Surgical navigation trajectory interpolation processing method, device and equipment and storage medium

Abstract

The invention relates to an interpolation processing method and device for a surgical navigation trajectory, equipment and a storage medium, and the method comprises the steps: taking an operated navigation trajectory as an input trajectory of equidistant interpolation, and determining the distance between interpolation points; starting from the starting point of the input track, taking adjacent track points as the starting point and the ending point of an interpolation section, and sequentially carrying out equidistant interpolation in the section; and storing all the interpolation points in sequence to form the interpolated navigation track point cloud. According to the invention, through equidistant interpolation of the track point clouds, uniformity and dense distribution of the track point clouds are realized, and high-quality input point clouds are provided for registration of regional point clouds and the track point clouds in a surgical operation; the adverse effect on registration caused by inaccurate calculation of a normal vector and a tangent vector due to non-uniform track point clouds in the registration process is avoided.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to an interpolation processing method, apparatus, device, and storage medium for surgical navigation trajectories. Background Technology

[0002] To achieve matching between surgical navigation equipment and the corresponding medical images of the operating area inside or outside the patient during surgery, preoperative registration is required. Registration typically uses surface point clouds of the patient's operating area and trajectory point clouds within that area obtained through the navigation equipment. However, due to practical limitations, unprocessed trajectory point clouds often cannot be directly used in the registration process.

[0003] The trajectories obtained by navigation devices within an area are typically generated by the doctor's hand-controlled drawing device moving within the operating area. Since the speed of the manually drawn device is not constant, the point spacing in the trajectory point cloud is not equal. Furthermore, due to the low data output frequency and large point spacing, further processing of the obtained trajectory point cloud is necessary to use more corresponding points for matching in the registration process to obtain more accurate registration results.

[0004] By performing equidistant interpolation on the trajectory point cloud, not only can the shortcomings caused by inconsistent manual drawing speed and low-frequency data acquisition be compensated, but also more corresponding points can be used in the registration process, thereby obtaining more accurate registration results and providing reliable navigation support for surgical procedures. Summary of the Invention

[0005] Based on the above analysis, the present invention aims to disclose an interpolation processing method, apparatus, device, and storage medium for surgical navigation trajectories; and to solve the problem that the trajectory point cloud data cannot meet the registration accuracy due to the inconsistent movement speed of manually drawn trajectories, the unequal spacing between points in the trajectory point cloud, and the excessively large spacing between trajectory points.

[0006] One aspect of the present invention discloses an interpolation processing method for surgical navigation trajectories, comprising:

[0007] Step S1: Use the navigation trajectory of the operation as the input trajectory for equidistant interpolation, and determine the interpolation point spacing;

[0008] Step S2: Starting from the starting point of the input trajectory, take the points between adjacent trajectory points as the starting and ending points of an interpolation segment, and perform equal-interval interpolation within the segment sequentially.

[0009] The first segment interpolation starting point is defined as the trajectory starting point. If the distance between the current segment interpolation starting point and the current segment ending point is less than the interpolation point spacing, no interpolation is performed on the current segment, and a point in the next segment with a distance equal to the interpolation point spacing is searched for as the next segment interpolation starting point. If the distance is not less than the interpolation point spacing, intra-segment equidistant interpolation is performed sequentially from the segment interpolation starting point until the segment interpolation ending point. If the segment interpolation ending point coincides with the segment ending point, the next segment interpolation starting point is the segment starting point. If they do not coincide, a point in the next segment with a distance equal to the interpolation point spacing is searched for as the next segment interpolation starting point.

[0010] Step S3: Sequentially store all interpolation points to form the interpolated navigation trajectory point cloud.

[0011] Another aspect of the present invention discloses an interpolation processing device employing the interpolation processing method for surgical navigation trajectories as described above, comprising a first module, a second module, and a third module;

[0012] The first module is used to take the navigation trajectory of the operation as the input trajectory for equidistant interpolation and determine the spacing between interpolation points;

[0013] The second module is used to perform equal-interval interpolation within an interpolation segment, starting from the starting point of the input trajectory and treating adjacent trajectory points as the starting and ending points of an interpolation segment.

