Acetabular fossa thickness determination method and device and surgical robot system

Abstract

The invention relates to an acetabular fossa thickness determination method and device and a surgical robot system. The method comprises the following steps: acquiring a region-of-interest image; the region-of-interest image comprises an acetabular fossa structure and an acetabular cup structure; determining acetabular fossa thickness corresponding to each second surface voxel of the acetabular cup structure according to the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure; and determining the target thickness of the acetabular fossa structure according to the acetabular fossa thickness corresponding to each second surface voxel. By adopting the method, the estimation accuracy of the thickness of the acetabular fossa can be improved.

Description

Technical Field

[0001] The present application relates to the field of image processing technology, and in particular to a method and device for determining acetabular thickness and a surgical robot system. Background Art

[0002] With the development of image processing technology, more and more doctors can make preoperative planning for the location of surgical auxiliary structures based on preoperative medical images, and estimate the relevant parameters of the tissue structure where the surgical auxiliary structures are located based on the planning results, so as to determine whether the planning results are reasonable. For example, in hip replacement surgery, it is necessary to plan the position and angle of the acetabular cup based on preoperative CT images, and further estimate the thickness of the acetabular fossa where the acetabular cup is located based on the planning results, and then determine whether the position and angle of the acetabular cup obtained by the above plan are reasonable based on the thickness.

[0003] Currently, the position and angle of the acetabular cup are planned by the doctor estimating the thickness of the acetabular socket where the acetabular cup is located.

[0004] However, the above-mentioned method for estimating the thickness of the acetabular socket has the problem of inaccuracy. Summary of the invention

[0005] Based on this, it is necessary to provide a method, device and surgical robot system for determining the thickness of the acetabulum, which can improve the estimation accuracy of the thickness of the acetabulum, in order to solve the above technical problems.

[0006] In a first aspect, the present application provides a method for determining acetabular thickness, comprising:

[0007] Acquire an image of a region of interest; the image of the region of interest includes an acetabular fossa structure and an acetabular cup structure;

[0008] Determine the acetabular fossa thickness corresponding to each second surface voxel of the acetabular cup structure according to the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure;

[0009] The target thickness of the acetabular structure is determined according to the acetabular thickness corresponding to each of the second surface voxels.

[0010] In one embodiment, acquiring the image of the region of interest includes:

[0011] Acquire a medical image including the acetabulum structure, and determine a center point and a first radius of the acetabulum structure according to the medical image;

[0012] obtaining a model including the acetabular cup structure;

[0013] The region of interest image is constructed according to the center point and the first radius of the acetabular structure and the model.

[0014] In one embodiment, determining the acetabular fossa thickness corresponding to each second surface voxel of the acetabular cup structure according to the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure comprises:

[0015] Determining a target search range according to the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure;

[0016] The acetabular fossa thickness corresponding to each second surface voxel of the acetabular cup structure is determined within the target search range.

[0017] In one embodiment, determining the target search range according to the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure includes:

[0018] Determine whether the position information of each of the first surface voxels meets a preset position condition, and use the position information of the first surface voxels that meets the preset position condition as the search target position information;

[0019] The target search range is determined according to the position information of the second surface voxels that match the search target position information.

[0020] In one embodiment, the position information includes the distance between the first surface voxel and the center point of the acetabular fossa structure and the angle between the line segment between the first surface voxel and the center point of the acetabular fossa structure and the axis of the acetabular fossa structure, and determining whether the position information of each first surface voxel meets the preset position condition includes:

[0021] determining whether an angle of the first surface voxel is less than a preset angle threshold, and determining whether a distance of the first surface voxel is less than a preset distance threshold;

[0022] If the angle of the first surface voxel is smaller than a preset angle threshold, and the distance of the first surface voxel is smaller than a preset distance threshold, it is determined that the position information of the first surface voxel meets the preset position condition.

[0023] In one embodiment, the method further comprises:

[0024] According to the distribution of each first surface voxel on the acetabular structure, an axial direction vector of the acetabular structure is obtained;

[0025] Acquire a center vector from each first surface voxel on the acetabular structure to a center point of the acetabular structure;

[0026] The angle between the axis direction vector and each of the center vectors is determined as the angle of each of the first surface voxels.

[0027] In one embodiment, obtaining the axial direction vector of the acetabular structure according to the distribution of each first surface voxel on the acetabular structure includes:

[0028] Obtaining the coordinate position of each voxel of the first surface;

[0029] Performing principal component analysis on the coordinate position of each voxel on the first surface to obtain characteristic values ​​of each voxel on the first surface in three coordinate directions, wherein the three coordinate directions are orthogonal to each other;

[0030] The axis direction vector is determined according to the smallest eigenvalue among the three eigenvalues ​​corresponding to each of the first surface voxels.

[0031] In one embodiment, the method further comprises:

[0032] Determine the distance between each voxel on the acetabular structure in the region of interest image and the center point of the acetabular structure;

[0033] Acquire a second radius of the acetabulum structure;

[0034] Determine whether the difference between the distance and the second radius is less than or equal to a preset difference threshold; if so, use the voxel corresponding to the distance as the first surface voxel of the acetabulum structure.

[0035] In one embodiment, determining the acetabular fossa thickness corresponding to each second surface voxel of the acetabular cup structure within the target search range includes:

[0036] Determining the ray direction of each second surface voxel of the acetabular cup structure within the target search range;

[0037] The distance between the outer surface of the acetabular cup structure and the dorsal side of the hip bone corresponding to the acetabular socket structure in each of the ray directions is determined, and each of the distances is determined as the acetabular socket thickness corresponding to each of the second surface voxels.

[0038] In one embodiment, determining the target thickness of the acetabular structure according to the acetabular thickness corresponding to each voxel of the second surface includes:

[0039] The acetabular thickness corresponding to the smallest second surface voxel is determined as the target thickness.

