Transcranial magnetic stimulation high-precision positioning method, device and equipment based on optical navigation

Abstract

This application relates to a high-precision positioning method, device, and equipment for transcranial magnetic stimulation (TMS) based on optical navigation. The method includes: selecting non-coplanar reference points based on a three-dimensional brain model of the patient; acquiring the image coordinates and physical coordinates of all reference points; matching corresponding points using the image and physical coordinates to calculate the optimal rigid transformation matrix; calculating the target registration error to achieve registration between the image and physical coordinate systems; calculating the spatial distribution of the electric field induced by the TMS coil in the target brain region based on the registered brain tissue conductivity parameters; dynamically correcting the stimulation target point coordinates of the virtual coil; dynamically displaying the position and orientation of the virtual coil corresponding to the TMS coil on the three-dimensional brain model based on the completed coordinate system registration results; and synchronously updating the brain slice view based on the corrected target point coordinates and highlighting the actual stimulated brain region boundary. This application achieves compensated target point correction by driving adaptive neural navigation through electric field remapping.

Description

Technical Field

[0001] This application relates to the field of medical technology, and in particular to a high-precision positioning method, device and equipment for transcranial magnetic stimulation based on optical navigation. Background Technology

[0002] With the rapid development of neuroscience technology, transcranial magnetic stimulation (TMS)-based treatment and research are receiving increasing attention in the medical field. However, traditional TMS treatment suffers from insufficient precision in brain localization and stimulation parameter adjustment, lacks efficient data processing capabilities, and is highly dependent on hardware resources (such as memory and graphics cards) (requiring at least 32GB of RAM). Furthermore, traditional techniques only support importing a single data format, making it difficult to generate personalized stimulation plans, and the limited coil position adjustment methods restrict treatment accuracy and operational flexibility.

[0003] Current transcranial magnetic stimulation (TMS) navigation systems face multiple technical bottlenecks: First, the insufficient positioning accuracy of traditional optical cameras leads to significant discrepancies between model and actual spatial registration, causing stimulation targets to frequently deviate from the intended brain regions. Second, in processing complex 3D brain models, even high-configuration hardware struggles to meet real-time computational demands, resulting in low data processing efficiency and hindering operational fluency. Furthermore, limited compatibility restricts support for only a limited number of brain scan data formats, failing to adapt to diverse clinical image import scenarios. Finally, operational flexibility is lacking, manifested in the absence of a dual-mode adjustment mechanism combining manual fine-tuning and mechanical control, making it difficult to dynamically respond to real-time needs during treatment. These factors collectively limit the depth and breadth of the system's clinical application in precise neuromodulation. Summary of the Invention

[0004] This application provides a high-precision transcranial magnetic stimulation positioning method based on optical navigation, characterized by comprising:

[0005] Based on the patient's three-dimensional brain model, non-coplanar reference points were selected to obtain the image coordinates and physical coordinates of all reference points;

[0006] By matching corresponding points between image coordinates and physical coordinates, the optimal rigid transformation matrix is ​​calculated and generated, and the target registration error is calculated to achieve registration between the image coordinate system and the physical coordinate system.

[0007] Based on the registered brain tissue conductivity parameters, the spatial distribution of the electric field induced by the transcranial magnetic stimulation coil in the target brain region is calculated, and the coordinates of the stimulation target point of the virtual coil are dynamically corrected.

[0008] Based on the completed coordinate system registration results, the position and orientation of the virtual coil corresponding to the transcranial magnetic stimulation coil are dynamically displayed on the three-dimensional brain model. The brain slice view is updated synchronously based on the corrected target coordinates, and the boundaries of the actual stimulated brain regions are highlighted.

[0009] Optionally, the step of selecting non-coplanar reference points based on the patient's three-dimensional brain model and obtaining the image coordinates and physical coordinates of all reference points includes:

[0010] Non-coplanar reference points are selected on the patient's head by manual operation. There are at least four reference points that are not on the same plane.

[0011] Before the operation, the center positions of all reference points were manually marked on the patient's three-dimensional brain model to obtain the three-dimensional coordinates of each point in the image coordinate system.

[0012] During the procedure, an optical tracking system is used to track and collect the real-time physical coordinates of the same set of reference points in the surgical space.

[0013] Optionally, the step of matching corresponding points through image coordinates and physical coordinates, calculating the optimal rigid transformation matrix, and calculating the target registration error to achieve registration between the image coordinate system and the physical coordinate system includes:

[0014] By ensuring the uniqueness of the reference points, the image coordinates and physical coordinates of all reference points are matched and corresponded, and the parameters are optimized based on the least squares method.

[0015] By optimizing the calculation, the spatial transformation relationship with the minimum deviation of the reference point position after the transformation from the image coordinate system to the physical coordinate system is obtained, and the optimal rigid transformation matrix is ​​generated.

[0016] Based on the generated optimal rigid transformation matrix, the average deviation between the physical position and the transformed position of all reference points is calculated and evaluated.

[0017] Optionally, the step of calculating the spatial distribution of the electric field induced by the transcranial magnetic stimulation coil in the target brain region based on the registered brain tissue conductivity parameters, and dynamically correcting the stimulation target point coordinates of the virtual coil, includes:

[0018] Obtain the layered conductivity parameters, time-varying current, and spatial location vector of brain tissue, and generate a magnetic vector potential through calculation;

[0019] The electric field strength is generated by using the coil electric field calculation formula to calculate the magnetic vector potential.

