condition is traversed, that is, all movement states of the femoral head are traversed.

[0058] In this way, the movement state of the femoral head is represented by the movement state in several limit conditions, thereby greatly reducing the calculation amount. Moreover, all movement states of the femoral head are counted, thereby realizing accurate simulation of the movement state of the femoral head and accurate counting of the collision data.

[0059] In one embodiment, the S304, determining the collision position of the femoral head and the acetabulum in the movement state, comprises:

[0060] determine the associated triangular patches of the femoral head and the acetabulum in the motion state;

[0061] calculate the minimum distance between each pair of the associated triangular patches;

[0062] if the minimum distance between two associated triangular patches is less than the preset threshold, determine that the two associated triangular patches collide;

[0063] determine the collision position in the motion state by traversing all the associated triangular patches;

[0064] In the present application, the determination of the associated triangular patches of the femoral head and the acetabulum can be that a triangular patch on the femoral head is taken as the center, a sphere is generated with a preset value as the radius (the preset value is greater than the preset threshold corresponding to the collision), and then the triangular patches on the acetabulum located in the sphere are the associated triangular patches of the triangular patch on the femoral head. Conversely, the associated triangular patches of a triangular patch on the acetabulum can be determined.

[0065] In the present application, by setting the associated triangular patches, the minimum distance calculation between the femoral head and the acetabulum is reduced to the minimum distance calculation between the associated triangular patches, thereby greatly reducing the corresponding calculation amount.

[0066] In the present application, there are multiple associated triangular patches of the triangular patches on the acetabulum / femoral head, so there are multiple associated triangular patch pairs; the minimum distance between each pair of the associated triangular patches, that is, the minimum distance between each pair of the associated triangular patch pairs.

[0067] Preferably, if there are multiple associated triangular patches of the triangular patches on the acetabulum / femoral head, the radius of the generated sphere is gradually reduced until only one triangular patch intersects with the sphere, and the associated triangular patch is the screened associated triangular patch.

[0068] In this way, by screening, the multiple associated triangular patches of the triangular patches on the acetabulum / femoral head are screened to one, thereby greatly reducing the number of associated triangular patches and the corresponding calculation amount.

[0069] In an embodiment, in the calculation of the minimum distance between each pair of the associated triangular patches, the two triangular patches are respectively located on the femoral head and the acetabulum.

[0070] In the present application, the minimum distance between each pair of the two triangular patches can be calculated by the GJK algorithm (Gilbert-Johnson-Keerthi).

[0071] In the present application, the minimum distance between two associated triangular facets is less than a preset threshold, and the two associated triangular facets are the collision position. All associated triangular facets are traversed to count the triangular facets as the collision position and the collision times of each triangular facet as the statistical data of the collision position in the motion state.

[0072] In an embodiment, after determining the collision position in the motion state by traversing all associated triangular facets, the S305 further includes:

[0073] generating a bone cutting surface according to the bone cutting position;

[0074] generating a corresponding associated region on the corresponding bone cutting surface based on the acetabular center point and the collision position;

[0075] counting the total area of the associated region in the motion state as the collision data.

[0076] In the present application, the intersection of the bone cutting position and the surface of the hip joint model forms a corresponding bone cutting surface.

[0077] In the present application, the center point of the collision position is determined according to the collision position on the acetabulum; a regular figure containing the collision position and having an axis passing through the acetabular center point and the center point of the collision position is generated according to the acetabular center point, the center point of the collision position, and the collision position, and the regular figure has the smallest size, which can be a cylinder or a cuboid; the overlapping part of the regular figure and the bone cutting surface is the associated region.

[0078] In the present application, the associated regions can overlap with each other, and the overlapping part is not repeated.

[0079] In the present application, the total area of the associated region in the motion state is counted as the collision data in the motion state.

[0080] In the present application, the collision data adjusted for the bone cutting position is generated by calculating the corresponding associated region, and then the corresponding bone cutting position is iterated.