[0040] In a second aspect, the present application further provides a device for determining acetabular thickness, comprising:

[0041] An area of ​​interest image acquisition module, used to acquire an area of ​​interest image; the area of ​​interest image includes an acetabular fossa structure and an acetabular cup structure;

[0042] An acetabular fossa thickness determination module, for determining the acetabular fossa thickness corresponding to each second surface voxel of the acetabular fossa structure according to the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure;

[0043] The target thickness determination module is used to determine the target thickness of the acetabular structure according to the acetabular thickness corresponding to each of the second surface voxels.

[0044] In a third aspect, the present application further provides a surgical robot system, characterized in that it comprises a planning system, wherein the planning system comprises a device for determining the thickness of the acetabulum as described in the second aspect above.

[0045] The above-mentioned method, device and surgical robot system for determining the thickness of the acetabular fossa obtain an image of the region of interest; the image of the region of interest includes the acetabular fossa structure and the acetabular cup structure; the acetabular fossa thickness corresponding to each second surface voxel of the acetabular cup structure is determined according to the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure; the target thickness of the acetabular fossa structure is determined according to the acetabular fossa thickness corresponding to each second surface voxel. The present application can obtain an image of the region of interest, that is, it can obtain a more accurate acetabular fossa structure and acetabular cup structure. Thus, it is possible to determine the acetabular fossa thickness corresponding to each second surface voxel of the acetabular cup structure according to the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure, that is, it is possible to more accurately determine the acetabular fossa thickness at the position of each first surface voxel corresponding to each second surface voxel within the target search range. Furthermore, it is possible to more accurately determine the target thickness of the acetabular fossa structure according to the more accurate acetabular fossa thickness corresponding to each second surface voxel. Therefore, the method for determining the acetabular fossa thickness of the present application can improve the estimation accuracy of the acetabular fossa thickness. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0047] Figure 1A schematic diagram of the structure of an acetabular cup and an acetabular socket in one embodiment;

[0048] Figure 2 is an application environment diagram of a method for determining acetabular fossa thickness in one embodiment;

[0049] Figure 3 is a schematic flow chart of a method for determining acetabular fossa thickness in one embodiment;

[0050] Figure 4 A schematic diagram of a flow chart of a target search range determination step in one embodiment;

[0051] Figure 5 A schematic flow chart of a step of determining an angle of a first surface voxel in another embodiment;

[0052] Figure 6 is a schematic diagram of the position of the axial direction vector of the acetabulum structure in one embodiment;

[0053] Figure 7 It is a flowchart of a first surface voxel determination step in another embodiment;

[0054] Figure 8 A schematic diagram of the position of the ray direction in one embodiment;

[0055] Fig. 9 is a schematic flow chart of a method for determining acetabular fossa thickness in an optional embodiment;

[0056] Fig.10 is a structural block diagram of a device for determining acetabular thickness in one embodiment;

[0057] Fig.11 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0059] With the development of image processing technology, more and more doctors can plan the location of surgical auxiliary structures based on preoperative medical images, and estimate the relevant parameters of the tissue structure where the surgical auxiliary structures are located based on the planning results, so as to determine whether the planning results are reasonable. For example, in hip replacement surgery, it is necessary to plan the position and angle of the acetabular cup based on preoperative CT images, and further estimate the thickness of the acetabular fossa where the acetabular cup is located based on the planning results, and then determine whether the position and angle of the acetabular cup obtained by the above plan are reasonable based on the thickness. Figure 1As shown, Figure 1 FIG. 1 is a schematic diagram of the structure of an acetabular cup and an acetabular fossa in one embodiment. Figure 1 The white area in the hemispherical shape allows the acetabular cup to be installed on the inner surface of the acetabular socket.

[0060] Currently, in the process of planning the position and angle of the acetabular cup, doctors estimate the thickness of the acetabular socket where the acetabular cup is located based on naked eyes.

[0061] However, the above-mentioned method for estimating the thickness of the acetabular socket has the problem of inaccuracy.

[0062] The method for determining the thickness of the acetabulum provided in the embodiment of the present application can be applied to Figure 2 In the application environment shown. Among them, the terminal 202 communicates with the server 204 through the network. The data storage system can store the data that the server 204 needs to process. The data storage system can be integrated on the server 204, or it can be placed on the cloud or other network servers. The server 204 extracts the regional image of the medical image to be processed to obtain the image of the region of interest; the image of the region of interest includes the acetabular fossa structure and the acetabular cup structure; the server 204 determines the target search range according to the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure; the server 204 determines the acetabular fossa thickness corresponding to each second surface voxel of the acetabular cup structure within the target search range; according to the acetabular fossa thickness corresponding to each second surface voxel, the target thickness of the acetabular fossa structure is determined. Among them, the terminal 202 can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, Internet of Things devices and portable wearable devices, and the Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. The portable wearable device can be a smart watch, a smart bracelet, a head-mounted device, etc. The server 204 may be implemented as an independent server or a server cluster consisting of multiple servers.

[0063] In an exemplary embodiment, Figure 3 As shown, a method for determining the thickness of the acetabulum is provided, and the method is applied to Figure 2 The server 204 in the example is used as an example to illustrate, including the following steps 302 to 306. Among them:

[0064] Step 302, obtaining an image of a region of interest; the image of the region of interest includes the acetabular fossa structure and the acetabular cup structure.

[0065] Wherein, the medical image to be processed refers to the patient's whole body or a CT image including the pelvis and part of the femur, and the medical image to be processed includes the acetabular fossa structure. The region of interest image refers to the regional image including the acetabular fossa structure and the acetabular cup structure in the medical image to be processed. Exemplarily, the server 204 can obtain the medical image to be processed from the terminal 202 or the database in advance. Thus, optionally, the server 204 can input the medical image to be processed into the trained image segmentation model to extract the regional image, and obtain the region of interest image corresponding to the medical image to be processed. Alternatively, the server 204 can also use a preset region extraction algorithm to determine the relevant parameters of the region of interest corresponding to the medical image to be processed, and determine the region of interest image according to the relevant parameters of the region of interest. Wherein, the preset region extraction algorithm may include but is not limited to the regional parameter extraction method such as the Hough circle detection algorithm. Of course, the specific method for extracting the region of interest image is not limited in the embodiment of the present application.

