Methods, devices, and readable storage media for measuring trunk rotation angle in scoliosis
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SOUTHERN UNIVERSITY OF SCIENCE AND TECHNOLOGY
- Filing Date
- 2022-12-02
- Publication Date
- 2026-06-30
Smart Images
Figure CN116784830B_ABST
Abstract
Description
Technical Field
[0001] This application belongs to the field of computer technology, and in particular relates to a method, apparatus and readable storage medium for measuring the trunk rotation angle of scoliosis. Background Technology
[0002] Adolescent idiopathic scoliosis is the most common 3D vertebral deformity. Early detection of adolescent idiopathic scoliosis allows for better treatment and prevents further deterioration. X-ray imaging is currently the "gold standard" for measuring adolescent idiopathic scoliosis and for monitoring the progression of spinal deformities in adolescents. However, repeated exposure to ionizing radiation during the progression of spinal deformities increases the risk of malignant tumors in adolescents. Therefore, a radiation-free assessment and progression monitoring method has emerged, which involves physicians manually measuring trunk rotation angles using a scoliosis measuring ruler. This method relies on the physician's individual skill, and inaccurate measurements may occur if the physician's skill is insufficient. Summary of the Invention
[0003] This application provides a method, apparatus, device, and readable storage medium for measuring the trunk rotation angle of scoliosis, which can solve the problem of inaccurate manual measurement of the trunk rotation angle.
[0004] In a first aspect, embodiments of this application provide a method for measuring the trunk rotation angle of scoliosis, including:
[0005] Obtain the user's torso point cloud data;
[0006] Based on the torso point cloud data, determine the user's torso depth information;
[0007] Based on the torso depth information, the user's torso contour information is determined;
[0008] The user's torso rotation angle is calculated based on the torso contour information.
[0009] Optionally, determining the user's torso depth information based on the torso point cloud data includes:
[0010] The torso point cloud data is divided into multiple pixel regions;
[0011] For each pixel region, the average depth value of the point cloud clusters within the pixel region is calculated, and the average depth value is used as the pixel value of the pixel region.
[0012] The torso depth information is obtained by acquiring the pixel values of each pixel region.
[0013] Optionally, the trunk depth information includes the depth information of each trunk segment;
[0014] Determining the user's torso contour information based on the torso depth information includes:
[0015] From the trunk depth information, obtain the depth information corresponding to each trunk segment;
[0016] For each of the torso segments, the contour information of the torso segment is determined based on the depth information of the torso segment;
[0017] The trunk contour information includes the contour information of each trunk segment.
[0018] Optionally, determining the contour information of the torso segment based on its depth information includes:
[0019] Based on the depth information of the torso segment, determine the contour curve of the torso segment;
[0020] In the contour curve of the torso segment, determine the number of peaks and the number of troughs;
[0021] The spinous process of the spine is determined based on the number of peaks and the number of troughs.
[0022] Based on the length of the scoliosis measuring ruler, a first stress point and a second stress point are determined according to the spinous process point of the spine. The first stress point and the second stress point are the simulated stress points of the scoliosis measuring ruler.
[0023] The contour information includes the location information of the spinous process point, the first stress point, and the second stress point.
[0024] Optionally, based on the torso contour information, the user's torso rotation angle is calculated, including:
[0025] The trunk rotation angle is calculated based on the position information of the spinous process point, the first stress point, and the second stress point.
[0026] Optionally, determining the number of peaks and troughs in the contour curve of the torso segment includes:
[0027] The contour curve of the torso segment is processed by removing zero values and noise to obtain the processed contour curve.
[0028] The number of peaks and the number of troughs are determined based on the processed contour curve.
[0029] Secondly, embodiments of this application provide a device for measuring the trunk rotation angle of scoliosis, comprising:
[0030] The acquisition unit is used to acquire the user's torso point cloud data.
[0031] The determining unit is used to determine the user's torso depth information based on the torso point cloud data;
[0032] It is also used to determine the user's torso contour information based on the torso depth information;
[0033] The calculation unit is used to calculate the user's torso rotation angle based on the torso contour information.
[0034] Optionally, the calculation unit is specifically used to calculate the trunk rotation angle based on the position information of the spinous process of the spine, the first stress point, and the second stress point.
[0035] Thirdly, embodiments of this application provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method as described in any one of the first aspects above.
[0036] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method as described in any one of the first aspects above.
