Transcranial stimulation magnetic therapy coil navigation method and system, storage medium and equipment

Abstract

The invention discloses a transcranial stimulation magnetic therapy coil navigation method, a transcranial stimulation magnetic therapy coil navigation system, a storage medium and equipment. The method comprises the following steps: acquiring three-dimensional structure information of the head of a target object, magnetic resonance imaging (MRI) data of an individual target object, or three-dimensional model data obtained by matching from a general MRI template library; real-time surface geometric information of the head of the target object is collected through an infrared optical tracking system; performing registration fusion on the three-dimensional structure information and the real-time surface geometric information, and generating an individualized three-dimensional brain model synchronized with a real space coordinate system on a navigation interface; the spatial position and posture of the optical marker fixed on the magnetic therapy coil are tracked in real time through an infrared optical tracking system and correspondingly mapped to the individualized three-dimensional brain model, and visual navigation of the magnetic therapy coil relative to the brain anatomical structure is achieved. Through the individualized three-dimensional navigation and real-time visualization technology, the problems that a traditional TMS is low in positioning precision, invisible in operation and poor in treatment repeatability are solved.

Description

Technical Field

[0001] This invention relates to the field of magnetotherapy technology, specifically to a transcranial stimulation magnetotherapy coil navigation method, system, storage medium, and device. Background Technology

[0002] Transcranial magnetic stimulation (TMS), as a non-invasive brain modulation technique, has demonstrated significant application value in the treatment of neuropsychiatric disorders such as depression and neurological rehabilitation. Its therapeutic effect is highly dependent on the precise targeting of the magnetic stimulation coil to the target brain functional area; therefore, the accuracy and reliability of the localization technique are key factors influencing the efficacy of TMS.

[0003] Currently, traditional TMS localization techniques mainly rely on skull anatomical landmarks to estimate the location of the target area in the cerebral cortex. Commonly used methods include the international 10-20 EEG system localization method, the localization cap marking method, and the lateral distance method based on "motor hotspots." Although these methods are simple to operate and low in cost, they have fundamental technical defects: First, the localization accuracy is low and the individual error is large. Due to ignoring the differences in individual brain anatomy, the target point estimated based on standardized formulas can deviate from the actual functional area by 1-3 centimeters. Second, the operation process lacks visualization support. Doctors cannot observe the correspondence between the coil and the brain anatomy in real time, nor can they verify whether the magnetic field covers the target area, which is equivalent to "blind operation." In addition, the treatment repeatability is poor. It is difficult to keep the coil placement consistent between different treatment courses, affecting the evaluation of efficacy. More importantly, these methods are difficult to effectively stimulate non-motor areas (such as the prefrontal cortex and language area) because they lack objective feedback indicators such as motor evoked potentials (MEP), which limits the application effect of TMS in diseases such as depression and aphasia.

[0004] The root cause of these shortcomings lies in the fact that traditional methods rely on standardized templates and surface landmarks, which cannot adapt to variations in individual anatomical structures and lack effective real-time feedback mechanisms. Therefore, developing a navigation method capable of personalized, visualized, and high-precision positioning has become a pressing technical challenge for improving the effectiveness of TMS treatment. Summary of the Invention

[0005] In view of the shortcomings of the prior art, the purpose of this invention is to provide a transcranial stimulation magnetic therapy coil navigation method, system, storage medium and device, which aims to solve the above-mentioned problems described in the prior art.

[0006] A first aspect of the present invention is to provide a transcranial stimulation magnetic therapy coil navigation method, the method comprising: Obtain three-dimensional structural information of the head of the target object; the three-dimensional structural information is magnetic resonance imaging (MRI) data of the target object or three-dimensional model data matched from a general MRI template library; The real-time surface geometry information of the target object's head is collected using an infrared optical tracking system. The three-dimensional structural information is registered and fused with the real-time surface geometric information to generate an individualized three-dimensional mind model synchronized with the real spatial coordinate system on the navigation interface. The infrared optical tracking system tracks the spatial position and orientation of the optical markers fixed on the magnetic therapy coil in real time and maps them to the individualized three-dimensional brain model, thereby realizing the visual navigation of the magnetic therapy coil relative to the brain anatomy.

