Robotic three-dimensional image navigation method, system, medium, and electronic device

Abstract

The application provides a kind of robot three-dimensional image navigation method, system, medium and electronic equipment, comprising: obtaining target puncture path in initial magnetic resonance image of target object;When the robot is punctured to the target object, real-time magnetic resonance image containing robot positioning sheath at the target object is obtained;The robot positioning sheath includes outer tubular structure, inner tubular long end component and inner spherical end component, and the inner tubular long end component is filled with copper sulfate developing solution;Real-time posture information of the robot positioning sheath is extracted based on the real-time magnetic resonance image;The posture of the robot is adjusted based on the target puncture path and the real-time posture information, until the real-time posture of the robot positioning sheath matches the target puncture path.The robot three-dimensional image navigation method, system, medium and electronic equipment of the application effectively improve the precision and robustness in the process of robot surgery navigation.

Description

Technical Field

[0001] This invention belongs to the technical field of three-dimensional navigation, and in particular relates to a method, system, medium and electronic device for three-dimensional image navigation of a robot. Background Technology

[0002] Brain biopsy is a neurosurgical technique in which a puncture device is inserted into a target location within the brain along a specific path according to a preoperative plan to perform procedures such as sampling, drainage, or implantation, in order to diagnose or treat brain diseases. Currently, brain biopsy is generally used to diagnose brain tumors, treat cerebral edema or intracranial hemorrhage, inject drugs, or implant electrodes, and has good clinical results.

[0003] Although brain puncture surgery has become increasingly sophisticated, surgical complications still occur frequently, including infection, bleeding, nerve damage, and seizures. Most of these are due to deviations in the puncture path or inaccurate target points. Current brain puncture procedures suffer from unavoidable accuracy bottlenecks due to registration errors between CT-MRI multimodal planning images, stereotactic frame deformation, displacement, inaccurate positioning, and manual puncture. MRI-compatible brain puncture surgical robots can effectively avoid these problems. Their MRI compatibility allows the entire surgical planning and execution process to be performed entirely within the MRI scanner, without the need for CT images. Furthermore, the robot can automatically navigate to the designated location for puncture based on preoperative path planning, reducing manual intervention. Therefore, MRI-compatible brain puncture surgical robots not only simplify the preoperative process and detect and correct errors in real time, but also improve surgical efficiency, expand the scope of surgical applications, and effectively enhance surgical precision.

[0004] Therefore, in robot-assisted brain puncture surgery, precise surgical navigation is crucial for achieving accurate puncture paths. Existing robot navigation methods include vision-based, inertial measurement unit-based, and ultrasound-based methods. However, these methods suffer from the following problems when applied to a magnetic resonance-compatible brain puncture surgical robot environment:

[0005] (1) Magnetic resonance compatibility issues

[0006] The additional electronic components required for robot positioning cannot function properly in the strong magnetic field environment of a magnetic resonance scanner, and may even affect the normal operation of the magnetic resonance scanner itself.

[0007] (2) Navigation accuracy issues

[0008] During the surgery, various uncertainties and errors exist, such as sensor errors and motion accumulation errors, which lead to insufficient robot navigation accuracy. In addition, there are matching errors between the information modes used for navigation and magnetic resonance images, which further affect the accuracy.

[0009] (3) Robustness issues

[0010] During brain puncture surgery, the surgical environment may change, and the brain may drift due to cerebrospinal fluid loss, resulting in inaccurate pre-calculated positioning data. Existing methods are difficult to make timely corrections during the surgery. Summary of the Invention

[0011] In view of the shortcomings of the prior art described above, the purpose of this invention is to provide a robot three-dimensional image navigation method, system, medium and electronic device, which effectively improves the accuracy and robustness of robot surgical navigation.

[0012] In a first aspect, the present invention provides a robot three-dimensional image navigation method, the method comprising the following steps: obtaining a target puncture path in an initial magnetic resonance image of a target object; when the robot performs a puncture operation on the target object, obtaining a real-time magnetic resonance image of the target object containing a robot positioning sheath; the robot positioning sheath comprising an outer tubular structure, an inner tubular long-end component, and an inner spherical end component, the inner tubular long-end component being filled with a copper sulfate contrast agent; extracting real-time attitude information of the robot positioning sheath based on the real-time magnetic resonance image; adjusting the robot's attitude based on the target puncture path and the real-time attitude information until the real-time attitude of the robot positioning sheath matches the target puncture path.

