Data processing methods, apparatus, electronic devices and storage media

Abstract

This invention discloses a data processing method, apparatus, electronic device, and storage medium. The method includes: determining a stimulation simulation model based on scanning data of the area to be detected and a pre-determined stimulation coil; determining a first relative position matrix based on first spatial information of at least three first marker points on the coil simulation model in the stimulation simulation model and second spatial information of at least three second marker points on the area simulation model in the stimulation simulation model; determining a second relative position matrix based on third spatial information of at least three first marker points in real space and fourth spatial information of at least three second marker points in real space; and determining positioning parameters of a positioning kit corresponding to the area to be detected based on the first and second relative position matrices. This embodiment achieves the effect of accurately calibrating the positioning accuracy parameters of the positioning kit.

Description

Technical Field

[0001] This invention relates to the field of medical technology, and in particular to a data processing method, apparatus, electronic device, and storage medium. Background Technology

[0002] Transcranial magnetic stimulation (TMS) is a neuromodulation technique that applies pulsed magnetic fields to the cerebral cortex. Applying pulsed magnetic fields to specific areas of the cerebral cortex can enable related treatments. Different areas of the brain have different functions; therefore, precise localization of the stimulation location is necessary in the clinical application of TMS.

[0003] Currently, transcranial magnetic stimulation coils are commonly used for precise positioning of stimulation sites. However, in practical applications, to determine the positioning accuracy of the stimulation coil, it is necessary to manually calculate relevant data or use third-party equipment to determine the positioning accuracy of the corresponding stimulation coil. This results in low efficiency in determining the positioning accuracy of the stimulation coil, hindering its widespread application. Summary of the Invention

[0004] This invention provides a data processing method, apparatus, electronic device, and storage medium to achieve accurate calibration of the positioning accuracy parameters of a positioning kit, thereby improving the efficiency of determining the positioning accuracy parameters.

[0005] According to one aspect of the present invention, a data processing method is provided, the method comprising:

[0006] Based on the scanning data of the area to be detected and the pre-determined stimulation coil, a stimulation simulation model is determined; wherein, the stimulation simulation model is constructed based on the area simulation model of the area to be detected and the coil simulation model of the stimulation coil.

[0007] Based on the first spatial information of at least three pre-determined first marker points on the coil simulation model in the stimulus simulation model in the model space, and the second spatial information of at least three pre-determined second marker points on the part simulation model in the stimulus simulation model in the model space, a first relative position matrix is ​​determined.

[0008] The third spatial information of the at least three first marker points in the real space and the fourth spatial information of the at least three second marker points in the real space are determined, and a second relative position matrix is ​​determined based on the third spatial information and the fourth spatial information;

[0009] Based on the first relative position matrix and the second relative position matrix, the positioning parameters of the positioning kit corresponding to the part to be detected are determined.

[0010] According to another aspect of the present invention, a data processing apparatus is provided, the apparatus comprising:

[0011] The stimulation simulation model determination module is used to determine the stimulation simulation model based on the scanning data of the site to be detected and the pre-determined stimulation coil; wherein, the stimulation simulation model is constructed based on the site simulation model of the site to be detected and the coil simulation model of the stimulation coil.

[0012] The first relative position matrix determination module is used to determine the first relative position matrix based on the first spatial information of at least three pre-determined first marker points on the coil simulation model in the stimulus simulation model in the model space, and the second spatial information of at least three pre-determined second marker points on the part simulation model in the stimulus simulation model in the model space.

[0013] The second relative position matrix determination module is used to determine the third spatial information of the at least three first marker points in the real space, and the fourth spatial information of the at least three second marker points in the real space, and to determine the second relative position matrix based on the third spatial information and the fourth spatial information;

[0014] The positioning parameter determination module is used to determine the positioning parameters of the positioning kit corresponding to the part to be detected based on the first relative position matrix and the second relative position matrix.

[0015] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0016] At least one processor; and

[0017] A memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the data processing method according to any embodiment of the present invention.

[0019] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the data processing method described in any embodiment of the present invention.

[0020] The technical solution of this invention, based on the scanning data of the area to be detected and a pre-determined stimulation coil, determines a stimulation simulation model. Then, based on the first spatial information of at least three pre-determined first marker points on the coil simulation model in the stimulation simulation model and the second spatial information of at least three pre-determined second marker points on the area simulation model in the stimulation simulation model, a first relative position matrix is ​​determined. Further, the third spatial information of at least three first marker points in real space and the fourth spatial information of at least three second marker points in real space are determined, and a second relative position matrix is ​​determined based on the third and fourth spatial information. Finally, based on the first and second relative position matrices, the positioning parameters of the positioning kit corresponding to the area to be detected are determined. This solves the problems of inaccurate determination of positioning accuracy parameters of the positioning kit in the prior art, as well as the cumbersome and inefficient process of determining positioning accuracy parameters. It achieves the effect of accurate calibration of positioning accuracy parameters of the positioning kit, improves the efficiency of determining positioning accuracy parameters, and thus enhances the promotion value and market application prospects of the positioning kit.

[0021] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a flowchart of a data processing method provided according to Embodiment 1 of the present invention;

[0024] Figure 2 This is a schematic diagram of a part simulation model provided according to Embodiment 2 of the present invention;

[0025] Figure 3 This is a schematic diagram of the coil simulation model provided according to Embodiment 2 of the present invention;

[0026] Figure 4 This is a schematic diagram of the target point provided in Embodiment 2 of the present invention;

[0027] Figure 5 This is a schematic diagram of the coil stimulation hot spot provided according to Embodiment 2 of the present invention;

[0028] Figure 6 This is a schematic diagram of the stimulus simulation model provided in Embodiment 2 of the present invention;

[0029] Figure 7 This is a schematic diagram of the stimulus simulation model provided in Embodiment 2 of the present invention;

[0030] Figure 8 This is a schematic diagram of the first marker point set on the coil simulation model provided according to Embodiment 2 of the present invention;

[0031] Figure 9 This is a schematic diagram of the second marker point set on the part simulation model provided according to Embodiment 2 of the present invention;

[0032] Figure 10 This is a schematic diagram of the part entity model, coil entity model and outer positioning entity model provided in Embodiment 2 of the present invention;

[0033] Figure 11 This is a schematic diagram of the first combined entity model provided according to Embodiment 2 of the present invention;

[0034] Figure 12 This is a schematic diagram of the second combined entity model provided according to Embodiment 2 of the present invention;

[0035] Figure 13 This is a schematic diagram of the structure of a data processing device according to Embodiment 3 of the present invention;

[0036] Figure 14 This is a schematic diagram of the structure of an electronic device that implements the data processing method of the present invention. Detailed Implementation

[0037] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0038] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0039] Example 1

[0040] Figure 1 This is a flowchart of a data processing method provided in Embodiment 1 of the present invention. This embodiment is applicable to the calibration of the positioning accuracy parameters of the positioning kit matched to the part to be detected. This method can be executed by a data processing device, which can be implemented in hardware and / or software, and can be configured in a terminal and / or server. Figure 1 As shown, the method includes:

[0041] S110. Based on the scanning data of the area to be detected and the pre-determined stimulation coil, determine the stimulation simulation model.