[0066] Step 304 : Determine the acetabular fossa thickness corresponding to each second surface voxel of the acetabular cup structure according to the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure.

[0067] Exemplarily, since the region of interest image includes the acetabular fossa structure and the acetabular cup structure, the server 204 can determine the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure from the region of interest image. Thus, optionally, the server 204 can directly determine the acetabular fossa thickness corresponding to each second surface voxel on the acetabular cup structure according to the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure. Alternatively, the server 204 can also determine the target search range according to the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure, thereby determining the acetabular fossa thickness corresponding to each second surface voxel in the acetabular cup structure within the target search range. Wherein, the acetabular fossa thickness refers to the distance between the two surfaces of the acetabular fossa structure corresponding to the position of the first surface voxel.

[0068] Step 306: Determine the target thickness of the acetabular structure according to the acetabular thickness corresponding to each second surface voxel.

[0069] Optionally, the server 204 may randomly select any acetabular fossa thickness from the acetabular fossa thicknesses at the locations of the first surface voxels corresponding to the second surface voxels within the target search range as the target thickness of the acetabular fossa structure. Alternatively, the server 204 may also determine the acetabular fossa thickness corresponding to the smallest second surface voxel from the acetabular fossa thicknesses at the locations of the first surface voxels corresponding to the second surface voxels within the target search range, and determine the acetabular fossa thickness corresponding to the smallest second surface voxel as the target thickness. Of course, the embodiment of the present application does not limit the specific method for determining the target thickness of the acetabular fossa structure.

[0070] In the above-mentioned method for determining the thickness of the acetabular fossa, an image of the region of interest can be obtained, that is, a more accurate acetabular fossa structure and acetabular cup structure can be obtained. Thus, the acetabular fossa thickness corresponding to each second surface voxel of the acetabular cup structure can be determined based on the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure, that is, the acetabular fossa thickness at the position of each first surface voxel corresponding to each second surface voxel within the target search range can be more accurately determined. Furthermore, based on the more accurate acetabular fossa thickness corresponding to each second surface voxel, the target thickness of the acetabular fossa structure can be more accurately determined. Therefore, the method for determining the thickness of the acetabular fossa of the present application can improve the estimation accuracy of the thickness of the acetabular fossa.

[0071] In the above embodiment, it involves obtaining an image of a region of interest, and the specific method thereof is introduced below. In an exemplary embodiment, S302 includes:

[0072] A medical image including the acetabular structure is acquired, and a center point and a first radius of the acetabular structure are determined according to the medical image.

[0073] A model including the acetabular cup structure is obtained.

[0074] An image of a region of interest is constructed according to the center point and the first radius of the acetabular structure and the model.

[0075] Optionally, since the physiological structure of the acetabular fossa structure is an approximate hemispherical structure, the server 204 can pre-acquire a medical image including the acetabular fossa structure (i.e., the medical image to be processed as described above), and obtain the gradient information of the medical image including the acetabular fossa structure, and then use the Hough circle detection algorithm to perform Hough circle detection on the gradient information of the medical image to obtain the center point of the acetabular fossa structure and the first radius of the acetabular fossa structure. In addition, the server 204 can also pre-acquire a model including the acetabular cup structure. Thus, the server 204 can select a suitable margin or range based on the center point of the acetabular fossa structure, the first radius of the acetabular fossa structure, and the model including the acetabular cup structure to construct an image of the region of interest. Among them, the first radius of the acetabular fossa structure refers to the radius of the acetabular fossa structure obtained by performing Hough circle detection using the Hough circle detection algorithm.

[0076] In this embodiment, a medical image including the acetabular fossa structure is obtained, and Hough circle detection is performed based on the medical image to determine a relatively accurate center point and first radius of the acetabular fossa structure; a model including the acetabular cup structure is obtained. Thus, a relatively accurate region of interest image can be constructed based on the relatively accurate center point and first radius of the acetabular fossa structure and the model.

[0077] In the above embodiment, it involves determining the acetabular fossa thickness corresponding to each second surface voxel of the acetabular cup structure according to the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure, and the specific method is introduced below. In an exemplary embodiment, S304 includes:

[0078] The target search range is determined according to the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure.

[0079] Optionally, the server 204 can directly determine the target search range based on the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure, and the positional relationship between each first surface voxel on the acetabular fossa structure and each second surface voxel on the acetabular cup structure. Alternatively, the server 204 can also first determine the search range corresponding to the acetabular fossa structure based on the position information of each first surface voxel on the acetabular fossa structure; and then determine the target search range based on the search range corresponding to the acetabular fossa structure and the positional relationship between the position information of each first surface voxel on the acetabular fossa structure and the positional relationship between the position information of each second surface voxel on the acetabular cup structure. Of course, the embodiment of the present application does not limit the specific method for determining the target search range. Among them, the target search range refers to the range constituted by each position where the acetabular fossa thickness needs to be estimated.

[0080] In the target search range, the acetabular fossa thickness corresponding to each second surface voxel of the acetabular cup structure is determined.

[0081] Optionally, the server 204 can determine each second surface voxel within the target search range from each second surface voxel of the acetabular cup structure, so that, for each second surface voxel in the acetabular cup structure within the target search range, the server 204 can determine the first surface voxel on the acetabular fossa structure corresponding to the second surface voxel within the target search range, and further, the server 204 can determine the acetabular fossa thickness at the location of each first surface voxel corresponding to each second surface voxel within the target search range.

