A method, system, storage medium and product for calibrating a navigation probe

Abstract

The application discloses a kind of calibration method, system, storage medium and product of navigation probe, wherein the method comprises: obtaining the first space position coordinates of at least two characteristic target points in calibration phantom under imaging space coordinate system, and using the first conversion relationship between imaging space coordinate system and positioning space coordinate system and the second conversion relationship between positioning space coordinate system and navigation probe coordinate system, the first space position coordinates are converted to navigation probe coordinate system, and the first coordinate point set is obtained;At least two characteristic target points are collected using navigation probe ultrasonic image, and the characteristic target point is converted from ultrasonic image coordinate system to ultrasonic array coordinate system, and the second coordinate point set is obtained;At least three groups of first / second coordinate point set are obtained;Based on hand-eye calibration principle, at least three groups of first / second coordinate point set are used to obtain the target conversion matrix of ultrasonic image coordinate system to navigation probe coordinate system.

Description

Technical Field

[0001] This application relates to the field of medical imaging technology, and more specifically, to a calibration method, system, storage medium, and product for a navigation probe. Background Technology

[0002] The intraoperative real-time multimodal image fusion navigation technology currently used in clinical practice integrates preoperative static images, such as CT and MRI, with intraoperative dynamic images, such as ultrasound images, through precise spatial registration and algorithm fusion. This is combined with spatial positioning devices (such as binocular visual positioning systems and magnetic navigation positioning systems) to form an integrated surgical navigation solution. The core is to integrate the advantages of different modal images and make up for the information shortcomings of single images. Through real-time registered fused images, it provides surgeons with real-time, three-dimensional, and comprehensive information on anatomical structures and lesion localization during surgery.

[0003] In high-precision image fusion navigation applications, establishing the spatial correspondence between two-dimensional ultrasound images and preoperative three-dimensional image data relies on the accurate tracking and calibration of the navigation probe. However, existing technologies typically assume that the structural relationship between the probe housing and the internal ultrasound array is fixed, modeling only based on the probe's mechanical dimensional parameters. This ignores potential deformation or displacement of the probe during actual use, leading to a drift in the transformation relationship between the ultrasound image coordinate system and the probe coordinate system. This uncontrollable structural change directly introduces registration errors, reducing the accuracy of the fused images during surgery and potentially causing incorrect navigation guidance. Summary of the Invention

[0004] To overcome the impact of probe structural uncertainties, this application discloses a calibration method, system, storage medium, and product for a navigation probe. By utilizing only two feature target points at different depths for scalable multi-point set registration, it eliminates the dependence on a pre-set structural model and achieves full verification of the calibration accuracy across the entire ultrasound image domain. Specifically, the technical solution of this application is as follows: In a first aspect, this application discloses a calibration method for a navigation probe, comprising the following steps: Based on the spatial positioning device, a first transformation relationship between the imaging spatial coordinate system and the positioning spatial coordinate system is determined, as well as a second transformation relationship between the positioning spatial coordinate system and the navigation probe coordinate system; wherein, the spatial positioning device is used to track the navigation probe and the sensors on the calibration phantom in real time, and output the corresponding spatial pose information; The first spatial position coordinates of at least two feature target points in the calibration phantom are obtained in the imaging space coordinate system, and the first spatial position coordinates are transformed to the navigation probe coordinate system using the first transformation relationship and the second transformation relationship to obtain a first set of coordinate points, wherein at least two feature target points are located at different depths; The navigation probe is used to acquire ultrasound images of at least two of the feature target points, and the second pixel position coordinates of the feature target points in the ultrasound image coordinate system are obtained. According to the physical configuration parameters of the navigation probe, the second pixel position coordinates are transformed to the ultrasound array coordinate system to obtain the second coordinate point set. Repeat the acquisition steps of the first / second coordinate point set to obtain at least three different sets of the first / second coordinate point set; based on the hand-eye calibration principle, use at least three sets of the first / second coordinate point set to solve for the target transformation matrix from the ultrasound image coordinate system to the navigation probe coordinate system.

[0005] In some embodiments, at least four calibration lines are provided in the calibration phantom. The calibration lines are arranged horizontally and vertically at different depths in the calibration phantom to form at least two intersection points, which are the feature target points.