[0007] According to one aspect of the above technical solution, when obtaining the three-dimensional structural information of the target object's head, three-dimensional model data is obtained by matching from a general MRI template library, including: The infrared optical tracking system is used to collect the head circumference and facial key feature information of the target object. Based on the head circumference and facial key feature information, the system traverses and queries a general MRI template library to determine the three-dimensional model corresponding to the target object, and extracts the three-dimensional model data.

[0008] According to one aspect of the above technical solution, an infrared optical tracking system is used to collect real-time surface geometric information of the target object's head, including: The infrared camera of the infrared optical tracking system performs a non-contact scan of the facial contour of the target object to obtain three-dimensional point cloud data of the face. Based on the facial 3D point cloud data, the spatial coordinates of multiple key facial anatomical feature points, including the corners of the eyes, the root of the nose, the tip of the nose, and the contours of the ears, are automatically identified and extracted.

[0009] According to one aspect of the above technical solution, the three-dimensional structural information is registered and fused with the real-time surface geometric information to generate an individualized three-dimensional mind model synchronized with the real spatial coordinate system on the navigation interface, including: Based on the coordinates of key facial anatomical feature points in the real-time surface geometry information, preliminary spatial matching is performed with the corresponding anatomical landmarks in the three-dimensional structural information to establish an initial coordinate transformation matrix. The iterative nearest point (ICP) algorithm is used to match the facial 3D point cloud data in the real-time surface geometry information with the outer surface model of the 3D structure information to optimize the spatial transformation parameters. Based on the optimized spatial transformation parameters, the three-dimensional structural information is mapped to the real spatial coordinate system of the infrared optical tracking system, completing the registration and fusion and generating a corresponding individualized three-dimensional brain model.

[0010] According to one aspect of the above technical solution, the Iterative Closest Point (ICP) algorithm is used to match the facial 3D point cloud data in the real-time surface geometry information with the outer surface model of the 3D structural information to optimize the spatial transformation parameters, including: Calculate the correspondence between each feature point in the facial 3D point cloud data and the nearest point on the outer surface model, and establish a set of point pairs; Based on the set of point pairs, the optimal rigid body transformation matrix is ​​solved by the least squares method. The transformation matrix includes a rotation matrix and a translation vector. The process of iteratively calculating the correspondence and solving the transformation matrix continues until the change in the spatial transformation parameters is less than a preset threshold or the maximum number of iterations is reached, thus obtaining the final optimized spatial transformation parameters.

[0011] According to one aspect of the above technical solution, the process of iteratively calculating the correspondence and solving the transformation matrix continues until the change in the spatial transformation parameters is less than a preset threshold or the maximum number of iterations is reached, thereby obtaining the final optimized spatial transformation parameters, including: During each iteration, the Euclidean norm change of the current rotation matrix and translation vector relative to the transformation parameters of the previous iteration is calculated. When the change is less than the preset convergence threshold or the number of iterations reaches the preset maximum number of iterations, the iteration process is terminated, and the current spatial transformation parameters are output as the final optimized spatial transformation parameters.

[0012] According to one aspect of the above technical solution, the navigation interface displays one or more of the following information in real time: The brain gyri and sulci structures covered by the virtual coil corresponding to the magnetic therapy coil, the tangential angle of the coil, and the estimated depth and range of the stimulation field strength distribution.