[0042] In this embodiment, the site to be detected can be the site to be subjected to neuromodulation stimulation. The site to be detected can be any part of the target object, optionally the head. The target object can be any object, optionally a human or an animal. Neuromodulation can include non-invasive and invasive neuromodulation. Non-invasive neuromodulation stimulation can be transcranial magnetic stimulation, or other methods such as ultrasound or electric fields. Invasive neuromodulation can be deep electrical stimulation, etc. The scanning data can be relevant data information obtained after scanning the site to be detected using a scanning device. For example, the scanning data can include, but is not limited to, CT (Computed Tomography) images or MRI (Magnetic Resonance Imaging) images. It should be noted that the scanning data can be acquired in real time from medical imaging equipment, acquired from an image database, or received from external scanning data transmission devices. This embodiment does not specifically limit this.

[0043] The stimulation coil can be a coil used to perform neuromodulation stimulation on the site to be tested. The stimulation coil can be any type of coil, optionally including circular coils, figure-eight coils, and biconical coils, etc.

[0044] The stimulation simulation model is constructed based on a site simulation model of the detection site and a coil simulation model of the stimulation coil. In this embodiment, the stimulation simulation model can be a combination of the site simulation model and the stimulation simulation model. This model can also be used to represent the process of stimulating the target point in the detection site to be subjected to neuromodulation stimulation based on the stimulation coil.

[0045] In practical applications, the stimulation simulation model is a model obtained by combining the site simulation model of the detection site and the coil simulation model of the stimulation coil according to a preset combination posture. Therefore, the site simulation model and the coil simulation model can be determined first, and then the stimulation simulation model can be constructed based on the site simulation model and the coil simulation model.

[0046] Optionally, a stimulation simulation model is determined based on the scanning data of the area to be detected and a pre-determined stimulation coil, including: constructing a site simulation model based on the scanning data of the area to be detected, and constructing a coil simulation model based on the stimulation coil; determining the target position on the site simulation model based on the pre-determined target point in the site simulation model, and determining the target posture of the coil simulation model at the target position; and constructing a stimulation simulation model based on the target position, target posture, coil simulation model, and site simulation model.

[0047] The site simulation model can be a three-dimensional simulation model constructed based on the site to be detected. For example, if the site to be detected is the head, the site simulation model can be a scalp simulation model and a brain simulation model. In practical applications, after obtaining the scan data of the site to be detected, image segmentation, smoothing, and three-dimensional isosurface reconstruction can be performed on the scan data to obtain the site simulation model. The coil simulation model can be a three-dimensional simulation model constructed based on the stimulation coil. It should be noted that the coil simulation model can be a three-dimensional structural model image of the stimulation coil obtained through image segmentation and three-dimensional reconstruction, or it can be a three-dimensional simulation model manufactured by the manufacturer using the stimulation coil shell.

[0048] In this embodiment, the target point can be a target point in the detection site that needs to be stimulated during subsequent neural modulation stimulation. The target position can be the installation position of the stimulation coil on the detection site during subsequent neural modulation stimulation, that is, the installation position of the coil simulation model on the site simulation model. The target posture can be the placement posture of the stimulation coil during subsequent neural modulation stimulation, that is, the placement posture of the coil simulation model on the site simulation model.

[0049] In practical applications, the position of the target point is first determined in the part simulation model, along with its horizontal, vertical, and axial directions. Then, starting from the target point, a target ray is emitted along the vertical direction. Based on the intersection of the target ray and the part simulation model, the target position of the coil simulation model on the part simulation model is determined. Furthermore, when the horizontal direction of the coil simulation model aligns with the horizontal direction of the target point, and the vertical direction of the coil simulation model aligns with the vertical direction of the target point, the current posture of the coil simulation model is determined as the target posture. Finally, the strongest point of the stimulus signal in the stimulus coil is determined, and the matching position of the coil simulation model is determined based on this strongest point. Using this matching position and the target position as alignment points, the coil simulation model is combined with the target posture and the part simulation model, and the combined model is used as the stimulus simulation model.

[0050] S120. Based on the first spatial information of at least three pre-determined first marker points on the coil simulation model in the stimulus simulation model in the model space, and the second spatial information of at least three pre-determined second marker points on the part simulation model in the stimulus simulation model in the model space, determine the first relative position matrix.

[0051] The first marker point can be a reference point pre-determined on the coil simulation model. Those skilled in the art should understand that the model space can be a three-dimensional virtual space, within which a corresponding three-dimensional simulation model can be constructed based on user requirements. In this embodiment, the model space can be the three-dimensional image space corresponding to simulation models such as the coil simulation model and the part simulation model. Correspondingly, the first spatial information can be information representing the spatial position of the first marker point in the model space. For example, the first spatial information can be the spatial coordinates of the first marker point in the model space. The second marker point can be a reference point pre-determined on the part simulation model. Correspondingly, the second spatial information can be information representing the spatial position of the second marker point in the model space. For example, the second spatial information can be the spatial coordinates of the second marker point in the model space. The first relative position matrix can represent the relative positional relationship between the first coordinate system constructed based on the first spatial information of the first marker point and the second coordinate system constructed based on the second spatial information of the second marker point.

[0052] In practical applications, at least three first marker points can be determined on the coil simulation model according to the preset marker point positions. At the same time, at least three second marker points can be determined on the part simulation model according to the preset marker point positions. Then, when the part simulation model and the coil simulation model are combined to obtain the stimulation simulation model, the first spatial information of these first marker points set on the coil simulation model in the model space can be obtained. At the same time, the second spatial information of these second marker points set on the part simulation model in the model space can be obtained. Furthermore, a first coordinate system can be constructed based on the first spatial information of these first marker points, and the corresponding coordinate system matrix can be determined. At the same time, a corresponding second coordinate system can be constructed based on the second spatial information of these second marker points, and the corresponding coordinate system matrix can be determined. Thus, the first relative position matrix can be determined based on these two coordinate system matrices.

[0053] It should be noted that the number of first marker points (or second marker points) is at least three, but can be three or more. If there are three first marker points (or second marker points), these three first marker points (or second marker points) can be marked on the coil simulation model according to the preset marker point setting positions. If there are multiple first marker points (or second marker points), three of these first marker points (or second marker points) can be marked on the coil simulation model according to the preset marker point setting positions, and the remaining first marker points (or second marker points) can be in any position. The preset marker point setting positions can be that the three first marker points (or second marker points) form a right triangle on the same plane. For example, if the first marker points are points A, B, and C, then the line connecting points A and B is perpendicular to the line connecting points A and C.

[0054] Optionally, based on the first spatial information of at least three pre-determined first marker points on the coil simulation model in the stimulus simulation model in the model space, and the second spatial information of at least three pre-determined second marker points on the part simulation model in the stimulus simulation model in the model space, a first relative position matrix is ​​determined, including: constructing a first coordinate system matrix corresponding to a first coordinate system based on the first spatial information of at least three first marker points in the first space; and constructing a second coordinate system matrix corresponding to a second coordinate system based on the second spatial information of at least three second marker points in the first space; and determining the first relative position matrix based on the first coordinate system matrix and the second coordinate system matrix.