[0006] In other embodiments, the calibration method for a navigation probe further includes verifying the calibration results: Randomly obtain the third pixel position coordinates of at least one of the feature target points in the two-dimensional ultrasound image coordinate system as a verification target point; use the target transformation matrix to transform the third pixel position coordinates to the imaging space coordinate system to obtain the three-dimensional coordinates of the theoretical imaging space; The three-dimensional coordinates of the theoretical imaging space are compared with the known coordinates of the verification target point in the imaging space coordinate system in order to calculate the spatial position error and evaluate the calibration accuracy.

[0007] Based on the above implementation, the verification target point used for verification and the feature target point used for calibration are obtained from the same ultrasound array, and their coordinates do not overlap in the two-dimensional ultrasound image coordinate system.

[0008] Optionally, it may also include: arranging and combining at least three sets of the first / second coordinate points to form multiple datasets, each dataset containing at least three sets of the first subset for calibration and at least one set of the second subset for verification; and performing cross-validation based on the datasets to comprehensively evaluate the consistency of the calibration results.

[0009] Secondly, this application also discloses a calibration system for a navigation probe, comprising: The calibration phantom contains at least two feature target points located at different depths. A navigation probe, on which sensors are mounted for tracking by a spatial positioning device, and an ultrasonic array is installed inside the probe; A spatial imaging device is used to acquire a three-dimensional image of the calibration phantom to determine the coordinates of the feature target points in the imaging space coordinate system; The spatial positioning device is used to track the spatial pose of the navigation probe and the calibration phantom in real time; The processor is electrically connected to the navigation probe, the space imaging device, and the space positioning device, respectively, and the processor is configured to perform the steps of the calibration method described in any of the above embodiments.

[0010] Thirdly, this application also discloses a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the calibration method described in any of the above embodiments.

[0011] Fourthly, this application also discloses a computer program product, including a computer program that, when executed by a processor, implements the steps of the calibration method described in any of the above embodiments.

[0012] Compared with the prior art, this application has at least one of the following beneficial effects: 1. This application only requires that the calibrated phantom contains at least two feature targets located at different depths, without relying on complex pre-set structures, models, or a specific number of feature points. This approach significantly reduces the requirements for phantom machining accuracy and materials, frees it from the constraints of traditional rigid registration methods on the pre-set structure of the phantom, significantly reduces the difficulty and cost of manufacturing calibration fixtures, and improves the universality and economy of the method.

[0013] 2. This application allows for multiple data acquisitions based on a small number of feature targets, thereby expanding the final data. This enables the acquisition points to cover any location within the effective area of ​​the ultrasound image, including extreme locations such as the image edge. Based on this, the remaining data is used for verification and cross-evaluation, comprehensively calculating the calibration error across the entire image domain, forming a closed loop from calibration to verification. This solves the problem that traditional methods cannot fully evaluate the accuracy across the entire image domain.

[0014] 3. This application is based on the hand-eye calibration principle and uses multiple sampling to form a point set for registration, rather than relying on a single image to simultaneously acquire multiple feature points. This method minimizes the impact of a single or a few outlier data points on the calibration results, significantly improving the robustness and fault tolerance of the calibration process. Attached Figure Description

[0015] The preferred embodiments will now be described in a clear and easy-to-understand manner, in conjunction with the accompanying drawings, to further explain the above-mentioned characteristics, technical features, advantages, and implementation methods of this application.

[0016] Figure 1 This is a flowchart illustrating the steps of an embodiment of a navigation probe calibration method according to this application; Figure 2 This is a schematic diagram of the calibration phantom structure in an embodiment of this application; Figure 3 This is a schematic diagram of extracting feature target points from ultrasound images in an embodiment of this application; Figure 4 This is a flowchart illustrating the steps of another embodiment of the calibration method for a navigation probe according to this application. Figure 5 This is a structural block diagram of one embodiment of a navigation probe calibration system according to this application; Figure 6 This is a schematic diagram of the navigation probe in an embodiment of this application. Detailed Implementation

[0017] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application can also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0018] It should be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or sets.

[0019] To keep the drawings concise, each figure only schematically shows the parts relevant to the invention, and these do not represent the actual structure of the product. Furthermore, to facilitate understanding, in some figures, only one of components with the same structure or function is schematically depicted, or only one is labeled. In this document, "one" not only means "only one," but can also mean "more than one."

[0020] It should also be further understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0021] Furthermore, in the description of this application, the terms "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0022] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the specific implementation methods of this application will be described below with reference to the accompanying drawings. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings and other implementation methods can be obtained based on these drawings without creative effort.