[0020] The formula for calculating the electric field of the coil is:

[0021] ;

[0022] in, The total electric field strength is For the potential gradient, It is the negative time derivative of the time potential magnetic vector potential;

[0023] The peak value of the electric field intensity is obtained as the actual stimulation target point, and the offset correction amount is generated by comparing it with the coordinates of the predetermined target point.

[0024] Optionally, the step of dynamically displaying the position and orientation of the virtual coil corresponding to the transcranial magnetic stimulation coil on the three-dimensional brain model based on the completed coordinate system registration results, and synchronously updating the brain slice view based on the corrected target coordinates and highlighting the boundary of the actual stimulated brain region includes:

[0025] Based on the optical tracking system, the physical coil pose data is acquired in real time and mapped to the image space of the three-dimensional brain model through the optimal rigid transformation matrix, thereby dynamically generating a synchronized virtual coil model.

[0026] Based on the target coordinates of the virtual coil, coronal, sagittal and transverse anatomical slices that pass through the target and are orthogonal to each other are generated, and the target brain region covered is dynamically highlighted in the slices.

[0027] Based on real-time calculated electric field distribution, the boundaries of the actually stimulated brain regions are dynamically highlighted in the brain slice view.

[0028] When the deviation between the peak position of the electric field and the predetermined target point exceeds the clinical threshold, a coil pose adjustment guide is generated.

[0029] Optionally, the step of obtaining brain tissue layered conductivity parameters, time-varying current, and spatial location vectors, and generating a magnetic vector potential through calculation, includes:

[0030] Based on the time-varying current and the position of the target point relative to the coil, the magnetic vector potential generated by the coil current in space is calculated using the magnetic vector potential calculation formula.

[0031] The formula for calculating the magnetic vector potential is:

[0032]

[0033] in, It is a magnetic vector potential. It is the permeability of free space. It is the time-varying current applied in the TMS coil. and To indicate the position of a point in space relative to a coil, This is the integral along the path of the coil wire.

[0034] Optionally, the high-precision positioning method for transcranial magnetic stimulation based on optical navigation is characterized by further comprising:

[0035] By setting unique IDs and spatial relationships for each benchmark point, all benchmark points can be uniquely identified.

[0036] Image coordinates with the same identifier and physical coordinates Perform matching to form a coordinate dataset;

[0037] Based on the offset of the overall position in the coordinate dataset, the least squares method is used to generate transformation parameters that minimize the overall deviation.

[0038] For each reference point, the theoretical coordinate transformation calculation formula is used to obtain the possible value that minimizes the sum of squared distances, and the optimal rigid transformation matrix is ​​generated.

[0039] The theoretical formula for calculating coordinate transformation is:

[0040] ;

[0041] in, For the first Homogeneous coordinate representation of the image coordinates of a reference point These are the theoretical coordinates in the physical coordinate system after the transformation. This is the optimal rigid transformation matrix;

[0042] The root mean square value of the deviation of all reference points is calculated using the target registration error calculation formula to generate the target registration error. This error is then compared with the set clinical threshold to obtain the evaluation conclusion.

[0043] The formula for calculating target registration error is:

[0044] ;

[0045] in, For the first The measured coordinates of the physical coordinate system of each reference point For the first Theoretical coordinates after image coordinate transformation of each reference point The optimal rigid transformation matrix is The target registration error.

[0046] This application also provides a high-precision transcranial magnetic stimulation positioning device based on optical navigation, characterized in that the device comprises:

[0047] The reference point sampling module is used to select non-coplanar reference points based on the patient's three-dimensional brain model and obtain the image coordinates and physical coordinates of all reference points.

[0048] The rigid matching module is used to match corresponding points between image coordinates and physical coordinates, calculate and generate the optimal rigid transformation matrix, and calculate the target registration error to achieve registration between the image coordinate system and the physical coordinate system.

[0049] The electric field remapping module is used to calculate the spatial distribution of the electric field induced by the transcranial magnetic stimulation coil in the target brain region based on the registered brain tissue conductivity parameters, and to dynamically correct the stimulation target point coordinates of the virtual coil.

[0050] The stimulation domain visualization module is used to dynamically display the position and orientation of the virtual coil corresponding to the transcranial magnetic stimulation coil on the 3D brain model based on the completed coordinate system registration results. It also updates the brain slice view based on the corrected target coordinates and highlights the actual stimulated brain region boundaries.

[0051] Optionally, the electric field remapping module further includes:

[0052] The magnetic potential field calculation module is used to calculate the spatial magnetic vector potential distribution using the magnetic vector potential calculation formula.

[0053] The conductivity building module is used to construct a hierarchical model of brain tissue conductivity.

[0054] The electric field solution module is used to calculate and generate the electric field strength using the coil electric field calculation formula.

[0055] The target point dynamic correction module is used to locate the peak coordinates of the electric field and compare them with the original target point to generate an offset vector.

[0056] This application also provides an electronic device, characterized in that it is used to implement the high-precision transcranial magnetic stimulation positioning method based on optical navigation as described in any one of claims 1 to 7, comprising:

[0057] Medical imaging scanning equipment is used to generate raw data for a patient's three-dimensional brain model, as well as image coordinate system coordinates that provide reference points;

[0058] Optical positioning and tracking equipment is used to acquire the physical coordinates of a reference point in real time, and to track the spatial pose of the transcranial magnetic stimulation coil;

[0059] Transcranial magnetic stimulation coils are used for non-invasive neuromodulation and to drive the dynamic mapping of virtual coils in a three-dimensional brain model.

[0060] The processor is used to perform all computationally intensive tasks, enabling a high-precision positioning method for transcranial magnetic stimulation based on optical navigation;

[0061] Memory is used to store processor-executable instructions and statically stored data.