[0013] In one implementation of the first aspect, obtaining the target puncture path from the initial magnetic resonance image of the target object includes the following steps:

[0014] The surface puncture point and target point of the target object are obtained from the initial magnetic resonance image of the target object;

[0015] Obtain the three-dimensional coordinates of the surface puncture point and the target point;

[0016] The line segment between the three-dimensional coordinates of the surface puncture point and the target point is taken as the target puncture path.

[0017] In one implementation of the first aspect, extracting the real-time attitude information of the robot positioning sheath based on the real-time magnetic resonance image includes the following steps;

[0018] Cropping an image of the region containing the robot positioning sheath from the real-time magnetic resonance imaging;

[0019] The image of the region is binarized to obtain a binarized image;

[0020] Perform morphological operations on the binarized image to obtain a smoothed image;

[0021] The smoothed image is labeled and analyzed to determine the center coordinates of the inner spherical end assembly and the inner tubular long end assembly of the robot positioning sheath on the real-time magnetic resonance image.

[0022] The center position coordinates of the inner spherical end assembly and the center position coordinates of the inner tubular long end assembly are converted into mapped coordinates under the physical coordinates defined by the magnetic resonance scanner.

[0023] The real-time attitude information is obtained based on the center position coordinates and mapped coordinates of the inner spherical end component and the inner tubular long end component.

[0024] In one implementation of the first aspect, binarizing the region image to obtain a binarized image includes the following steps:

[0025] According to argmax T W0×(G0-T) 2 +W1×(G1-T) 2 Determine the binarization threshold T, where W1 = 1 - W0, where N is the total number of pixels. i Let i be the number of pixels with a grayscale value of i.

[0026] The region image is binarized based on the binarization threshold T.

[0027] In one implementation of the first aspect, performing morphological operations on the binarized image to obtain a smoothed image includes the following steps:

[0028] The binarized image is processed based on the closing operation function to fill the holes in the binarized image;

[0029] The binarized image is processed using an opening operation function to smooth its edges.

[0030] In one implementation of the first aspect, obtaining the real-time attitude information based on the center position coordinates and mapped coordinates of the inner spherical end assembly and the inner tubular long end assembly includes the following steps:

[0031] Construct a linear model equation: k1x + k2y + k3z + b = 0, where k1 2 +k1 2 +k3 2 =1;

[0032] according to Find the optimal parameter [kb], where ||.| is the Euclidean norm, and k = [k1, k2, k3]. (x,y,z) represents the center position coordinates, (x',y',z') represents the mapped coordinates, and p1,p2,…,p n This represents the mapping coordinates of each layer of the inner tubular long-end component image, where n equals the number of image layers within the range of the inner tubular long-end component.

[0033] [k1,k2,k3,b] is used as the real-time attitude information.

[0034] In one implementation of the first aspect, when the real-time posture of the robot positioning sheath matches the target puncture path, the extension line of the real-time posture information coincides with the target puncture path.

[0035] In a second aspect, the present invention provides a robot three-dimensional image navigation system, the system comprising a first acquisition module, a second acquisition module, an extraction module and a navigation module;

[0036] The first acquisition module is used to acquire the target puncture path in the initial magnetic resonance image of the target object;

[0037] The second acquisition module is used to acquire real-time magnetic resonance images of the target object containing the robot positioning sheath when the robot performs a puncture operation on the target object; the robot positioning sheath includes an outer tubular structure, an inner tubular long end assembly and an inner spherical end assembly, and the inner tubular long end assembly is filled with copper sulfate imaging solution;

[0038] The extraction module is used to extract the real-time attitude information of the robot positioning sheath based on the real-time magnetic resonance image;

[0039] The navigation module is used to adjust the robot's posture based on the target puncture path and the real-time posture information until the robot's real-time posture of positioning the sheath matches the target puncture path.

[0040] Thirdly, the present invention provides an electronic device comprising a processor and a memory.

[0041] The memory is used to store computer programs;

[0042] The processor is used to execute the computer program stored in the memory, so that the electronic device performs the above-described robot three-dimensional image navigation method.