[0082] In this embodiment, a more accurate target search range can be determined based on the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure. Thus, within the target search range, the acetabular fossa thickness corresponding to each second surface voxel of the acetabular cup structure can be accurately and quickly determined.

[0083] In the above embodiment, it is involved to determine the target search range according to the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure, and the specific method thereof is introduced below. In an exemplary embodiment, as Figure 4 As shown, according to the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure, the target search range is determined, including:

[0084] Step 402 : determining whether the position information of each first surface voxel satisfies a preset position condition, and taking the position information of the first surface voxel that satisfies the preset position condition as the search target position information.

[0085] Optionally, the server 204 can determine whether the position information of each first surface voxel on the acetabular structure meets the preset position condition. If the position information of the first surface voxel meets the preset position condition, the server 204 can use the position information of the first surface voxel that meets the preset position condition as the search target position information. Among them, the preset position condition can be set according to the actual acetabular structure, and the embodiment of the present application is not limited to this. The search target position information refers to the position information corresponding to the position where the acetabular thickness needs to be estimated. Exemplarily, assuming that the preset position condition is that the first surface voxel is within a preset interval of the acetabular structure, and the preset interval is set based on the acetabular structure, then, if the position information of the first surface voxel on the acetabular structure is within the preset interval on the acetabular structure, it means that the position information of the first surface voxel meets the preset position condition. At this time, the server 204 can use the position information of the first surface voxel within the preset interval of the acetabular structure as the search target position information.

[0086] Step 404: determine the target search range according to the position information of the second surface voxels that match the search target position information.

[0087] Among them, the first surface voxel refers to the voxel on the first surface of the acetabular structure, and the first surface is the inner surface of the acetabular structure; the second surface voxel refers to the voxel on the second surface of the acetabular cup structure, and the second surface is the outer surface of the acetabular cup structure; and the first surface of the acetabular structure and the second surface of the acetabular cup structure are adjacent surfaces. Based on this, exemplarily, according to the position information of the first surface voxel that meets the preset position condition (i.e., the search target position information), the server 204 can determine the position information of the second surface voxel that matches / corresponds to the search target position information. Thus, the server 204 can determine the target search range on the acetabular cup structure according to the position information of the second surface voxel that matches the search target position information.

[0088] In this embodiment, by determining whether the position information of each first surface voxel meets the preset position condition, the position information of each first surface voxel that meets the preset position condition can be determined more accurately, and the position information of the first surface voxel that meets the preset position condition is used as the search target position information, so that more accurate search target position information can be determined. Thus, according to the position information of the second surface voxel that matches the more accurate search target position information, the target search range can be determined more accurately.

[0089] In the above embodiment, it is involved to determine whether the position information of each first surface voxel meets the preset position condition, and the specific method is introduced below. In an exemplary embodiment, the position information includes the distance between the first surface voxel and the center point of the acetabular structure and the angle between the line segment between the first surface voxel and the center point of the acetabular structure and the axis of the acetabular structure, and S402 includes:

[0090] It is determined whether the angle of the first surface voxel is less than a preset angle threshold, and it is determined whether the distance of the first surface voxel is less than a preset distance threshold.

[0091] If the angle of the first surface voxel is less than the preset angle threshold, and the distance of the first surface voxel is less than the preset distance threshold, it is determined that the position information of the first surface voxel meets the preset position condition.

[0092] Among them, the position information of the first surface voxel includes the distance of the first surface voxel and the angle of the first surface voxel. The distance of the first surface voxel represents the distance between the first surface voxel and the center point of the acetabular structure. The angle of the first surface voxel represents the angle between the line segment between the first surface voxel and the center point of the acetabular structure and the axis of the acetabular structure, that is, the angle of the first surface voxel represents the angle between the axis direction vector and each center vector. The axis direction vector is the vector corresponding to the axis of the acetabular structure, and the center vector is the vector formed by the line segment between the first surface voxel and the center point of the acetabular structure. The process of determining the axis direction vector, each center vector, and the angle of the first surface voxel can refer to the following embodiments. In this embodiment, exemplarily, the preset angle threshold can be 90 degrees, and the preset distance threshold can be greater than zero and less than 4 mm. Of course, the preset angle threshold and the preset distance threshold can be set according to the actual acetabular structure, and the embodiments of the present application are not limited to this.

[0093] It should be noted that, based on the observation of the acetabular structure and the pelvic structure, it can be found that the position requirement for the minimum thickness of the acetabular structure generally exists in a region within a preset angle threshold range with the axial direction vector of the acetabular structure, and the preset angle threshold is generally 90 degrees. Therefore, when determining the thickness of the acetabular structure, it is not necessary to traverse all voxels on the second surface of the acetabular cup structure, but the angle search range can be reduced based on the position requirement for the minimum thickness of the acetabular structure, thereby greatly improving the efficiency of determining the thickness of the acetabular structure.

[0094] Optionally, for each first surface voxel, the server 204 may obtain the angle of the first surface voxel and the distance of the first surface voxel, thereby determining whether the angle of the first surface voxel is less than a preset angle threshold, and determining whether the distance of the first surface voxel is less than a preset distance threshold. If the angle of the first surface voxel is less than the preset angle threshold, and the distance of the first surface voxel is less than the preset distance threshold, the server 204 may determine that the position information of the first surface voxel meets the preset position condition.

[0095] In this embodiment, it is determined whether the angle of the first surface voxel is less than the preset angle threshold, and whether the distance of the first surface voxel is less than the preset distance threshold. If the angle of the first surface voxel is less than the preset angle threshold, and the distance of the first surface voxel is less than the preset distance threshold, it is determined that the position information of the first surface voxel meets the preset position condition. It is possible to comprehensively determine each first surface voxel that meets the preset position condition based on the two dimensions of the distance of the first surface voxel and the angle of the first surface voxel, so that the position information of each first surface voxel that meets the preset position condition can be determined more accurately.