[0062] The beneficial effects of this application are as follows: This application achieves sub-millimeter-level coordinate system registration through image-physical coordinate mapping of non-coplanar reference points and rigid transformation matrix calculation, significantly improving the positioning accuracy of stimulation targets; based on the layered conductivity parameters of brain tissue, the spatial distribution of the electric field is calculated in real time using the finite element method, and the coordinates of the stimulation targets are dynamically corrected, overcoming the positioning deviation of deep targets caused by tissue conduction differences in traditional rigid navigation; and the registration results drive the dynamic mapping of the three-dimensional brain model and the real-time updating of multi-planar slices, combined with the high-brightness display of the actual stimulation brain region boundary after electric field correction, ensuring smooth operation in low-configuration hardware environments; and through the automatic correction guidance of coil pose driven by electric field peak, it is compatible with the parsing interface of multiple brain scan formats and the manual / mechanical dual-mode control mechanism, synchronously responding to the dynamic adjustment needs in clinical operation, and constructing a treatment closed loop of adaptive electric field navigation. Attached Figure Description

[0063] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the accompanying drawings required in the description of the embodiments or the prior art are briefly introduced below. Obviously, the accompanying drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0064] Figure 1 The flowchart illustrates an embodiment of a high-precision transcranial magnetic stimulation positioning method based on optical navigation disclosed in this application.

[0065] Figure 2 This illustration shows a reference point diagram of an embodiment of a transcranial magnetic stimulation high-precision positioning method based on optical navigation disclosed in this application;

[0066] Figure 3 This illustration shows a position display diagram of an embodiment of a high-precision transcranial magnetic stimulation positioning method based on optical navigation disclosed in this application;

[0067] Figure 4 This diagram shows a structural block diagram of an embodiment of a transcranial magnetic stimulation high-precision positioning method based on optical navigation disclosed in this application. Detailed Implementation

[0068] Various exemplary embodiments, features, and aspects of this application will now be described in detail with reference to the accompanying drawings. The same reference numerals in the drawings denote elements that have the same or similar functions. Although various aspects of the embodiments are shown in the drawings, they are not necessarily drawn to scale unless specifically indicated otherwise.

[0069] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0070] The term “exemplary” as used herein means “serving as an example, embodiment, or illustration.” Any embodiment illustrated herein as “exemplary” is not necessarily to be construed as superior to or better than other embodiments.

[0071] Furthermore, to better illustrate this application, numerous specific details are provided in the following detailed embodiments. Those skilled in the art should understand that this application can be implemented without certain specific details. In some instances, methods, means, components, and circuits well-known to those skilled in the art have not been described in detail in order to highlight the main points of this application.

[0072] This application proposes a high-precision transcranial magnetic stimulation (TMS) localization method based on optical navigation to address the problems of traditional rigid navigation, such as deep target localization errors, inefficient data processing, distorted visualization of the stimulation range, limited compatibility, and poor operational flexibility caused by neglecting differences in tissue conductivity. By establishing an image-physical coordinate mapping of non-coplanar reference points, the optimal rigid transformation matrix is ​​calculated to achieve precise coordinate system registration. Based on the registered brain tissue conductivity parameters, the electric field distribution induced by the coil is calculated in real time using Bio-Savart's law and the finite element method, dynamically correcting the target coordinates. The system uses the registration results to dynamically display the virtual position and orientation of the TMS coil in a 3D brain model, synchronously updating the brain slice view based on the electric field-corrected target coordinates, and highlighting the actual stimulated brain region boundaries. This application significantly improves data processing efficiency, expands brain scan format compatibility, and integrates a dual-mode adjustment mechanism of manual and mechanical control to meet the needs of dynamic clinical operation while ensuring accurate matching between the model and the actual space.

[0073] Example 1

[0074] like Figure 1 The diagram shown is a flowchart of a high-precision transcranial magnetic stimulation positioning method based on optical navigation according to an embodiment of this application, which specifically includes the following:

[0075] S100, based on the patient's three-dimensional brain model, selects non-coplanar reference points and obtains the image coordinates and physical coordinates of all reference points.

[0076] Specifically, based on the patient's three-dimensional brain model, at least four spatially distinct non-coplanar reference points (such as the root of the nose, tragus, and cranial vertex markers) are selected, and their spatial distribution must satisfy the mathematical completeness condition of rigid transformation. The image coordinates of these reference points are extracted using medical imaging (CT / MRI), and simultaneously, their physical coordinates are obtained in the actual space of the patient's head using surface markers or the tips of surgical instruments. The reference points of these two coordinate systems constitute a spatial mapping.

[0077] S200 calculates the optimal rigid transformation matrix by matching corresponding points between image coordinates and physical coordinates, and performs target registration error calculation to achieve registration between the image coordinate system and the physical coordinate system.

[0078] Specifically, by matching and calculating the corresponding points of the image coordinates and physical coordinates, the optimal rigid transformation matrix is ​​generated, and the registration accuracy is verified based on the target registration error, thus realizing a spatial mapping from the image coordinate system to the physical coordinate system that conforms to neurosurgical standards.

[0079] S300 calculates the spatial distribution of the electric field induced by the transcranial magnetic stimulation coil in the target brain region based on the registered brain tissue conductivity parameters, and dynamically corrects the stimulation target coordinates of the virtual coil.