[0055] In this embodiment, the first coordinate system can be a coordinate system constructed based on the first spatial information of at least three first marker points in the model space. In practical applications, a target marker point can be selected from these three first marker points as the origin of the coordinate system. The vector between the target marker point and any one of the remaining marker points (excluding the target marker point) is used as the horizontal axis, and the vector between the target marker point and the last of the three first marker points is used as the vertical axis. The product of these two vectors is then used as the vertical axis to obtain the first coordinate system. Correspondingly, the first coordinate system matrix can be the coordinate representation matrix of the first coordinate system in the model space. The second coordinate system can be a coordinate system constructed based on the second spatial information of at least three second marker points in the model space. It should be noted that the construction process of the second coordinate system is the same as that of the first coordinate system, and will not be described in detail here. The second coordinate system matrix can be the coordinate representation matrix of the second coordinate system in the model space.

[0056] In practical applications, after determining the first spatial information of the first marker point in the model space and the second spatial information of the second marker point in the model space, a first coordinate system can be constructed based on the first spatial information of the first marker point, and the first coordinate system matrix corresponding to the first coordinate system can be determined. At the same time, a second coordinate system can be constructed based on the second spatial information of the second marker point, and the second coordinate system matrix corresponding to the second coordinate system can be determined. Furthermore, the first coordinate system matrix and the second coordinate system matrix are processed to finally obtain the first relative position matrix.

[0057] For example, if the first marker points are points A, B, and C, and the first spatial information of these three first marker points in the model space are respectively (X... A ,Y A Z A ), (X B ,Y B Z B ) and (X C ,Y C Z C Let point A be the origin of the first coordinate system. It can represent the X-axis of the first coordinate system. It can represent the Y-axis of the first coordinate system. and The vector product of can represent the Z-axis of the first coordinate system, and the matrix of the first coordinate system can be expressed based on the following formula:

[0058] C c =[X coil ,Y coil Z coil O coil ]

[0059] in,

[0060] O coil =(X A ,Y A Z A ,1) T ;

[0061]

[0062]

[0063]

[0064] Substituting the above formula into C c =[X coil ,Y coil ,Z,O coil From this, we can obtain:

[0065]

[0066] Among them, C c It can represent the first coordinate system, X coil It can represent the X-axis and Y-axis of the first coordinate system. coil It can represent the Y-axis and Z-axis of the first coordinate system. coil It can represent the Z-axis of the first coordinate system, O coil It can represent the origin of the first coordinate system.

[0067] Similarly, if the second marker points are D, E, and F, and the second spatial information of these three second marker points in the model space are respectively (X... D ,Y D Z D ), (X E ,Y E Z E ) and (X F ,Y F Z F (), with point D as the origin of the second coordinate system, It can represent the X-axis of the second coordinate system. It can represent the Y-axis of the second coordinate system. and The vector product of can represent the Z-axis of the second coordinate system, and the matrix of the second coordinate system can be expressed based on the following formula:

[0068] C s =[X head ,Y head Z head O head ]

[0069] in,

[0070] O head =(X D ,Y D Z D ,1) T ;

[0071]

[0072]

[0073]

[0074] Substituting the above formula into C s =[X head ,Y head Z head O head From this, we can obtain:

[0075]

[0076] Among them, C s It can represent a second coordinate system, X head It can represent the X-axis and Y-axis of the second coordinate system. head It can represent the Y-axis and Z-axis of the second coordinate system. head It can represent the Z-axis of the second coordinate system, O head It can represent the origin of the second coordinate system.

[0077] Optionally, determining the first relative position matrix based on the first coordinate system matrix and the second coordinate system matrix includes: performing orthogonalization on the first coordinate system matrix to obtain a first orthogonal unit matrix; and performing orthogonalization on the second coordinate system matrix to obtain a second orthogonal unit matrix; and determining the first relative position matrix based on the first orthogonal unit matrix and the second orthogonal unit matrix.

[0078] In this embodiment, the first identity orthogonal matrix can be the matrix obtained by normalizing and orthogonalizing the first coordinate system matrix. Similarly, the second identity orthogonal matrix can be the matrix obtained by normalizing and orthogonalizing the first coordinate system matrix.

[0079] In practical applications, after obtaining the first coordinate system matrix and the second coordinate system matrix, the first coordinate system matrix and the second coordinate system matrix can be processed according to the matrix normalization formula and the matrix orthogonalization formula respectively to obtain the first orthogonal identity matrix and the second orthogonal identity matrix. Further, the inverse matrix of the first orthogonal identity matrix is ​​determined, and then the product between the inverse matrix and the second orthogonal identity matrix is ​​determined, and the product is used as the first relative position matrix.

[0080] It should be noted that when determining the first relative position matrix, after obtaining the first orthogonal identity matrix and the second orthogonal identity matrix, the inverse matrix of the second orthogonal identity matrix can also be determined. Then, the product between the inverse matrix and the first orthogonal identity matrix is ​​determined, and this product is used as the first relative position matrix.

[0081] For example, the first relative position matrix can be represented based on the following formula:

[0082] E1=T_Cc -1 *T_Cs

[0083] Where T_Cc can represent the first identity orthogonal matrix, T_Cs can represent the second identity orthogonal matrix, and E1 can represent the first relative position matrix.

[0084] S130. Determine the third spatial information of at least three first marker points in the real space, and the fourth spatial information of at least three second marker points in the real space, and determine the second relative position matrix based on the third spatial information and the fourth spatial information.

[0085] Those skilled in the art should understand that real space can be an objectively existing three-dimensional space in the real world, that is, the three-dimensional space where real objects reside. Third spatial information can be information representing the spatial position of the first marker point in real space. For example, the third spatial information can be the spatial coordinates of the first marker point in real space. Fourth spatial information can be information representing the spatial position of the second marker point in real space. For example, the fourth spatial information can be the spatial coordinates of the second marker point in real space.

[0086] In practical applications, the third and fourth spatial information are both spatial location information of the corresponding marker points in the real space. Therefore, when determining the third and fourth spatial information, we can first determine the entity model of the corresponding simulation model, and then determine the spatial location information of each marker point on the corresponding entity model, thereby obtaining the third and fourth spatial information.

[0087] Optionally, determining the third spatial information of at least three first marker points in real space, and the fourth spatial information of at least three second marker points in real space, includes: determining the part entity model, the coil entity model, and the outer positioning entity model based on the part simulation model, the coil simulation model, and the outer positioning entity model used for wrapping the stimulation simulation model; combining the part entity model, the coil entity model, and the outer positioning entity model according to a preset combination posture to obtain a first combined entity model; acquiring the first laser scanning data corresponding to the first combined entity model, and determining the third spatial information of at least three first marker points in real space and the fourth spatial information of at least three second marker points in real space based on the first laser scanning data.

[0088] In this embodiment, the outer positioning model can be a model covering the stimulus simulation model, i.e., the three-dimensional model corresponding to the subsequent positioning kit. In practical applications, the coil simulation model is set at the target position on the part simulation model, and the coil simulation model is adjusted to the target posture. Then, the combined model of the coil simulation model and the part simulation model is used as the stimulus simulation model. Furthermore, a shell is covered on the outside of the stimulus simulation model, and the shell is used as the outer positioning model. It can be considered that the stimulus simulation model is a solid model and the outer positioning model is a hollow model.