[0043] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by an electronic device, implements the above-described robot three-dimensional image navigation method.

[0044] As described above, the robot three-dimensional image navigation method, system, medium, and electronic device of the present invention have the following advantages:

[0045] Beneficial effects:

[0046] (1) It can automatically position the robot's posture by combining fast nuclear magnetic resonance imaging without the need for additional devices. Therefore, it is not affected by the high field strength of the magnetic resonance scanner and does not affect the operation of the instrument itself.

[0047] (2) The robot's attitude is located by rapid magnetic resonance structural imaging, and after multiple adjustments, it is repositioned to convergence, eliminating the matching error between the additional sensing modes and the magnetic resonance images; compared with the planned path, the absolute accuracy error and angle error of the robot end can be less than 1 mm and 1 degree, respectively.

[0048] (3) The method does not require a frame or external camera, nor does it require pre-calculation of positioning data. It can correct errors in a timely manner according to changes during surgery, making it more flexible and efficient and with a wider range of applications. It is especially suitable for three-dimensional image navigation of MRI-compatible brain puncture surgery robots. Attached Figure Description

[0049] Figure 1 The flowchart shown is an embodiment of the robot three-dimensional image navigation method of the present invention;

[0050] Figure 2 The diagram shown is a structural schematic of the robot positioning sheath of the present invention in one embodiment;

[0051] Figure 3 The diagram shows a navigation result in one embodiment of the robot three-dimensional image navigation method of the present invention;

[0052] Figure 4 The diagram shown is a structural schematic of a robot three-dimensional image navigation system according to an embodiment of the present invention.

[0053] Figure 5 The diagram shown is a structural schematic of an embodiment of the electronic device of the present invention. Detailed Implementation

[0054] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, unless otherwise specified, the following embodiments and features described therein can be combined with each other.

[0055] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0056] The robot three-dimensional image navigation method, system, medium and electronic equipment of the present invention combine magnetic resonance imaging for preoperative navigation path planning, and acquire real-time posture information and automatically adjust position during surgery, thereby realizing three-dimensional image navigation of the robot, which is particularly suitable for three-dimensional image navigation of magnetic resonance compatible brain puncture surgery robots.

[0057] The technical solutions of the present invention will now be described in detail with reference to the accompanying drawings.

[0058] like Figure 1 As shown, in one embodiment, the robot three-dimensional image navigation method of the present invention includes steps S1-S4.

[0059] Step S1: Obtain the target puncture path from the initial magnetic resonance image of the target object.

[0060] Specifically, before the procedure, the target object, such as the brain, is scanned using a magnetic resonance scanner to obtain an initial magnetic resonance image, and the target puncture path is obtained from the initial magnetic resonance image.

[0061] In one embodiment, the surface puncture point and the target point of the target object are first obtained from the initial magnetic resonance image of the target object, then the three-dimensional coordinates of the surface puncture point and the target point are obtained, and finally the line segment between the three-dimensional coordinates of the surface puncture point and the target point is used as the target puncture path.

[0062] Step S2: When the robot performs a puncture operation on the target object, a real-time magnetic resonance image of the target object containing the robot positioning sheath is acquired; the robot positioning sheath includes an outer tubular structure, an inner tubular long-end assembly and an inner spherical end assembly, and the inner tubular long-end assembly is filled with copper sulfate imaging solution.

[0063] Specifically, during the procedure, when the robot performs a puncture on the target object, a magnetic resonance scanner is used to scan the target object and acquire real-time magnetic resonance images including the robot-positioned sheath. For example... Figure 2As shown, the robot positioning sheath is rigidly fixed to the moving parts of the surgical robot and includes an outer tubular structure 1, an inner tubular long-end assembly 2, and an inner spherical end assembly 3, all of which are non-metallic structures. The inner tubular long-end assembly is filled with copper sulfate contrast agent. The robot positioning sheath also has perforations for electrode passage.

[0064] Step S3: Extract the real-time attitude information of the robot positioning sheath based on the real-time magnetic resonance image.

[0065] Specifically, extracting the real-time attitude information of the robot positioning sheath based on the real-time magnetic resonance imaging includes the following steps:

[0066] 31) Cropping an image of the region containing the robot positioning sheath from the real-time magnetic resonance image.