[0023] In clinical surgery, multimodal image fusion navigation technology integrates preoperative static images with intraoperative dynamic images, combined with spatial positioning devices, to provide surgeons with real-time information on anatomical structures and lesion localization. However, to achieve high-precision image fusion, a precise spatial correspondence between two-dimensional ultrasound images and preoperative three-dimensional image data must be established. This process relies on the accurate calibration of the navigation probe. Relying solely on the mechanical dimensions of the probe cannot guarantee a fixed transformation relationship between the probe and the ultrasound image coordinate system. Assembly errors, human damage, or long-term use can all cause slight displacement between the internal ultrasound array and the probe housing, resulting in data acquired by the navigation probe deviating from the preset parameters, directly affecting the accuracy of fusion registration and the navigation effect.

[0024] In existing technologies, some calibration methods require rigid registration of multiple feature points in a single ultrasound image based on a pre-set phantom structure. This method is highly dependent on the processing accuracy of the phantom and the distribution of feature points. If the data acquired in a certain instance is distorted, the entire calibration result becomes unreliable. Furthermore, it is impossible to fully evaluate the calibration accuracy of the entire ultrasound image and it is difficult to perform effective calibration and traceability when the probe experiences inaccuracy or malfunction.

[0025] Therefore, this application provides a calibration method for a navigation probe, which eliminates the dependence on a preset structural model by using only two feature target points at different depths for multi-point set registration, thereby achieving full verification of the calibration accuracy of the entire ultrasound image and significantly improving the reliability of the calibration.

[0026] Reference manual attached Figure 1 As shown, one embodiment of the calibration method for a navigation probe according to this application specifically includes the following steps: S1, based on the spatial positioning device, calibrates the first transformation relationship between the imaging spatial coordinate system and the positioning spatial coordinate system, and the second transformation relationship between the positioning spatial coordinate system and the navigation probe coordinate system. The spatial positioning device is used to track the navigation probe and the sensors on the calibration phantom in real time and output corresponding spatial pose information.

[0027] Specifically, in this embodiment, the spatial positioning device is a key equipment for real-time tracking of the spatial pose of the navigation probe and the calibration phantom, including a binocular vision positioning system, a magnetic navigation positioning system, etc. Its core function is to transmit or generate positioning signals and receive signals reflected or returned by sensors on the navigation probe and the calibration phantom, and then convert these signals into accurate spatial coordinate information and send them to the processor, so that the processor can obtain the position and attitude of the navigation probe and the calibration phantom in the positioning space in real time.

[0028] In response to the spatial pose data tracked by the spatial positioning device, a first transformation relationship between the imaging spatial coordinate system and the positioning spatial coordinate system, and a second transformation relationship between the positioning spatial coordinate system and the navigation probe coordinate system are determined respectively.

[0029] The imaging space coordinate system is derived from the three-dimensional Cartesian coordinate system of the space imaging device. Its origin is located at the scanning center or detection center of the space imaging device, and it is used to describe the absolute position of the feature target points inside the calibration phantom and the registration mark points in this space.

[0030] The positioning space coordinate system is a three-dimensional Cartesian coordinate system established based on the spatial positioning device. Its origin is located at the reference center of the positioning device and is used to track the spatial pose of the navigation probe and the sensors on the phantom in real time.

[0031] The navigation probe coordinate system is a three-dimensional Cartesian coordinate system established with the navigation probe body as the reference. Its origin is usually defined at the center of the spatial positioning sensor on the probe, and it is used to describe the position and orientation of the probe itself and the ultrasonic array installed on it relative to the probe body.

[0032] S2, obtain the first spatial position coordinates of at least two feature target points in the calibration phantom under the imaging space coordinate system, and use the first transformation relationship and the second transformation relationship to transform the first spatial position coordinates to the navigation probe coordinate system to obtain a first coordinate point set, wherein at least two of the feature target points are located at different depths.

[0033] Specifically, the processor uses the image data of the calibration phantom acquired by the spatial imaging device to automatically identify or assist the operator in marking at least two feature targets and calculate their three-dimensional coordinates in the imaging space coordinate system, i.e., the first spatial position coordinates.

[0034] In some embodiments, the feature targets are spatial location markers within the phantom for calibration and verification. In other alternative embodiments, refer to the appendix to the specification. Figure 2 As shown, Figure 2 This is a schematic diagram of the calibration phantom structure in an embodiment of this application. Figure 2 As can be seen, at least four calibration lines are set within the calibration phantom. These calibration lines are arranged horizontally and vertically at different depths within the calibration phantom, forming at least two intersection points. These intersection points are the feature target points. As shown in points a, b, ... g, h in the figure, these feature points can be randomly distributed in space to cover different locations in space as completely as possible, with at least two points distributed at different depths.