[0096] In the above embodiment, it is involved to determine whether the angle of the first surface voxel is less than the preset angle threshold. Another implementation method is introduced below. In an exemplary embodiment, Figure 5 As shown, the method for determining the thickness of the acetabulum further includes:

[0097] Step 502: Obtain the axis direction vector of the acetabular structure according to the distribution of each first surface voxel on the acetabular structure.

[0098] Optionally, the server 204 may obtain the axial direction vector of the acetabular structure based on the distribution of each first surface voxel on the acetabular structure. Exemplarily, the server 204 may perform principal component analysis on each first surface voxel on the acetabular structure to obtain the axial direction vector of the acetabular structure. Principal component analysis refers to the process of converting multiple indicators into a few comprehensive indicators using the idea of ​​dimensionality reduction. Exemplarily, Figure 6 As shown, Figure 6 FIG. 1 is a schematic diagram of the position of the axial direction vector of the acetabular fossa structure in one embodiment. The axial direction vector of the acetabular fossa structure is located at Figure 6 At the location of the black line segment in , the direction of the axis direction vector of the acetabular structure refers to the direction from the center point of the acetabular structure to the point on the first surface of the acetabular structure.

[0099] In one optional embodiment, step 502 includes:

[0100] Get the coordinate position of each first surface voxel.

[0101] The coordinate position of each first surface voxel is subjected to principal component analysis to obtain the eigenvalues ​​of each first surface voxel in three coordinate directions, where the three coordinate directions are orthogonal to each other.

[0102] The axis direction vector is determined according to the smallest eigenvalue among the three eigenvalues ​​corresponding to each first surface voxel.

[0103] Optionally, the server 204 can obtain the coordinate position of each first surface voxel on the acetabular structure. In the present embodiment, the coordinate position of the first surface voxel refers to the three-dimensional coordinate position of the first surface voxel. Thus, the server 204 can perform principal component analysis on the coordinate position of each first surface voxel to obtain the eigenvalues ​​of each first surface voxel in the three coordinate directions, and three eigenvectors corresponding to the eigenvalues ​​in the three coordinate directions. Furthermore, the server 204 can determine the minimum eigenvalue from the eigenvalues ​​of each first surface voxel in the three coordinate directions, and determine the eigenvector corresponding to the minimum eigenvalue as the axial direction vector of the acetabular structure. Among them, the three coordinate directions are orthogonal to each other.

[0104] Step 504: Obtain a center vector from each first surface voxel on the acetabular structure to the center point of the acetabular structure.

[0105] Step 506: determine the angle between the axis direction vector and each center vector as the angle of each first surface voxel.

[0106] Optionally, the server 204 can determine the center vector of each first surface voxel on the acetabular structure to the center point of the acetabular structure, and calculate the angle between the axis direction vector of the acetabular structure and each center vector. Thus, the server 204 can determine the angle between the axis direction vector and each center vector as the angle of each first surface voxel. Exemplarily, assuming that the center vector of the first surface voxel on the acetabular structure to the center point of the acetabular structure is OA, and the axis direction vector of the acetabular structure is OB, then the server 204 can calculate the value of cosσ according to the formula cosσ=OA*OB / |OA||OB|. Thus, the angle σ between the direction of the first surface voxel pointing to the center point of the acetabular structure and the direction of the axis direction vector can be calculated by the inverse cosine function, and the angle σ can be determined as the angle of the first surface voxel.

[0107] In this embodiment, principal component analysis is performed on each first surface voxel on the acetabular structure, so that the axial direction vector of the acetabular structure can be obtained more accurately; the center vector from each first surface voxel on the acetabular structure to the center point of the acetabular structure is obtained. Thus, the angle between the more accurate axial direction vector and each center vector can be determined as the angle of each first surface voxel, that is, the more accurate angle of each first surface voxel can be determined.

[0108] In the above embodiment, the target search range is determined according to the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure. Another implementation method is described below. In an exemplary embodiment, Figure 7 As shown, the method for determining the thickness of the acetabulum further includes:

[0109] Step 702: determine the distance between each voxel on the acetabular structure in the region of interest image and the center point of the acetabular structure.

[0110] Optionally, the server 204 may predetermine each voxel on the acetabular fossa structure in the region of interest image and the center point of the acetabular fossa structure. Thus, for each voxel on the acetabular fossa structure in the region of interest image, the server 204 may determine the distance between the voxel on the acetabular fossa structure in the region of interest image and the center point of the acetabular fossa structure. Among them, each voxel on the acetabular fossa structure in the region of interest image includes each voxel on the surface of the acetabular fossa structure and each voxel in the acetabular fossa structure. Since the acetabular fossa structure is a hemispherical deep socket, the center point of the acetabular fossa structure refers to the center of the hemisphere corresponding to the acetabular fossa structure.

[0111] Step 704: Obtain a second radius of the acetabulum structure.

[0112] Optionally, the server 204 may directly obtain the second radius of the acetabular structure from a preset database or the terminal 202. The second radius of the acetabular structure is the true value of the radius of the acetabular structure and is a reference value for subsequent difference comparison. It should be noted that, although the first radius and the second radius are determined in different ways, the values ​​of the first radius and the second radius may be equal.

[0113] Step 706, determining whether the difference between the distance and the second radius is less than or equal to a preset difference threshold, and if so, taking the voxel corresponding to the distance as the first surface voxel of the acetabulum structure.

[0114] Optionally, for each voxel on the acetabular structure in the region of interest image, the server 204 can calculate the distance between the voxel on the acetabular structure and the center point of the acetabular structure, and the difference between the distance and the second radius of the acetabular structure, and determine whether the difference is less than or equal to a preset difference threshold. If the difference between the distance corresponding to the voxel and the second radius is less than or equal to the preset difference threshold, the server 204 can use the voxel corresponding to the distance as the first surface voxel of the acetabular structure. Exemplarily, the preset difference threshold can be 4mm. Of course, the preset difference threshold can be set according to the actual acetabular structure, and the embodiment of the present application is not limited to this.