[0080] Specifically, based on the registered brain tissue layer conductivity parameters (scalp / skull / cerebrospinal fluid), the three-dimensional electric field spatial distribution induced by the transcranial magnetic stimulation coil in the target brain region is calculated in real time using the finite element method, and the stimulation target coordinates of the virtual coil are dynamically corrected according to the peak position of the electric field intensity.

[0081] S400 dynamically displays the position and orientation of the virtual coil corresponding to the transcranial magnetic stimulation coil on the three-dimensional brain model based on the completed coordinate system registration results. It also synchronously updates the brain slice view based on the corrected target coordinates and highlights the actual brain region boundary being stimulated.

[0082] Specifically, based on the coordinate system registration results, the real-time pose of the transcranial magnetic stimulation coil is dynamically mapped in the three-dimensional brain model, and the multi-planar brain slice view is synchronously updated based on the target coordinates corrected in step S300. At the same time, the anatomical boundaries of the brain regions actually stimulated by the electric field are highlighted.

[0083] In summary, this application constructs a non-coplanar reference point spatial registration system. By selecting at least four spatially distinct surface markers (such as the root of the nose, tragus, and cranial vault), precise coordinate data of the image coordinate system and the physical coordinate system are acquired simultaneously, forming control point pairs that satisfy the completeness of rigid transformation. This non-coplanar reference layout effectively avoids registration singularities caused by coplanar points, laying a geometric foundation for sub-millimeter-level spatial mapping and fundamentally solving the positioning deviation problem caused by the defective distribution of reference points in traditional schemes. Secondly, a rigid transformation-driven registration verification architecture is designed. The optimal rigid transformation matrix is ​​generated by matching corresponding points in the image-physical coordinate system, and the registration accuracy is dynamically verified based on the target registration error (TRE). This architecture ensures that the transformation process from the image coordinate system to the physical coordinate system always meets neurosurgical accuracy standards, completely eliminating the risk of stimulation target point offset caused by coordinate mapping inaccuracies, and providing rigid spatial transformation assurance for precise neuromodulation. Then, breaking through the limitations of traditional rigid navigation, this method dynamically corrects target coordinate shifts caused by tissue penetration attenuation through layered conductivity modeling and finite element solution of the electric field equations, solving the industry-wide problem of focal point upward shift in deep brain regions such as the dorsolateral prefrontal cortex. Finally, an optical tracker captures the physical pose of the coil in real time, converts it into image coordinate parameters through a rigid transformation matrix, and dynamically renders a fully synchronized virtual coil in a 3D brain model. The orthogonal anatomical slice plane (coronal / sagittal / horizontal plane) is automatically determined by the virtual coil axis, enabling real-time updates of the brain slice view. This mechanism instantly transforms the doctor's operational intentions into multi-dimensional visual navigation, forming a millisecond-level closed loop of "physical operation - virtual display," significantly improving the efficiency and reliability of target localization in complex clinical scenarios.

[0084] As one possible implementation, in step S100, based on the patient's three-dimensional brain model, non-coplanar reference points are selected, and the image coordinates and physical coordinates of all reference points are obtained, including:

[0085] S101, Select non-coplanar reference points on the patient's head by manual operation, wherein there are at least 4 reference points that are not on the same plane.

[0086] Specifically, the doctor manually marks four spatially distinct points on the patient's head surface as reference points. These reference points are not located on the same anatomical plane to ensure that the spatial distribution of the reference points satisfies the geometric non-coplanar constraints required for rigid transformation.

[0087] In neurosurgery, reference points are typically surface markers and surgical instrument tips. The surface markers are carried by infrared reflective balls or electromagnetic positioning markers on the patient's head, and the surgical instrument tips are located in real time using optical tracking devices.

[0088] S102, Before the operation, the center positions of all reference points are manually marked on the patient's three-dimensional brain model to obtain the three-dimensional coordinates of each point in the image coordinate system.

[0089] Specifically, such as Figure 2 As shown, in the preoperative three-dimensional brain model of the patient reconstructed based on CT / MRI data, the anatomical center position of the reference point selected in step S101 is manually located and marked by the doctor. The coordinate extraction function of medical image processing software (such as 3DSlicer) is used to accurately obtain the three-dimensional coordinate value of each reference point in the image coordinate system.

[0090] S103, during the operation, the optical tracking system tracks and collects the real-time physical coordinates of the same set of reference points in the surgical space.

[0091] Specifically, during the operation, the physical coordinates of the patient's head reference point in the actual surgical space are acquired in real time using a positioning probe or reflective ball of an optical tracking system (such as NDI Polaris). The system uses the fixed coordinate system of the operating room as a reference, captures the spatial position of the reflective marker point through an infrared camera, and outputs three-dimensional physical coordinates with millimeter-level accuracy by combining the probe's geometric calibration parameters.

[0092] This process needs to be performed on the same set of reference points as the image coordinate acquisition in step S102.

[0093] As one possible implementation, in step S200, by matching corresponding points between image coordinates and physical coordinates, an optimal rigid transformation matrix is ​​calculated and generated, and target registration error is calculated to achieve registration between the image coordinate system and the physical coordinate system, including:

[0094] S201 achieves the matching and correspondence of image coordinates and physical coordinates of all reference points through the uniqueness of the reference points, and performs parameter optimization based on the least squares method.

[0095] Specifically, based on the unique anatomical identifier of the reference point (such as a specific surface marker location), the coordinates of the preoperatively labeled image coordinate system are precisely matched point-to-point with the coordinates of the physical coordinate system acquired during surgery, forming a one-to-one spatial coordinate dataset. A least squares optimization algorithm is then used to iteratively calculate the rotation and translation parameters, minimizing the overall deviation between the actual physical position and the theoretical transformed position of all reference points.