[0035] The processor calls the pre-calibrated first transformation relationship to transform the coordinates from the imaging space coordinate system to the positioning space coordinate system, obtaining intermediate coordinates. Then, it calls the pre-calibrated second transformation relationship to transform the intermediate coordinates from the positioning space coordinate system to the navigation probe coordinate system, finally obtaining the first set of coordinate points used for subsequent calibration calculations. This series of coordinate transformations ensures that the spatial position information of the feature target points can be uniformly expressed in the navigation probe body coordinate system.

[0036] S3, use the navigation probe to acquire ultrasound images of at least two of the feature target points, obtain the second pixel position coordinates of the feature target points in the ultrasound image coordinate system, and transform the second pixel position coordinates to the ultrasound array coordinate system according to the physical configuration parameters of the navigation probe to obtain the second coordinate point set.

[0037] For details, please refer to the attached instruction manual. Figure 3 As shown, Figure 3 This is a schematic diagram illustrating the extraction of feature target points from an ultrasound image in an embodiment of this application. The processor controls the navigation probe to emit ultrasound waves and receive echo signals, generating a two-dimensional ultrasound image containing at least two feature target points. An image recognition algorithm is run to automatically identify or manually mark the positions of the feature target points from the ultrasound image, and their pixel coordinates in the ultrasound image coordinate system are recorded, i.e., the second pixel position coordinates.

[0038] The processor reads the physical parameters of the ultrasonic array corresponding to the navigation probe, including but not limited to the ultrasonic pixel spacing parameter. By multiplying the pixel coordinates by the pixel spacing, the second pixel position coordinates are transformed from the image coordinate system in pixels to the ultrasonic array coordinate system in actual physical size, thus obtaining the second set of coordinate points for subsequent calibration calculations.

[0039] The ultrasound image coordinate system is a two-dimensional Cartesian coordinate system used to describe the pixel positions within an ultrasound image. Its origin is usually located at the center of the image and is used to record the specific pixel positions of the feature target points in the two-dimensional ultrasound image.

[0040] The ultrasonic array coordinate system is a three-dimensional Cartesian coordinate system that describes the actual physical position of the ultrasonic array. Its origin is located at the geometric center of the ultrasonic array, and it is used to convert the pixel positions in the ultrasonic image into three-dimensional coordinates in the actual physical space of the array. Optionally, the navigation probe includes at least one ultrasonic array.

[0041] S4, repeat the acquisition steps for the first / second coordinate point set to obtain at least three distinct sets of the first / second coordinate point set. Based on the hand-eye calibration principle, use the at least three sets of the first / second coordinate point set to solve for the target transformation matrix from the ultrasound image coordinate system to the navigation probe coordinate system.

[0042] Specifically, the processor repeatedly executes the acquisition steps of the first coordinate point set and the second coordinate point set. Each time it acquires data, it changes the pose of the navigation probe or selects different feature target points, thereby obtaining at least three sets of corresponding point sets that are different from each other. Each set contains the three-dimensional coordinates of the same feature target point in the navigation probe coordinate system and the three-dimensional coordinates in the ultrasonic array coordinate system.

[0043] In practice, at least three sets of points are randomly selected for calibration. The processor uses a coordinate registration algorithm to optimize and solve the above multiple sets of equations. By minimizing the reprojection error, the optimal transformation matrix is ​​calculated, thereby obtaining the target transformation matrix from the ultrasonic image coordinate system to the navigation probe coordinate system.

[0044] Based on the above embodiments, this application discloses another embodiment of a navigation probe calibration method, and the calibration method of this application for a navigation probe is described in conjunction with specific examples: Specifically, in this embodiment, step S1 includes the following sub-steps: S11, Establish the first transformation relationship between the imaging space coordinate system and the positioning space coordinate system, Mat Camera2Img .

[0045] Specifically, the spatial positioning device serves as a data acquisition tool; optionally, it can be a binocular vision positioning system or a magnetic navigation positioning system. First, the coordinates Pt of the registration point within the imaging space are obtained using the spatial positioning device. RegInImg .

[0046] Optionally, the registration point is a small metal ball installed in the phantom. The coordinates of the registration point in the imaging space are the center coordinates of the small metal ball.