[0115] In this embodiment, the distance between each voxel on the acetabular structure in the region of interest image and the center point of the acetabular structure can be determined more accurately, and the second radius of the acetabular structure can be obtained more accurately. Therefore, it can be determined whether the difference between the more accurate distance and the more accurate second radius is less than the preset difference threshold. If the difference between the distance and the second radius is less than the preset difference threshold, the voxel corresponding to the distance is used as the first surface voxel of the acetabular structure, and the first surface voxel of the acetabular structure can be determined more accurately.

[0116] In the above embodiment, it is involved to determine the acetabular fossa thickness corresponding to each second surface voxel of the acetabular cup structure within the target search range, and the specific method is introduced below. In an exemplary embodiment, determining the acetabular fossa thickness corresponding to each second surface voxel of the acetabular cup structure within the target search range includes:

[0117] In the target search range, the ray direction of each second surface voxel of the acetabular cup structure is determined.

[0118] The distance between the outer surface of the acetabular cup structure and the dorsal side of the hip bone corresponding to the acetabular socket structure in each ray direction is determined, and each distance is determined as the acetabular socket thickness corresponding to each second surface voxel.

[0119] Optionally, for each second surface voxel of the acetabular cup structure within the target search range, the server 204 may determine the normal vector direction of the second surface voxel on the second surface of the acetabular cup structure within the target search range as the ray direction of the second surface voxel of the acetabular cup structure. Figure 8 As shown, Figure 8 It is a schematic diagram of the position of the ray direction in an embodiment. Thus, the server 204 can make a ray in the ray direction of the second surface voxel and determine the thickness of the acetabular fossa structure through which the ray passes, that is, determine the distance between the intersection of the ray and the outer surface of the acetabular cup structure to the intersection of the ray and the dorsal side of the hip bone corresponding to the acetabular fossa structure in each ray direction, and determine the distance as the acetabular fossa thickness corresponding to the second surface voxel. Thus, the server 204 can determine the acetabular fossa thickness corresponding to each second surface voxel within the target search range based on each distance.

[0120] In this embodiment, within the target search range, the ray direction of each second surface voxel of the acetabular cup structure can be determined more accurately and quickly. Thus, the distance between the outer surface of the acetabular cup structure and the dorsal side of the hip bone corresponding to the acetabular fossa structure in each more accurate ray direction can be determined, and each distance is determined as the acetabular fossa thickness corresponding to each second surface voxel, so that the acetabular fossa thickness corresponding to each second surface voxel can be determined more accurately based on the more accurate ray direction of each second surface voxel.

[0121] In the above embodiment, it is involved to determine the target thickness of the acetabular structure according to the acetabular thickness corresponding to each second surface voxel, and the specific method is introduced below. In an exemplary embodiment, S306 includes:

[0122] The acetabular thickness corresponding to the smallest second surface voxel is determined as the target thickness.

[0123] Optionally, the server 204 may determine the acetabular fossa thickness corresponding to the smallest second surface voxel from the acetabular fossa thicknesses at the locations of the first surface voxels corresponding to the second surface voxels within the target search range, and determine the acetabular fossa thickness corresponding to the smallest second surface voxel as the target thickness.

[0124] In this embodiment, the acetabular fossa thickness corresponding to the smallest second surface voxel can be determined more accurately, and the acetabular fossa thickness corresponding to the smallest second surface voxel more accurately can be determined as the target thickness.

[0125] In an optional embodiment, if Fig. 9 As shown, a method for determining the thickness of the acetabulum is provided, which is applied to the server 204 and includes:

[0126] Step 902, obtaining a medical image including the acetabulum structure, and determining a center point and a first radius of the acetabulum structure according to the medical image;

[0127] Obtaining a model including the acetabular cup structure;

[0128] Constructing an image of a region of interest according to the center point and the first radius of the acetabulum structure and the model;

[0129] Step 904, determining the distance between each voxel on the acetabular structure in the region of interest image and the center point of the acetabular structure;

[0130] obtaining a second radius of the acetabular structure;

[0131] determining whether the difference between the distance and the second radius is less than or equal to a preset difference threshold, and if the difference between the distance and the second radius is less than the preset difference threshold, taking the voxel corresponding to the distance as the first surface voxel of the acetabulum structure;

[0132] Step 906, obtaining the coordinate position of each first surface voxel;

[0133] Performing principal component analysis on the coordinate position of each first surface voxel to obtain the eigenvalues ​​of each first surface voxel in three coordinate directions, where the three coordinate directions are orthogonal to each other;

[0134] Determine the axis direction vector according to the smallest eigenvalue among the three eigenvalues ​​corresponding to each first surface voxel;

[0135] Step 908, obtaining a center vector from each first surface voxel on the acetabular structure to the center point of the acetabular structure;

[0136] The angle between the axis direction vector and each center vector is determined as the angle of each first surface voxel;

[0137] Determine whether the angle of the first surface voxel is less than a preset angle threshold, and determine whether the distance of the first surface voxel is less than a preset distance threshold; the distance represents the distance between the first surface voxel and the center point of the acetabular structure;

[0138] If the angle of the first surface voxel is less than the preset angle threshold, and the distance of the first surface voxel is less than the preset distance threshold, determining that the position information of the first surface voxel meets the preset position condition;

[0139] Using the position information of the first surface voxel that meets the preset position condition as the search target position information;

[0140] Determining a target search range according to position information of a second surface voxel that matches the search target position information;

[0141] Step 910, determining the ray direction of each second surface voxel of the acetabular cup structure within the target search range;

[0142] Determine the distance between the outer surface of the acetabular cup structure and the dorsal side of the hip bone corresponding to the acetabular socket structure in each ray direction, and determine each distance as the thickness of the acetabular socket corresponding to each second surface voxel;

[0143] Step 912: determine the acetabular thickness corresponding to the smallest second surface voxel as the target thickness.