[0014] The third module is used to sequentially store all interpolation points to form the interpolated navigation trajectory point cloud;

[0015] In the second module, the starting point of the trajectory is taken as the starting point of the first segment interpolation. If the distance between the starting point of the current segment interpolation and the ending point of the current segment is less than the interpolation point spacing, no interpolation is performed on the current segment, and a point in the next segment with a distance equal to the interpolation point spacing is searched for as the starting point of the next segment interpolation. If the distance is not less than the interpolation point spacing, equal-distance interpolation is performed successively from the starting point of the segment interpolation until the ending point of the segment interpolation. If the ending point of the segment interpolation coincides with the ending point of the segment interpolation, the starting point of the next segment interpolation is the starting point of the segment. If they do not coincide, a point in the next segment with a distance equal to the interpolation point spacing of the ending point of the current segment interpolation is searched for as the starting point of the next segment interpolation.

[0016] Another aspect of the present invention discloses an electronic device, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the interpolation processing method for surgical navigation trajectories as described above.

[0017] Another aspect of the present invention discloses a computer-readable storage medium storing a computer program that, when executed by a processor, implements the interpolation processing method for surgical navigation trajectories as described above.

[0018] The present invention can achieve the following beneficial effects:

[0019] The method proposed in this invention achieves uniform spatial distribution and enhanced density of point cloud data by performing equidistant interpolation on the trajectory point cloud. This improvement effectively solves the problem of uneven point spacing caused by inconsistent operating speeds of doctors in traditional hand-drawn trajectory point clouds, thereby improving the overall quality of the point cloud data. Uniform and dense point cloud data not only provides richer geometric information but also significantly improves the accuracy and stability of subsequent registration processes.

[0020] Specifically, the point cloud after equidistant interpolation ensures that the distance between each point and its neighbors is approximately equal, a consistency crucial for the registration algorithm. During registration, the normal and tangent vectors in the point cloud need to be calculated. If the point spacing is uneven, the estimation of these vectors will be biased, affecting the accuracy of registration. The uniform point cloud provided by this invention ensures more accurate and reliable calculation of the normal and tangent vectors, avoiding calculation errors caused by uneven point cloud distribution, thus significantly reducing the negative impact on the registration results. Attached Figure Description

[0021] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts.

[0022] Figure 1 This is a flowchart of the interpolation processing method for surgical navigation trajectory in an embodiment of the present invention;

[0023] Figure 2 This is a schematic block diagram showing the connection of the interpolation processing device for the surgical navigation trajectory in this embodiment of the invention. Detailed Implementation

[0024] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and, together with the embodiments of the present invention, serve to illustrate the principles of the present invention.

[0025] Example 1

[0026] One embodiment of the present invention discloses an interpolation processing method for surgical navigation trajectories, used in the registration of region point clouds and trajectory point clouds during surgical procedures, to process the uniformity and density of the trajectory point clouds. For example... Figure 1 As shown, the method includes:

[0027] Step S1: Use the navigation trajectory of the operation as the input trajectory for equidistant interpolation, and determine the interpolation point spacing;

[0028] Step S2: Starting from the starting point of the input trajectory, take the points between adjacent trajectory points as the starting and ending points of an interpolation segment, and perform equal-interval interpolation within the segment sequentially.

[0029] The first segment interpolation starting point is defined as the trajectory starting point. If the distance between the current segment interpolation starting point and the current segment ending point is less than the interpolation point spacing, no interpolation is performed on the current segment, and a point in the next segment with a distance equal to the interpolation point spacing is searched for as the next segment interpolation starting point. If the distance is not less than the interpolation point spacing, intra-segment equidistant interpolation is performed sequentially from the segment interpolation starting point until the segment interpolation ending point. If the segment interpolation ending point coincides with the segment ending point, the next segment interpolation starting point is the segment starting point. If they do not coincide, a point in the next segment with a distance equal to the interpolation point spacing is searched for as the next segment interpolation starting point.

[0030] Step S3: Sequentially store all interpolation points to form the interpolated navigation trajectory point cloud.