[0096] Specifically, by setting unique IDs and spatial relationships for each reference point, all reference points are uniquely identified, and image coordinates with the same identifier are linked together. and physical coordinates Matching is performed to form a coordinate dataset, and based on the offset of the overall position in the coordinate dataset, the least squares method is used to generate transformation parameters that minimize the overall deviation.

[0097] S202, through optimization calculation, obtains the spatial transformation relationship with the minimum deviation of the reference point position after the transformation from the image coordinate system to the physical coordinate system, and generates the optimal rigid transformation matrix.

[0098] Specifically, based on the optimized spatial correspondence, an optimal rigid transformation matrix is ​​generated. This matrix consists of three-dimensional rotation parameters and three-dimensional translation parameters, which can convert the coordinates of any point in the image coordinate system into theoretical coordinates in the physical coordinate system. The transformation process strictly preserves the rigid body characteristics of the spatial structure (i.e., the distance and angle between points remain unchanged), achieving conformal mapping between image space and physical space.

[0099] Specifically, for each reference point, the theoretical coordinate transformation calculation formula is used to obtain the minimum possible value of the sum of squared distances, generating the optimal rigid transformation matrix. The theoretical coordinate transformation calculation formula is as follows:

[0100] ;

[0101] The above, For the first Homogeneous coordinate representation of the image coordinates of a reference point These are the theoretical coordinates in the physical coordinate system after the transformation. This is the optimal rigid transformation matrix.

[0102] S203. Based on the generated optimal rigid transformation matrix, calculate and obtain the average deviation between the physical position and the transformed position of all reference points, and then evaluate it.

[0103] Specifically, using the generated rigid transformation matrix, the theoretical coordinates of all reference points in physical space are calculated and compared with the actual coordinates measured by the optical tracking system. The registration accuracy is quantitatively evaluated by calculating the average spatial distance between the theoretical and actual values ​​of each point (i.e., the target registration error, TRE). This error value is compared in real time with a neurosurgical clinical safety threshold (typically 2 mm). If the error is below the threshold, registration is deemed valid and navigation begins; if it exceeds the threshold, an alarm is triggered prompting re-registration.

[0104] Specifically, the root mean square value of the deviation of all reference points is calculated using the target registration error calculation formula to generate the target registration error. This target registration error is then compared with a set clinical threshold to obtain an evaluation conclusion. The target registration error calculation formula is as follows:

[0105] ;

[0106] The above, For the first The measured coordinates of the physical coordinate system of each reference point For the first Theoretical coordinates after image coordinate transformation of each reference point The optimal rigid transformation matrix is The target registration error.

[0107] As one possible implementation, in step S300, based on the registered brain tissue conductivity parameters, the spatial distribution of the electric field induced by the transcranial magnetic stimulation coil in the target brain region is calculated, and the coordinates of the stimulation target point of the virtual coil are dynamically corrected, including:

[0108] S301 acquires the brain tissue layer conductivity parameters, time-varying current, and spatial position vector, and generates a magnetic vector potential through calculation.

[0109] Specifically, by integrating multi-source input parameters to construct the electromagnetic computation foundation, standardized or personalized conductivity values ​​of the scalp (high conductivity), skull (ultra-low conductivity), and cerebrospinal fluid (high conductivity) layers are loaded to form a spatial conduction model of bioelectromagnetic properties. By incorporating the pulse current waveform function output from the transcranial magnetic stimulation device, the instantaneous intensity and time-varying characteristics of the coil driving current are characterized. By capturing the coil's physical pose based on an optical tracking system and combining it with the registered brain model's spatial coordinate system, the three-dimensional spatial vector of the target brain region relative to the coil conductor is determined. Finally, based on the Bio-Savart law, the spatial integration of the coil conductor path is performed to calculate the magnetic vector potential field excited by the time-varying current at the target location.

[0110] Specifically, based on the time-varying current and the position of the target point relative to the coil, the magnetic vector potential generated by the coil current in space is calculated using the magnetic vector potential calculation formula. The magnetic vector potential calculation formula is as follows:

[0111]

[0112] in, It is a magnetic vector potential. It is the permeability of free space. It is the time-varying current applied in the TMS coil. and To indicate the position of a point in space relative to a coil, This is the integral along the path of the coil wire.

[0113] S302 uses the coil electric field calculation formula to generate the electric field strength for the magnetic vector potential.

[0114] Specifically, the time partial derivative of the magnetic vector potential function output in step S301 is calculated, and the electric field control equation is constructed in combination with the brain tissue conductivity parameters. The solution is iteratively obtained on the brain tissue grid nodes using the finite element method, and the electric field intensity vector at each point in three-dimensional space is output.

[0115] The formula for calculating the electric field of the coil is as follows:

[0116] ;

[0117] in, The total electric field strength is For the potential gradient, It is the negative time derivative of the time potential magnetic vector potential;

[0118] S303: Obtain the peak value of the electric field intensity as the actual stimulation target point, and compare it with the coordinates of the predetermined target point to generate an offset correction amount.

[0119] Specifically, by scanning the three-dimensional electric field intensity distribution calculated in step S302, the peak coordinates of the electric field intensity (i.e. the position with the highest neuronal depolarization probability) are identified as the real physiological stimulation target. The Euclidean distance between the actual target and the preset target (based on anatomical landmarks) is calculated. If the distance exceeds the clinically permissible threshold (typical value 2mm), a spatial offset vector from the preset target to the actual target is generated.