[0089] The component entity model can be a solid model prepared based on a virtual component simulation model. The coil entity model can be a solid model prepared based on a virtual coil simulation model. The outer layer positioning entity model can be a solid model prepared based on a virtual outer layer positioning model. In practical applications, the specific method for preparing the entity model can be: based on molding technology, using the virtual simulation model as a template to prepare the corresponding entity model, wherein the molding technology can include 3D printing, injection molding, or other molding technologies that can materialize the virtual simulation model.

[0090] It should be noted that, to facilitate subsequent laser scanning of the physical models and to quickly obtain the spatial position information of the corresponding marker points from the laser scanning data, before materializing each virtual simulation model, for each first marker point, a 3D model can be constructed with the current first marker point as the center and an arbitrary radius as the model radius; similarly, for each second marker point, a 3D model can be constructed with the current second marker point as the center and an arbitrary radius as the model radius. Further materializing the coil simulation model yields a coil physical model including multiple 3D physical models, each located at the corresponding first marker point position; similarly, materializing the part simulation model yields a part physical model including multiple 3D physical models, each located at the corresponding second marker point position. The 3D model can be any model, optionally a sphere.

[0091] The preset combined posture can be a pre-set posture used to define the combined posture of the three entity models. The first combined entity model can be a combined entity model obtained by combining the part entity model, the coil entity model, and the outer positioning entity model.

[0092] In practical applications, the component simulation model, coil simulation model, and outer positioning model can first be processed separately using molding technology to obtain component entity models, coil entity models, and outer positioning entity models. Then, these entity models can be combined according to a preset arrangement. This combined entity model can then be used as the first combined entity model. Further, the first combined entity model is laser-scanned using a laser scanning device to obtain first laser scan data. This first laser scan data can be the 3D point cloud data corresponding to the first combined entity model.

[0093] Furthermore, after obtaining the first laser scanning data, the laser scanning data of each three-dimensional entity model can be extracted from the first laser scanning data. For each three-dimensional entity model, the laser scanning data of the current three-dimensional entity model can be fitted to obtain the center point data corresponding to the current three-dimensional entity model. The center point data obtained at this time can be used as the spatial information of the marker point corresponding to the current three-dimensional entity model in the real space. Thus, the third spatial information of each first marker point in the real space and the fourth spatial information of each second marker point in the real space can be obtained.

[0094] In practical applications, after obtaining the third spatial information of each first marker point in real space and the fourth spatial information of each second marker point in real space, a second relative position matrix can be determined based on the third spatial information of the first marker points and the fourth spatial information of the second marker points. The second relative position matrix can represent the relative positional relationship between the third coordinate system constructed based on the third spatial information of the first marker points and the fourth coordinate system constructed based on the fourth spatial information of the second marker points.

[0095] It should be noted that the process of determining the second relative position matrix is ​​the same as that of determining the first relative position matrix, and will not be described in detail here.

[0096] For example, the second relative position matrix can be represented based on the following formula:

[0097] E2=T_Cc′ -1 *T_Cs′

[0098] Where T_Cc′ can represent the third unit orthogonal matrix corresponding to the third coordinate system matrix, T_Cs′ can represent the fourth unit orthogonal matrix corresponding to the fourth coordinate system matrix, and E2 can represent the second relative position matrix.

[0099] S140. Based on the first relative position matrix and the second relative position matrix, determine the positioning parameters of the positioning kit corresponding to the part to be detected.

[0100] In this embodiment, the positioning parameters can be parameters characterizing the positioning accuracy of the positioning kit. Optionally, the positioning parameters may include positioning translation error and / or positioning angle error.

[0101] In practical applications, the coil entity model, component entity model, and outer positioning model are all prepared proportionally based on the corresponding virtual simulation model. Ideally, the relative positional relationships in the model space and the relative positional relationships in the real space should be equal, i.e., E1 = E2. However, there will be certain errors in the actual model preparation process and the actual model scanning process. Furthermore, there will also be certain errors in the combination and fitting of entity models. Therefore, E1 and E2 are not equal. At this time, the corresponding error can be determined based on the difference between the two relative position matrices, and the final error can be used as the positioning parameter of the positioning kit in the actual application process and calibrated on the corresponding positioning kit.

[0102] In practical applications, positioning parameters include positioning translation error and / or positioning angle error. The determination process of these two parameters is explained below:

[0103] Optionally, when the positioning parameter is the positioning translation error, the positioning parameters of the positioning kit corresponding to the part to be detected are determined based on the first relative position matrix and the second relative position matrix, including: subtracting the first relative position matrix and the second relative position matrix to obtain a first error matrix, and determining the positioning translation error in the positioning parameters of the positioning kit corresponding to the part to be detected based on the first error matrix.

[0104] The first error matrix can be a matrix representing the difference between two matrices.

[0105] In practical applications, after obtaining the first and second relative position matrices, the difference between them can be calculated to determine the difference between the two relative position matrices. This difference matrix can then be used as the first error matrix. Furthermore, the last vector value of each row in the first error matrix can be extracted, each extracted vector value can be squared, and the squares can be summed to obtain a sum of squares. Then, the square root of this sum of squares can be taken as the positioning translation error.

[0106] For example, the first error matrix and the positioning translation error can be represented by the following formula:

[0107] Error1 = E1 - E2

[0108]

[0109] Where Error1 can represent the first error matrix, and T_error1 can represent the positioning and translation error. 1,4 This can represent the vector value in the first row and fourth column of the first error matrix. (Error1) 2,4 This can represent the vector value in the second row and fourth column of the first error matrix. (Error1) 3,4 This can represent the vector value in the third row and fourth column of the first error matrix. (Error1) 4,4 It can represent the vector value in the fourth row and fourth column of the first error matrix.

[0110] Optionally, the positioning parameter is the positioning angle error. Based on the first relative position matrix and the second relative position matrix, the positioning parameters of the positioning kit corresponding to the part to be detected are determined, including: determining the inverse matrix of the second relative position matrix, and determining the product of the inverse matrix and the first relative position matrix to obtain the second error matrix. Based on the second error matrix, the positioning angle error in the positioning parameters of the positioning kit corresponding to the part to be detected is determined.

[0111] In this embodiment, after obtaining the first relative position matrix and the second relative position matrix, the inverse matrix of the second relative position matrix can be determined first, and then the inverse matrix can be multiplied by the first relative position matrix. The matrix obtained after multiplication can be used as the second error matrix. Furthermore, the second error matrix can be used as the rotation and translation matrix in coordinate transformation, and the second relative matrix can be converted into the form of axis angle representation. That is, the second error matrix can be converted into an axis angle composed of two parts: the rotation axis and the rotation angle around the rotation axis. At this time, the absolute value of the rotation angle can be used as the positioning angle error.

[0112] For example, the second error matrix can be represented based on the following formula:

[0113] Error2 = E1 * E2 -1

[0114] Furthermore, assuming (k, θ) represents the axis angle of Error2, the positioning angle error is:

[0115] R_error1=|θ|

[0116] Here, Error2 can represent the second error matrix, k can represent the rotation axis corresponding to the second error matrix, θ can represent the rotation angle corresponding to the second error matrix, and R_error1 can represent the positioning angle error.

