Determination method and device of stop point range, electronic equipment and storage medium

Abstract

The application provides a stop point range determination method and device, electronic equipment and a storage medium, and applies to the technical field of data processing. The method comprises the following steps: acquiring a to-be-processed image, wherein the to-be-processed image is a segmentation image of a carpal bone and a ligament structure; determining first edge information of the carpal bone and second edge information of the ligament structure in the to-be-processed image, and performing cross extraction based on the first edge information and the second edge information to obtain first stop point information of the ligament structure; performing plane fitting processing based on the first stop point information to obtain second stop point information of the ligament structure; wherein the edge volume of the second stop point information is smaller than the edge volume of the first stop point information, and the second stop point information is used for indicating a stop point range of the ligament structure on the carpal bone.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a method, device, electronic device and storage medium for determining a stop range. Background Art

[0002] Triangular fibrocartilage complex (TFCC) injuries are the most common cause of wrist pain and instability. In clinical practice, wrist MRI scan data can be used as a guide for diagnosis and treatment of TFCC injuries. However, due to the delicate structure of wrist ligaments and the limited perspective of wrist MRI scan data, a comprehensive understanding of the true morphology of the ligaments cannot be achieved simply by examining wrist MRI scan data, leading to significant uncertainty in the diagnosis and treatment of TFCC injuries. Summary of the Invention

[0003] The present invention provides a method, device, electronic device and storage medium for determining an insertion range, which are used to solve the problem of difficulty in diagnosis and treatment caused by the lack of information on the true morphology of ligaments in clinical medicine.

[0004] The present invention provides a method for determining an end point range, comprising: acquiring an image to be processed, wherein the image to be processed is a segmented image of a carpal bone and a ligament structure; determining first edge information of the carpal bone and second edge information of the ligament structure in the image to be processed, and performing cross-extraction based on the first edge information and the second edge information to obtain first end point information of the ligament structure; performing plane fitting processing based on the first end point information to obtain second end point information of the ligament structure; wherein the edge volume of the second end point information is smaller than the edge volume of the first end point information, and the second end point information is used to indicate the end point range of the ligament structure on the carpal bone.

[0005] According to the present invention, a method for determining an end point range is provided, and the method for determining the first edge information of the carpal bone and the second edge information of the ligament structure in the image to be processed includes: calculating a first gradient value of the carpal bone edge and a second gradient value of the ligament structure edge based on a preset edge extraction algorithm; determining first gradient information according to the first gradient value, and determining second gradient information according to the second gradient value, wherein the gradient information includes a gradient amplitude and a gradient direction; filtering the first gradient information through a preset edge threshold to obtain third gradient information, and filtering the second gradient information through the preset edge threshold to obtain fourth gradient information; processing the third gradient information through a morphological dilation and erosion algorithm to obtain the first edge information, and processing the second gradient information through the morphological dilation and erosion algorithm to obtain the second edge information.

[0006] According to a method for determining a dead point range provided by the present invention, the preset edge threshold includes a first edge threshold and a second edge threshold, the first edge threshold is greater than the second edge threshold, the first edge threshold is used to mark a strong edge, and the second edge threshold is used to mark a weak edge.

[0007] According to the present invention, a method for determining an end point range is provided, in which plane fitting processing is performed based on the first end point information to obtain second end point information of the ligament structure, including: randomly determining a first plane composed of three points in the first end point information; calculating a first distance from the remaining points in the first end point information to the first plane; determining the number of inliers by comparing the first distance with a preset distance threshold; if the number of inliers is greater than the number of historical inliers, re-determining the plane; if the number of inliers is less than or equal to the number of historical inliers, determining the first plane as the second end point information.

[0008] According to the method for determining the dead point range provided by the present invention, after acquiring the image to be processed, the method further comprises: performing an alternate-frame interpolation operation and a smoothing operation on the image to be processed.

[0009] According to a method for determining an end point range provided by the present invention, after performing plane fitting processing based on the first end point information to obtain the second end point information of the ligament structure, the method further includes: counting the volume and surface area of ​​the end point range of the ligament structure based on the second end point information.