[0031] Specifically, in this embodiment, the navigation trajectory of the operation is the navigation trajectory obtained by the electromagnetic navigation registration device through electromagnetic positioning when the surgeon operates on the surgical site using surgical instruments including an electromagnetic navigation registration device.

[0032] To achieve matching between surgical navigation equipment and corresponding medical images of the patient's intraoperative / external surgical area during surgery, preoperative registration is required. Registration typically involves using surface point clouds of the patient's surgical area and trajectory point clouds obtained from the navigation equipment within that area. The surgical navigation equipment used to obtain the trajectory point clouds generally employs electromagnetic or optical systems.

[0033] Surgical electromagnetic navigation equipment comprises a magnetic field generator, surgical instruments containing magnetic sensors, a sensor acquisition unit, and a system calculation and control unit. The magnetic field generator of the navigation equipment generates an electromagnetic field of known intensity and direction covering a plotted trajectory area. Within the operating area covering the patient, the surgical instruments containing magnetic sensors slide (move) on the surface of the area, and the motion trajectory data is obtained by the sensor acquisition unit and the system calculation and control unit. The surgical instruments containing magnetic sensors sense the changes in the magnetic field generated by the magnetic field generator. Using the known characteristics of the magnetic field, the sensor acquisition unit and the system calculation and control unit calculate the changes in the six degrees of freedom of the surgical instruments (position changes along the X, Y, and Z axes, and rotation angles).

[0034] Surgical optical navigation equipment typically includes a binocular camera, surgical instruments with light sensors, and a system calculation and control unit. The binocular camera's field of view covers the patient's operating area, while the surgical instruments with light sensors slide (move) across the surface within this area. The binocular camera and system calculation and control unit acquire motion trajectory data. The surgical instruments with light sensors detect specific light sources in the external environment and the position information of marker points (usually infrared LEDs, typically optical markers integrated into a registration pen). As the surgical instruments move, their light sensors are captured by the binocular camera. The system calculation and control unit calculates the precise position and orientation of the surgical instruments in three-dimensional space based on the light source position information captured by the binocular camera. Throughout the mapping process, the movement trajectory of the surgical instruments is continuously recorded.

[0035] Compared to optical navigation devices for surgery, electromagnetic navigation devices for surgery have the advantage of not being limited by line of sight and have a wider range of applications. This invention embodiment uses an electromagnetic navigation device for surgery.

[0036] Because the trajectory within the area obtained through the surgical electromagnetic navigation device is manually drawn by the doctor, and the movement speed of the manually drawn trajectory is not constant, the spacing between points in the trajectory point cloud is not equal. Furthermore, due to the low data output frequency and the large spacing between trajectory points, further processing of the navigation trajectory is performed in this embodiment to use more corresponding points for matching and obtain more accurate registration results.

[0037] Specifically, step S1 includes:

[0038] Step S101: Input the trajectory that needs to be interpolated at equal intervals, and output the number of points N that the trajectory point cloud needs to contain after determining the equal interval interpolation.

[0039] Step S102: Calculate the Euclidean distance between each pair of adjacent points in the trajectory. Let M be the trajectory point. Accumulate the Euclidean distances between each pair of M-1 adjacent points to obtain the total distance dist of the input trajectory.

[0040] Step S103: Determine the interpolation point spacing intv = dist / (N-1);

[0041] The interpolation point spacing should not exceed 0.2 mm.

[0042] Specifically, step S2 includes:

[0043] Step S201: Perform interpolation initialization, set the trajectory between each pair of adjacent points as an interpolation segment, divide the trajectory of M points into M-1 segments, set the trajectory start point as the segment interpolation start point of the first interpolation segment, and the trajectory points adjacent to the trajectory start point as the segment end point of the first interpolation segment; initialize segment number i = 1;

[0044] Step S202: Determine whether segment number i = M is true; if yes, then the equidistant interpolation has reached the end of the trajectory and the interpolation is stopped; if no, then calculate the segment direction vector X = {X(1), X(2), X(3)} of the current interpolation segment with segment number i; calculate the Euclidean distance inter1 between the segment interpolation start point and the segment end point of the current interpolation segment.