[0067] Specifically, the real-time magnetic resonance image is cropped using an image recognition algorithm to obtain an image of the region containing the robot positioning sheath.

[0068] 32) Perform binarization processing on the region image to obtain a binarized image.

[0069] In this invention, the region image is segmented into two parts—background and target (robot positioning sheath)—through binarization. The optimal binarization threshold T is determined using a grayscale histogram to maximize the inter-class variance between the target and the background. Specifically, it is first determined based on argmax. T W0×(G0-T) 2 +W1×(G1-T) 2 Determine the binarization threshold T, where W1 = 1 - W0, where N is the total number of pixels. i Let i be the number of pixels with a grayscale value of i. It should be noted that W0 and W1 represent the target probability and background probability, respectively. G0 and G1 represent the average gray level of the target and the average gray level of the background, respectively. Then, the region image is binarized based on the binarization threshold T. That is, when the pixel value of a pixel in the region image is less than the binarization threshold T, the pixel value is marked as 0; when the pixel value of a pixel in the region image is greater than the binarization threshold T, the pixel value is marked as 255, thus obtaining a binarized image.

[0070] 33) Perform morphological operations on the binarized image to obtain a smoothed image.

[0071] Specifically, the binarized image is processed using a closing operation function to fill in holes in the binarized image; and the binarized image is processed using an opening operation function to eliminate small protrusions, thereby smoothing the edges of the binarized image and achieving further smoothing and thinning of the binarized image.

[0072] 34) The smoothed image is labeled and analyzed to determine the center coordinates of the inner spherical end assembly and the inner tubular long end assembly of the robot positioning sheath on the real-time magnetic resonance image.

[0073] Specifically, the smoothed image is labeled and analyzed to segment the inner spherical end component and the inner tubular long end component of the robot positioning sheath into independent objects, and the center position coordinates of the two on the real-time magnetic resonance image are obtained.

[0074] 35) Convert the center position coordinates of the inner spherical end assembly and the center position coordinates of the inner tubular long end assembly into mapped coordinates under the physical coordinates defined by the magnetic resonance scanner.

[0075] Among them, according to The center position coordinates of the inner spherical end assembly and the center position coordinates of the inner tubular long end assembly are converted into mapped coordinates in the physical coordinates defined by the magnetic resonance scanner. (x, y, z) represent the center position coordinates, and (x', y', z') represent the mapped coordinates. Transformation matrix. These are known parameters, determined jointly by the magnetic resonance scanner and the scanning parameters.

[0076] 36) Obtain the real-time attitude information based on the center position coordinates and mapping coordinates of the inner spherical end component and the inner tubular long end component.

[0077] First, the linear model equation k1x + k2y + k3z + b = 0 is constructed, where k1, k2, and k3 are uniquely determined, and the constraint k1 must be satisfied. 2 +k1 2 +k3 2 =1.

[0078] Next, the RANSAC outlier removal algorithm is used to solve the following least squares problem. The optimal parameter [kb] is obtained, where ||.| is the Euclidean norm, and k = [k1, k2, k3]. (x,y,z) represents the center position coordinates, (x',y',z') represents the mapped coordinates, and p1,p2,…,p n This represents the mapping coordinates of each layer of the inner tubular long-end component image, where n equals the number of image layers within the range of the inner tubular long-end component.

[0079] Finally, the vector [k1,k2,k3,b] is used as the real-time attitude information, that is, the direction and position of the robot positioning sheath.

[0080] Step S4: Adjust the robot's posture based on the target puncture path and the real-time posture information until the robot's real-time posture of positioning the sheath matches the target puncture path.

[0081] Specifically, based on the target puncture path and the real-time posture information, the robot's posture is adjusted according to the motion mechanism settings and forward kinematics system equations of different robots. If the real-time posture of the robot positioning sheath does not match the target puncture path, the process returns to step S2, real-time magnetic resonance imaging and real-time posture information are acquired again, and the robot's posture is adjusted again until the real-time posture of the robot positioning sheath matches the target puncture path. Wherein, if... Figure 3 As shown, when the real-time attitude of the robot positioning sheath matches the target puncture path, the extension line of the real-time attitude information coincides with the target puncture path. That is, the direction of the extension line of the real-time attitude information coincides with the direction of the target puncture path.