[0010] The present invention also provides an end point range determination device, comprising: an image acquisition module, an edge extraction module and a plane fitting module; the image acquisition module is used to acquire an image to be processed, which is a segmented image of the carpal bone and ligament structure; the edge extraction module is used to determine the first edge information of the carpal bone and the second edge information of the ligament structure in the image to be processed, and perform cross-extraction based on the first edge information and the second edge information to obtain the first end point information of the ligament structure; the plane fitting module is used to perform plane fitting processing based on the first end point information to obtain the second end point information of the ligament structure; wherein the edge volume of the second end point information is smaller than the edge volume of the first end point information, and the second end point information is used to indicate the end point range of the ligament structure on the carpal bone.

[0011] According to the application, the edge extraction module is configured to calculate a first gradient value of the wrist bone edge and a second gradient value of the ligament structure edge based on a preset edge extraction algorithm; determine first gradient information based on the first gradient value and determine second gradient information based on the second gradient value, wherein the gradient information comprises a gradient amplitude and a gradient direction; filter the first gradient information based on a preset edge threshold to obtain third gradient information, and filter the second gradient information based on the preset edge threshold to obtain fourth gradient information; and process the third gradient information based on a morphological dilation and erosion algorithm to obtain the first edge information, and process the second gradient information based on the morphological dilation and erosion algorithm to obtain the second edge information.

[0012] According to the application, the preset edge threshold comprises a first edge threshold and a second edge threshold, wherein the first edge threshold is greater than the second edge threshold, the first edge threshold is used for marking a strong edge, and the second edge threshold is used for marking a weak edge.

[0013] According to the application, the plane fitting module is configured to randomly determine a first plane formed by three points in the first stop point information; calculate a first distance from the remaining points in the first stop point information to the first plane; determine the number of inliers by comparing the first distance with a preset distance threshold; if the number of inliers is greater than a historical number of inliers, re-determine the plane; and if the number of inliers is less than or equal to the historical number of inliers, determine the first plane as the second stop point information.

[0014] According to the application, the image processing module is configured to perform a frame interpolation operation and a smoothing operation on the image to be processed.

[0015] According to the application, the data analysis module is configured to statistically analyze the volume and the surface area of the ligament structure stop point range based on the second stop point information.

[0016] The application further provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the stop point range determination method.

[0017] The application further provides a non-transitory computer readable storage medium, wherein the non-transitory computer readable storage medium stores a computer program, and the computer program is executable on a processor to implement the steps of the stop point range determination method.

[0018] The method, device, electronic device, and storage medium for determining the end-point range provided by the present invention can obtain an image to be processed, wherein the image to be processed is a segmented image of a carpal bone and ligament structure; determine first edge information of the carpal bone and second edge information of the ligament structure in the image to be processed, and perform cross-extraction based on the first and second edge information to obtain first end-point information of the ligament structure; and perform plane fitting processing based on the first end-point information to obtain second end-point information of the ligament structure; wherein the edge volume of the second end-point information is smaller than the edge volume of the first end-point information, and the second end-point information is used to indicate the end-point range of the ligament structure on the carpal bone. Through this solution, the first end-point information of the ligament structure can be determined based on the segmented image of the carpal bone and ligament structure, and the second end-point information with higher accuracy can be further obtained through plane fitting processing. Since the end-point information of the ligament structure can be accurately determined, it can provide a data basis for research on the end-point range of the ligament, thereby playing a guiding role in clinical diagnosis and treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction is given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0020] Figure 1 This is one of the flow charts of the method for determining the stop range provided by the present invention;

[0021] Figure 2 This is the second flow chart of the method for determining the stop range provided by the present invention;

[0022] Figure 3 It is a structural schematic diagram of the dead point range determination device provided by the present invention;

[0023] Figure 4 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0024] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0025] It should be noted that, in the embodiments of the present invention, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present invention should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0026] It should be noted that, in this article, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present invention is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in the opposite order according to the functions involved. For example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0027] In order to clearly describe the technical solutions of the embodiments of the present invention, in the embodiments of the present invention, words such as "first" and "second" are used to distinguish between identical or similar items with basically the same functions and effects. Those skilled in the art can understand that words such as "first" and "second" do not limit the quantity and execution order.

[0028] The embodiments of the present invention describe some exemplary embodiments for the purpose of explanation. It should be understood that the present invention can be implemented in other ways not specifically shown in the drawings.

[0029] The above implementation will be described in detail below with reference to specific embodiments and drawings.

[0030] like Figure 1 As shown, an embodiment of the present invention provides a method for determining a dead point range, which can be applied to a dead point range determination device. The method for determining a dead point range may include S101-S103:

[0031] S101: The dead point range determining device obtains an image to be processed.