[0081] In an embodiment, the S102 includes:

[0082] generating a plurality of conditional constraints according to the three-dimensional model of the hip joint, the conditional constraints including at least joint activity constraints, nerve sensitive region constraints, and stress constraints;

[0083] generating a bone cutting position conforming to the plurality of conditional constraints based on the plurality of conditional constraints, as the initial bone cutting position.

[0084] The stress constraint is a stress distribution of the joint: the position of the acetabulum after the osteotomy should ensure that the stress distribution of the hip joint during weight-bearing is as uniform as possible, and the stress direction is not parallel to the osteotomy surface. Thus, the risk of joint degeneration is reduced by avoiding excessive stress on certain areas of the acetabulum and femoral head.

[0085] In the joint movement constraint, the position of the acetabulum after the osteotomy should ensure that the joint movement range of the patient after the operation is large enough, greater than a preset value, to meet the daily needs.

[0086] In the nerve sensitive area constraint, the osteotomy position should avoid the distribution area of important nerve bundles around the hip joint to avoid complications caused by postoperative nerve damage. According to the three-dimensional model of the hip joint, the nerve sensitive area is circled and noted on the three-dimensional model, and the osteotomy position is constrained to not intersect with the nerve sensitive area.

[0087] In this application, the specific constraint formulas of the joint movement constraint, the nerve sensitive area constraint, and the stress constraint are determined according to the actual situation, which will not be repeated in this application.

[0088] In this application, based on multiple condition constraints, the generated osteotomy position meets multiple condition constraints, and the specific constraint formula of the generated osteotomy position meets multiple condition constraints.

[0089] In an embodiment, the S104 optimizes the adjustment position and the osteotomy position of the acetabulum based on the collision data, including:

[0090] Based on the collision position, a collision position less area is determined;

[0091] Adjust the adjustment position of the acetabulum towards the collision position less area;

[0092] Based on the total area of the associated area, a collision condition constraint is generated;

[0093] According to the adjusted acetabulum adjustment position, the multiple condition constraints and the collision condition constraint, an optimized osteotomy position is generated;

[0094] The collision data is simulated again and the adjustment position and the osteotomy position of the acetabulum are iterated until a preset condition is met.

[0095] In this application, the collision position less area is an area where the femoral head and the acetabulum have sufficient margin; this part of the position is marked and the center point coordinates of this position are determined; adjusting the adjustment position of the acetabulum towards the collision position less area means rotating the center of the bottom surface of the acetabulum towards the center point coordinates.

[0096] Wherein, the acetabulum is a part of the pelvis, in the form of a hemispherical concave structure, the center of the bottom surface of the acetabulum (also known as the acetabular center or the acetabular vertex) usually refers to the deepest point of the medial surface of the acetabulum, that is, the center point of the acetabular depression.

[0097] In this application, the adjustment position of the acetabulum is adjusted towards the less area of the collision position, and the opening direction of the acetabulum, the position and extent of the defect coverage are evaluated at the same time; the opening direction of the acetabulum, the position and extent of the defect coverage are determined to meet the corresponding constraints.

[0098] In this application, based on the total area of the associated area, the overlapping part of the associated area in the generated collision condition constraint is not counted; the generated collision condition constraint, that is, the corresponding osteotomy position is selected to minimize the total area of the corresponding associated area.

[0099] In this application, the specific formula of the collision condition constraint is generated according to the actual situation, which is not limited in this application.

[0100] In this application, according to the adjusted acetabular adjustment position, the plurality of condition constraints and the collision condition constraint, the optimized osteotomy position is generated, the osteotomy position and the osteotomy surface are recalculated based on the adjusted acetabular adjustment position, and the collision condition constraint is added to the plurality of condition constraints, based on the added condition constraint, the osteotomy position that meets the plurality of condition constraints is generated as the optimized osteotomy position.

[0101] The embodiment of the present application provides an acetabular periphery osteotomy planning device based on collision detection, which is used to execute the acetabular periphery osteotomy planning method based on collision detection described in the above content of the present application. The acetabular periphery osteotomy planning device based on collision detection is described in detail as follows.