[0082] The scope of protection of the robot three-dimensional image navigation method described in this embodiment is not limited to the execution order of the steps listed in this embodiment. Any solution implemented by adding, subtracting, or replacing steps in the prior art based on the principle of this invention is included within the scope of protection of this invention.

[0083] This invention also provides a robot three-dimensional image navigation system, which can implement the robot three-dimensional image navigation method described in this invention. However, the implementation device of the robot three-dimensional image navigation system described in this invention includes, but is not limited to, the structure of the robot three-dimensional image navigation system listed in this embodiment. All structural modifications and substitutions of the prior art made in accordance with the principles of this invention are included within the protection scope of this invention.

[0084] like Figure 4 As shown, in one embodiment, the robot three-dimensional image navigation system of the present invention includes a first acquisition module 41, a second acquisition module 42, an extraction module 43, and a navigation module 44.

[0085] The first acquisition module 41 is used to acquire the target puncture path in the initial magnetic resonance image of the target object.

[0086] The second acquisition module 42 is used to acquire real-time magnetic resonance images of the target object containing the robot positioning sheath when the robot performs a puncture operation on the target object; the robot positioning sheath includes an outer tubular structure, an inner tubular long end assembly and an inner spherical end assembly, and the inner tubular long end assembly is filled with copper sulfate imaging solution.

[0087] The extraction module 43 is connected to the second acquisition module 42 and is used to extract the real-time attitude information of the robot positioning sheath based on the real-time magnetic resonance image.

[0088] The navigation module 44 is connected to the first acquisition module 41 and the extraction module 43, and is used to adjust the robot's posture based on the target puncture path and the real-time posture information until the robot's real-time posture of positioning the sheath matches the target puncture path.

[0089] The structure and principle of the first acquisition module 41, the second acquisition module 42, the extraction module 43 and the navigation module 44 correspond one-to-one with the steps in the above-mentioned robot three-dimensional image navigation method, so they will not be described again here.

[0090] In the embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, or methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of modules / units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or units 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 of apparatuses or modules or units may be electrical, mechanical, or other forms.

[0091] The modules / units described as separate components may or may not be physically separate. The components shown as modules / units may or may not be physical modules; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules / units can be selected to achieve the objectives of the embodiments of the present invention, depending on actual needs. For example, the functional modules / units in the various embodiments of the present invention may be integrated into one processing module, or each module / unit may exist physically separately, or two or more modules / units may be integrated into one module / unit.

[0092] Those skilled in the art will further 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, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. 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 implementations should not be considered beyond the scope of this invention.

[0093] This invention also provides a computer-readable storage medium. Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing a processor. The program can be stored in a computer-readable storage medium, which is a non-transitory medium, such as random access memory, read-only memory, flash memory, hard disk, solid-state drive, magnetic tape, floppy disk, optical disk, and any combination thereof. The storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. This available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., digital video disc (DVD)), or a semiconductor medium (e.g., solid-state drive (SSD)).

[0094] This invention also provides an electronic device. The electronic device includes a processor and a memory.

[0095] The memory is used to store computer programs.

[0096] The memory includes various media capable of storing program code, such as ROM, RAM, magnetic disk, USB flash drive, memory card, or optical disk.

[0097] The processor is connected to the memory and is used to execute the computer program stored in the memory so that the electronic device performs the above-described robot three-dimensional image navigation method.

[0098] Preferably, the processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0099] like Figure 5 As shown, the electronic device of the present invention is embodied in the form of a general-purpose computing device. The components of the electronic device may include, but are not limited to: one or more processors or processing units 51, a memory 52, and a bus 53 connecting different system components (including the memory 52 and the processing unit 51).

[0100] Bus 53 represents one or more of several bus architectures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any of the various bus architectures. Examples of these architectures include, but are not limited to, the Industry Standard Architecture (ISA) bus, the Micro Channel Architecture (MAC) bus, the Enhanced ISA bus, the Video Electronics Standards Association (VESA) local bus, and the Peripheral Component Interconnect (PCI) bus.

[0101] Electronic devices typically include a variety of computer-readable media. These media can be any available media that can be accessed by the electronic device, including volatile and non-volatile media, and removable and non-removable media.