[0032] The image to be processed is a segmented image of the carpal bones and ligament structures.

[0033] Optionally, the image to be processed may be an image with a TFCC imaging area annotation added to a magnetic resonance imaging (MRI) image.

[0034] Optionally, the image to be processed may be a two-dimensional image or a three-dimensional image. In the case where the image to be processed is a two-dimensional image, the stop range determination device may first map the two-dimensional image into a three-dimensional space to obtain three-dimensional information of the image to be processed.

[0035] Optionally, after acquiring the image to be processed, the dead point range determining device may perform an alternate-frame interpolation operation and a smoothing operation on the image to be processed.

[0036] Specifically, if Figure 2 As shown, the stop range determining device can perform interpolation operation on the image to be processed to supplement the Z-axis spatial information of the image to be processed. Then, the stop range determining device can use a joint smoothing algorithm to smooth the image to be processed after the interpolation operation, thereby removing the jagged edges of the image segmentation result while retaining the intersection area between the wrist bone and the TFCC, thereby improving the image quality.

[0037] S102. The end point range determining device determines first edge information of the carpal bone and second edge information of the ligament structure in the image to be processed, and performs cross extraction based on the first edge information and the second edge information to obtain first end point information of the ligament structure.

[0038] Optionally, the end point range determination device can calculate a first gradient value of the wrist bone edge and a second gradient value of the ligament structure edge based on a preset edge extraction algorithm; determine first gradient information according to the first gradient value, and determine second gradient information according to the second gradient value, the gradient information including gradient amplitude and gradient direction; filter the first gradient information through a preset edge threshold to obtain third gradient information, and filter the second gradient information through the preset edge threshold to obtain fourth gradient information; process the third gradient information through a morphological expansion and corrosion algorithm to obtain the first edge information, and process the second gradient information through the morphological expansion and corrosion algorithm to obtain the second edge information.

[0039] Specifically, if Figure 2As shown, the end point range determination device can separate the carpal bones and TFCC based on the image to be processed in S101, and then use the edge extraction algorithm on the carpal bones and TFCC respectively to obtain the first edge information of the carpal bones and the second edge information of the TFCC. The specific implementation process of the edge extraction algorithm includes: applying the edge extraction algorithm to the separated carpal bones to obtain the first gradient values ​​in the horizontal and vertical directions of the carpal bone edge, and then determining the first gradient information based on the first gradient value of each pixel point. The first gradient information may include the first gradient amplitude calculated using the Euclidean distance formula and the first gradient direction calculated using the inverse tangent function. Afterwards, the third gradient information is obtained by filtering based on the relationship between the first gradient amplitude and the preset edge threshold, and finally the third gradient information is processed by the morphological dilation and corrosion algorithm to obtain the first edge information.

[0040] It should be noted that the process of determining the second edge information by the dead point range determining device can refer to the process of determining the first edge information, which will not be repeated here.

[0041] Optionally, the edge extraction algorithm may be a Sobel edge extraction algorithm, and the stop range determination device may apply the SobelX convolution kernel, the SobelY convolution kernel, and the SobelZ convolution kernel to the separated carpal bones and TFCC to determine the first gradient value and the second gradient value.

[0042] Optionally, the preset edge threshold may include a first edge threshold and a second edge threshold, wherein the first edge threshold is greater than the second edge threshold, the first edge threshold being used to mark strong edges, and the second edge threshold being used to mark weak edges. In this manner, the first edge threshold can be used to accurately label strong edges, while the second edge threshold can be used to label weak edges, thereby maximizing edge labeling.

[0043] Optionally, the above morphological dilation-erosion algorithm refers to the formula Determine the image edge, where f represents the original image, b represents the structural element, represents the dilation operation, and Θ represents the erosion operation.

[0044] S103. The end point range determining device performs plane fitting processing based on the first end point information to obtain second end point information of the ligament structure.

[0045] The edge volume of the second end point information is smaller than the edge volume of the first end point information, and the second end point information is used to indicate the end point range of the ligament structure on the wrist bone.

[0046] It should be noted that the insertion range refers to the connection area of ​​the ligament structure on the wrist bone.

[0047] Optionally, the end point range determination device can randomly determine a first plane composed of three points in the first end point information based on the first end point information; calculate a first distance from the remaining points in the first end point information to the first plane; determine the number of inner points by comparing the first distance with a preset distance threshold; if the number of inner points is greater than the number of historical inner points, re-determine the plane; if the number of inner points is less than or equal to the number of historical inner points, determine the first plane as the second end point information.