[0047] The processor obtains the coordinates Pt of the registration point in the positioning space. ResInTracke Based on equation Pt RegInImg =Mat Tracker2Img *Pt ResInTracker The transformation matrix Mat from camera to phantom is obtained. Tracker2Img .

[0048] Similarly, the coordinates of the spatial positioning sensor in the coordinate system of the spatial positioning device and the body coordinate system are obtained, Pt TrackerInCamera and Pt TrackerInSelf The transformation matrix Mat from phantom to image is calculated. Camera2Tracker .

[0049] The processor establishes the first transformation relationship between the imaging space coordinate system and the positioning space coordinate system: Mat Camera2Img =Mat Camera2Tracker *Mat Tracker2Img .

[0050] S12, Establish the second transformation relationship between the positioning space and the navigation probe coordinate system, Mat Camera2Probe .

[0051] Specifically, similarly, since the structural data of the sensors on the navigation probe is known, and their coordinates in the coordinate system of the spatial positioning device are obtained, the second transformation relationship matrix between the coordinate system of the navigation probe and the coordinate system of the spatial positioning device is obtained, Mat. Camera2Probe .

[0052] Step S2 includes: transforming the position coordinates of the feature target point from the imaging space coordinate system to the navigation probe coordinate system, Pt InProbe .

[0053] Specifically, the position coordinates of the feature target points in the calibration phantom within the imaging space are obtained and transformed into the navigation probe coordinate system: Pt InProbe =Mat Camera2Probe *Mat Camera2Tracker *Mat Tracker2Img *Pt InImg .

[0054] Step S3 includes: recording the pixel position of the feature target point in the ultrasound image and converting it into spatial coordinates Pt in the ultrasound array coordinate system. InUS .

[0055] Specifically, the pixel positions of the feature target points in the ultrasound image are recorded and converted into spatial coordinates Pt in the actual physical space coordinate system of the ultrasound array. InUS .

[0056] Step S4 includes: S41, each array is individually calibrated, and for two feature target points at different longitudinal depths, the above steps are repeated to collect at least three sets of data Pt. InUS (x i ,y i The target point can be any location in the ultrasound image, i = 1, 2, 3, ..., representing the nth feature target point used for calibration.

[0057] Specifically, taking the calibration of a certain array as an example, it is only necessary to obtain two feature target points with different longitudinal depth distributions, and repeatedly acquire at least three sets of two-dimensional ultrasound images Pt. InUS (x i ,y i ,0) and Pt InProbe (x i ,y i ,z i), i=1,2,3,……. In particular, this method does not require rigid registration based on the pre-set relationship between feature points in the phantom, and can be repeatedly acquired without being limited by the number of target points or a certain pre-set structure, so that the target points can cover the edge and other extreme positions of the ultrasound image frame, so as to fully evaluate the calibration accuracy.

[0058] S42, Given the coordinates of the feature target point in different coordinate systems, according to the hand-eye calibration principle, Pt InUS =Mat US2Probe *Pt InImg The target transformation matrix Mat is obtained. US2Probe .

[0059] Specifically, based on the hand-eye calibration principle, at least three are randomly selected for calibration, and the analytical equation Pt is obtained. InUS (x i ,y i ,0)=Mat US2Probe *Pt InProbe (x i ,y i ,z i Then, the target transformation matrix Mat can be obtained. US2Probe .

[0060] Based on the above embodiments, this application discloses another embodiment of a navigation probe calibration method, which further includes verifying the calibration results, as detailed in the appendix to the specification. Figure 4 As shown, the specific steps include: S5, randomly obtain the third pixel position coordinates of at least one of the feature target points in the two-dimensional ultrasound image coordinate system as a verification target point. Using the target transformation matrix, transform the third pixel position coordinates to the imaging space coordinate system to obtain the three-dimensional coordinates of the theoretical imaging space.

[0061] Specifically, randomly select any feature target point within the calibration phantom (similarly, this could be multiple data acquisitions of the same target point, or multiple data acquisitions of different target points), and obtain their respective coordinates Pt under ultrasound images. InUS (x jk ,y jk ,0), j=1,2, corresponding to different arrays set for the probe (if any), k=1,2,3..., indicating which feature target data is used for verification.

[0062] The verification target point used for verification and the feature target point used for calibration are acquired by the same ultrasound array, and their coordinates do not overlap in the two-dimensional ultrasound image coordinate system. In practice, the verification target point and the feature target point may be the same target point in actual physical space.