[0117] In practical applications, after determining the positioning parameters of the positioning kit corresponding to the part to be detected, the obtained positioning parameters can be tested to determine whether the positioning translation error and positioning angle error determined based on the technical solution provided in this embodiment are accurate.

[0118] Based on this, and building upon the aforementioned technical solutions, the method further includes: combining the part simulation model, the coil simulation model, and the outer positioning model used for wrapping the stimulation simulation model according to a preset combination posture to obtain a combined simulation model; determining a second combined entity model based on the combined simulation model; acquiring second laser scanning data corresponding to the second combined entity model, and determining, based on the second laser scanning data, the fifth spatial information of at least three first marker points in real space and the sixth spatial information of at least three second marker points in real space; determining a third relative position matrix based on the fifth and sixth spatial information; and determining detection parameters for evaluating the positioning parameters of the positioning kit based on the first and third relative position matrices.

[0119] In this embodiment, the combined simulation model can be a simulation model obtained by combining the part simulation model, the coil simulation model, and the outer positioning model in the model space. Correspondingly, the second combined solid model can be a solid model prepared based on the virtual combined simulation model. It should be noted that the second combined solid model is a single, integrated model; that is, it is a single model directly prepared by solidifying the combined simulation model using molding technology. The second laser scanning data can be three-dimensional point cloud data obtained by scanning the second combined solid model using a laser scanning device.

[0120] In practical applications, the component simulation model, coil simulation model, and outer positioning model can be set to an editable state. Users can move these models using input devices or their fingers. Then, based on the user's movement input, these three simulation models can be combined according to a preset combination posture to obtain a combined simulation model. Alternatively, parameters corresponding to the preset combination posture can be predetermined. Then, when the component simulation model, coil simulation model, and outer positioning model are obtained, the predetermined parameters can be input using input devices to combine them according to the preset combination posture to obtain a combined simulation model. Furthermore, the combined simulation model can be solidified using molding technology to obtain a second combined solid model. Then, the second combined solid model can be laser-scanned using a laser scanning device to obtain second laser scan data.

[0121] It should be noted that the process of determining the fifth spatial information of the first marker point in the real space and the sixth spatial information of the second marker point in the real space based on the second laser scanning data is the same as the process of determining the third spatial information of the first marker point in the real space and the fourth spatial information of the second marker point in the real space based on the first laser scanning data. This embodiment will not elaborate on the details here.

[0122] It should also be noted that the process of determining the third relative position matrix based on the fifth and sixth spatial information is the same as the process of determining the second relative position matrix based on the third and fourth spatial information, and will not be described in detail here.

[0123] For example, the third relative position matrix can be represented based on the following formula:

[0124] E3=T_Cc″ -1 *T_Cs″

[0125] Where T_Cc″ can represent the fifth unit orthogonal matrix, T_Cs″ can represent the sixth unit orthogonal matrix, and E3 can represent the third relative position matrix.

[0126] Furthermore, after obtaining the third relative position matrix, detection parameters for evaluating the positioning parameters of the positioning kit can be determined based on the third relative position matrix and the first relative position matrix. Optionally, the detection parameters include translation detection error and / or angle detection error. Specifically, the difference between the first and third relative position matrices is used to obtain the third error matrix. Then, the last vector value of each row in the third error matrix can be extracted, each extracted vector value is squared, and the squares are summed to obtain a sum of squares. The square root of this sum is then taken as the translation detection error.

[0127] For example, the third error matrix and translation detection error can be represented by the following formula:

[0128] Error3 = E1 - E3

[0129]

[0130] Where Error3 can represent the third error matrix, T_error2 can represent the translation detection error, and Error3... 1,4 This can represent the vector value in the first row and fourth column of the third error matrix. (Error3) 2,4 This can represent the vector value in the second row and fourth column of the third error matrix. (Error3) 3,4 This can represent the vector value in the third row and fourth column of the third error matrix. (Error3) 4,4 It can represent the vector value in the fourth row and fourth column of the third error matrix.

[0131] Simultaneously, the inverse matrix of the third relative position matrix is ​​determined, and the inverse matrix is ​​multiplied by the first relative position matrix to obtain the fourth error matrix. Furthermore, the fourth error matrix can be converted into an axis-angle representation, that is, the fourth error matrix is ​​converted into an axis-angle consisting of a rotation axis and a rotation angle. At this time, the absolute value of the rotation angle can be used as the angle detection error.

[0132] For example, the fourth error matrix can be represented based on the following formula:

[0133] Error4 = E1 * E3 -1

[0134] Furthermore, assuming (k′, θ′) is the axis-angle representation of Error4, then the angle detection error is:

[0135] R_error2=|θ′|

[0136] Here, Error4 can represent the fourth error matrix, k′ can represent the rotation axis corresponding to the fourth error matrix, θ′ can represent the rotation angle corresponding to the fourth error matrix, and R_error2 can represent the angle detection error.

[0137] The technical solution of this invention, based on the scanning data of the area to be detected and a pre-determined stimulation coil, determines a stimulation simulation model. Then, based on the first spatial information of at least three pre-determined first marker points on the coil simulation model in the stimulation simulation model and the second spatial information of at least three pre-determined second marker points on the area simulation model in the stimulation simulation model, a first relative position matrix is ​​determined. Further, third spatial information and fourth spatial information of at least three first marker points in world space are determined, and based on the third and fourth spatial information, a second relative position matrix is ​​determined. Finally, based on the first and second relative position matrices, the positioning parameters of the positioning kit corresponding to the area to be detected are determined. This solves the problems of inaccurate determination of positioning accuracy parameters of the positioning kit in the prior art, as well as the cumbersome and inefficient process of determining positioning accuracy parameters. It achieves the effect of accurate calibration of positioning accuracy parameters of the positioning kit, improves the efficiency of determining positioning accuracy parameters, and thus enhances the promotion value and market application prospects of the positioning kit.

[0138] Example 2

[0139] Figures 2 to 12 This is a flowchart of a data processing method provided in Embodiment 2 of the present invention. This embodiment is a preferred embodiment of the above-described embodiments. See also... Figures 2 to 12 As shown, taking the head simulation model (including the brain simulation model and the scalp simulation model) as an example, and the stimulation coil as an 8-shaped coil, the method of this embodiment of the invention may include the following steps:

[0140] 1. Obtain MRI or CT images of the target object's head. After image segmentation and 3D isosurface reconstruction, obtain a simulation model of the target object's head. (See [link to relevant documentation]). Figure 2 As shown;

[0141] 2. Determine the stimulation coil. Obtain a coil simulation model of the stimulation coil through 3D laser scanning and point cloud reconstruction. (See [link to relevant documentation]). Figure 3 As shown;

[0142] 3. Set target points on the brain simulation model in the head simulation model obtained in step 1, and determine the position and orientation of the target points (i.e., Figure 4 (The direction indicated by the middle arrow);