[0013] A second aspect of the present invention is to provide a transcranial stimulation magnetic therapy coil navigation system, applied to the method described in the above-mentioned technical solution, the system comprising: The information acquisition module is used to acquire the three-dimensional structural information of the head of the target object; the three-dimensional structural information is the magnetic resonance imaging (MRI) data of the target object, or the three-dimensional model data matched from a general MRI template library; The feature acquisition module is used to acquire real-time surface geometric information of the head of the target object through an infrared optical tracking system; The registration processing module is used to register and fuse the three-dimensional structural information with the real-time surface geometric information to generate an individualized three-dimensional mind model synchronized with the real space coordinate system on the navigation interface. The navigation execution module is used to track the spatial position and orientation of the optical markers fixed on the magnetic therapy coil in real time through the infrared optical tracking system, and map them to the individualized three-dimensional brain model to realize the visual navigation of the magnetic therapy coil relative to the brain anatomy.

[0014] A third aspect of the present invention is to provide a readable storage medium having computer instructions stored thereon, which, when executed by a processor, implement the steps of the method described in the above-described technical solution.

[0015] A fourth aspect of the present invention is to provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the method described in the above technical solutions.

[0016] Compared with existing technologies, the transcranial stimulation magnetic therapy coil navigation method, system, storage medium, and device shown in this invention have the following advantages: This invention achieves high-precision data acquisition based on individual anatomical features by acquiring individual MRI data of the target object or intelligently matching three-dimensional model data from a general MRI template library, combined with real-time surface geometric information collected by an infrared optical tracking system. By registering and fusing three-dimensional structural information with real-time surface geometric information, an individualized three-dimensional brain model synchronized with the real spatial coordinate system is generated, solving the problem of individual positioning error caused by the reliance on standardized templates in traditional methods. Furthermore, by using an infrared optical tracking system to track the spatial position and orientation of optical markers on the magnetic therapy coil in real time and accurately map them into the individualized three-dimensional brain model, real-time visual navigation during treatment is achieved, overcoming the shortcomings of traditional blind operation and ensuring the high repeatability of treatment positions and the accuracy of stimulation of non-motor areas. Attached Figure Description

[0017] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which: Figure 1 This is a flowchart illustrating the transcranial magnetic stimulation coil navigation method provided in an embodiment of the present invention. Figure 2 This is a structural block diagram of a transcranial stimulation magnetic therapy coil navigation system provided in an embodiment of the present invention. Detailed Implementation

[0018] To facilitate understanding of the present invention, a more complete description will be given below with reference to the accompanying drawings. Several embodiments of the invention are illustrated in the drawings. However, the invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.

[0019] It should be noted that when a component is said to be "fixed to" another component, it can be directly on the other component or there may be an intervening component. When a component is said to be "connected to" another component, it can be directly connected to the other component or there may be an intervening component. The terms "vertical," "horizontal," "left," "right," and similar expressions used in this document are for illustrative purposes only.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0021] Example 1 Please see Figure 1 The first embodiment of the present invention provides a transcranial magnetic stimulation coil navigation method, the method comprising steps S10-S40: Step S10: Obtain the three-dimensional structural information of the target object's head.

[0022] The three-dimensional structural information refers to the magnetic resonance imaging (MRI) data of the target object or the three-dimensional model data matched from a general MRI template library.

[0023] It should be noted that the method shown in this embodiment is applied to transcranial magnetic stimulation (TMS) for patients who have their own MRI and those who lack MRI for special reasons, i.e., the target subjects. The MRI data of the target subject is the image data output from examinations conducted at medical institutions. This method can directly use existing MRI data for subsequent processing, thereby achieving operational navigation of the magnetic stimulation coil. For target subjects who lack MRI data due to the presence of metal or other abnormalities preventing MRI detection, corresponding three-dimensional model data can be obtained by matching from a general MRI template library.

[0024] Specifically, when acquiring the three-dimensional structural information of the target object's head, three-dimensional model data is obtained by matching from a general MRI template library, including: The infrared optical tracking system is used to collect the head circumference and facial key feature information of the target object. Based on the head circumference and facial key feature information, the system traverses and queries a general MRI template library to determine the three-dimensional model corresponding to the target object, and extracts the three-dimensional model data.