[0037] Fifthly, embodiments of this application provide a computer program product that, when run on an electronic device, causes the electronic device to perform the method described in any one of the first aspects above.
[0038] It is understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here.
[0039] The beneficial effects of the embodiments in this application compared with the prior art are:
[0040] This application obtains a user's torso point cloud data; determines the user's torso depth information based on the torso point cloud data; determines the user's torso contour information based on the torso depth information; and calculates the user's torso rotation angle based on the torso contour information. This method can automatically and accurately measure the torso rotation angle, eliminating reliance on the doctor's skills and reducing the impact of the doctor's skills on the measurement results. Attached Figure Description
[0041] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0042] Figure 1 This is a flowchart illustrating a method for measuring the trunk rotation angle of scoliosis according to an embodiment of this application;
[0043] Figure 2 This is a schematic diagram illustrating the acquisition of torso point cloud data according to an embodiment of this application;
[0044] Figure 3 This is a schematic diagram illustrating the determination of torso depth information according to an embodiment of this application;
[0045] Figure 4 This is a schematic diagram of a defined contour curve provided in an embodiment of this application;
[0046] Figure 5 This is a schematic diagram of the spinous process point, the first stress point, and the second stress point of the spine provided in an embodiment of this application;
[0047] Figure 6 This is a schematic diagram illustrating the removal of zero values according to an embodiment of this application;
[0048] Figure 7 This is a schematic diagram of low-frequency drift removal provided in an embodiment of this application;
[0049] Figure 8 This is a schematic diagram illustrating the validity provided in one embodiment of this application;
[0050] Figure 9 This is a schematic diagram of the structure of a device for measuring the trunk rotation angle of scoliosis provided in an embodiment of this application;
[0051] Figure 10 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation
[0052] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.
[0053] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.
[0054] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.
[0055] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."
[0056] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.
[0057] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.
[0058] Figure 1 This is a schematic flowchart illustrating a method for measuring the trunk rotation angle of scoliosis according to an embodiment of this application. Figure 1 As shown, the method includes:
[0059] S11: Obtain the user's torso point cloud data.
[0060] Figure 2 This is a schematic diagram illustrating the acquisition of torso point cloud data according to an embodiment of this application. For example... Figure 2 As shown, when a user is in the Adams test forward flexion posture, point cloud data of the user's torso in this state is acquired using a 3D scanner. The 3D torso model shown in the figure is a representation of the torso point cloud data.
[0061] S12: Determine the user's torso depth information based on torso point cloud data;
[0062] In the application, a 3D to 2D projection method is used to obtain a 2D torso depth image, i.e., torso depth information, from a 3D torso model.
[0063] Among them, each row of information in the trunk depth information is the trunk outline of the user as seen by the doctor when the user is in the Adams test forward flexion posture.
[0064] S13: Determine the user's torso contour information based on torso depth information.
[0065] In the application, the user's 1D torso contour curve, i.e., torso contour information, is obtained from the torso depth image.
[0066] S14: Calculate the user's torso rotation angle based on the torso contour information.
[0067] In application, based on the measurement principle of the scoliosis measuring ruler, the trunk rotation angle is calculated according to the structural information of the trunk contour curve.
[0068] Understandably, automatically measuring trunk rotation angles can reduce doctors' workload and save testing time. Simultaneously, reducing the 3D features of the trunk point cloud data to 1D enables real-time measurement of trunk rotation angles.
[0069] This application embodiment acquires the user's torso point cloud data; determines the user's torso depth information based on the torso point cloud data; determines the user's torso contour information based on the torso depth information; and calculates the user's torso rotation angle based on the torso contour information. This method can automatically and accurately measure the torso rotation angle, eliminating reliance on the doctor's skills and reducing the impact of the doctor's skills on the measurement results.
[0070] In one embodiment, step S12 includes:
[0071] S121: Divide the torso point cloud data into multiple pixel regions.
[0072] S122: For each pixel region, calculate the average depth value of the point cloud clusters within the pixel region, and use the average depth value as the pixel value of the pixel region.
[0073] S123: Obtain the pixel value of each pixel region to get the torso depth information.
[0074] Figure 3 This is a schematic diagram illustrating the determination of torso depth information according to an embodiment of this application. For example... Figure 3As shown, because the torso point cloud data is dense and irregular, point cloud clusters are projected onto the pixel region, and there are multiple points in each point cloud cluster. In a pixel region, the depth value of the points projected onto that pixel region is used as the pixel value. Since the depth of the torso surface is continuously changing, the average depth value of the point cloud clusters in the pixel region is calculated as the pixel value of the pixel region.