[0102] As shown in Figure 3 The acetabular periphery osteotomy planning device based on collision detection comprises:

[0103] The model construction module 101 is used to acquire a hip joint medical image and construct a hip joint three-dimensional model;

[0104] The position determination module 102 is used to determine an initial adjustment position and an initial osteotomy position of the acetabulum according to the hip joint three-dimensional model;

[0105] The collision detection module 103 is used to simulate collision data of the femoral head and the acetabulum in different motion states;

[0106] The position optimization module 104 is used to optimize the adjustment position and the osteotomy position of the acetabulum based on the collision data, and determine the best adjustment position and the best osteotomy position of the acetabulum.

[0107] In a specific implementation, the collision detection module 103 is further used to:

[0108] obtaining a current acetabular adjustment position and an osteotomy position; representing the femoral head and the acetabulum as a polygonal mesh composed of a plurality of triangular facets; simulating a motion state of the femoral head; determining a collision position of the femoral head and the acetabulum in the motion state; traversing all motion states of the femoral head to determine the collision position in each motion state as the collision data.

[0109] In one specific implementation, the collision detection module 103 is further configured to:

[0110] determining associated triangular facets of the femoral head and the acetabulum in the motion state; calculating minimum distances between the associated triangular facets in pairs; determining that a collision occurs between two associated triangular facets if the minimum distance between the two associated triangular facets is less than a preset threshold; and traversing all associated triangular facets to determine the collision position in the motion state.

[0111] In one specific implementation, in the calculation of the minimum distances between the associated triangular facets in pairs, the two triangular facets are located on the femoral head and the acetabulum, respectively.

[0112] In one specific implementation, the collision detection module 103 is further configured to:

[0113] generating an osteotomy surface according to the osteotomy position; generating corresponding associated regions on the corresponding osteotomy surface based on the acetabular center point and the collision position; and calculating a total area of the associated regions in the motion state as the collision data.

[0114] In one specific implementation, the position determination module 102 is further configured to:

[0115] generating a plurality of conditional constraints based on the three-dimensional model of the hip joint, the conditional constraints including at least a joint activity constraint, a nerve sensitive region constraint, and a stress constraint; and generating an osteotomy position that meets the plurality of conditional constraints as the initial osteotomy position based on the plurality of conditional constraints.

[0116] In one specific implementation, the position optimization module 104 is further configured to:

[0117] determining a collision position less region based on the collision position; adjusting the adjustment position of the acetabulum towards the collision position less region; generating a collision conditional constraint based on the total area of the associated regions; generating an optimized osteotomy position based on the adjusted acetabular adjustment position, the plurality of conditional constraints, and the collision conditional constraint; and re-simulating the collision data and iterating the adjustment position of the acetabulum and the osteotomy position until a preset condition is met.

[0118] The device for planning a periacetabular osteotomy based on collision detection provided by the above-mentioned embodiments of the present application has a corresponding relationship with the method for planning a periacetabular osteotomy based on collision detection provided by the embodiments of the present application, and thus the specific content in the device has a corresponding relationship with the method for planning a periacetabular osteotomy, and the specific content can be referred to the record in the method for planning a periacetabular osteotomy, which will not be described here again.

[0119] The device for planning a periacetabular osteotomy based on collision detection provided by the above-mentioned embodiments of the present application and the method for planning a periacetabular osteotomy based on collision detection provided by the embodiments of the present application are based on the same inventive concept, and have the same beneficial effects as the method adopted, run or implemented by the application program stored therein.

[0120] The internal functions and structures of the device for planning a periacetabular osteotomy based on collision detection are described above, as shown in the Figure 4 In practice, the device for planning a periacetabular osteotomy based on collision detection can be realized as an electronic device, which includes a memory 301 and a processor 303.

[0121] The memory 301 can be configured to store programs.

[0122] In addition, the memory 301 can also be configured to store other various data to support the operation on the electronic device. Examples of these data include instructions for any application or method operating on the electronic device, contact data, phonebook data, messages, pictures, videos, etc.