[0048] Specifically, if Figure 2 As shown, the stop range determination device can perform precise processing of the stop information based on the RANSAC plane fitting algorithm. The specific implementation process includes: the stop range determination device can randomly select three points within the stop range indicated by the first stop information, and calculate the plane parameters of a first plane containing the three points based on the plane equation Ax+By+Cz+d=0; then, the device calculates a first distance from the remaining points within the stop range to the first plane, and then compares the first distance with a preset distance threshold. If the first distance is greater than the preset distance threshold, the point is determined to be an inlier; otherwise, it is an outlier. If the number of inliers among the remaining points is greater than the number of historical inliers, the plane is re-determined; if the number of inliers is less than or equal to the number of historical inliers, the first plane is determined as the second stop information.

[0049] By using the RANSAC plane fitting algorithm to perform plane fitting on the first stop point information, the volume of the processed stop point range can be greatly reduced. In this way, the accuracy of the stop point range statistics algorithm can be effectively guaranteed and the accuracy of the stop point range area calculation can be improved.

[0050] Optionally, after performing plane fitting processing based on the first end point information to obtain the second end point information of the ligament structure, the end point range determination device can calculate the volume and surface area of ​​the end point range of the ligament structure according to the second end point information.

[0051] Specifically, if Figure 2 As shown, the end point range determination device can use 3D Slicer software to convert the data into a Model module based on the second end point information, and then obtain the volume and surface area of ​​the end point range indicated by the second end point information through data statistics, so as to determine the distribution shape and distribution range of the ligament structure on the wrist bone.

[0052] The insertion range determination method proposed in the present invention establishes a complete analysis process for the ligament structure and carpal bones. By comprehensively using the edge extraction algorithm and the RANSAC plane fitting algorithm, a spatial map of the TFCC three-dimensional morphology including the real information of the ligament origin and insertion footprint area can be accurately mapped, accurately depicting the complex and fine three-dimensional anatomical structure of the TFCC, and realizing the automated and accurate correspondence between the fine three-dimensional anatomy of the TFCC and imaging, thereby guiding the clinical diagnosis and treatment of TFCC injuries.

[0053] In an embodiment of the present invention, the first end point information of the ligament structure can be determined based on the segmented image of the wrist bone and ligament structure, and the second end point information with higher accuracy can be further obtained through plane fitting processing. Since the end point information of the ligament structure can be accurately determined, it can provide a data basis for the study of the range of ligament end points, thereby playing a guiding role in clinical diagnosis and treatment.

[0054] The above mainly introduces the solution provided by the embodiment of the present invention from the perspective of method. In order to realize the above functions, it includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiment disclosed herein, the embodiment of the present invention can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0055] The method for determining a dead-point range provided in embodiments of the present invention can be executed by a dead-point range determining device or a control module within the dead-point range determining device for determining a dead-point range. The dead-point range determining device provided in embodiments of the present invention is described using the dead-point range determining device executing the method as an example.

[0056] It should be noted that embodiments of the present invention can divide the dead-point range determination device into functional modules based on the above-described method examples. For example, separate functional modules can be divided according to their respective functions, or two or more functions can be integrated into a single processing module. These integrated modules can be implemented as either hardware or software functional modules. Optionally, the module division in the embodiments of the present invention is illustrative and represents only one logical functional division. In actual implementation, other division methods may be employed.

[0057] like Figure 3As shown, an embodiment of the present invention provides a device 300 for determining a dead point range. The device 300 comprises: an image acquisition module 301, an edge extraction module 302, and a plane fitting module 303;

[0058] The image acquisition module 301 is used to acquire an image to be processed, wherein the image to be processed is a segmented image of the carpal bones and ligament structures;

[0059] The edge extraction module 302 is configured to determine first edge information of the carpal bone and second edge information of the ligament structure in the image to be processed, and perform cross extraction based on the first edge information and the second edge information to obtain first end point information of the ligament structure;

[0060] The plane fitting module 303 is configured to perform plane fitting processing based on the first end point information to obtain second end point information of the ligament structure;

[0061] The edge volume of the second end point information is smaller than the edge volume of the first end point information, and the second end point information is used to indicate the end point range of the ligament structure on the wrist bone.