[0075] Formula for calculating average depth: Where, d avg is the average depth value, M is the number of points in the pixel region, and i is the index.
[0076] In one embodiment, step S13 includes:
[0077] S131: Obtain the depth information corresponding to each torso segment from the torso depth information.
[0078] The trunk depth information includes the depth information of each trunk segment.
[0079] S132: For each torso segment, determine the contour information of the torso segment based on the depth information of the torso segment.
[0080] The trunk contour information includes the contour information of each trunk segment.
[0081] Figure 4 This is a schematic diagram of a contour curve defined according to an embodiment of this application. Figure 4 As shown, the left image displays a torso depth image, with torso depth information from... Figure 2 The 3D torso model was obtained. When the user is in the Adams test forward flexion posture, the torso can be divided into the thoracic, thoracolumbar, and lumbar segments. Therefore, the torso depth image includes 2D depth images of the thoracic, thoracolumbar, and lumbar segments. Correspondingly, the first image on the right shows the 1D contour curve of the thoracic segment. The second image on the right shows the 1D contour curve of the thoracolumbar segment. The third image on the right shows the 1D contour curve of the lumbar segment.
[0082] In the application, the contour curve of the trunk segment is determined based on the depth information of the trunk segment. The number of peaks and troughs in the contour curve of the trunk segment is determined. Based on the number of peaks and troughs, the spinous process of the spine is determined.
[0083] Generally, when a user is in the Adams test forward flexion posture, the spine is fully exposed. Therefore, in the 3D trunk model, the tips of the spinous processes are closest to the skin surface, and these tips are points with a specific depth. This provides the basis for determining the spinous process points. Specifically, each 1D contour curve undergoes the following operations: after determining the 1D contour curve from the 2D depth image, the number of peaks and troughs is determined using second-order calculus. The type of contour curve is determined based on the number of peaks, and the location information of the spinous process points is calculated based on the type of contour curve and the number of troughs.
[0084] Based on the length of the scoliosis measuring ruler, and according to the spinous process point, the first and second stress points are determined. These first and second stress points are the simulated stress points of the scoliosis measuring ruler. Generally, the search range is the length of the scoliosis measuring ruler, searching for the highest point on both the left and right sides of the spinous process point. Therefore, the highest point is found within the search range to the left of the spinous process point as the first stress point; and the highest point is found within the search range to the right of the spinous process point as the second stress point.
[0085] Correspondingly, the contour information includes the location information of the spinous process of the spine, the first stress point, and the second stress point. Figure 5 This is a schematic diagram of the spinous process point, the first stress point, and the second stress point of the spine provided in an embodiment of this application. Figure 5 As shown, the first image displays the contour curve of the thoracic segment. From left to right, the first point is the first stress point, the second point is the spinous process of the spine, and the third point is the second stress point. The second image displays the contour curve of the thoracolumbar segment. From left to right, the first point is the first stress point, the second point is the spinous process of the spine, and the third point is the second stress point. The third image displays the contour curve of the lumbar segment. From left to right, the first point is the first stress point, the second point is the spinous process of the spine, and the third point is the second stress point.
[0086] This embodiment determines the contour curve of the trunk segment based on the depth information of the trunk segment, determines the number of peaks and troughs in the contour curve of the trunk segment, determines the spinous process point of the spine based on the number of peaks and troughs, and determines the first stress point and the second stress point based on the length of the scoliosis measuring ruler and the spinous process point of the spine. It can accurately locate the spinous process point, the first stress point and the second stress point of the contour curve of various trunk segments and has strong robustness.
[0087] Step S14 includes:
[0088] Calculate the trunk rotation angle based on the location information of the spinous process of the spine, the first stress point, and the second stress point.
[0089] In application, based on the measurement principle of the scoliosis measuring ruler, the trunk rotation angle is calculated according to the position information of each point.
[0090] In one embodiment, determining the number of peaks and troughs in the contour curve of the torso segment includes:
[0091] The contour curve of the torso segment is processed by removing zero values and noise to obtain the processed contour curve; based on the processed contour curve, the number of peaks and troughs is determined.