[0123] The memory 301 can be realized by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0124] The processor 303 is coupled to the memory 301 and is used to execute the programs in the memory 301 for:

[0125] obtaining a medical image of a hip joint and constructing a three-dimensional model of the hip joint;

[0126] determining an initial adjustment position and an initial osteotomy position of the acetabulum according to the three-dimensional model of the hip joint;

[0127] simulating collision data of the femoral head and the acetabulum in different motion states;

[0128] optimizing the adjustment position and the osteotomy position of the acetabulum based on the collision data to determine an optimal adjustment position and an optimal osteotomy position of the acetabulum.

[0129] In an embodiment, the processor 303 is further configured to:

[0130] acquire a current acetabular adjustment position and an osteotomy position; represent the femoral head and the acetabulum as a polygonal mesh composed of a plurality of triangular facets; simulate a motion state of the femoral head; determine a collision position of the femoral head and the acetabulum in the motion state; iterate through all motion states of the femoral head to determine the collision position in each motion state as the collision data.

[0131] In an embodiment, the processor 303 is further configured to:

[0132] determine associated triangular facets of the femoral head and the acetabulum in the motion state; calculate minimum distances between the associated triangular facets two by two; determine that two associated triangular facets collide if the minimum distance between the two associated triangular facets is less than a preset threshold; iterate through all associated triangular facets to determine the collision position in the motion state;

[0133] In an embodiment, in the calculation of the minimum distances between the associated triangular facets two by two, the two triangular facets are located on the femoral head and the acetabulum respectively.

[0134] In an embodiment, the processor 303 is further configured to:

[0135] generate an osteotomy surface according to the osteotomy position; generate corresponding associated regions on the corresponding osteotomy surface based on the center point of the acetabulum and the collision position; and calculate a total area of the associated regions in the motion state as the collision data.

[0136] In an embodiment, the processor 303 is further configured to:

[0137] generate a plurality of conditional constraints according to the three-dimensional model of the hip joint, the conditional constraints including at least a joint activity constraint, a nerve sensitive region constraint, and a stress constraint; and generate an osteotomy position that meets the plurality of conditional constraints as the initial osteotomy position based on the plurality of conditional constraints.

[0138] In an embodiment, the processor 303 is further configured to:

[0139] determine a region with less collision positions based on the collision position; adjust the adjustment position of the acetabulum towards the region with less collision positions; generate a collision conditional constraint based on the total area of the associated regions; generate an optimized osteotomy position according to the adjusted acetabular adjustment position, the plurality of conditional constraints, and the collision conditional constraint; and re-simulate the collision data and iterate the adjustment position of the acetabulum and the osteotomy position until a preset condition is met.

[0140] In the present application, the processor is also specifically configured to execute all processes and steps of the above-mentioned hip around osteotomy planning method based on collision detection, and specific contents can be referred to the records in the hip around osteotomy planning method, which will not be described here again in the present application.

[0141] In the present application, Figure 4 Only some components are shown in the present application, and it does not mean that the electronic device only includes Figure 4 The components shown.

[0142] The electronic device provided by the embodiment of the present application has the same beneficial effects as the method adopted, run or implemented by the application program stored therein, based on the same inventive concept as the hip around osteotomy planning method based on collision detection provided by the embodiment of the present application.

[0143] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-readable storage media (including but not limited to disk memory, CD-ROM, optical memory, etc.) containing computer usable program code.

[0144] The present application is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, as well as the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the computer or other programmable data processing device produce a device that implements the functions specified in the flowcharts and / or block diagrams. Figure 1 The functions specified in one or more flows and / or blocks Figure 1 The functions specified in one or more flows and / or blocks

[0145] These computer program instructions can also be stored in a computer readable memory capable of guiding a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer readable memory produce a product including instruction means, which implements the functions specified in the flowcharts and / or block diagrams. Figure 1 The functions specified in one or more flows and / or blocks Figure 1 The functions specified in one or more flows and / or blocks

[0146] These computer program instructions can also be loaded into a computer or other programmable data processing devices, so that a series of operational steps are performed on the computer or other programmable devices to generate a computer-implemented process, so that the instructions executed by the computer or other programmable devices provide the function implemented in the flow Figure 1 one or more flows and / or blocks Figure 1 one or more blocks or steps of the function specified in the flow

[0147] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0148] The memory can include non-persistent memory in the form of random access memory (RAM) and / or non-volatile memory, such as read only memory (ROM) or flash memory (Flash RAM). The memory is an example of computer-readable media.