[0025] More specifically, when the target object lacks MRI and 3D model data is matched from a general MRI template library, it is first necessary to determine the individual characteristics of the target object. Specifically, this is done by using an infrared optical tracking system to collect the target object's head circumference (mm) and facial key point feature information. The individual characteristics of the target object are characterized based on the head circumference and facial key point feature information. The individual characteristics of each target object usually have certain differences. Based on the above individual characteristics, the general MRI template library is used to traverse and query the 3D models corresponding to the target user, using the head circumference and facial key point feature information as query conditions, and the corresponding 3D model data is extracted.

[0026] Step S20: Collect real-time surface geometry information of the head of the target object using an infrared optical tracking system.

[0027] In this embodiment, an infrared optical tracking system is used to collect real-time surface geometric information of the target object's head, including: The infrared camera of the infrared optical tracking system performs a non-contact scan of the facial contour of the target object to obtain three-dimensional point cloud data of the face. Based on the facial 3D point cloud data, the spatial coordinates of multiple key facial anatomical feature points, including the corners of the eyes, the root of the nose, the tip of the nose, and the contours of the ears, are automatically identified and extracted.

[0028] Specifically, in this embodiment, the infrared camera in the infrared optical tracking system performs a non-contact scan of the facial contour of the target object to obtain three-dimensional point cloud data of the face. Then, based on the three-dimensional point cloud data of the face, the spatial coordinates of multiple key facial anatomical feature points such as the corners of the eyes, the root of the nose, the tip of the nose, and the contours of the ears of the target object are automatically identified and extracted. Specifically, the coordinates include coordinates in three dimensions: X, Y, and Z. For example, the geometric center point of the tip of the nose is set as the origin, and the spatial coordinates of the above multiple key facial feature anatomical points are determined respectively. Thus, the spatial coordinates corresponding to the above multiple key facial feature anatomical points are fused to obtain the real-time surface geometric information of the target object's head.

[0029] Step S30: Register and fuse the three-dimensional structural information with the real-time surface geometric information to generate an individualized three-dimensional mind model synchronized with the real spatial coordinate system on the navigation interface.

[0030] Specifically, the registration and fusion process in step S30 is a core step that maps the virtual image space to the real physical space with high precision. This process achieves a one-to-one correspondence between two different coordinate systems through mathematical calculations, ensuring the accuracy of subsequent navigation.

[0031] First, the process involves standardizing and preprocessing the two types of data acquired. For three-dimensional structural information, i.e., individual MRI or a matching generic template, the scalp surface model is automatically extracted and key anatomical landmarks, such as the root of the nose, the corner of the eye, and the tragus, are identified. Simultaneously, the facial three-dimensional point cloud data in the real-time surface geometry information undergoes filtering and noise reduction processing to eliminate noise points caused by minor patient movements or environmental interference.

[0032] Secondly, the registration process employs a two-stage strategy, from coarse to fine: The first stage is coarse registration based on feature points. Real-time acquired facial key points (such as the tip of the nose and the corners of the eyes) are matched with corresponding anatomical landmarks in the 3D structural model. An initial rotation and translation matrix, i.e., the initial coordinate transformation matrix, is calculated using the least squares method, initially addressing the question of "approximately where it is." The second stage uses the Iterative Closest Point (ICP) algorithm for fine registration. This algorithm automatically calculates the correspondence between real-time point cloud data and the nearest point on the model surface, and continuously adjusts the rotation and translation parameters through iterative optimization until the mean square error converges to within a preset threshold (e.g., <0.5mm). This stage utilizes massive amounts of surface point cloud data to average out individual errors, ultimately achieving millimeter-level precise spatial locking.

[0033] Finally, based on the optimized spatial transformation parameters, the three-dimensional structural information is mapped to the real-world coordinate system of the infrared optical tracking system, completing coordinate system one. The navigation interface then generates and renders an individualized three-dimensional mind model that is completely synchronized with the real space.

[0034] It should be noted that the model not only includes detailed anatomical structures of the gyri and sulci, but also responds in real time to the movement of the real coil, providing doctors with an intuitive and accurate navigation view.