[0120] As one possible implementation, in step S400, based on the completed coordinate system registration results, the position and orientation of the virtual coil corresponding to the transcranial magnetic stimulation coil are dynamically displayed on the three-dimensional brain model. The brain slice view is synchronously updated based on the corrected target coordinates, and the boundaries of the actually stimulated brain regions are highlighted. This includes:

[0121] S401 acquires physical coil pose data in real time based on an optical tracking system, maps it to the image space of a three-dimensional brain model through an optimal rigid transformation matrix, and dynamically generates a synchronized virtual coil model.

[0122] Specifically, such as Figure 3 As shown, the pose data of the physical coil is captured in real time by an optical tracker, and the rigid transformation matrix T generated in step S202 is applied to convert the physical pose into image coordinate system parameters. A fully synchronized virtual coil is dynamically rendered in the three-dimensional brain model, and the spatial position and axial angle of the virtual coil are strictly consistent with those of the physical coil.

[0123] S402 generates coronal, sagittal, and transverse anatomical slices that pass through the target point and are orthogonal to each other, based on the target point coordinates of the virtual coil, and dynamically highlights the covered target brain region in the slices.

[0124] Specifically, such as Figure 3As shown, based on the target point coordinates of the virtual coil tip in the image space, three orthogonal anatomical planes are automatically determined: the coronal plane, the sagittal plane, and the transverse plane. The coronal plane is parallel to the line connecting the frontal and occipital lobes, the sagittal plane is parallel to the plane separating the left and right hemispheres of the brain, and the transverse plane is parallel to the line connecting the base and top of the skull. The three-plane tomographic images passing through the target point are extracted and rendered in real time from the 3D brain model. The target brain region covered by the stimulation electric field (such as the primary motor cortex) is dynamically highlighted. Furthermore, when the operator adjusts the physical coil, all views are synchronously refreshed within milliseconds, forming an operational feedback loop.

[0125] The operator can manually adjust the coil position by dragging the control slider or button with the mouse. The target area is highlighted synchronously in the slice view on the right, and keyboard shortcuts are supported for quick fine-tuning. External mechanical devices can be controlled to move according to instructions, and the position display is linked with the actual equipment to control the coil position.

[0126] S403, based on real-time calculated electric field distribution, dynamically highlights the boundaries of the actually stimulated brain regions in the brain slice view.

[0127] Specifically, based on the electric field intensity distribution data calculated in real time in step S302, the field intensity values ​​of different brain regions are extracted. By setting the electric field intensity threshold for neuron activation, the anatomical contours of brain regions that meet the threshold are filled with a bright color, and the boundaries are refreshed in real time as the coil moves.

[0128] S404 generates coil pose adjustment guidance when the deviation between the peak position of the electric field and the predetermined target point exceeds the clinical threshold.

[0129] Specifically, when the target offset determined in step S303 continues to exceed the clinical threshold (e.g., 2mm), it is determined that the current coil pose needs to be adjusted. A translation vector is generated by calculating the direction of the line connecting the actual target and the preset target, and the electric field distribution pattern is analyzed. If there is focal distortion, a rotation angle suggestion is generated.

[0130] Example 2

[0131] Based on the same principle as the aforementioned methods, a high-precision transcranial magnetic stimulation positioning method based on optical navigation is also proposed, see [link to relevant documentation]. Figure 4 A high-precision transcranial magnetic stimulation positioning device 100 based on optical navigation according to an embodiment of this disclosure includes:

[0132] The reference point sampling module 110 is used to select non-coplanar reference points based on the patient's three-dimensional brain model and obtain the image coordinates and physical coordinates of all reference points.

[0133] The rigid matching module 120 is used to match corresponding points between image coordinates and physical coordinates, calculate and generate the optimal rigid transformation matrix, and calculate the target registration error to achieve registration between the image coordinate system and the physical coordinate system.

[0134] The electric field remapping module 130 is used to calculate the spatial distribution of the electric field induced by the transcranial magnetic stimulation coil in the target brain region based on the registered brain tissue conductivity parameters, and to dynamically correct the stimulation target coordinates of the virtual coil.

[0135] The stimulation domain visualization module 140 is used to dynamically display the position and orientation of the virtual coil corresponding to the transcranial magnetic stimulation coil on the three-dimensional brain model based on the completed coordinate system registration results, and to update the brain slice view synchronously based on the corrected target coordinates and highlight the actual stimulated brain region boundary.

[0136] As an optional implementation of this application, the electric field remapping module 130 may further include:

[0137] The magnetic potential field calculation module 131 is used to calculate the spatial magnetic vector potential distribution using the magnetic vector potential calculation formula.

[0138] Electrical conductivity construction module 132 is used to construct a hierarchical model of brain tissue electrical conductivity.

[0139] Electric field solving module 133 is used to calculate and generate electric field strength using the coil electric field calculation formula;

[0140] The target point dynamic correction module 134 is used to locate the peak coordinates of the electric field and compare them with the original target point to generate an offset vector.

[0141] Obviously, those skilled in the art should understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the control methods described above. The modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device, or fabricating them separately as individual integrated circuit modules, or fabricating multiple modules or steps into a single integrated circuit module. Thus, the present invention is not limited to any specific hardware and software combination.

[0142] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the control methods described above. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk drive (HDD), or solid-state drive (SSD), etc.; the storage medium can also include combinations of the above types of memory.