[0045] Specifically, the segment direction vector X = nextpt – curpt; where curpt is the coordinate vector of the starting point of the current interpolation segment, and nextpt is the coordinate vector of the ending point of the current interpolation segment;

[0046] Step S203: Determine whether inter1≥intv is true. If true, proceed to step S204; otherwise, proceed to step S207.

[0047] Step S204: In the segment direction of the current interpolation segment, perform intra-segment equidistant interpolation successively from the segment interpolation start point until the segment interpolation end point;

[0048] Step S205: Determine whether the segment interpolation endpoint coincides with the segment endpoint of the current interpolation segment; if yes, determine the segment interpolation starting point of the next segment as the segment starting point; if no, search for a point in the next segment that is at a distance of intv-dist1 from the current segment endpoint as the segment interpolation starting point of the next segment; dist1 is the distance from the segment interpolation endpoint of the current segment to the current segment endpoint; the current segment endpoint is the segment starting point of the next segment.

[0049] Step S206: After determining the starting point of the next segment interpolation, set i = i + 1 and return to step S202;

[0050] Step S207: Do not interpolate the current segment; search for a point in the next segment that is at a distance of intv-dist2 from the end point of the current segment as the starting point for segment interpolation of the next segment; dist2 is the length of the current segment; the end point of the current segment is the starting point of the next segment.

[0051] Step S208: After determining the starting point of the next segment interpolation, set i = i + 1 and return to step S202.

[0052] Specifically, in step S204, the equidistant interpolation includes:

[0053] 1) Find a point on the segment direction vector X that is at a distance of the interpolation point spacing intv from the segment interpolation starting point, and use it as the second interpolation point for segment interpolation;

[0054] 2) Starting from the second interpolation point, determine whether the distance between the current interpolation point and the end point of this segment is less than or equal to the interpolation point spacing intv; if not, proceed to 3); if yes, proceed to 4).

[0055] 3) Find the interpolation point on the segment direction vector X; find the point on the segment direction vector X that is at a distance of the interpolation point spacing intv from the current interpolation point, and use it as the next interpolation point for segment interpolation; use the next interpolation point as the current interpolation point and return to step 2) to continue the distance judgment;

[0056] Find the interpolation point k on the segment direction vector X i The formula is:

[0057] k i =[intv*l+k i-1 (1),intv*m+k i-1 (2), intv*n+k i-1 (3)]

[0058] Where, l=x(1),m=x(2),n=x(3); x={x(1),x(2),x(3)} are the three direction vectors after normalizing the segment direction vector X={X(1),X(2),X(3)}; the normalization method is: x=X / norm(X); i=2,3,…,{k1(1),k1(2),k1(3)} are the coordinates of the three directions of the segment interpolation starting point.

[0059] 4) Determine whether the distance between the current interpolation point and the end point of the current segment is equal to or less than the interpolation point spacing intv; if equal, then the end point of the segment is taken as the end point of the segment interpolation; if less than, then the current interpolation point is taken as the end point of the segment interpolation.

[0060] In step S3, interpolation data is stored using an N-bit storage array. The first bit of the storage array stores the trajectory starting point, and starting from the second bit, the interpolation points generated in step S204 are stored sequentially until the storage array is full, thus forming the interpolated navigation trajectory point cloud.

[0061] The interpolated navigation trajectory point cloud obtained using this invention can be registered with the surface point cloud of the same area using the Iterative Closest Point (ICP) algorithm.

[0062] To avoid the complex operation of manually selecting points on the target point cloud during the coarse registration process of the ICP algorithm.

[0063] The following registration methods can be used, specifically including:

[0064] Step 1: Obtain the interpolated navigation trajectory point cloud and the surface point cloud of the same area;

[0065] Among them, the surface point cloud is used as the target point cloud for registration, and the interpolated navigation trajectory point cloud is used as the source point cloud for registration.

[0066] Step 2: Perform coarse registration; use Principal Component Analysis (PCA) to obtain the coordinate systems of the target point cloud and the source point cloud. Using the coordinate system of the target point cloud as the reference, adjust the pointing directions of each axis of the source point cloud coordinate system in sequence to align it with the coordinate system of the target point cloud; calculate each alignment case and output the rotation and translation homogeneous matrices of the three cases with the smallest Euclidean distance between the origins of the source and target point clouds during alignment.