[0062] Optionally, the above-mentioned edge extraction module 302 is used to calculate the first gradient value of the wrist bone edge and the second gradient value of the ligament structure edge based on a preset edge extraction algorithm; determine the first gradient information according to the first gradient value, and determine the second gradient information according to the second gradient value, and the gradient information includes the gradient amplitude and gradient direction; filter the first gradient information through a preset edge threshold to obtain the third gradient information, and filter the second gradient information through the preset edge threshold to obtain the fourth gradient information; process the third gradient information through a morphological expansion and corrosion algorithm to obtain the first edge information, and process the second gradient information through the morphological expansion and corrosion algorithm to obtain the second edge information.

[0063] Optionally, the preset edge threshold includes a first edge threshold and a second edge threshold, the first edge threshold is greater than the second edge threshold, the first edge threshold is used to mark a strong edge, and the second edge threshold is used to mark a weak edge.

[0064] Optionally, the plane fitting module 303 is configured to randomly determine a first plane consisting of three points in the first stop point information according to the first stop point information; calculate a first distance from the remaining points in the first stop point information to the first plane; determine the number of inliers by comparing the first distance with a preset distance threshold; re-determine the plane if the number of inliers is greater than the number of historical inliers; and determine the first plane as the second stop point information if the number of inliers is less than or equal to the number of historical inliers.

[0065] Optionally, the apparatus further includes an image processing module 304, and the image processing module 304 is configured to perform interpolation and smoothing operations on the image to be processed.

[0066] Optionally, the above-mentioned device further includes a data analysis module 305, and the data analysis module 305 is used to count the volume and surface area of ​​the end point range of the ligament structure according to the second end point information.

[0067] In an embodiment of the present invention, the first end point information of the ligament structure can be determined based on the segmented image of the wrist bone and ligament structure, and the second end point information with higher accuracy can be further obtained through plane fitting processing. Since the end point information of the ligament structure can be accurately determined, it can provide a data basis for the study of the range of ligament end points, thereby playing a guiding role in clinical diagnosis and treatment.

[0068] Figure 4 An example of a physical structure diagram of an electronic device is shown below. Figure 4 As shown, the electronic device may include: a processor 410, a communication interface 420, a memory 430, and a communication bus 440, wherein the processor 410, the communication interface 420, and the memory 430 communicate with each other via the communication bus 440. The processor 410 may call logic instructions in the memory 430 to execute a method for determining an end point range, the method comprising: acquiring an image to be processed, wherein the image to be processed is a segmented image of a carpal bone and a ligament structure; determining first edge information of the carpal bone and second edge information of the ligament structure in the image to be processed, and performing cross-extraction based on the first edge information and the second edge information to obtain first end point information of the ligament structure; performing plane fitting processing based on the first end point information to obtain second end point information of the ligament structure; wherein the edge volume of the second end point information is smaller than the edge volume of the first end point information, and the second end point information is used to indicate the end point range of the ligament structure on the carpal bone.

[0069] In addition, the logic instructions in the above-mentioned memory 430 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0070] On the other hand, the present invention also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the end point range determination method provided by the above methods, the method including: obtaining an image to be processed, wherein the image to be processed is a segmented image of the carpal bone and ligament structure; determining the first edge information of the carpal bone and the second edge information of the ligament structure in the image to be processed, and performing cross-extraction based on the first edge information and the second edge information to obtain the first end point information of the ligament structure; performing plane fitting processing based on the first end point information to obtain the second end point information of the ligament structure; wherein the edge volume of the second end point information is smaller than the edge volume of the first end point information, and the second end point information is used to indicate the end point range of the ligament structure on the carpal bone.

[0071] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the above-mentioned methods for determining the end point range, the methods comprising: acquiring an image to be processed, the image to be processed being a segmented image of the carpal bone and ligament structure; determining the first edge information of the carpal bone and the second edge information of the ligament structure in the image to be processed, and performing cross-extraction based on the first edge information and the second edge information to obtain the first end point information of the ligament structure; performing plane fitting processing based on the first end point information to obtain the second end point information of the ligament structure; wherein the edge volume of the second end point information is smaller than the edge volume of the first end point information, and the second end point information is used to indicate the end point range of the ligament structure on the carpal bone.

[0072] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0073] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course, by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the existing technology can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or certain parts of the embodiments.