[0102] Memory 52 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 521 and / or cache memory 522. The electronic device may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 523 may be used to read and write non-removable, non-volatile magnetic media (…). Figure 5 Not shown; usually referred to as a "hard drive"). Although Figure 5Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk") and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 53 via one or more data media interfaces. Memory 52 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of the present invention.

[0103] A program / utility 524 having a set (at least one) of program modules 5241 may be stored, for example, in memory 52. ​​Such program modules 5241 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. Program modules 5241 typically perform the functions and / or methods described in the embodiments of the present invention.

[0104] The electronic device can also communicate with one or more external devices (e.g., keyboard, pointing device, display, etc.), one or more devices that enable a user to interact with the electronic device, and / or any device that enables the electronic device to communicate with one or more other computing devices (e.g., network interface card, modem, etc.). This communication can be performed through input / output (I / O) interface 54. Furthermore, the electronic device can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) through network adapter 55. Figure 5 As shown, network adapter 55 communicates with other modules of the electronic device via bus 53. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the electronic device, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0105] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A robot three-dimensional image navigation system, characterized in that, The system includes a first acquisition module, a second acquisition module, an extraction module, and a navigation module; The first acquisition module is used to acquire the target puncture path in the initial magnetic resonance image of the target object; The second acquisition module is used to acquire real-time magnetic resonance images of the target object containing the robot positioning sheath when the robot performs a puncture operation on the target object; the robot positioning sheath includes an outer tubular structure, an inner tubular long end assembly and an inner spherical end assembly, and the inner tubular long end assembly is filled with copper sulfate imaging solution; The extraction module is used to extract the real-time attitude information of the robot positioning sheath based on the real-time magnetic resonance image; The navigation module is used to adjust the robot's posture based on the target puncture path and the real-time posture information until the robot's real-time posture of positioning the sheath matches the target puncture path; Extracting the real-time attitude information of the robot positioning sheath based on the real-time magnetic resonance image includes the following steps; Cropping an image of the region containing the robot positioning sheath from the real-time magnetic resonance imaging; The image of the region is binarized to obtain a binarized image; Perform morphological operations on the binarized image to obtain a smoothed image; The smoothed image is labeled and analyzed to determine the center coordinates of the inner spherical end assembly and the inner tubular long end assembly of the robot positioning sheath on the real-time magnetic resonance image. The center position coordinates of the inner spherical end assembly and the center position coordinates of the inner tubular long end assembly are converted into mapped coordinates under the physical coordinates defined by the magnetic resonance scanner. The real-time attitude information is obtained based on the center position coordinates and mapped coordinates of the inner spherical end component and the inner tubular long end component. Obtaining the real-time attitude information based on the center position coordinates and mapped coordinates of the inner spherical end assembly and the inner tubular long end assembly includes the following steps: Constructing linear model equations ,in ; according to Solve for the optimal parameters ,in For the Euclidean norm, , , Indicates the coordinates of the center position. Represents the mapped coordinates. Represents the mapped coordinates of each layer of the inner tubular long-end component image. It equals the number of image layers within the range of the inner tubular long-end component; Will This serves as the real-time attitude information.

2. The robot three-dimensional image navigation system according to claim 1, characterized in that: Obtaining the target puncture path from the initial magnetic resonance image of the target object includes the following steps: The surface puncture point and target point of the target object are obtained from the initial magnetic resonance image of the target object; Obtain the three-dimensional coordinates of the surface puncture point and the target point; The line segment between the three-dimensional coordinates of the surface puncture point and the target point is taken as the target puncture path.

3. The robot three-dimensional image navigation system according to claim 1, characterized in that: Binarizing the region image to obtain a binarized image includes the following steps: according to Determine the binarization threshold T, where , , This represents the total number of pixels. The grayscale value is The number of pixels, , ; The region image is binarized based on the binarization threshold T.

4. The robot three-dimensional image navigation system according to claim 1, characterized in that: Performing morphological operations on the binarized image to obtain a smoothed image includes the following steps: The binarized image is processed based on the closing operation function to fill the holes in the binarized image; The binarized image is processed using an opening operation function to smooth its edges.

5. The robot three-dimensional image navigation system according to claim 1, characterized in that: When the real-time posture of the robot positioning sheath matches the target puncture path, the extension line of the real-time posture information coincides with the target puncture path.