[0143] 4. Set up coil stimulation hotspots on the coil simulation model obtained in step 2, and determine the position and direction of the coil stimulation hotspots (i.e., Figure 5 (The direction indicated by the middle arrow), where the coil stimulation hotspot is the location and direction of the maximum magnetic field output;

[0144] 5. Calculate the intersection of the Z-axis of the target and the scalp simulation model. Determine the planned coil position at a certain distance (distance parameter can be set) along the Z-axis from the intersection point, and set the coil simulation model at the planned coil position. Simultaneously, ensure that the Z-axis of the coil stimulation hotspot coincides with the Z-axis of the target point. At this point, the combined model of the current coil simulation model and the head simulation model can be used as the stimulation simulation model. See [link to relevant documentation]. Figure 6 and Figure 7 As shown;

[0145] 6. Set three small balls with a diameter of 20 mm (parameters not fixed) on the coil simulation model, and define them as ball A, ball B, and ball C respectively. The center AB of ball A is perpendicular to the center AC of ball B. Figure 8 (The three small balls indicated by the middle arrow);

[0146] 7. Place three small spheres with a diameter of 20 mm (parameters not fixed) in front of the head simulation model, and define them as sphere D, sphere E, and sphere F respectively. The center of sphere DE is perpendicular to the center of sphere DF (i.e., ...). Figure 9 (The three small balls indicated by the middle arrow);

[0147] 8. Obtain the coordinates of the centers of the six spheres in the model space as follows: (X...) A ,Y A Z A ), (X B ,Y B Z B ), (X C ,Y C Z C ), (X D ,Y D Z D ), (X E ,Y E Z E ) and (X F ,Y F Z F ).

[0148] 9. Construct two regional coordinate systems C using points A, B, and C, and points D, E, and F respectively. c and C s Point A is C. c Origin of coordinate system C c The X-axis, Cc The Y-axis, and The vector product is C c The Z-axis, then C c The coordinates in the model space are represented as follows:

[0149] C c =[X coil ,Y coil Z coil O coil ]

[0150] in,

[0151] O coil =(X A ,Y A Z A ,1) T ;

[0152]

[0153]

[0154]

[0155] Meanwhile, taking point D as C s The origin of the coordinate system C s The X-axis, C s Y-axis, and

[0156] The vector product is C s The Z-axis, then C s It can be expressed based on the following formula:

[0157] C s =[X head ,Y head Z head O head ]

[0158] in,

[0159] O head =(X D ,Y D Z D ,1) T ;

[0160]

[0161]

[0162]

[0163] 10. Regarding C c and C s After performing unit orthogonalization, we obtain C. c and C s The identity orthogonal matrices T_Cc and T_Cs;

[0164] 11. Determine the coordinate system C for the two regions. c and C s First relative position matrix:

[0165] E1=T_Cc -1 *T_Cs

[0166] 12. 3D print the part simulation model, coil simulation model, and outer positioning model respectively to obtain the corresponding solid models. See [link / reference]. Figure 10 As shown;

[0167] 13. Combine the individual entity models to obtain the first combined entity model. See [link / reference]. Figure 11 As shown, based on the 3D laser scanning of the first combined solid model, the first laser scanning data is obtained. Based on the first laser scanning data, the three-dimensional coordinate data of the six spheres are obtained. The three-dimensional coordinate data of each sphere is fitted to obtain the coordinate position of the sphere's center, which is the spatial information of each sphere in real space, denoted as A′(X). A ′,Y A ′,Z A ′), (X B ′,Y B ′,Z B ′), (X C ′,Y C ′,Z C ′), (X D ′,Y D ′,Z D ′), (X E ′,Y E ′,Z E ′) and (X F ′,Y F ′,Z F ′);

[0168] 14. Based on the fitted sphere center coordinates, execute steps 9 to 11 to obtain the relative positional relationship between Cc′ and Cs′ in real space, i.e., the second relative position matrix:

[0169] E2=T_Cc′ -1 *T_Cs′

[0170] Where T_Cc′ is the orthogonal unit matrix corresponding to Cc′, T_Cs′ is the orthogonal unit matrix corresponding to Cs′, and E2 can represent the second relative position matrix.

[0171] 15. Based on the first relative error matrix and the second relative error matrix, determine the first error matrix and the second error matrix:

[0172] Error1=E1-E2; Error2=E1*E2 -1

[0173] 16. Based on the first error matrix, determine the positioning translation error:

[0174]

[0175] Where T_error1 is the positioning translation error, Error1 1,4 The vector value in the first row and fourth column of E1, Error1 2,4 The vector value in the second row and fourth column of E1, Error1 3,4 The vector value in the third row and fourth column of E1, Error1 4,4 It is the vector value in the fourth row and fourth column of E1.

[0176] 17. Based on the second error matrix, determine the positioning angle error:

[0177] Assuming (k, θ) represents the axis angle of Error2, then the positioning angle error is:

[0178] R_error1=|θ|

[0179] Where k is the rotation axis corresponding to Error2, θ is the rotation angle corresponding to Error2, and R_error1 is the positioning angle error.

[0180] 18. Combine the component simulation model, coil simulation model, and outer positioning model in model space, and 3D print the combined simulation model to obtain a single integrated solid model (i.e., the second integrated solid model). See [link to documentation]. Figure 12 As shown;

[0181] 19. Use 3D laser scanning to scan the second combined solid model, obtain the three-dimensional coordinates of the six spheres, and fit the coordinates of the sphere centers, denoted as A″(X). A ",Y A ",Z A "), (X B ",Y B ",Z B "), (X C ",YC ",Z C "), (X D ",Y D ",Z D "), (X E ",Y E ",Z E ") and (X F ",Y F ",Z F ");

[0182] 20. Based on the fitted sphere center coordinates, execute steps 9 to 11 to obtain the relative positional relationship between Cc″ and Cs″ in real space, i.e., the third relative position matrix:

[0183] E3=T_Cc″ -1 *T_Cs″

[0184] Where T_Cc″ is the orthogonal unit matrix corresponding to Cc″, T_Cs″ is the orthogonal unit matrix corresponding to Cs″, and E3 can represent the second relative position matrix;

[0185] 21. Based on the first and third relative error matrices, determine the third and fourth error matrices:

[0186] Error3=E1-E3; Error4=E1*E3 -1

[0187] 22. Determine the translation detection error based on the third error matrix:

[0188]

[0189] Where T_error2 is the translation detection error, and Error3 is the error. 1,4 The vector value in the first row and fourth column of E3, Error3 2,4 The vector value in the second row and fourth column of E3, Error3 3,4 The vector value in the third row and fourth column of E3, Error3 4,4 This is the vector value in the fourth row and fourth column of E3.

[0190] 23. Based on the fourth error matrix, determine the angle detection error:

[0191] Assuming (k′, θ′) represents the axis angle of Error4, the angle detection error is:

[0192] R_error2=|θ′|

[0193] Where k′ is the rotation axis corresponding to Error4, θ′ is the rotation angle corresponding to Error4, and R_error2 is the angle detection error.