[0067] Step 3: Perform fine registration; use the three homogeneous rotation and translation matrices from the coarse registration as the initial transformation matrices for the source point cloud, and perform seven registrations between the source and target point clouds, including point-to-point, point-to-plane, plane-to-plane, point-to-point followed by plane-to-plane, point-to-plane followed by plane-to-plane, plane-to-plane followed by point-to-point, and plane-to-plane followed by point-to-plane, resulting in 21 rigid body rotation matrices and Euclidean distances. Select the rigid body rotation matrix with the shortest Euclidean distance as the output of the fine registration result.

[0068] In this registration process, the navigation trajectory point cloud obtained through equidistant interpolation in this embodiment is used, achieving a uniform spatial distribution and enhanced density of the point cloud data. This improvement effectively solves the problem of uneven point spacing caused by inconsistent doctor operation speeds in traditional hand-drawn trajectory point clouds, thereby improving the overall quality of the point cloud data. Uniform and dense point cloud data not only provides richer geometric information but also significantly improves the accuracy and stability of subsequent registration processes.

[0069] Specifically, the point cloud after equidistant interpolation ensures that the distance between each point and its neighbors is approximately equal, a consistency crucial for the registration algorithm. During registration, the normal and tangent vectors in the point cloud need to be calculated. If the point spacing is uneven, the estimation of these vectors will be biased, affecting the accuracy of registration. The uniform point cloud provided by this invention ensures more accurate and reliable calculation of the normal and tangent vectors, avoiding calculation errors caused by uneven point cloud distribution, thus significantly reducing the negative impact on the registration results.

[0070] Example 2

[0071] One embodiment of the present invention discloses an interpolation processing device employing the interpolation processing method for surgical navigation trajectories as described in Embodiment 1, such as... Figure 2 As shown, it includes: a first module, a second module, and a third module;

[0072] The first module is used to take the navigation trajectory of the operation as the input trajectory for equidistant interpolation and determine the spacing between interpolation points;

[0073] The second module is used to perform equal-interval interpolation within an interpolation segment, starting from the starting point of the input trajectory and treating adjacent trajectory points as the starting and ending points of an interpolation segment.

[0074] The third module is used to sequentially store all interpolation points to form the interpolated navigation trajectory point cloud;

[0075] In the second module, the starting point of the trajectory is taken as the starting point of the first segment interpolation. If the distance between the starting point of the current segment interpolation and the ending point of the current segment is less than the interpolation point spacing, no interpolation is performed on the current segment, and a point in the next segment with a distance equal to the interpolation point spacing is searched for as the starting point of the next segment interpolation. If the distance is not less than the interpolation point spacing, equal-distance interpolation is performed successively from the starting point of the segment interpolation until the ending point of the segment interpolation. If the ending point of the segment interpolation coincides with the ending point of the segment interpolation, the starting point of the next segment interpolation is the starting point of the segment. If they do not coincide, a point in the next segment with a distance equal to the interpolation point spacing of the ending point of the current segment interpolation is searched for as the starting point of the next segment interpolation.

[0076] The technical details and beneficial effects in this embodiment are the same as in Embodiment 1. Please refer to them for details, and they will not be repeated here.

[0077] Example 3

[0078] One embodiment of the present invention discloses an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor.

[0079] In one example, the processor may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0080] The memory may include read-only memory (ROM), random access memory (RAM), disk storage media devices, optical storage media devices, flash memory devices, and electrical, optical, or other physical / tangible memory storage devices. Therefore, typically, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform an interpolation processing method referencing the surgical navigation trajectory according to Embodiment 1.

[0081] The processor runs a computer program corresponding to the executable program code by reading the executable program code stored in the memory, in order to implement the interpolation processing method for the surgical navigation trajectory in Embodiment 1.

[0082] In one example, a communication interface and a bus may also be included.

[0083] The memory, processor, and communication interface are connected via a bus and communicate with each other.