[0144] In the above-mentioned method for determining the thickness of the acetabular fossa, an image of the region of interest can be obtained, that is, a more accurate acetabular fossa structure and acetabular cup structure can be obtained. Thus, the acetabular fossa thickness corresponding to each second surface voxel of the acetabular cup structure can be determined according to the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure, that is, the acetabular fossa thickness at the position of each first surface voxel corresponding to each second surface voxel within the target search range can be more accurately determined. Furthermore, the target thickness of the acetabular fossa structure can be more accurately determined according to the more accurate acetabular fossa thickness corresponding to each second surface voxel. Therefore, through the method for determining the thickness of the acetabular fossa of the present application, the estimation accuracy of the thickness of the acetabular fossa can be improved, so that in the preoperative planning stage of hip replacement, the minimum thickness of the acetabular fossa can be estimated in real time according to the planned position of the acetabular cup, and the unreasonable planned position of the acetabular cup can be reminded in time, thereby assisting the doctor in making a reasonable plan and obtaining the position and angle of the acetabular cup after reasonable planning.

[0145] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0146] Based on the same inventive concept, the embodiment of the present application also provides a device for determining the thickness of the acetabular fossa for implementing the method for determining the thickness of the acetabular fossa mentioned above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the embodiments of one or more devices for determining the thickness of the acetabular fossa provided below can refer to the limitations of the method for determining the thickness of the acetabular fossa above, and will not be repeated here.

[0147] In an exemplary embodiment, Fig.10 As shown, a device 1000 for determining acetabular thickness is provided, comprising: an area of ​​interest image acquisition module 1020, an acetabular thickness determination module 1040 and a target thickness determination module 1060, wherein:

[0148] The region of interest image acquisition module 1020 is used to acquire a region of interest image; the region of interest image includes the acetabular fossa structure and the acetabular cup structure.

[0149] The acetabular fossa thickness determination module 1040 is used to determine the acetabular fossa thickness corresponding to each second surface voxel of the acetabular fossa structure according to the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure.

[0150] The target thickness determination module 1060 is used to determine the target thickness of the acetabular structure according to the acetabular thickness corresponding to each second surface voxel.

[0151] In one embodiment, the region of interest image acquisition module 1020 includes:

[0152] A center point and first radius determining unit, used to obtain a medical image including the acetabulum structure, and determine a center point and a first radius of the acetabulum structure according to the medical image;

[0153] A model acquisition unit, used for acquiring a model including an acetabular cup structure;

[0154] The region of interest image construction unit is used to construct the region of interest image according to the center point and the first radius and the model of the acetabulum structure.

[0155] In one embodiment, the acetabular thickness determination module 1040 includes:

[0156] A target search range determination unit, used to determine the target search range according to the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure;

[0157] The acetabular fossa thickness determination unit is used to determine the acetabular fossa thickness corresponding to each second surface voxel of the acetabular cup structure within the target search range.

[0158] In one embodiment, the target search range determination unit includes:

[0159] A search target position information determination subunit is used to determine whether the position information of each first surface voxel meets a preset position condition, and use the position information of the first surface voxel that meets the preset position condition as the search target position information;

[0160] The target search range determination subunit is used to determine the target search range according to the position information of the second surface voxel that matches the search target position information.

[0161] In one embodiment, the position information includes the distance between the first surface voxel and the center point of the acetabular structure and the angle between the line segment between the first surface voxel and the center point of the acetabular structure and the axis of the acetabular structure, and the search target position information determination subunit includes:

[0162] a determination subunit, used to determine whether the angle of the first surface voxel is less than a preset angle threshold, and to determine whether the distance of the first surface voxel is less than a preset distance threshold;

[0163] The preset position condition satisfying subunit is used to determine that the position information of the first surface voxel satisfies the preset position condition when the angle of the first surface voxel is less than the preset angle threshold and the distance of the first surface voxel is less than the preset distance threshold.

[0164] In one embodiment, the device 1000 for determining acetabular thickness further includes:

[0165] An axis direction vector determination module is used to obtain the axis direction vector of the acetabular structure according to the distribution of each first surface voxel on the acetabular structure;

[0166] A center vector acquisition module is used to acquire a center vector from each first surface voxel on the acetabular structure to the center point of the acetabular structure;

[0167] The angle determination module is used to determine the angle between the axis direction vector and each center vector as the angle of each first surface voxel.

[0168] In one embodiment, the axis direction vector determination module includes:

[0169] A coordinate position acquisition unit, used to acquire the coordinate position of each first surface voxel;

[0170] An eigenvalue determination unit is used to perform principal component analysis on the coordinate position of each first surface voxel to obtain the eigenvalues ​​of each first surface voxel in three coordinate directions, where the three coordinate directions are orthogonal to each other;

[0171] The axis direction vector determining unit is used to determine the axis direction vector according to the smallest eigenvalue among the three eigenvalues ​​corresponding to each first surface voxel.

[0172] In one embodiment, the device 1000 for determining acetabular thickness further includes:

[0173] A distance determination module is used to determine the distance between each voxel on the acetabular fossa structure in the region of interest image and the center point of the acetabular fossa structure;

[0174] A second radius acquisition module, used to acquire a second radius of the acetabulum structure;

[0175] The first surface voxel determination module is used to determine whether the difference between the distance and the second radius is less than or equal to a preset difference threshold. If so, the voxel corresponding to the distance is used as the first surface voxel of the acetabulum structure.