[0143] Example 3

[0144] Furthermore, this application proposes an electronic device characterized in that, for implementing any of the described high-precision positioning methods for transcranial magnetic stimulation based on optical navigation, it comprises:

[0145] Medical imaging scanning equipment is used to generate raw data for a patient's three-dimensional brain model, as well as image coordinate system coordinates that provide reference points;

[0146] Optical positioning and tracking equipment is used to acquire the physical coordinates of a reference point in real time, and to track the spatial pose of the transcranial magnetic stimulation coil;

[0147] Transcranial magnetic stimulation coils are used for non-invasive neuromodulation and to drive the dynamic mapping of virtual coils in a three-dimensional brain model.

[0148] The processor is used to perform all computationally intensive tasks, enabling a high-precision positioning method for transcranial magnetic stimulation based on optical navigation;

[0149] Memory is used to store processor-executable instructions and statically stored data.

[0150] Medical imaging scanning equipment serves as the data source for spatial modeling of the patient's brain. It generates the raw tomographic image sequences (such as DICOM data from CT / MRI) required to construct a three-dimensional brain model and extracts the precise three-dimensional coordinates of reference points in the image coordinate system using image processing software. The coordinate data output by this equipment constitutes the image spatial reference for spatial registration.

[0151] The optical positioning and tracking device serves as a real-time acquisition system for surgical spatial coordinates. It tracks the physical coordinates of the patient's head reference point at the millimeter level during surgery and simultaneously captures the six-degree-of-freedom spatial pose (three-dimensional position + three-axis orientation) of the transcranial magnetic stimulation coil. Its output dynamic coordinate data stream provides physical spatial motion parameters for coordinate system registration and navigation mapping.

[0152] Transcranial magnetic stimulation coils serve as both neuromodulation actuators and navigation feedback carriers. On one hand, they deliver non-invasive brain region stimulation therapy via time-varying magnetic fields; on the other hand, their spatial pose data drives the real-time dynamic mapping of virtual coils within a three-dimensional brain model. This device simultaneously performs the dual functions of physical manipulation and virtual navigation during treatment.

[0153] It should be noted that the number of processors can be one or more. Furthermore, the electronic device in this embodiment may also include input devices and output devices. The processor, memory, input devices, and output devices can be connected via a bus or other means, without specific limitations herein.

[0154] The memory, as a computer-readable storage medium for a data-driven large language model performance prediction system, can be used to store software programs, computer-executable programs, and various modules, such as the program or module corresponding to the optical navigation-based transcranial magnetic stimulation high-precision positioning method in this disclosure. The processor executes various functional applications and data processing of the electronic device by running the software programs or modules stored in the memory.

[0155] The various embodiments of this application have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or improvement of the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A high-precision transcranial magnetic stimulation positioning device based on optical navigation, characterized in that, The device includes: The reference point sampling module is used to select non-coplanar reference points based on the patient's three-dimensional brain model. The reference points are at least four points that are not on the same plane, and the image coordinates and physical coordinates of all reference points are obtained. The rigid matching module is used to match corresponding points between image coordinates and physical coordinates, calculate and generate the optimal rigid transformation matrix, and calculate the target registration error to achieve registration between the image coordinate system and the physical coordinate system. The electric field remapping module is used to calculate the spatial distribution of the electric field induced by the transcranial magnetic stimulation coil in the target brain region based on the registered brain tissue conductivity parameters, and to dynamically correct the stimulation target point coordinates of the virtual coil, including: Obtain the layered conductivity parameters, time-varying current, and spatial location vector of brain tissue, and generate a magnetic vector potential through calculation; Based on the time-varying current and the position of the target point relative to the coil, the magnetic vector potential generated by the coil current in space is calculated using the magnetic vector potential calculation formula. The formula for calculating the magnetic vector potential is: where is the magnetic vector potential, is the permeability of free space, is the applied time-varying current in the TMS coil, and is a position of a point in space relative to the coil, is a path integral along the coil wire. The electric field strength is generated by using the coil electric field calculation formula to calculate the magnetic vector potential. The formula for calculating the electric field of the coil is: ； in, The total electric field strength is For the potential gradient, It is the negative time derivative of the time potential magnetic vector potential; The peak value of the electric field intensity is obtained as the actual stimulation target point, and the offset correction amount is generated by comparing it with the coordinates of the predetermined target point. The stimulation domain visualization module dynamically displays the position and orientation of the virtual coil corresponding to the transcranial magnetic stimulation coil on the 3D brain model based on the completed coordinate system registration results. It also updates the brain slice view synchronously based on the corrected target coordinates and highlights the boundaries of the actually stimulated brain regions, including: Based on the optical tracking system, the physical coil pose data is acquired in real time and mapped to the image space of the three-dimensional brain model through the optimal rigid transformation matrix, thereby dynamically generating a synchronized virtual coil model. Based on the target coordinates of the virtual coil, coronal, sagittal and transverse anatomical slices that pass through the target and are orthogonal to each other are generated, and the target brain region covered is dynamically highlighted in the slices. Based on real-time calculated electric field distribution, the boundaries of the actually stimulated brain regions are dynamically highlighted in the brain slice view. When the deviation between the peak position of the electric field and the predetermined target point exceeds the clinical threshold, a physical coil pose adjustment guide is generated.

2. The transcranial magnetic stimulation high-precision positioning device based on optical navigation as described in claim 1, characterized in that, The three-dimensional brain model based on the patient selects non-coplanar reference points and obtains the image coordinates and physical coordinates of all reference points, including: Non-coplanar reference points are selected on the patient's head through manual operation; Before the operation, the center positions of all reference points were manually marked on the patient's three-dimensional brain model to obtain the three-dimensional coordinates of each point in the image coordinate system. During the procedure, an optical tracking system is used to track and collect the real-time physical coordinates of the same set of reference points in the surgical space.