[0084] The communication interface is mainly used to enable communication between modules, devices, units, and / or equipment in the embodiments of this application. Input devices and / or output devices can also be connected through the communication interface.

[0085] A bus can be hardware, software, or both, where components of an electronic device are coupled together. For example, and not limitingly, a bus can include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a MicroChannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-E) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses, or a combination of two or more of these. Where appropriate, a bus can include one or more buses. Although specific buses are described and illustrated in the embodiments of this application, this application considers any suitable bus or interconnection.

[0086] Example 4

[0087] One embodiment of the present invention discloses a computer-readable storage medium storing computer program instructions. When executed by a processor, these computer program instructions can implement the interpolation processing method for surgical navigation trajectories described in Embodiment 1, achieving the same technical effect. To avoid repetition, further details are omitted here. The aforementioned computer-readable storage medium may include non-transitory computer-readable storage media, such as read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks, etc., and is not limited thereto.

[0088] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for interpolating surgical navigation trajectories, characterized in that, include: Step S1: Use the navigation trajectory of the operation as the input trajectory for equidistant interpolation, and determine the interpolation point spacing; Step S2: Starting from the starting point of the input trajectory, take the points between adjacent trajectory points as the starting and ending points of an interpolation segment, and perform equal-interval interpolation within the segment sequentially. The first segment interpolation starting point is defined as the trajectory starting point. If the distance between the current segment interpolation starting point and the current segment ending point is less than the interpolation point spacing, no interpolation is performed on the current segment, and a point in the next segment with a distance equal to the interpolation point spacing is searched for as the next segment interpolation starting point. If the distance is not less than the interpolation point spacing, intra-segment equidistant interpolation is performed sequentially from the segment interpolation starting point until the segment interpolation ending point. If the segment interpolation ending point coincides with the segment ending point, the next segment interpolation starting point is the segment starting point. If they do not coincide, a point in the next segment with a distance equal to the interpolation point spacing is searched for as the next segment interpolation starting point. Step S3: Sequentially store all interpolation points to form the interpolated navigation trajectory point cloud.

2. The interpolation processing method for surgical navigation trajectories according to claim 1, characterized in that, The navigation trajectory of the operation is the navigation trajectory obtained by the electromagnetic navigation registration device through electromagnetic positioning when the surgeon operates on the surgical site using surgical instruments including an electromagnetic navigation registration device.

3. The interpolation processing method for surgical navigation trajectories according to claim 2, characterized in that, Step S1 includes: Step S101: Input the trajectory that needs to be interpolated at equal intervals, and output the number of points N that the trajectory point cloud needs to contain after determining the equal interval interpolation. Step S102: Calculate the Euclidean distance between each pair of adjacent points in the trajectory. Let M be the trajectory point. Accumulate the Euclidean distances between each pair of M-1 adjacent points to obtain the total distance dist of the input trajectory. Step S103: Determine the interpolation point spacing intv = dist / (N-1) for equidistant interpolation.

4. The interpolation processing method for surgical navigation trajectories according to claim 3, characterized in that, Step S2 includes: Step S201: Perform interpolation initialization, set the trajectory between each pair of adjacent points as an interpolation segment, divide the trajectory of M points into M-1 segments, set the trajectory start point as the segment interpolation start point of the first interpolation segment, and the trajectory points adjacent to the trajectory start point as the segment end point of the first interpolation segment; initialize segment number i = 1; Step S202: Determine whether segment number i = M is true; if yes, then the equidistant interpolation has reached the end of the trajectory and the interpolation is stopped; if no, then calculate the segment direction vector X = {X(1), X(2), X(3)} of the current interpolation segment with segment number i; calculate the Euclidean distance inter1 between the segment interpolation start point and the segment end point of the current interpolation segment. Step S203: Determine whether inter1≥intv is true. If true, proceed to step S204; otherwise, proceed to step S207. Step S204: In the segment direction of the current interpolation segment, perform equidistant interpolation within the segment successively from the segment interpolation start point until the segment interpolation end point; Step S205: Determine whether the segment interpolation endpoint coincides with the segment endpoint of the current interpolation segment; if yes, determine the segment interpolation starting point of the next segment as the segment starting point; if no, search for a point in the next segment that is at a distance of intv-dist1 from the current segment endpoint as the segment interpolation starting point of the next segment; dist1 is the distance from the segment interpolation endpoint of the current segment to the current segment endpoint; the current segment endpoint is the segment starting point of the next segment. Step S206: After determining the starting point of the next segment interpolation, set i = i + 1 and return to step S202; Step S207: Do not interpolate the current segment; search for a point in the next segment that is at a distance of intv-dist2 from the end point of the current segment as the starting point for segment interpolation of the next segment; dist2 is the length of the current segment; the end point of the current segment is the starting point of the next segment. Step S208: After determining the starting point of the next segment interpolation, set i = i + 1 and return to step S202.