6. An electronic device, characterized in that, The electronic device includes: a processor and a memory; The memory is used to store computer programs; The processor is used to execute the computer program stored in the memory, so that the electronic device implements a robot three-dimensional image navigation method when executed; The robot 3D image navigation method includes the following steps: Obtain the target puncture path from the initial magnetic resonance image of the target object; When the robot performs a puncture operation on the target object, a real-time magnetic resonance image of the target object containing the robot positioning sheath is acquired; the robot positioning sheath includes an outer tubular structure, an inner tubular long-end assembly and an inner spherical end assembly, and the inner tubular long-end assembly is filled with copper sulfate imaging solution; The real-time attitude information of the robot positioning sheath is extracted based on the real-time magnetic resonance image. The robot's posture is adjusted based on the target puncture path and the real-time posture information until the robot's real-time posture of positioning the sheath matches the target puncture path. Extracting the real-time attitude information of the robot positioning sheath based on the real-time magnetic resonance image includes the following steps; Cropping an image of the region containing the robot positioning sheath from the real-time magnetic resonance imaging; The image of the region is binarized to obtain a binarized image; Perform morphological operations on the binarized image to obtain a smoothed image; The smoothed image is labeled and analyzed to determine the center coordinates of the inner spherical end assembly and the inner tubular long end assembly of the robot positioning sheath on the real-time magnetic resonance image. The center position coordinates of the inner spherical end assembly and the center position coordinates of the inner tubular long end assembly are converted into mapped coordinates under the physical coordinates defined by the magnetic resonance scanner. The real-time attitude information is obtained based on the center position coordinates and mapped coordinates of the inner spherical end component and the inner tubular long end component. Obtaining the real-time attitude information based on the center position coordinates and mapped coordinates of the inner spherical end assembly and the inner tubular long end assembly includes the following steps: Constructing linear model equations ,in ; according to Solve for the optimal parameters ,in For the Euclidean norm, , , Indicates the coordinates of the center position. Represents the mapped coordinates. Represents the mapped coordinates of each layer of the inner tubular long-end component image. It equals the number of image layers within the range of the inner tubular long-end component; Will This serves as the real-time attitude information.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by an electronic device, this program implements a three-dimensional image navigation method for robots. The robot 3D image navigation method includes the following steps: Obtain the target puncture path from the initial magnetic resonance image of the target object; When the robot performs a puncture operation on the target object, a real-time magnetic resonance image of the target object containing the robot positioning sheath is acquired; the robot positioning sheath includes an outer tubular structure, an inner tubular long-end assembly and an inner spherical end assembly, and the inner tubular long-end assembly is filled with copper sulfate imaging solution; The real-time attitude information of the robot positioning sheath is extracted based on the real-time magnetic resonance image. The robot's posture is adjusted based on the target puncture path and the real-time posture information until the robot's real-time posture of positioning the sheath matches the target puncture path. Extracting the real-time attitude information of the robot positioning sheath based on the real-time magnetic resonance image includes the following steps; Cropping an image of the region containing the robot positioning sheath from the real-time magnetic resonance imaging; The image of the region is binarized to obtain a binarized image; Perform morphological operations on the binarized image to obtain a smoothed image; The smoothed image is labeled and analyzed to determine the center coordinates of the inner spherical end assembly and the inner tubular long end assembly of the robot positioning sheath on the real-time magnetic resonance image. The center position coordinates of the inner spherical end assembly and the center position coordinates of the inner tubular long end assembly are converted into mapped coordinates under the physical coordinates defined by the magnetic resonance scanner. The real-time attitude information is obtained based on the center position coordinates and mapped coordinates of the inner spherical end component and the inner tubular long end component. Obtaining the real-time attitude information based on the center position coordinates and mapped coordinates of the inner spherical end assembly and the inner tubular long end assembly includes the following steps: Constructing linear model equations ,in ; according to Solve for the optimal parameters ,in For the Euclidean norm, , , Indicates the coordinates of the center position. Represents the mapped coordinates. Represents the mapped coordinates of each layer of the inner tubular long-end component image. It equals the number of image layers within the range of the inner tubular long-end component; Will This serves as the real-time attitude information.

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