3. The transcranial magnetic stimulation high-precision positioning device based on optical navigation as described in claim 1, characterized in that, The process of matching corresponding points between image coordinates and physical coordinates, calculating the optimal rigid transformation matrix, and calculating target registration error to achieve registration between the image coordinate system and the physical coordinate system includes: By ensuring the uniqueness of the reference points, the image coordinates and physical coordinates of all reference points are matched and corresponded, and the parameters are optimized based on the least squares method. By optimizing the calculation, the spatial transformation relationship with the minimum deviation of the reference point position after the transformation from the image coordinate system to the physical coordinate system is obtained, and the optimal rigid transformation matrix is ​​generated. Based on the generated optimal rigid transformation matrix, the average deviation between the physical position and the transformed position of all reference points is calculated and evaluated.

4. The transcranial magnetic stimulation high-precision positioning device based on optical navigation as described in claim 3, characterized in that, Also includes: By setting unique IDs and spatial relationships for each benchmark point, all benchmark points can be uniquely identified. Image coordinates with the same identifier and physical coordinates Perform matching to form a coordinate dataset; Based on the offset of the overall position in the coordinate dataset, the least squares method is used to generate transformation parameters that minimize the overall deviation. For each reference point, the theoretical coordinate transformation calculation formula is used to obtain the possible value that minimizes the sum of squared distances, and the optimal rigid transformation matrix is ​​generated. The theoretical formula for calculating coordinate transformation is: ； in, For the first Homogeneous coordinate representation of the image coordinates of a reference point These are the theoretical coordinates in the physical coordinate system after the transformation. This is the optimal rigid transformation matrix; The root mean square value of the deviation of all reference points is calculated using the target registration error calculation formula to generate the target registration error. This error is then compared with the set clinical threshold to obtain the evaluation conclusion. The formula for calculating target registration error is: ； in, For the first The measured coordinates of the physical coordinate system of each reference point For the first Theoretical coordinates after image coordinate transformation of each reference point The optimal rigid transformation matrix is The target registration error.

5. The high-precision transcranial magnetic stimulation positioning device based on optical navigation according to claim 1, wherein the electric field remapping module further comprises: The magnetic potential field calculation module is used to calculate the spatial magnetic vector potential distribution using the magnetic vector potential calculation formula. The conductivity building module is used to construct a hierarchical model of brain tissue conductivity. The electric field solution module is used to calculate and generate the electric field strength using the coil electric field calculation formula. The target point dynamic correction module is used to locate the peak coordinates of the electric field and compare them with the original target point to generate an offset vector.

6. An electronic device, characterized in that, include: Medical imaging scanning equipment is used to generate raw data for a patient's three-dimensional brain model, as well as image coordinate system coordinates that provide reference points; Optical positioning and tracking equipment is used to acquire the physical coordinates of a reference point in real time, and to track the spatial pose of the transcranial magnetic stimulation coil; Transcranial magnetic stimulation coils are used for non-invasive neuromodulation and to drive the dynamic mapping of virtual coils in a three-dimensional brain model. The processor is configured as follows: For use in a three-dimensional brain model of a patient, select non-coplanar reference points, wherein there are at least four reference points that are not on the same plane, and obtain the image coordinates and physical coordinates of all reference points. By matching corresponding points between image coordinates and physical coordinates, the optimal rigid transformation matrix is ​​calculated and generated, and the target registration error is calculated to achieve registration between the image coordinate system and the physical coordinate system. Based on the registered brain tissue conductivity parameters, the spatial distribution of the electric field induced by the transcranial magnetic stimulation coil in the target brain region is calculated, and the coordinates of the stimulation target point of the virtual coil are dynamically corrected, including: Obtain the layered conductivity parameters, time-varying current, and spatial location vector of brain tissue, and generate a magnetic vector potential through calculation; Based on the time-varying current and the position of the target point relative to the coil, the magnetic vector potential generated by the coil current in space is calculated using the magnetic vector potential calculation formula. The formula for calculating the magnetic vector potential is: in, It is a magnetic vector potential. It is the permeability of free space. It is the time-varying current applied in the TMS coil. and To indicate the position of a point in space relative to a coil, Integral along the path of the coil wire; The electric field strength is generated by using the coil electric field calculation formula to calculate the magnetic vector potential. The formula for calculating the electric field of the coil is: ； in, The total electric field strength is For the potential gradient, It is the negative time derivative of the time potential magnetic vector potential; The peak value of the electric field intensity is obtained as the actual stimulation target point, and the offset correction amount is generated by comparing it with the coordinates of the predetermined target point. This is used to dynamically display the position and orientation of the virtual coil corresponding to the transcranial magnetic stimulation coil on a 3D brain model based on the completed coordinate system registration results. It also updates the brain slice view synchronously based on the corrected target coordinates and highlights the boundaries of the actually stimulated brain regions, including: Based on the optical tracking system, the physical coil pose data is acquired in real time and mapped to the image space of the three-dimensional brain model through the optimal rigid transformation matrix, thereby dynamically generating a synchronized virtual coil model. Based on the target coordinates of the virtual coil, coronal, sagittal and transverse anatomical slices that pass through the target and are orthogonal to each other are generated, and the target brain region covered is dynamically highlighted in the slices. Based on real-time calculated electric field distribution, the boundaries of the actually stimulated brain regions are dynamically highlighted in the brain slice view. When the deviation between the peak position of the electric field and the predetermined target point exceeds the clinical threshold, a physical coil pose adjustment guide is generated. Memory is used to store processor-executable instructions and statically stored data.

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