[0035] Step S40: The spatial position and orientation of the optical markers fixed on the magnetic therapy coil are tracked in real time by the infrared optical tracking system and mapped to the individualized three-dimensional brain model to realize the visual navigation of the magnetic therapy coil relative to the brain anatomy.

[0036] Specifically, step S40 is a key conversion step from spatial registration to final clinical application. Its core lies in establishing a continuous and stable dynamic mapping relationship between the real physical space and the virtual image space. This process uses infrared optical tracking technology to convert the coil operation in the physical world into precise visual information in the navigation interface in real time, enabling doctors to "see through" the skull and intuitively observe the relative position of the coil and the brain's anatomical structure.

[0037] The infrared optical tracking system uses multiple high-resolution infrared cameras deployed around the treatment area to continuously capture the spatial coordinates of passive reflective marker spheres or active infrared light-emitting diodes fixed on the magnetotherapy coil. These markers are arranged in a specific geometric configuration on the coil surface. By identifying this configuration, the system can not only calculate the three-dimensional coordinates (X, Y, Z) of the coil's center point, but also accurately calculate the coil's three rotation angles, including pitch, yaw, and roll angles, by calculating the relative positional changes between the markers—that is, complete six-degree-of-freedom pose information.

[0038] After acquiring the real-time six-degree-of-freedom pose data of the coil, the physical coordinates are converted into corresponding coordinates in the virtual image coordinate system by applying the spatial transformation matrix calculated in step S30, so that the virtual coil model can move in complete synchronization with the real coil. Then, the navigation software engine renders and overlays the virtual coil model with the individualized three-dimensional brain model in real time to generate a fused image.

[0039] In actual magnetic therapy, on the navigation interface, doctors can clearly see the specific brain anatomy structure covered by the virtual coil model, such as which gyrus or sulcus is being stimulated. The effective stimulation range and estimated stimulation depth of the magnetic field distribution can be displayed intuitively in the form of color coding, semi-transparent rendering, or contour lines, thereby predicting which neuronal groups may be activated.

[0040] In addition, the navigation interface displays treatment parameters in real time, such as the tangential angle between the coil and the scalp surface, and the straight-line distance to the target point. If the angle or distance deviates from the preset optimal range, a visual or auditory warning will be automatically issued.

[0041] Compared with existing technologies, the transcranial magnetic stimulation coil navigation method shown in this embodiment has the following advantages: This embodiment achieves high-precision data acquisition based on individual anatomical features by acquiring individual MRI data of the target object or intelligently matching three-dimensional model data from a general MRI template library, combined with real-time surface geometric information collected by an infrared optical tracking system. By registering and fusing three-dimensional structural information with real-time surface geometric information, an individualized three-dimensional brain model synchronized with the real spatial coordinate system is generated, solving the problem of individual positioning error caused by the reliance on standardized templates in traditional methods. Furthermore, by tracking the spatial position and orientation of optical markers on the magnetic therapy coil in real time through the infrared optical tracking system and accurately mapping them into the individualized three-dimensional brain model, real-time visual navigation during the treatment process is achieved, overcoming the defects of traditional blind operation and ensuring the high repeatability of treatment positions and the accuracy of non-motor area stimulation.

[0042] Example 2 The second embodiment of the present invention also provides a transcranial stimulation magnetic therapy coil navigation method. The method shown in this embodiment is basically similar to the method shown in the first embodiment, except that: In this embodiment, the three-dimensional structural information and the real-time surface geometric information are registered and fused to generate an individualized three-dimensional mind model synchronized with the real spatial coordinate system on the navigation interface, including: Based on the coordinates of key facial anatomical feature points in the real-time surface geometry information, preliminary spatial matching is performed with the corresponding anatomical landmarks in the three-dimensional structural information to establish an initial coordinate transformation matrix. The iterative nearest point (ICP) algorithm is used to match the facial 3D point cloud data in the real-time surface geometry information with the outer surface model of the 3D structure information to optimize the spatial transformation parameters. Based on the optimized spatial transformation parameters, the three-dimensional structural information is mapped to the real spatial coordinate system of the infrared optical tracking system, completing the registration and fusion and generating a corresponding individualized three-dimensional brain model.