[0092] In applications, the discrete distribution characteristics of point clouds and noise cause zero values and / or low-frequency drift in the contour curve. To obtain more accurate information from the contour curve, zero values and noise are removed from the contour curve of the torso segment. Figure 6 This is a schematic diagram illustrating the removal of zero values according to an embodiment of this application, as shown below. Figure 6 As shown, the left side shows the contour curve with zero values, and the right side shows the contour curve after the zero values have been removed by a low-pass filter. Figure 7 This is a schematic diagram illustrating the removal of low-frequency drift according to an embodiment of this application. For example... Figure 7 As shown, the left figure shows the profile curve with low-frequency drift, and the right figure shows the profile curve after noise removal by a dynamic filter.
[0093] In addition, the automatic measurement method described in the embodiments of this application is compared with the manual measurement method to illustrate its effectiveness. Figure 8 This is a schematic diagram illustrating the validity of an embodiment of this application. For example... Figure 8 As shown in the comparison diagram (a) for ATR (torso rotation angle) ≤ 5°, the positions of the spinous process and two stress points determined by the automatic measurement method of this application embodiment are approximately the same as those determined by the manual measurement method. In the comparison diagram (b) for ATR (torso rotation angle) > 5°, the positions of the spinous process and two stress points determined by the automatic measurement method of this application embodiment are approximately the same as those determined by the manual measurement method. Regarding the fifth column of the comparison diagram (b), if a person is in the Adams test forward flexion posture, it is difficult to expose the spinous process of the thoracolumbar spine, and it is even more difficult for people with severe back deformities or a large body mass index to expose the spinous process of the thoracolumbar spine in the Adams test forward flexion posture. In this case, the manual measurement method will have difficulty detecting the spinous process. However, the automatic measurement method of this application embodiment involves the adjacent position information of the spinous process, which can locate the spinous process. Therefore, the automatic measurement method described in this application embodiment can automatically and effectively measure the rotation angle of the torso with different degrees of deformity.
[0094] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.
[0095] For ease of explanation, only the parts related to the embodiments of this application are shown in the methods described in the above embodiments.
[0096] Figure 9 This is a schematic diagram of a device for measuring the trunk rotation angle of scoliosis according to an embodiment of this application. Figure 9 As shown, the device includes:
[0097] Acquisition unit 10 is used to acquire the user's torso point cloud data.
[0098] The determining unit 11 is used to determine the user's torso depth information based on the torso point cloud data;
[0099] It is also used to determine the user's torso contour information based on torso depth information.
[0100] The calculation unit 12 is used to calculate the user's torso rotation angle based on the torso contour information.
[0101] In one embodiment, the determining unit is specifically used to divide the torso point cloud data into multiple pixel regions;
[0102] Specifically, it is used to calculate the average depth value of the point cloud clusters within each pixel region, and to use the average depth value as the pixel value of the pixel region.
[0103] Specifically, it is used to obtain the torso depth information by acquiring the pixel values of each pixel region.
[0104] In one embodiment, the determining unit is specifically used to obtain the depth information corresponding to each torso segment from the torso depth information;
[0105] Specifically, it is used to determine the contour curve of each torso segment based on the depth information of the torso segment.
[0106] The trunk depth information includes the depth information of each trunk segment, and the trunk contour information includes the contour information of each trunk segment.
[0107] In one embodiment, the determining unit is specifically used to determine the number of peaks and troughs in the contour curve of the torso segment;
[0108] Specifically, it is used to determine the spinous process of the spine based on the number of peaks and troughs;
[0109] Specifically, it is used to determine the first stress point and the second stress point based on the length of the scoliosis measuring ruler and the spinous process point of the spine. The first stress point and the second stress point are the simulated stress points of the scoliosis measuring ruler.
[0110] The contour information includes the location information of the spinous process of the spine, the first stress point, and the second stress point.
[0111] In one embodiment, the calculation unit is specifically used to calculate the trunk rotation angle based on the position information of the spinous process of the spine, the first stress point, and the second stress point.
[0112] Figure 10 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 10 As shown, the electronic device 2 of this embodiment includes: at least one processor 20 ( Figure 10 (Only one is shown in the diagram), memory 21, and computer program 22 stored in said memory 21 and executable on said at least one processor 20, wherein said processor 20 executes said computer program 22 to implement the steps in any of the above method embodiments.