[0194] The technical solution of this invention, based on the scanning data of the area to be detected and a pre-determined stimulation coil, determines a stimulation simulation model. Then, based on the first spatial information of at least three pre-determined first marker points on the coil simulation model in the stimulation simulation model and the second spatial information of at least three pre-determined second marker points on the area simulation model in the stimulation simulation model, a first relative position matrix is ​​determined. Further, third spatial information and fourth spatial information of at least three first marker points in world space are determined, and based on the third and fourth spatial information, a second relative position matrix is ​​determined. Finally, based on the first and second relative position matrices, the positioning parameters of the positioning kit corresponding to the area to be detected are determined. This solves the problems of inaccurate determination of positioning accuracy parameters of the positioning kit in the prior art, as well as the cumbersome and inefficient process of determining positioning accuracy parameters. It achieves the effect of accurate calibration of positioning accuracy parameters of the positioning kit, improves the efficiency of determining positioning accuracy parameters, and thus enhances the promotion value and market application prospects of the positioning kit.

[0195] Example 3

[0196] Figure 13 This is a schematic diagram of the structure of a data processing device provided in Embodiment 3 of the present invention. Figure 13 As shown, the device includes: a stimulus simulation model determination module 310, a first relative position matrix determination module 320, a second relative position matrix determination module 330, and a positioning parameter determination module 340.

[0197] The stimulation simulation model determination module 310 is used to determine a stimulation simulation model based on the scanning data of the site to be detected and a pre-determined stimulation coil; wherein the stimulation simulation model is constructed based on the site simulation model of the site to be detected and the coil simulation model of the stimulation coil.

[0198] The first relative position matrix determination module 320 is used to determine the first relative position matrix based on the first spatial information of at least three pre-determined first marker points on the coil simulation model in the stimulus simulation model in the model space, and the second spatial information of at least three pre-determined second marker points on the part simulation model in the stimulus simulation model in the model space.

[0199] The second relative position matrix determination module 330 is used to determine the third spatial information of the at least three first marker points in the real space and the fourth spatial information of the at least three second marker points in the real space, and to determine the second relative position matrix based on the third spatial information and the fourth spatial information.

[0200] The positioning parameter determination module 340 is used to determine the positioning parameters of the positioning kit corresponding to the part to be detected based on the first relative position matrix and the second relative position matrix.

[0201] The technical solution of this invention, based on the scanning data of the area to be detected and a pre-determined stimulation coil, determines a stimulation simulation model. Then, based on the first spatial information of at least three pre-determined first marker points on the coil simulation model in the stimulation simulation model and the second spatial information of at least three pre-determined second marker points on the area simulation model in the stimulation simulation model, a first relative position matrix is ​​determined. Further, the third spatial information of at least three first marker points in real space and the fourth spatial information of at least three second marker points in real space are determined, and a second relative position matrix is ​​determined based on the third and fourth spatial information. Finally, based on the first and second relative position matrices, the positioning parameters of the positioning kit corresponding to the area to be detected are determined. This solves the problems of inaccurate determination of positioning accuracy parameters of the positioning kit in the prior art, as well as the cumbersome and inefficient process of determining positioning accuracy parameters. It achieves the effect of accurate calibration of positioning accuracy parameters of the positioning kit, improves the efficiency of determining positioning accuracy parameters, and thus enhances the promotion value and market application prospects of the positioning kit.

[0202] Optionally, the stimulus simulation model determination module 310 includes: a simulation model construction unit, a target attitude determination unit, and a stimulus simulation model construction unit.

[0203] The simulation model building unit is used to build a simulation model of the part to be detected based on the scanning data of the part to be detected, and to build a simulation model of the coil based on the stimulation coil.

[0204] The target attitude determination unit is used to determine the target position on the part simulation model based on the pre-determined target point in the part simulation model, and to determine the target attitude of the coil simulation model at the target position;

[0205] The stimulus simulation model construction unit is used to construct the stimulus simulation model based on the target position, the target posture, the coil simulation model, and the part simulation model.

[0206] Optionally, the first relative position matrix determination module 320 includes: a first coordinate system matrix construction unit, a second coordinate system matrix construction unit, and a first relative position matrix determination unit.

[0207] The first coordinate system matrix construction unit is used to construct a first coordinate system matrix corresponding to the first coordinate system based on the first spatial information of the at least three first marker points in the model space; and

[0208] The second coordinate system matrix construction unit is used to construct a second coordinate system matrix corresponding to the second coordinate system based on the second spatial information of the at least three second marker points in the model space.

[0209] The first relative position matrix determination unit is used to determine the first relative position matrix based on the first coordinate system matrix and the second coordinate system matrix.

[0210] Optionally, the first relative position matrix determining unit includes: a first unit orthogonal matrix determining subunit, a second unit orthogonal matrix determining subunit, and a first relative position matrix determining subunit.

[0211] The first unit orthogonal matrix determines the sub-unit, used to perform orthogonalization processing on the first coordinate system matrix to obtain the first orthogonal unit matrix; and...

[0212] The second orthogonal identity matrix determines the sub-unit, which is used to orthogonalize the second coordinate system matrix to obtain the second orthogonal identity matrix.

[0213] The first relative position matrix determination sub-unit is used to determine the first relative position matrix based on the first orthogonal identity matrix and the second orthogonal identity matrix.

[0214] Optionally, the second relative position matrix determination module 330 includes: an entity model determination unit, a combined entity model determination unit, and a spatial information determination unit.

[0215] The entity model determination unit is used to determine the entity model of the part, the entity model of the coil, and the outer positioning entity model for wrapping the stimulus simulation model, respectively, based on the part simulation model, the coil simulation model, and the outer positioning entity model for wrapping the stimulus simulation model.

[0216] The combined entity model determination unit is used to combine the part entity model, the coil entity model and the outer positioning entity model according to a preset combination posture to obtain a first combined entity model;

[0217] The spatial information determination unit is used to acquire first laser scanning data corresponding to the first combined entity model, and based on the first laser scanning data, determine the third spatial information of the at least three first marker points in the real space and the fourth spatial information of the at least three second marker points in the real space.

[0218] Optionally, the positioning parameters include positioning translation error and / or positioning angle error. Accordingly, the positioning parameter determination module 340 includes: a first error matrix determination unit, a positioning translation error determination unit, and a positioning angle error determination unit.

[0219] The first error matrix determination unit is used to calculate the difference between the first relative position matrix and the second relative position matrix to obtain the first error matrix.

[0220] A positioning translation error determination unit is used to determine, based on the first error matrix, the positioning translation error in the positioning parameters of the positioning kit corresponding to the part to be detected; and / or,

[0221] The positioning angle error determination unit is used to determine the inverse matrix of the second relative position matrix, and to determine the product of the inverse matrix and the first relative position matrix to obtain a second error matrix. Based on the second error matrix, the positioning angle error in the positioning parameters of the positioning kit corresponding to the part to be detected is determined.

[0222] Optionally, the device further includes: a combined simulation model determination module, a second combined entity model determination module, a spatial information determination module, a relative position matrix determination module, and a detection parameter determination module.

[0223] The combined simulation model determination module is used to combine the part simulation model, the coil simulation model, and the outer positioning model used to wrap the stimulus simulation model according to a preset combination posture to obtain a combined simulation model.