[0043] Specifically, the registration and fusion process in this embodiment achieves precise implementation from coarse registration to fine registration through hierarchical optimization. In the preliminary spatial matching stage, based on the coordinates of key facial anatomical feature points acquired in real time, such as the root of the nose, the corner of the eye, and the auricle contour points, these are matched with the corresponding predefined anatomical landmarks in the three-dimensional structural information to establish an initial coordinate transformation matrix. Specifically, the spatial transformation parameters are calculated using the least squares algorithm to initially converge the registration error to an operable range.

[0044] In the fine registration stage, the Iterative Closest Point (ICP) algorithm is used to densely match the real-time acquired facial 3D point cloud data with the outer surface model of the 3D structural information. By iteratively calculating the correspondence of the closest points and solving the optimal transformation matrix, the registration accuracy reaches the millimeter-level clinical requirements.

[0045] Finally, by applying the optimized spatial transformation parameters, the three-dimensional structural information is mapped to the real spatial coordinate system of the infrared optical tracking system, thereby completing the registration and fusion, and generating a corresponding individualized three-dimensional brain model, providing a precise spatial reference for subsequent real-time navigation.

[0046] Specifically, the Iterative Nearest Point (ICP) algorithm is used to match the facial 3D point cloud data in the real-time surface geometry information with the outer surface model of the 3D structural information to optimize spatial transformation parameters, including: Calculate the correspondence between each feature point in the facial 3D point cloud data and the nearest point on the outer surface model, and establish a set of point pairs; Based on the set of point pairs, the optimal rigid body transformation matrix is ​​solved by the least squares method. The transformation matrix includes a rotation matrix and a translation vector. The process of iteratively calculating the correspondence and solving the transformation matrix continues until the change in the spatial transformation parameters is less than a preset threshold or the maximum number of iterations is reached, thus obtaining the final optimized spatial transformation parameters.

[0047] Specifically, in this embodiment, high-precision spatial registration is achieved through an iterative nearest point algorithm. Its core is to gradually eliminate the spatial deviation between point cloud data and 3D model through iterative optimization.

[0048] In the first iteration, the Euclidean distance between each feature point in the real-time acquired 3D facial point cloud and the nearest point on the outer surface model of the 3D structural information is first calculated to establish an initial set of point pair correspondences. Specifically, the KD-tree spatial data structure is used to accelerate the search, ensuring that the nearest neighbor of each point can still be found quickly under large-scale point cloud data.

[0049] In addition, based on the established set of point pairs, this embodiment will also solve for the optimal rigid body transformation matrix by the least squares method. Specifically, the unit quaternion method or the singular value decomposition algorithm will be used to calculate the rotation matrix R and the translation vector T respectively, so as to minimize the mean square error between the set of point pairs. After each iteration, the position of the point cloud data will be updated by applying the currently obtained transformation matrix, and the correspondence between the set of point pairs will be recalculated.

[0050] The process of iteratively calculating the correspondence and solving the transformation matrix continues until the change in the spatial transformation parameters is less than a preset threshold or the maximum number of iterations is reached, thus obtaining the final optimized spatial transformation parameters, including: During each iteration, the Euclidean norm change of the current rotation matrix and translation vector relative to the transformation parameters of the previous iteration is calculated. When the change is less than the preset convergence threshold or the number of iterations reaches the preset maximum number of iterations, the iteration process is terminated, and the current spatial transformation parameters are output as the final optimized spatial transformation parameters.

[0051] The iteration termination condition adopts a dual judgment standard: when the change in transformation parameters between two consecutive iterations is less than a preset threshold, usually the change in rotation matrix is ​​<0.01 radians, the change in translation vector is <0.1 mm, or the number of iterations reaches the maximum limit, for example, set to 200 times, the iteration terminates and the final optimized spatial transformation parameters are output.