[0113] The electronic device 2 can be a desktop computer, laptop, handheld computer, cloud server, or other computing device. The electronic device 2 may include, but is not limited to, a processor 20 and a memory 21. Those skilled in the art will understand that... Figure 10 This is merely an example of electronic device 2 and does not constitute a limitation on electronic device 2. It may include more or fewer components than shown in the figure, or combine certain components, or different components. For example, it may also include input / output devices, network access devices, etc.
[0114] The processor 20 may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.
[0115] In some embodiments, the memory 21 may be an internal storage unit of the electronic device 2, such as a hard disk or memory of the electronic device 2. In other embodiments, the memory 21 may be an external storage device of the electronic device 2, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the electronic device 2. Furthermore, the memory 21 may include both internal and external storage units of the electronic device 2. The memory 21 is used to store the operating system, applications, bootloader, data, and other programs, such as the program code of the computer program. The memory 21 can also be used to temporarily store data that has been output or will be output.
[0116] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.
[0117] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.
[0118] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the steps in the above-described method embodiments.
[0119] This application provides a computer program product that, when run on an electronic device, enables the electronic device to implement the steps described in the various method embodiments above.
[0120] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to a photographing device / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.
[0121] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.
[0122] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.
[0123] In the embodiments provided in this application, it should be understood that the disclosed apparatus / network devices and methods can be implemented in other ways. For example, the apparatus / network device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.
[0124] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.
[0125] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.
Claims
1. A method for measuring the trunk rotation angle of scoliosis, characterized in that, include: Obtain the user's torso point cloud data; Based on the torso point cloud data, determine the user's torso depth information; Based on the torso depth information, the user's torso contour information is determined; Calculate the user's torso rotation angle based on the torso contour information; The step of determining the user's torso contour information based on the torso depth information includes: Based on the depth information of the torso segment, the contour curve of the torso segment is determined; In the contour curve of the torso segment, determine the number of peaks and the number of troughs; The spinous process of the spine is determined based on the number of peaks and the number of troughs. Based on the length of the scoliosis measuring ruler, a first stress point and a second stress point are determined according to the spinous process point of the spine. The first stress point and the second stress point are the simulated stress points of the scoliosis measuring ruler. The contour information includes the location information of the spinous process point of the spine, the first stress point, and the second stress point; Based on the torso contour information, the user's torso rotation angle is calculated, including: The trunk rotation angle is calculated based on the position information of the spinous process point, the first stress point, and the second stress point.
2. The method as described in claim 1, characterized in that, The step of determining the user's torso depth information based on the torso point cloud data includes: The torso point cloud data is divided into multiple pixel regions; For each pixel region, the average depth value of the point cloud clusters within the pixel region is calculated, and the average depth value is used as the pixel value of the pixel region. The torso depth information is obtained by acquiring the pixel values of each pixel region.
3. The method as described in claim 1 or 2, characterized in that: The trunk depth information includes the depth information of each trunk segment; Determining the user's torso contour information based on the torso depth information includes: From the trunk depth information, obtain the depth information corresponding to each trunk segment; For each of the torso segments, the contour information of the torso segment is determined based on the depth information of the torso segment; The trunk contour information includes the contour information of each trunk segment.
4. The method as described in claim 1, characterized in that, Determining the number of peaks and troughs in the contour curve of the torso segment includes: The contour curve of the torso segment is processed by removing zero values and noise to obtain the processed contour curve. The number of peaks and the number of troughs are determined based on the processed contour curve.
5. A device for measuring the trunk rotation angle of scoliosis, characterized in that, include: The acquisition unit is used to acquire the user's torso point cloud data. The determining unit is used to determine the user's torso depth information based on the torso point cloud data; It is also used to determine the user's torso contour information based on the torso depth information; A calculation unit is used to calculate the user's torso rotation angle based on the torso contour information; Specifically, the determining unit is used to determine the contour curve of the torso segment based on the depth information of the torso segment. Specifically, it is used to determine the number of peaks and troughs in the contour curve of the torso segment; Specifically, it is used to determine the spinous process of the spine based on the number of peaks and troughs; Specifically, it is used to determine the first stress point and the second stress point based on the length of the scoliosis measuring ruler and the spinous process point of the spine. The first stress point and the second stress point are the simulated stress points of the scoliosis measuring ruler. The contour information includes the location information of the spinous process of the spine, the first stress point, and the second stress point; The calculation unit is specifically used to calculate the trunk rotation angle based on the position information of the spinous process of the spine, the first stress point, and the second stress point.
6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method as described in any one of claims 1 to 4.
7. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 4.