5. The interpolation processing method for surgical navigation trajectories according to claim 4, characterized in that, When performing equidistant interpolation in step S204, the following is included: 1) Find a point on the segment direction vector X that is at a distance of the interpolation point spacing intv from the segment interpolation starting point, and use it as the second interpolation point for segment interpolation; 2) Starting from the second interpolation point, determine whether the distance between the current interpolation point and the end point of this segment is less than or equal to the interpolation point spacing intv; if not, proceed to 3); if yes, proceed to 4). 3) Find a point on the segment direction vector X that is at a distance of the interpolation point spacing intv from the current interpolation point, and use it as the next interpolation point for segment interpolation; return to step 2) to continue the distance judgment. 4) Determine whether the distance between the current interpolation point and the end point of the current segment is equal to or less than the interpolation point spacing intv; if equal, then the end point of the segment is taken as the end point of the segment interpolation; if less than, then the current interpolation point is taken as the end point of the segment interpolation.

6. The interpolation processing method for surgical navigation trajectories according to claim 5, characterized in that, Find the interpolation point k on the segment direction vector X i The formula is: k i =[intv*l+k i-1 (1), int*m+k i-1 (2), int*n+k i-1 (3)] Where, l = x(1), m = x(2), n = x(3); x = {x(1), x(2), x(3)} are the three direction vectors after normalizing the segment direction vector X = {X(1), X(2), X(3)}; the normalization method is: x = X / norm(X); i = 2, 3, ..., {k1(1), k1(2), k1(3)} are the coordinates in the three directions of the segment interpolation starting point.

7. The interpolation processing method for surgical navigation trajectories according to claim 5, characterized in that, In step S3, interpolation data is stored using an N-bit storage array. The first bit of the storage array stores the trajectory starting point, and starting from the second bit, the interpolation points generated in step S204 are stored sequentially until the storage array is full, thus forming the interpolated navigation trajectory point cloud.

8. An interpolation processing device employing the interpolation processing method for surgical navigation trajectories as described in any one of claims 1-7, characterized in that, It includes Module 1, Module 2, and Module 3; The first module is used to take the navigation trajectory of the operation as the input trajectory for equidistant interpolation and determine the spacing between interpolation points; The second module is used to perform equal-interval interpolation within an interpolation segment, starting from the starting point of the input trajectory and treating adjacent trajectory points as the starting and ending points of an interpolation segment. The third module is used to sequentially store all interpolation points to form the interpolated navigation trajectory point cloud; In the second module, the starting point of the trajectory is taken as the starting point of the first segment interpolation. If the distance between the starting point of the current segment interpolation and the ending point of the current segment is less than the interpolation point spacing, no interpolation is performed on the current segment, and a point in the next segment with a distance equal to the interpolation point spacing is searched for as the starting point of the next segment interpolation. If the distance is not less than the interpolation point spacing, equal-distance interpolation is performed successively from the starting point of the segment interpolation until the ending point of the segment interpolation. If the ending point of the segment interpolation coincides with the ending point of the segment interpolation, the starting point of the next segment interpolation is the starting point of the segment. If they do not coincide, a point in the next segment with a distance equal to the interpolation point spacing of the ending point of the current segment interpolation is searched for as the starting point of the next segment interpolation.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the interpolation processing method for surgical navigation trajectories as described in any one of claims 1-7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the interpolation processing method for surgical navigation trajectories as described in any one of claims 1-7.

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