[0052] Example 3 Please see Figure 2 A third embodiment of the present invention provides a transcranial magnetic stimulation coil navigation system, applied to the method described in any of the above embodiments, the system comprising: The information acquisition module 10 is used to acquire the three-dimensional structural information of the head of the target object; the three-dimensional structural information is the magnetic resonance imaging (MRI) data of the target object, or the three-dimensional model data matched from a general MRI template library; The feature acquisition module 20 is used to acquire real-time surface geometric information of the head of the target object through an infrared optical tracking system; The registration processing module 30 is used to register and fuse the three-dimensional structural information with the real-time surface geometric information to generate an individualized three-dimensional mind model synchronized with the real space coordinate system on the navigation interface. The navigation execution module 40 is used to track the spatial position and orientation of the optical markers fixed on the magnetic therapy coil in real time through the infrared optical tracking system, and map them to the individualized three-dimensional brain model to realize the visual navigation of the magnetic therapy coil relative to the brain anatomy.

[0053] Compared with existing technologies, the transcranial stimulation magnetic therapy coil navigation system shown in this embodiment has the following advantages: This embodiment achieves high-precision data acquisition based on individual anatomical features by acquiring individual MRI data of the target object or intelligently matching three-dimensional model data from a general MRI template library, combined with real-time surface geometric information collected by an infrared optical tracking system. By registering and fusing three-dimensional structural information with real-time surface geometric information, an individualized three-dimensional brain model synchronized with the real spatial coordinate system is generated, solving the problem of individual positioning error caused by the reliance on standardized templates in traditional methods. Furthermore, by tracking the spatial position and orientation of optical markers on the magnetic therapy coil in real time through the infrared optical tracking system and accurately mapping them into the individualized three-dimensional brain model, real-time visual navigation during the treatment process is achieved, overcoming the defects of traditional blind operation and ensuring the high repeatability of treatment positions and the accuracy of non-motor area stimulation.

[0054] Example 4 A fourth embodiment of the present invention provides a readable storage medium having computer instructions stored thereon, which, when executed by a processor, implement the steps of the method described in any of the above embodiments.

[0055] Example 5 A fifth embodiment of the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the method described in any of the above embodiments.

[0056] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0057] Those skilled in the art will understand that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequential list of executable instructions for implementing logical functions, and can be embodied in any computer-readable storage medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable storage medium" can mean any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0058] More specific examples (a non-exhaustive list) of computer-readable storage media include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable storage media can even be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0059] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0060] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0061] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

Claims

1. A transcranial magnetic stimulation coil navigation method, characterized in that, The method includes: Obtain three-dimensional structural information of the head of the target object; the three-dimensional structural information is magnetic resonance imaging (MRI) data of the target object or three-dimensional model data matched from a general MRI template library; The real-time surface geometry information of the target object's head is collected using an infrared optical tracking system. The three-dimensional structural information is registered and fused with the real-time surface geometric information to generate an individualized three-dimensional mind model synchronized with the real spatial coordinate system on the navigation interface. The infrared optical tracking system tracks the spatial position and orientation of the optical markers fixed on the magnetic therapy coil in real time and maps them to the individualized three-dimensional brain model, thereby realizing the visual navigation of the magnetic therapy coil relative to the brain anatomy.

2. The transcranial magnetic stimulation coil navigation method according to claim 1, characterized in that, When acquiring the three-dimensional structural information of the target object's head, three-dimensional model data is obtained by matching from a general MRI template library, including: The infrared optical tracking system is used to collect the head circumference and facial key feature information of the target object. Based on the head circumference and facial key feature information, the system traverses and queries a general MRI template library to determine the three-dimensional model corresponding to the target object, and extracts the three-dimensional model data.

