Coordinate system deviation correction method of surgical positioning navigation device and laser emitting assembly

Abstract

The coordinate system deviation correction method for surgical positioning and navigation devices provided by this invention solves the problem of dual rotation and translation deviations between the image pixel coordinate system and the local mechanical coordinate system of the laser positioning and driving device caused by the imaging angle of the C-arm X-ray machine, equipment installation deviation, and changes in patient position in the prior art. This is achieved through adaptive recognition based on physical markers, deterministic identity calibration, and coordinate system reconstruction driven by mechanical constraints. This method can reduce the errors generated during the use of laser positioning and navigation.

Description

Technical Field

[0001] This invention relates to the field of medical devices, and more particularly to a coordinate system deviation correction method and a laser emission component for surgical positioning and navigation devices. Background Technology

[0002] In minimally invasive surgery, laser positioning and navigation technology has become an important surgical aid for achieving precise localization of lesions on the body surface and reducing surgical trauma and intraoperative radiation exposure. Its core technology involves converting the pixel coordinates of lesions in two-dimensional fluoroscopic images captured by medical imaging equipment such as C-arm X-ray machines into the physical motion coordinates of the laser positioning and navigation device. The laser beam then precisely points to the surgical target on the patient's body surface, replacing traditional methods of manual experience-based localization and multiple fluoroscopic verifications, thus improving the efficiency and accuracy of surgical positioning.

[0003] Currently, the non-invasive real-time surgical positioning and navigation device with publication number CN103519902A sets a total of 8 stainless steel ball markers on the upper and lower plane fixing plates and bearing mounting seats of the laser positioning drive device. It uses a matrix correction plate to complete image distortion correction and extracts the scalar distance information of the ball marker pairs to complete the linear scaling conversion between pixels and actual physical size, thus realizing the automated control of laser positioning drive.

[0004] However, the aforementioned technology implicitly assumes that "the local mechanical coordinate system of the laser positioning device is completely parallel to the image pixel coordinate system of the C-arm X-ray machine" and "the laser beam and laser tube are completely coaxial." It assumes the imaging plane coincides with the laser motion plane, completely ignoring the non-parallelism that occurs between the local mechanical coordinate system of the laser positioning device and the image pixel coordinate system of the C-arm X-ray machine during actual installation at the surgical site. This deviation is not a manufacturing error but is caused by various factors such as equipment installation, C-arm rotation angle, and patient position during each surgery, making it an unavoidable systematic error. Furthermore, the laser beam and laser tube will become out of axis during movement due to changes in translation and rotation angles. Summary of the Invention