[0176] In one embodiment, the acetabular thickness determination unit comprises:

[0177] A ray direction determination subunit, used to determine the ray direction of each second surface voxel of the acetabular cup structure within the target search range;

[0178] The acetabular socket thickness determination subunit is used to determine the distance between the outer surface of the acetabular cup structure and the dorsal side of the hip bone corresponding to the acetabular socket structure in each ray direction, and determine each distance as the acetabular socket thickness corresponding to each second surface voxel.

[0179] In one embodiment, the target thickness determination module 1060 includes:

[0180] The target thickness determination unit is used to determine the acetabular thickness corresponding to the smallest second surface voxel as the target thickness.

[0181] Each module in the above-mentioned device for determining the thickness of the acetabulum can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each of the above modules.

[0182] In one embodiment, the present application further provides a surgical robot system, which includes a planning system, and the planning system includes a device for determining the thickness of the acetabulum as described above.

[0183] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Fig.11 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the determination data of the acetabular fossa thickness. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for determining the thickness of the acetabular fossa is implemented.

[0184] Those skilled in the art will understand that Fig.11 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0185] In one embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiments when executing the computer program.

[0186] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0187] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0188] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0189] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0190] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0191] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for determining the thickness of the acetabulum, It is characterized in that The method comprises: Acquire an image of a region of interest; Regions of interest images included acetabular socket structures and acetabular cup structures; Determine the acetabular fossa thickness corresponding to each second surface voxel of the acetabular cup structure according to the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure; The target thickness of the acetabular structure is determined according to the acetabular thickness corresponding to each of the second surface voxels.

2. The method according to claim 1, It is characterized in that The step of acquiring an image of a region of interest comprises: Acquire a medical image including the acetabulum structure, and determine a center point and a first radius of the acetabulum structure according to the medical image; obtaining a model including the acetabular cup structure; The region of interest image is constructed according to the center point and the first radius of the acetabular structure and the model.

3. The method according to claim 1, It is characterized in that Determining the acetabular fossa thickness corresponding to each second surface voxel of the acetabular cup structure according to the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure comprises: Determining a target search range according to the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure; The acetabular fossa thickness corresponding to each second surface voxel of the acetabular cup structure is determined within the target search range.

4. The method according to claim 3, It is characterized in that Determining the target search range according to the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure includes: Determine whether the position information of each of the first surface voxels meets a preset position condition, and use the position information of the first surface voxels that meets the preset position condition as the search target position information; The target search range is determined according to the position information of the second surface voxels that match the search target position information.

5. The method according to claim 4, It is characterized in that The position information includes a distance between the first surface voxel and the center point of the acetabular fossa structure and an angle between a line segment between the first surface voxel and the center point of the acetabular fossa structure and an axis of the acetabular fossa structure, and determining whether the position information of each first surface voxel meets a preset position condition includes: determining whether an angle of the first surface voxel is less than a preset angle threshold, and determining whether a distance of the first surface voxel is less than a preset distance threshold; If the angle of the first surface voxel is smaller than a preset angle threshold, and the distance of the first surface voxel is smaller than a preset distance threshold, it is determined that the position information of the first surface voxel meets the preset position condition.

6. The method according to claim 5, It is characterized in that The method further comprises: According to the distribution of each first surface voxel on the acetabular structure, an axial direction vector of the acetabular structure is obtained; Acquire a center vector from each first surface voxel on the acetabular structure to a center point of the acetabular structure; The angle between the axis direction vector and each of the center vectors is determined as the angle of each of the first surface voxels.

7. The method according to claim 6, It is characterized in that The step of obtaining the axial direction vector of the acetabular structure according to the distribution of each first surface voxel on the acetabular structure comprises: Obtaining the coordinate position of each voxel of the first surface; Performing principal component analysis on the coordinate position of each voxel on the first surface to obtain eigenvalues ​​of each voxel on the first surface in three coordinate directions, wherein the three coordinate directions are orthogonal to each other; The axis direction vector is determined according to the smallest eigenvalue among the three eigenvalues ​​corresponding to each of the first surface voxels.

8. The method according to any one of claims 1 to 7, It is characterized in that The method further comprises: Determine the distance between each voxel on the acetabular structure in the region of interest image and the center point of the acetabular structure; Acquire a second radius of the acetabulum structure; Determine whether the difference between the distance and the second radius is less than or equal to a preset difference threshold; if so, use the voxel corresponding to the distance as the first surface voxel of the acetabulum structure.

9. The method according to any one of claims 3 to 7, It is characterized in that Determining the acetabular fossa thickness corresponding to each second surface voxel of the acetabular cup structure within the target search range includes: Determining the ray direction of each second surface voxel of the acetabular cup structure within the target search range; The distance between the outer surface of the acetabular cup structure and the dorsal side of the hip bone corresponding to the acetabular socket structure in each of the ray directions is determined, and each of the distances is determined as the acetabular socket thickness corresponding to each of the second surface voxels.

10. The method according to any one of claims 1 to 7, It is characterized in that Determining the target thickness of the acetabular structure according to the acetabular thickness corresponding to each voxel of the second surface includes: The acetabular thickness corresponding to the smallest second surface voxel is determined as the target thickness.

11. A device for determining the thickness of an acetabulum, It is characterized in that The device comprises: An area of ​​interest image acquisition module, used to acquire an area of ​​interest image; the area of ​​interest image includes an acetabular fossa structure and an acetabular cup structure; An acetabular fossa thickness determination module, for determining the acetabular fossa thickness corresponding to each second surface voxel of the acetabular fossa structure according to the position information of each first surface voxel on the acetabular fossa structure and the position information of each second surface voxel on the acetabular cup structure; The target thickness determination module is used to determine the target thickness of the acetabular structure according to the acetabular thickness corresponding to each of the second surface voxels.

12. A surgical robot system, It is characterized in that A planning system is included, the planning system comprising the device for determining the thickness of the acetabular socket according to claim 11.

Images