[0063] In some implementations, the coordinates of the feature target points obtained in the previous step are transformed from the ultrasound image coordinate system to the imaging space to obtain the theoretical imaging space coordinates, which are then calculated using the following formula: Pt' InImg (x jk ,y jk ,0)=Mat Camera2Img *Mat Camera2Tracker *Mat Probe2Camera *Mat US2Probe * Pt InUS (x jk ,y jk ,0).

[0064] S6. Compare the three-dimensional coordinates of the theoretical imaging space with the known coordinates of the verification target point in the imaging space coordinate system in order to calculate the spatial position error and evaluate the calibration accuracy.

[0065] Specifically, the obtained theoretical imaging space coordinates are compared with the known coordinates of the corresponding feature target point Pt' in the imaging space. InImg (x jk ,y jk ,0), calculate the spatial position error one by one to obtain the accuracy result of the calibration error.

[0066] Optionally, there are many algorithms for obtaining the transformation matrix through coordinate registration, including analytical algorithms such as the Tsai-Lenz and Park-Martin algorithms, extrinsic parameter calibration methods based on planar motion, SVD singular value decomposition algorithms, and numerical optimization methods. Preferably, this embodiment uses the SVD singular value decomposition algorithm for coordinate registration.

[0067] In other embodiments of this example, step S5, which transforms the coordinates of the third pixel position to the imaging space coordinate system to obtain the theoretical imaging space coordinates, specifically includes: The processor uses the solved target transformation matrix to transform the physical coordinates from the ultrasonic array coordinate system to the navigation probe coordinate system, obtaining the calculated coordinates in the probe coordinate system. Then, the processor calls the inverse matrix of the second transformation relation to transform the calculated coordinates from the navigation probe coordinate system to the positioning space coordinate system, obtaining the intermediate coordinates in the positioning space. Finally, the processor calls the inverse matrix of the first transformation relation to transform the intermediate coordinates from the positioning space coordinate system to the imaging space coordinate system, ultimately obtaining the theoretical imaging space coordinates.

[0068] In practice, the position coordinates of the remaining feature target points in the two-dimensional ultrasound image are obtained and transformed into the imaging space coordinate system.

[0069] The specific steps include: using the acquired ultrasound image of a specific target feature, and deriving the coordinates of the navigation probe in the coordinate system using a formula: Pt InProbe (x' jk ,y' jk ,z' jk )=(Mat US2Probe ) -1 *Pt InUS (x jk ,y jk ,0).

[0070] Or, to further extrapolate, to coordinates within the imaging space: Pt InImg (x' jk ,y' jk ,z' jk )=(Mat Tracker2Img ) -1 *(Mat Camera2Tracker ) -1 *(Mat Camera2Probe ) -1 *Pt InProbe (x' jk ,y' jk ,z' jk ).

[0071] Finally, the errors of multiple positions are verified, the minimum, maximum, average and standard deviation are calculated, and the calibration accuracy is evaluated.

[0072] Based on the above embodiments, this application provides another embodiment of a navigation probe calibration method, which further includes: arranging and combining at least three sets of first / second coordinate points to form multiple datasets, each dataset containing at least three first subsets for calibration and at least one second subset for verification. Cross-validation is performed based on the datasets to comprehensively evaluate the consistency of the calibration results.

[0073] Specifically, and further, existing data can be permuted and combined to form multiple datasets. In a given dataset, one set of data is used for calibration (≥3), and the remaining data is used for validation (≥1). The results of multiple combinations are summarized to form cross-validation, comprehensively evaluating the consistency of the calibration results.

[0074] This application provides another embodiment of a calibration method for a navigation probe. Based on any of the embodiments described above, the navigation probe includes more than one ultrasonic array. The angle between the planes where the images generated by two ultrasonic arrays are located is not less than 60°, and a 90° orthogonal angle is generally recommended.

[0075] The calibration of a probe with multiple ultrasound arrays can be performed separately on either the first or second ultrasound array to obtain the corresponding first and second target transformation matrices. The first and second target transformation matrices are used to transform the coordinate information of the feature target points in the two two-dimensional images to the imaging space coordinate system, and then compared with the initial coordinates of the feature target points in the imaging space coordinate system. This is not limited by the position of existing target points within the phantom or the installation limitations of the ultrasound arrays on the probe. The required target points can be obtained and the calibration accuracy fully verified based on the actual situation of each ultrasound array. Based on the same concept, this application also discloses a calibration system for a navigation probe. Specifically, an embodiment of the calibration system for a navigation probe of this application is described in the appendix to the specification. Figure 5 The specific details shown include: The calibration phantom 11 has at least two feature target points located at different depths inside.