[0005] To address the aforementioned problems, the present invention provides a coordinate system deviation correction method for a surgical positioning and navigation device and a laser emitting component for a surgical laser positioning and navigation device that allows for better adjustment of coaxiality, which can reduce the errors generated during the use of laser positioning and navigation.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: The coordinate system deviation correction method for the surgical positioning and navigation device provided by the present invention includes the following steps: S1: The user operates a mobile C-arm X-ray machine for clinical surgery to ensure that the eight physical markers of the laser positioning drive device are fully visible in the image field of view. The imaging device transmits a single frame of two-dimensional X-ray image to the image processing and control unit in DICOM format. The control unit converts it into an 8-bit grayscale image to obtain an 8-bit grayscale two-dimensional X-ray image containing the patient's lesion and the projection of the eight physical markers. S2: The image processing and control unit inputs the grayscale two-dimensional X-ray image obtained in step S1 into its built-in image processing system. The system uses a circular detection algorithm, sets an initial circular detection radius starting from the image center, performs detection, and counts the number of circular contours. If the number is not 8, the detection radius is automatically increased or decreased and the detection is repeated until exactly 8 circular regions are identified. Finally, the center pixel coordinates of each circular region are extracted to obtain an unordered set of pixel coordinates of 8 marker points in the image, denoted as {P1(x1,y1), P2(x2,y2)……P8(x8,y8)}. S3: The image processing and control unit takes the set of pixel coordinates of the 8 unordered marker points obtained in step S2, and performs identity calibration and angle and distance threshold verification on the 8 unordered points in the set in sequence to obtain the pixel coordinates of the 8 marker points that have been identified. The 8 calibrated points correspond one-to-one with the 8 physical markers preset on the laser device. The physical markers are divided into H-plane markers {H1, H2, H3, Hm} and L-plane markers {L1, L2, L3, Lm}, where Hm and Lm are moving reference points M. The specific steps for the image processing system to identify 8 unordered points include: S31: Select the point with the smallest X coordinate from 8 unordered points and label it L3; select the point with the smallest Y coordinate and label it H3. S32: Select the two points with the largest X coordinates from the eight unordered points and assign them to the L plane point set; select the two points with the largest Y coordinates and assign them to the H plane point set; the remaining two are the moving reference points M. S33: Based on the already marked L3 point and two points on the L plane, calculate the angle between L3 and the line connecting these two points respectively. Mark the point whose angle with the line connecting to L3 is closest to 90° as L2, and the other as L1; and check the deviation of the calculated angle from 90°. If the deviation exceeds the preset threshold, the system records the error. S34: Based on the already calibrated point H3 and two points on the H plane, calculate the angle between H3 and the line connecting these two points respectively. Mark the point whose angle with H3 is closest to 90° as H2 and the other as H1. Verify the deviation of the calculated angle from 90°. If the deviation exceeds the preset threshold, the system records the error. S35: Calculate the coordinates of the midpoint of the line connecting the calibrated points H2 and H3, and mark the point closer to the midpoint of the two moving reference points M as Hm. At the same time, calculate the coordinates of the midpoint of the line connecting the calibrated points L2 and L3, and mark the remaining moving reference point M as Lm. The distance of this point to the midpoint of the line connecting L2 and L3 must meet the preset threshold requirement. S4: The image processing system of the image processing and control unit retrieves the pixel coordinates of the 8 marker points completed in step S3 for identity verification. Simultaneously, it calls the fixed angle α pre-stored in the system, determined by the mechanical design of the laser positioning drive device. It selects the calibrated feature point pair H1 and H3, and calculates the connection direction vector V_image in the image pixel coordinate system. It then rotates the direction vector V_image in the opposite direction by the fixed angle α to obtain the true direction vector V_xloc of the local mechanical coordinate system x_loc axis in the image pixel coordinate system. Finally, it rotates V_xloc by 90° to obtain the true direction vector V_yloc of the local mechanical coordinate system y_loc axis in the image pixel coordinate system, ensuring that the x_loc and y_loc axes are perpendicular. The final result is the true direction vectors (V_xloc, V_yloc) of the local mechanical coordinate system x_loc and y_loc axes in the image pixel coordinate system. S5: The image processing system of the image processing and control unit retrieves the local mechanical coordinate system axis direction vectors (V_xloc, V_yloc) obtained in step S4, as well as the pixel coordinates of the moving reference points Hm and Lm that were used for identity calibration in step S3. Based on the mechanical design constraint that Hm is parallel to the x_loc axis and Lm is parallel to the y_loc axis, draw an infinitely extending straight line Lx through point Hm along the V_xloc direction, and draw an infinitely extending straight line Ly through point Lm along the V_yloc direction; calculate the intersection point of the straight lines Lx and Ly, and determine the intersection point as the origin O_loc of the local mechanical coordinate system. S6: The image processing system of the image processing and control unit establishes a coordinate transformation relationship based on the local machine coordinate system axes (V_xloc, V_yloc) output in step S4 and the origin O_loc of the local machine coordinate system output in step S5. For any pixel in the image pixel coordinate system, the offset vector of the point relative to the origin O_loc is first calculated, and then the offset vector is projected onto the V_xloc and V_yloc axes respectively. The projection length is used as the coordinate value of the point in the local machine coordinate system. The projection calculation is achieved by multiplying the pixel coordinates by the inverse matrix of the rotation matrix composed of V_xloc and V_yloc. Based on the above projection calculation principle, a general coordinate transformation formula is derived and solidified, and a transformation model from the image pixel coordinate system to the local machine coordinate system that can be adapted to any pixel in the image is output, realizing the coordinate conversion between the two coordinate systems. S7: Based on the coordinate transformation model output in step S6, the doctor clicks on the surgical target location on the X-ray image in the interactive interface of the image processing and control unit; the image processing system of the image processing and control unit extracts the pixel coordinates P_target(x_p,y_p) of the target location, and uses the coordinate transformation model to convert P_target into local mechanical coordinates P_loc(x_l,y_l) that can be recognized by the laser positioning drive device; the control unit of the laser positioning drive device receives the local mechanical coordinates P_loc and converts them into motor drive commands; the two-dimensional precision motion platform of the laser positioning drive device executes the movement action according to the drive commands, driving the laser emitter to move to the physical position corresponding to the patient's body surface, and the laser emitter emits laser light and forms an indicator spot on the patient's body surface.