[0149] The application also provides a computer-readable storage medium corresponding to the collision detection-based acetabular bone cutting planning method provided by the foregoing embodiments, and a computer program (i.e., a program product) is stored on the computer-readable storage medium. When the computer program is executed by a processor, the collision detection-based acetabular bone cutting planning method provided by any of the foregoing embodiments is executed.

[0150] Computer-readable media includes permanent and non-permanent, removable and non-removable media, which can be implemented by any method or technology to store information. The 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 disc read only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible by a computing device. According to the definition herein, computer-readable media does not include transitory media such as modulated data signals and carriers.

[0151] The computer-readable storage medium provided by the above embodiments of the application has the same beneficial effects as the method adopted, executed or implemented by the application program stored therein, based on the same inventive concept as the collision detection-based acetabular bone cutting planning method provided by the embodiments of the application.

[0152] It should be noted that in the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the application can be practiced without these specific details. In some instances, well-known structures and techniques have not been shown in detail in order not to obscure the understanding of this description.

[0153] It is also important to note that the term "comprising" or "including" or any other variation thereof is intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by "comprises... a" does not, without more constraints, exclude the existence of additional identical elements in the process, method, article, or apparatus that comprises the recited element.

[0154] The foregoing is merely illustrative of the principles of this application and various modifications can be made by persons skilled in the art. The present application is not intended to be limited to the embodiments shown, but is to be accorded the full scope consistent with the principles of the present application, including functional, structural, and positional equivalents that are within the scope of this description.

Claims

1. A method for planning periacetabular osteotomy based on collision detection, characterized in that: include: Acquire medical images of the hip joint and construct a three-dimensional model of the hip joint; According to the three-dimensional model of the hip joint, determine the initial adjustment position of the acetabulum and the initial osteotomy position; Simulate the collision data of the femoral head and acetabulum in different motion states; Optimizing the adjustment position and osteotomy position of the acetabulum based on the collision data to determine the optimal adjustment position and optimal osteotomy position of the acetabulum; The simulated collision data between the femoral head and acetabulum in different motion states include: Obtain the current acetabulum adjustment position and osteotomy position; The femoral head and acetabulum are represented as polygonal meshes, wherein the polygonal meshes are composed of a plurality of triangular facets; Simulate the motion state of the femoral head; Determine the collision position between the femoral head and acetabulum in this motion state; Traversing all motion states of the femoral head and determining the collision position in each motion state as the collision data; Determining the collision position of the femoral head and the acetabulum in the motion state includes: Determine the associated triangular surface between the femoral head and acetabulum in this motion state; Calculate the minimum distance between any two associated triangles; If the minimum distance between two associated triangles is less than a preset threshold, it is determined that the two associated triangles collide; Traverse all associated triangles to determine the collision position under the motion state; Generate osteotomy surface according to osteotomy position; Based on the acetabulum center point and the collision position, a corresponding associated area is generated on the corresponding osteotomy surface; The total area of ​​the associated regions in the motion state is counted as the collision data.

2. The method for planning periacetabular osteotomy based on collision detection according to claim 1, wherein: In the calculation of the minimum distance between two associated triangular facets, the two triangular facets are located on the femoral head and the acetabulum respectively.

3. The acetabular periarthritis osteotomy planning method based on collision detection according to claim 1, characterized in that: Determining the initial osteotomy position of the acetabulum based on the three-dimensional model of the hip joint includes: generating a plurality of conditional constraints according to the three-dimensional model of the hip joint, wherein the conditional constraints at least include a joint movement constraint, a nerve sensitive area constraint, and a stress constraint; Based on the multiple conditional constraints, an osteotomy position that meets the multiple conditional constraints is generated as the initial osteotomy position.