[0076] The navigation probe 10 is equipped with sensors for being tracked by the spatial positioning device 40, and the probe 10 contains an ultrasonic array.

[0077] The spatial imaging device 30 is used to acquire a three-dimensional image of the calibration phantom 11 in order to determine the coordinates of the feature target points in the imaging space coordinate system.

[0078] The spatial positioning device 40 is used to track the spatial pose of the navigation probe 10 and the calibration phantom 11 in real time.

[0079] The processor 20 is electrically connected to the navigation probe 10, the spatial imaging device 30, and the spatial positioning device 40, respectively, and the processor 20 is configured to perform the steps described in any of the above method embodiments.

[0080] The navigation probe 10 has its bottom surface flush against the human body and contains an ultrasonic array. It also houses the sensors required for the spatial positioning device 40, such as reflective spheres or magnetic positioning sensors for a binocular positioning camera.

[0081] In some optional embodiments, the number of ultrasonic arrays can be expanded to two or more, as detailed in the appendix to the specification. Figure 6 , Figure 6 This is a schematic diagram of the navigation probe 10 in an embodiment of this application. Here, we take one ultrasonic linear array in the horizontal direction and one in the vertical direction as an example. The horizontal array is T1, and the vertical array is T2, both arranged in a 90° T-shape. Optionally, the distribution of the ultrasonic arrays T1 in the horizontal direction and T2 in the vertical direction can be expanded to m or n arrays as needed, where m and n ≥ 1. The ultrasonic arrays used include, but are not limited to, linear arrays, arc arrays, and umbrella arrays.

[0082] In some alternative implementations, the processor 20 is electrically connected to the navigation probe 10 and is used to control the ultrasonic array mounted on the navigation probe 10 to generate ultrasonic waves when the navigation probe 10 is in contact with the surface of human skin, and to construct a first image and a second image of the ultrasonic array T1 and T2 based on the reflected echoes.

[0083] The processor 20 is electrically connected to the spatial positioning device 40 and is used to control the spatial positioning device 40, transmit / generate positioning signals, and receive positioning information from the positioning sensors of the navigation probe 10 and the calibration phantom 11. For example, the binocular vision positioning system emits near-infrared light, which is reflected by the reflective ball on the navigation probe 10 and received by the binocular vision positioning system, converted into spatial coordinates, and finally identified and sent to the processor 20.

[0084] The processor 20 is electrically connected to the space imaging device 30 and is used to receive the coordinates of the feature target points of the calibration phantom 11 and register them with the coordinates obtained by the space positioning device 40 to form a transformation matrix between the model coordinate system of the phantom 11 and the coordinate system of the navigation probe 10.

[0085] The spatial positioning device 40 is used to track the spatial pose of the navigation probe 10 and the calibration phantom 11 in real time and send it to the processor 20.

[0086] The spatial imaging device 30 is used for spatial imaging and localization of the characteristic sites of the calibration phantom 11, including but not limited to CT, MRI, 3D ultrasound, structured light localizer, or 3D spatial localizer. Here, a 3D spatial localizer is used as an example.

[0087] Calibration phantom 11, see attached instruction manual. Figure 2 As shown, a spatial positioning sensor is installed on the top of the calibration phantom 11 or at another location. Taking a binocular vision positioning system as an example, four reflective balls are installed, with a different distribution structure than the navigation probe 10, so that they can be recognized by the binocular vision positioning system.

[0088] The calibration phantom 11 contains multiple calibration lines made of materials with high density and strong acoustic impedance differences, including but not limited to stainless steel, titanium alloy, nylon filament, tungsten filament, hydroxyapatite, or barium sulfate-polyurethane composite materials—materials that can be clearly visualized under both CT and ultrasound. These lines are distributed at different depths, interwoven horizontally and vertically, forming multiple intersection points at different depths, i.e., characteristic target points, such as points a, b, ... g, h in the figure. These characteristic points can be randomly distributed in space, aiming to completely cover different locations in space, with at least two points distributed at different depths.

[0089] Specifically, the calibration phantom 11 may include metal spheres, typically ≤2mm in diameter, used for coordinate registration of the CT images of the calibration phantom 11 with the binocular vision positioning system. There are at least three metal spheres, distributed non-linearly, and they may be located on a surface of the calibration phantom 11, installed at the center of a reflective sphere, or at any position within the calibration phantom 11 (but must be separated from the calibration line feature target points by a certain distance to avoid interfering with each other's imaging).