[0007] The laser emitting assembly provided by the present invention includes an outer sleeve and a laser module; the outer sleeve has a accommodating cavity in the vertical direction; the laser module is disposed in the accommodating cavity; the side wall of the outer sleeve has a plurality of centering holes and a plurality of coaxiality adjustment holes in the horizontal direction; a centering screw is provided in the centering hole; the end of the centering screw can be pressed against the laser module; a coaxiality adjustment screw is provided in the coaxiality adjustment hole; the end of the coaxiality adjustment screw can be pressed against the laser module.

[0008] The laser emitting component provided by the present invention preferably has three centering holes.

[0009] The laser emitting component provided by the present invention preferably has three coaxiality adjustment holes.

[0010] In the laser emitting assembly provided by the present invention, preferably, the centering hole is disposed above the coaxiality adjustment hole.

[0011] The above technical solution has the following advantages or beneficial effects: The coordinate system deviation correction method for the surgical positioning and navigation device provided by this invention solves the problem of rotational and translational deviations between the image pixel coordinate system and the local mechanical coordinate system of the laser positioning and driving device caused by the imaging angle of the C-arm X-ray machine, equipment installation deviation, and changes in patient position in the prior art. This is achieved through adaptive recognition based on physical markers in step S1, deterministic identity calibration in steps S2 to S6, and coordinate system reconstruction driven by mechanical constraints in step S7. This method can reduce the errors generated during the use of laser positioning and navigation. Attached Figure Description

[0012] The invention, its features, shape, and advantages will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings. Like reference numerals denote like parts throughout the drawings. The drawings are not intentionally drawn to scale; the focus is on illustrating the spirit of the invention.

[0013] Figure 1 This is a wireframe flowchart illustrating the coordinate system deviation correction method for the surgical positioning and navigation device provided in Embodiment 1 of the present invention.

[0014] Figure 2 This is a physical marker reference layout diagram of the laser positioning drive device for the coordinate system deviation correction method of the surgical positioning and navigation device provided in Embodiment 2 of the present invention.

[0015] Figure 3 This is a schematic diagram of the coordinate system deviation and the projection of the marker in the X-ray image of the coordinate system deviation correction method of the surgical positioning and navigation device provided in Embodiment 2 of the present invention.

[0016] Figure 4 This is a schematic diagram of the overall structure of the laser emitting assembly for the surgical laser positioning and navigation device in Embodiment 3 of the present invention, which allows for better adjustment of coaxiality. Detailed Implementation

[0017] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, but these are not intended to limit the scope of the invention.