[0224] The second combined entity model determination module is used to determine the second combined entity model based on the combined simulation model;

[0225] The spatial information determination module is used to acquire second laser scanning data corresponding to the second combined entity model, and based on the second laser scanning data, determine the fifth spatial information of the at least three first marker points in the real space and the sixth spatial information of the at least three second marker points in the real space;

[0226] The relative position matrix determination module is used to determine the third relative position matrix based on the fifth spatial information and the sixth spatial information;

[0227] The detection parameter determination module is used to determine detection parameters for evaluating the positioning parameters of the positioning kit based on the first relative position matrix and the third relative position matrix; wherein the detection parameters include translation detection error and / or angle detection error.

[0228] The data processing apparatus provided in the embodiments of the present invention can execute the data processing method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of executing the method.

[0229] Example 4

[0230] Figure 14 A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0231] like Figure 14 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0232] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0233] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as data processing methods.

[0234] In some embodiments, the data processing method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or mounted on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the data processing method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the data processing method by any other suitable means (e.g., by means of firmware).

[0235] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0236] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0237] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0238] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0239] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0240] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0241] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0242] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A data processing method, characterized by, The method comprises the following steps: determining a stimulation simulation model according to scanning data of a to-be-detected part and a predetermined stimulation coil, wherein the stimulation simulation model is constructed based on a part simulation model of the to-be-detected part and a coil simulation model of the stimulation coil; determining a first relative position matrix based on first spatial information of at least three first marker points predetermined on the coil simulation model in a model space and second spatial information of at least three second marker points predetermined on the part simulation model in the model space; determining third spatial information of the at least three first marker points in a real space and fourth spatial information of the at least three second marker points in the real space, and determining a second relative position matrix based on the third spatial information and the fourth spatial information; determining a positioning parameter of a positioning kit corresponding to the to-be-detected part based on the first relative position matrix and the second relative position matrix; The method for determining the third spatial information of the at least three first marker points in the real space and the fourth spatial information of the at least three second marker points in the real space comprises the following steps:

2. The method of claim 1, wherein, determining a part entity model, a coil entity model and an outer positioning entity model based on the part simulation model, the coil simulation model and an outer positioning model for wrapping the stimulation simulation model respectively; combining the part entity model, the coil entity model and the outer positioning entity model according to a preset combined posture to obtain a first combined entity model; obtaining first laser scanning data corresponding to the first combined entity model, and determining the third spatial information of the at least three first marker points in the real space and the fourth spatial information of the at least three second marker points in the real space based on the first laser scanning data. The method for determining the stimulation simulation model according to the scanning data of the to-be-detected part and the predetermined stimulation coil comprises the following steps:

3. The method of claim 1, wherein, constructing a part simulation model according to the scanning data of the to-be-detected part, and constructing a coil simulation model based on the stimulation coil; determining a target position on the part simulation model based on a target target point predetermined in the part simulation model, and determining a target posture of the coil simulation model at the target position; constructing the stimulation simulation model based on the target position, the target posture, the coil simulation model and the part simulation model. The method for determining the first relative position matrix based on the first spatial information of the at least three first marker points predetermined on the coil simulation model in the model space and the second spatial information of the at least three second marker points predetermined on the part simulation model in the model space comprises the following steps: constructing a first coordinate system matrix corresponding to a first coordinate system based on the first spatial information of the at least three first marker points in the model space; and constructing a second coordinate system matrix corresponding to a second coordinate system based on the second spatial information of the at least three second marker points in the model space. determine the first relative position matrix based on the first coordinate system matrix and the second coordinate system matrix.

4. The method of claim 3, wherein, The determination of the first relative position matrix based on the first coordinate system matrix and the second coordinate system matrix comprises: unit orthogonal processing of the first coordinate system matrix to obtain a first unit orthogonal matrix; and unit orthogonal processing of the second coordinate system matrix to obtain a second unit orthogonal matrix; determination of the first relative position matrix based on the first unit orthogonal matrix and the second unit orthogonal matrix.

5. The method of claim 1, wherein, The positioning parameters include positioning translation errors and / or positioning angle errors. Correspondingly, the determination of the positioning parameters of the positioning set corresponding to the to-be-detected part based on the first relative position matrix and the second relative position matrix comprises: differencing the first relative position matrix and the second relative position matrix to obtain a first error matrix, determination of the positioning translation errors in the positioning parameters of the positioning set corresponding to the to-be-detected part based on the first error matrix; and / or determination of an inverse matrix of the second relative position matrix and determination of a product of the inverse matrix and the first relative position matrix to obtain a second error matrix, and determination of the positioning angle errors in the positioning parameters of the positioning set corresponding to the to-be-detected part based on the second error matrix.

6. The method of claim 1, wherein, Further comprising: combining the part simulation model, the coil simulation model, and an outer positioning model for wrapping the stimulation simulation model according to a preset combined posture to obtain a combined simulation model; determination of a second combined entity model based on the combined simulation model; acquisition of second laser scanning data corresponding to the second combined entity model, and determination of fifth spatial information of the at least three first marker points in the real space and sixth spatial information of the at least three second marker points in the real space based on the second laser scanning data; determination of a third relative position matrix based on the fifth spatial information and the sixth spatial information; determination of a detection parameter for evaluating the positioning parameters of the positioning set based on the first relative position matrix and the third relative position matrix; wherein the detection parameter includes a translation detection error and / or an angle detection error.

7. A data processing apparatus, characterized by, Comprising: a stimulation simulation model determination module configured to determine a stimulation simulation model according to scanning data of a to-be-detected part and a pre-determined stimulation coil, wherein the stimulation simulation model is constructed based on a part simulation model of the to-be-detected part and a coil simulation model of the stimulation coil; a first relative position matrix determination module configured to determine a first relative position matrix based on first spatial information of at least three first marker points pre-determined on a coil simulation model in a model space in the stimulation simulation model, and second spatial information of at least three second marker points pre-determined on a part simulation model in the model space in the stimulation simulation model; The second relative position matrix determination module is configured to determine third spatial information of the at least three first marker points in a real space and fourth spatial information of the at least three second marker points in the real space, and determine a second relative position matrix based on the third spatial information and the fourth spatial information. The positioning parameter determination module is configured to determine a positioning parameter of a positioning kit corresponding to the to-be-detected part based on the first relative position matrix and the second relative position matrix. The second relative position matrix determination module includes an entity model determination unit, a combined entity model determination unit, and a spatial information determination unit. The entity model determination unit is configured to determine a part entity model, a coil entity model, and an outer positioning entity model based on the part simulation model, the coil simulation model, and an outer positioning model used for wrapping the stimulation simulation model, respectively. The combined entity model determination unit is configured to combine the part entity model, the coil entity model, and the outer positioning entity model according to a preset combined posture to obtain a first combined entity model. The spatial information determination unit is configured to obtain first laser scanning data corresponding to the first combined entity model, and determine the third spatial information of the at least three first marker points in the real space and the fourth spatial information of the at least three second marker points in the real space based on the first laser scanning data.

8. An electronic device, comprising: The electronic device includes: at least one processor; and a memory connected with the at least one processor in communication; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the data processing method in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions, and the computer instructions are used to enable the processor to implement the data processing method in any one of claims 1-6 when executed.

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