4. The method for planning periacetabular osteotomy based on collision detection according to claim 3, wherein: The step of optimizing the adjustment position and osteotomy position of the acetabulum based on the collision data includes: Based on the collision locations, determining an area with fewer collision locations; Adjusting the adjustment position of the acetabulum toward the area with less collision; Generate collision condition constraints based on the sum of the areas of the associated regions; generating an optimized osteotomy position according to the adjusted acetabulum adjustment position, the multiple condition constraints, and the collision condition constraints; The collision data is re-simulated and the adjustment position and osteotomy position of the acetabulum are iterated until the preset conditions are met.

5. A periacetabular osteotomy planning device based on collision detection, characterized in that: include: A model building module, which is used to obtain medical images of the hip joint and build a three-dimensional model of the hip joint; A position determination module, which is used to determine the initial adjustment position and initial osteotomy position of the acetabulum based on the three-dimensional model of the hip joint; Collision detection module, which is used to simulate the collision data of the femoral head and acetabulum in different motion states; a position optimization module, which is used to optimize the adjustment position and osteotomy position of the acetabulum based on the collision data, and determine the optimal adjustment position and optimal osteotomy position of the acetabulum; The simulated collision data between the femoral head and the acetabulum in different motion states include: Obtain the current acetabulum adjustment position and osteotomy position; The femoral head and acetabulum are represented as polygonal meshes, wherein the polygonal meshes are composed of a plurality of triangular facets; Simulate the motion state of the femoral head; Determine the collision position between the femoral head and acetabulum in this motion state; Traversing all motion states of the femoral head and determining the collision position in each motion state as the collision data; Determining the collision position of the femoral head and the acetabulum in the motion state includes: Determine the associated triangular surface between the femoral head and acetabulum in this motion state; Calculate the minimum distance between any two associated triangles; If the minimum distance between two associated triangles is less than a preset threshold, it is determined that the two associated triangles collide; Traverse all associated triangles to determine the collision position under the motion state; Generate osteotomy surface according to osteotomy position; Based on the acetabulum center point and the collision position, a corresponding associated area is generated on the corresponding osteotomy surface; The total area of ​​the associated regions in the motion state is counted as the collision data.

6. An electronic device, characterized in that: include: memory and processor; The memory is used to store programs; The processor, coupled to the memory, is configured to execute the program to: Acquire medical images of the hip joint and construct a three-dimensional model of the hip joint; According to the three-dimensional model of the hip joint, determine the initial adjustment position of the acetabulum and the initial osteotomy position; Simulate the collision data of the femoral head and acetabulum in different motion states; Optimizing the adjustment position and osteotomy position of the acetabulum based on the collision data to determine the optimal adjustment position and optimal osteotomy position of the acetabulum; The simulated collision data between the femoral head and the acetabulum in different motion states include: Obtain the current acetabulum adjustment position and osteotomy position; The femoral head and acetabulum are represented as polygonal meshes, wherein the polygonal meshes are composed of a plurality of triangular facets; Simulate the motion state of the femoral head; Determine the collision position between the femoral head and acetabulum in this motion state; Traversing all motion states of the femoral head and determining the collision position in each motion state as the collision data; Determining the collision position of the femoral head and the acetabulum in the motion state includes: Determine the associated triangular surface between the femoral head and acetabulum in this motion state; Calculate the minimum distance between any two associated triangles; If the minimum distance between two associated triangles is less than a preset threshold, it is determined that the two associated triangles collide; Traverse all associated triangles to determine the collision position under the motion state; Generate osteotomy surface according to osteotomy position; Based on the acetabulum center point and the collision position, a corresponding associated area is generated on the corresponding osteotomy surface; The total area of ​​the associated regions in the motion state is counted as the collision data.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the acetabular periarthritis osteotomy planning method based on collision detection according to any one of claims 1 to 4.

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