[0090] Based on the same technical concept, this application also discloses a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the calibration method described in any of the above embodiments.

[0091] And a computer program product, comprising a computer program that, when executed by a processor, implements the steps of the calibration method described in any of the above embodiments.

[0092] The calibration method, system, storage medium, and product of the navigation probe disclosed in this application share the same technical concept. The technical details of the embodiments of the four are applicable to each other, and will not be repeated here to reduce repetition.

[0093] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of program modules is merely an example. In practical applications, the above functions can be assigned to different program modules as needed, that is, the internal structure of the device can be divided into different program units or modules to complete all or part of the functions described above. The program modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one processing unit. The integrated unit can be implemented in hardware or as a software program unit. Furthermore, the specific names of the program modules are only for easy differentiation and are not intended to limit the scope of protection of this application.

[0094] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A calibration method for a navigation probe, characterized in that, Includes the following steps: Based on the spatial positioning device, a first transformation relationship between the imaging spatial coordinate system and the positioning spatial coordinate system is determined, as well as a second transformation relationship between the positioning spatial coordinate system and the navigation probe coordinate system; wherein, the spatial positioning device is used to track the navigation probe and the sensors on the calibration phantom in real time, and output the corresponding spatial pose information; The first spatial position coordinates of at least two feature target points in the calibration phantom are obtained in the imaging space coordinate system, and the first spatial position coordinates are transformed to the navigation probe coordinate system using the first transformation relationship and the second transformation relationship to obtain a first set of coordinate points, wherein at least two feature target points are located at different depths; The navigation probe is used to acquire ultrasound images of at least two of the feature target points, and the second pixel position coordinates of the feature target points in the ultrasound image coordinate system are obtained. According to the physical configuration parameters of the navigation probe, the second pixel position coordinates are transformed to the ultrasound array coordinate system to obtain the second coordinate point set. Repeat the acquisition steps of the first / second coordinate point set to obtain at least three different sets of the first / second coordinate point set; based on the hand-eye calibration principle, use at least three sets of the first / second coordinate point set to solve for the target transformation matrix from the ultrasound image coordinate system to the navigation probe coordinate system.

2. The calibration method for a navigation probe as described in claim 1, characterized in that, The calibration phantom has at least four calibration lines arranged horizontally and vertically at different depths within the calibration phantom, forming at least two intersection points, which are the feature target points.

3. A calibration method for a navigation probe as described in claim 1 or 2, characterized in that, This also includes verifying the calibration results: Randomly obtain the third pixel position coordinates of at least one of the feature target points in the two-dimensional ultrasound image coordinate system as a verification target point; use the target transformation matrix to transform the third pixel position coordinates to the imaging space coordinate system to obtain the three-dimensional coordinates of the theoretical imaging space; The three-dimensional coordinates of the theoretical imaging space are compared with the known coordinates of the verification target point in the imaging space coordinate system in order to calculate the spatial position error and evaluate the calibration accuracy.

4. The calibration method for a navigation probe as described in claim 3, characterized in that, The verification target point used for verification and the feature target point used for calibration are acquired by the same ultrasound array, and their coordinates do not overlap in the two-dimensional ultrasound image coordinate system.

5. The calibration method for a navigation probe as described in claim 4, characterized in that, Also includes: At least three sets of the first / second coordinate points are arranged and combined to form multiple datasets, each dataset containing at least three first subsets for calibration and at least one second subset for verification; Cross-validation was performed based on the dataset to comprehensively evaluate the consistency of the calibration results.

6. A calibration system for a navigation probe, characterized in that, include: The calibration phantom contains at least two feature target points located at different depths. A navigation probe, on which sensors are mounted for tracking by a spatial positioning device, and an ultrasonic array is installed inside the probe; A spatial imaging device is used to acquire a three-dimensional image of the calibration phantom to determine the coordinates of the feature target points in the imaging space coordinate system; The spatial positioning device is used to track the spatial pose of the navigation probe and the calibration phantom in real time; The processor is electrically connected to the navigation probe, the space imaging device, and the space positioning device, respectively, and the processor is configured to perform the steps of the calibration method according to any one of claims 1-5.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the calibration method according to any one of claims 1-5.

8. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the steps of the calibration method according to any one of claims 1-5.

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