[0018] Example 1: like Figure 1 As shown, Embodiment 1 of the present invention provides a coordinate system deviation correction method for a surgical positioning and navigation device, such as... Figures 1 to 3 The steps shown are as follows: S1: The user operates a mobile C-arm X-ray machine for clinical surgery to ensure that the eight physical markers of the laser positioning drive device are fully visible in the image field of view. The imaging device transmits a single frame of two-dimensional X-ray image to the image processing and control unit in DICOM format. The control unit converts it into an 8-bit grayscale image to obtain an 8-bit grayscale two-dimensional X-ray image containing the patient's lesion and the projection of the eight physical markers. S2: The image processing and control unit inputs the grayscale two-dimensional X-ray image obtained in step S1 into its built-in image processing system. The system uses a circular detection algorithm, sets an initial circular detection radius starting from the image center, performs detection, and counts the number of circular contours. If the number is not 8, the detection radius is automatically increased or decreased and the detection is repeated until exactly 8 circular regions are identified. Finally, the center pixel coordinates of each circular region are extracted to obtain an unordered set of pixel coordinates of 8 marker points in the image, denoted as {P1(x1,y1), P2(x2,y2)……P8(x8,y8)}. S3: The image processing and control unit takes the set of pixel coordinates of the 8 unordered marker points obtained in step S2, and performs identity calibration and angle and distance threshold verification on the 8 unordered points in the set in sequence to obtain the pixel coordinates of the 8 marker points that have been identified. The 8 calibrated points correspond one-to-one with the 8 physical markers preset on the laser device. The physical markers are divided into H-plane markers {H1, H2, H3, Hm} and L-plane markers {L1, L2, L3, Lm}, where Hm and Lm are moving reference points M. The specific steps for the image processing system to identify 8 unordered points include: S31: Select the point with the smallest X coordinate from 8 unordered points and label it L3; select the point with the smallest Y coordinate and label it H3. S32: Select the two points with the largest X coordinates from the eight unordered points and assign them to the L plane point set; select the two points with the largest Y coordinates and assign them to the H plane point set; the remaining two are the moving reference points M. S33: Based on the already marked L3 point and two points on the L plane, calculate the angle between L3 and the line connecting these two points respectively. Mark the point whose angle with the line connecting to L3 is closest to 90° as L2, and the other as L1; and check the deviation of the calculated angle from 90°. If the deviation exceeds the preset threshold, the system records the error. S34: Based on the already calibrated point H3 and two points on the H plane, calculate the angle between H3 and the line connecting these two points respectively. Mark the point whose angle with H3 is closest to 90° as H2 and the other as H1. Verify the deviation of the calculated angle from 90°. If the deviation exceeds the preset threshold, the system records the error. S35: Calculate the coordinates of the midpoint of the line connecting the calibrated points H2 and H3, and mark the point closer to the midpoint of the two moving reference points M as Hm. At the same time, calculate the coordinates of the midpoint of the line connecting the calibrated points L2 and L3, and mark the remaining moving reference point M as Lm. The distance of this point to the midpoint of the line connecting L2 and L3 must meet the preset threshold requirement. S4: The image processing system of the image processing and control unit retrieves the pixel coordinates of the 8 marker points completed in step S3 for identity verification. Simultaneously, it calls the fixed angle α pre-stored in the system, determined by the mechanical design of the laser positioning drive device. It selects the calibrated feature point pair H1 and H3, and calculates the connection direction vector V_image in the image pixel coordinate system. It then rotates the direction vector V_image in the opposite direction by the fixed angle α to obtain the true direction vector V_xloc of the local mechanical coordinate system x_loc axis in the image pixel coordinate system. Finally, it rotates V_xloc by 90° to obtain the true direction vector V_yloc of the local mechanical coordinate system y_loc axis in the image pixel coordinate system, ensuring that the x_loc and y_loc axes are perpendicular. The final result is the true direction vectors (V_xloc, V_yloc) of the local mechanical coordinate system x_loc and y_loc axes in the image pixel coordinate system. S5: The image processing system of the image processing and control unit retrieves the local mechanical coordinate system axis direction vectors (V_xloc, V_yloc) obtained in step S4, as well as the pixel coordinates of the moving reference points Hm and Lm that were used for identity calibration in step S3. Based on the mechanical design constraint that Hm is parallel to the x_loc axis and Lm is parallel to the y_loc axis, draw an infinitely extending straight line Lx through point Hm along the V_xloc direction, and draw an infinitely extending straight line Ly through point Lm along the V_yloc direction; calculate the intersection point of the straight lines Lx and Ly, and determine the intersection point as the origin O_loc of the local mechanical coordinate system. S6: The image processing system of the image processing and control unit establishes a coordinate transformation relationship based on the local machine coordinate system axes (V_xloc, V_yloc) output in step S4 and the origin O_loc of the local machine coordinate system output in step S5. For any pixel in the image pixel coordinate system, the offset vector of the point relative to the origin O_loc is first calculated, and then the offset vector is projected onto the V_xloc and V_yloc axes respectively. The projection length is used as the coordinate value of the point in the local machine coordinate system. The projection calculation is achieved by multiplying the pixel coordinates by the inverse matrix of the rotation matrix composed of V_xloc and V_yloc. Based on the above projection calculation principle, a general coordinate transformation formula is derived and solidified, and a transformation model from the image pixel coordinate system to the local machine coordinate system that can be adapted to any pixel in the image is output, realizing the coordinate conversion between the two coordinate systems. S7: Based on the coordinate transformation model output in step S6, the doctor clicks on the surgical target location on the X-ray image in the interactive interface of the image processing and control unit; the image processing system of the image processing and control unit extracts the pixel coordinates P_target(x_p,y_p) of the target location, and uses the coordinate transformation model to convert P_target into local mechanical coordinates P_loc(x_l,y_l) that can be recognized by the laser positioning drive device; the control unit of the laser positioning drive device receives the local mechanical coordinates P_loc and converts them into motor drive commands; the two-dimensional precision motion platform of the laser positioning drive device executes the movement action according to the drive commands, driving the laser emitter to move to the physical position corresponding to the patient's body surface, and the laser emitter emits laser light and forms an indicator spot on the patient's body surface.