[0074] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for determining a dead point range, characterized in that: include: Acquiring an image to be processed, wherein the image to be processed is a segmented image of the carpal bone and ligament structure; Determining first edge information of the carpal bone and second edge information of the ligament structure in the image to be processed, and performing cross extraction based on the first edge information and the second edge information to obtain first end point information of the ligament structure; Performing plane fitting processing based on the first stop point information to obtain second stop point information of the ligament structure; The edge volume of the second end point information is smaller than the edge volume of the first end point information, and the second end point information is used to indicate the end point range of the ligament structure on the carpal bone; The performing plane fitting processing based on the first end point information to obtain the second end point information of the ligament structure includes: Randomly determine a first plane consisting of three points therein according to the first stop point information; Calculating a first distance from the remaining point in the first dead point information to the first plane; determining the number of inliers by comparing the first distance with a preset distance threshold; If the number of inliers is greater than the number of historical inliers, the plane is re-determined; if the number of inliers is less than or equal to the number of historical inliers, the first plane is determined as the second end point information.

2. The method for determining the dead center range according to claim 1, wherein: The determining of the first edge information of the carpal bone and the second edge information of the ligament structure in the image to be processed includes: Calculating a first gradient value of the carpal bone edge and a second gradient value of the ligament structure edge based on a preset edge extraction algorithm; determining first gradient information according to the first gradient value, and determining second gradient information according to the second gradient value, wherein the gradient information includes a gradient magnitude and a gradient direction; filtering the first gradient information using a preset edge threshold to obtain third gradient information, and filtering the second gradient information using the preset edge threshold to obtain fourth gradient information; The third gradient information is processed by a morphological dilation and erosion algorithm to obtain the first edge information, and the second gradient information is processed by the morphological dilation and erosion algorithm to obtain the second edge information.

3. The method for determining the dead point range according to claim 2, wherein: The preset edge threshold includes a first edge threshold and a second edge threshold, the first edge threshold is greater than the second edge threshold, the first edge threshold is used to mark a strong edge, and the second edge threshold is used to mark a weak edge.

4. The method for determining the dead center range according to claim 1, wherein: After obtaining the image to be processed, the method further includes: Performing interpolation and smoothing operations on the image to be processed.

5. The method for determining the dead center range according to claim 1, wherein: After performing plane fitting processing based on the first end point information to obtain second end point information of the ligament structure, the method further includes: The volume and surface area of ​​the end point range of the ligament structure are calculated based on the second end point information.

6. A dead point range determination device, characterized in that: include: Image acquisition module, edge extraction module and plane fitting module; The image acquisition module is used to acquire an image to be processed, wherein the image to be processed is a segmented image of the carpal bone and ligament structure; The edge extraction module is configured to determine first edge information of the carpal bone and second edge information of the ligament structure in the image to be processed, and perform cross extraction based on the first edge information and the second edge information to obtain first end point information of the ligament structure; The plane fitting module is configured to perform plane fitting processing based on the first stop point information to obtain second stop point information of the ligament structure; The edge volume of the second end point information is smaller than the edge volume of the first end point information, and the second end point information is used to indicate the end point range of the ligament structure on the carpal bone; The performing plane fitting processing based on the first end point information to obtain the second end point information of the ligament structure includes: Randomly determine a first plane consisting of three points therein according to the first stop point information; Calculating a first distance from the remaining point in the first dead point information to the first plane; determining the number of inliers by comparing the first distance with a preset distance threshold; If the number of inliers is greater than the number of historical inliers, the plane is re-determined; if the number of inliers is less than or equal to the number of historical inliers, the first plane is determined as the second end point information.

7. The dead center range determining device according to claim 6, characterized in that: The edge extraction module is used to calculate a first gradient value of the wrist bone edge and a second gradient value of the ligament structure edge based on a preset edge extraction algorithm; determine first gradient information based on the first gradient value, and determine second gradient information based on the second gradient value, wherein the gradient information includes gradient amplitude and gradient direction; filter the first gradient information using a preset edge threshold to obtain third gradient information, and filter the second gradient information using the preset edge threshold to obtain fourth gradient information; process the third gradient information using a morphological expansion and corrosion algorithm to obtain the first edge information, and process the second gradient information using the morphological expansion and corrosion algorithm to obtain the second edge information.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the dead point range determination method according to any one of claims 1 to 5 are implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for determining a dead point range according to any one of claims 1 to 5 are implemented.

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