3. The transcranial magnetic stimulation coil navigation method according to claim 1, characterized in that, The real-time surface geometry information of the target object's head is acquired using an infrared optical tracking system, including: The infrared camera of the infrared optical tracking system performs a non-contact scan of the facial contour of the target object to obtain three-dimensional point cloud data of the face. Based on the facial 3D point cloud data, the spatial coordinates of multiple key facial anatomical feature points, including the corners of the eyes, the root of the nose, the tip of the nose, and the contours of the ears, are automatically identified and extracted.

4. The transcranial magnetic stimulation coil navigation method according to claim 1, characterized in that, The three-dimensional structural information is registered and fused with the real-time surface geometry information to generate an individualized three-dimensional mind model synchronized with the real spatial coordinate system on the navigation interface, including: Based on the coordinates of key facial anatomical feature points in the real-time surface geometry information, preliminary spatial matching is performed with the corresponding anatomical landmarks in the three-dimensional structural information to establish an initial coordinate transformation matrix. The iterative nearest point (ICP) algorithm is used to match the facial 3D point cloud data in the real-time surface geometry information with the outer surface model of the 3D structure information to optimize the spatial transformation parameters. Based on the optimized spatial transformation parameters, the three-dimensional structural information is mapped to the real spatial coordinate system of the infrared optical tracking system, completing the registration and fusion and generating a corresponding individualized three-dimensional brain model.

5. The transcranial magnetic stimulation coil navigation method according to claim 4, characterized in that, The Iterative Nearest Point (ICP) algorithm is used to match the facial 3D point cloud data in the real-time surface geometry information with the outer surface model of the 3D structural information to optimize the spatial transformation parameters, including: Calculate the correspondence between each feature point in the facial 3D point cloud data and the nearest point on the outer surface model, and establish a set of point pairs; Based on the set of point pairs, the optimal rigid body transformation matrix is ​​solved by the least squares method. The transformation matrix includes a rotation matrix and a translation vector. The process of iteratively calculating the correspondence and solving the transformation matrix continues until the change in the spatial transformation parameters is less than a preset threshold or the maximum number of iterations is reached, thus obtaining the final optimized spatial transformation parameters.

6. The transcranial magnetic stimulation coil navigation method according to claim 5, characterized in that, The process of iteratively calculating the correspondence and solving the transformation matrix continues until the change in the spatial transformation parameters is less than a preset threshold or the maximum number of iterations is reached, yielding the final optimized spatial transformation parameters, including: During each iteration, the Euclidean norm change of the current rotation matrix and translation vector relative to the transformation parameters of the previous iteration is calculated. When the change is less than the preset convergence threshold or the number of iterations reaches the preset maximum number of iterations, the iteration process is terminated, and the current spatial transformation parameters are output as the final optimized spatial transformation parameters.

7. The transcranial magnetic stimulation coil navigation method according to any one of claims 1-6, characterized in that, The navigation interface displays one or more of the following information in real time: The brain gyri and sulci structures covered by the virtual coil corresponding to the magnetic therapy coil, the tangential angle of the coil, and the estimated depth and range of the stimulation field strength distribution.

8. A transcranial magnetic stimulation coil navigation system, characterized in that, The system, applicable to the method of any one of claims 1-7, comprises: The information acquisition module is used to acquire the three-dimensional structural information of the head of the target object; the three-dimensional structural information is the magnetic resonance imaging (MRI) data of the target object, or the three-dimensional model data matched from a general MRI template library; The feature acquisition module is used to acquire real-time surface geometric information of the head of the target object through an infrared optical tracking system; The registration processing module is used to register and fuse the three-dimensional structural information with the real-time surface geometric information to generate an individualized three-dimensional mind model synchronized with the real space coordinate system on the navigation interface. The navigation execution module is used to track the spatial position and orientation of the optical markers fixed on the magnetic therapy coil in real time through the infrared optical tracking system, and map them to the individualized three-dimensional brain model to realize the visual navigation of the magnetic therapy coil relative to the brain anatomy.

9. A readable storage medium having computer instructions stored thereon, characterized in that, When executed by the processor, this instruction implements the steps of the method as described in any one of claims 1-7.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the method as described in any one of claims 1-7.

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