[0019] The coordinate system deviation correction method for the surgical positioning and navigation device provided in Embodiment 1 of this invention, in step S1, involves acquiring a two-dimensional X-ray image that meets the algorithm processing requirements and contains complete and valid information. A mobile C-arm X-ray machine is used to perform fluoroscopic imaging of the surgical area, ensuring that the eight physical markers of the laser positioning drive device are completely visible within the field of view, while also including patient lesion information. This provides the image information basis for subsequent marker identification, coordinate system calculation, and surgical target localization. Missing markers will directly prevent the subsequent algorithm from executing. The imaging device transmits images in the DICOM (Digital Imaging and Communication in Medicine) standard format, which is a medical... The universal standard for imaging ensures the standardized transmission of image data between imaging devices and image processing and control units, avoiding information loss or processing failures caused by format incompatibility. The control unit converts the DICOM format X-ray image into an 8-bit grayscale image, transforming the raw medical image data into an image format that meets the requirements of the subsequent circular detection algorithm. The pixel value range of the 8-bit grayscale image is 0-255, which can reflect the brightness and contrast of the image. It is a conventional and suitable image format for circular detection and feature point extraction in computer vision. Finally, an 8-bit grayscale two-dimensional X-ray image containing the patient's lesion and the projection of 8 physical markers is obtained. The coordinate system deviation correction method for the surgical positioning and navigation device provided in Embodiment 1 of this invention, in step S2, uses an adaptive circular detection algorithm to extract the center pixel coordinates of eight physical markers from the grayscale X-ray image, providing a two-dimensional coordinate data foundation for subsequent geometric calculations and coordinate system reconstruction. Specifically, this includes inputting the standardized 8-bit grayscale image obtained in S1 into the image processing system, formally initiating feature recognition at the machine vision level, and converting the visual physical markers (the existing technology mentioned in the background, specifically the stainless steel balls in the non-invasive real-time surgical positioning and navigation device with publication number CN103519902A, which are the eight physical markers in this embodiment) into computer-calcifiable pixel coordinate data, realizing the conversion from image visual information to digital coordinate information. Then, using the image center as the starting point, the algorithm dynamically... An adaptive circular detection algorithm with dynamically adjusted detection radius, rather than fixed-parameter detection, can adapt to different C-arm imaging conditions during surgery (different imaging conditions such as image brightness, contrast, and differences in marker imaging size). This solves the problem of inconsistent marker projection contours caused by changes in the imaging environment in X-ray images, ensuring that all eight circular regions can be identified precisely regardless of imaging conditions, avoiding subsequent calculation failures caused by missed or over-detection. For the eight identified circular regions, the center pixel coordinates are extracted. The projection of a spherical marker under X-ray is circular, and the center is its unique geometric feature reference point. Extracting this coordinate can eliminate coordinate errors caused by the blurring of the marker projection contour edge. The eight center coordinates are organized into an unordered set {P1(x1,y1)……P8(x8,y8)}, completing the full digital extraction of the eight markers.

[0020] The coordinate system deviation correction method for the surgical positioning and navigation device provided in Embodiment 1 of this invention, in step S3, through steps S31-S35, calibrates the unordered coordinate set {P1~P8} obtained in S2 into {H1, H2, H3, Hm, L1, L2, L3, Lm} that correspond one-to-one with the physical structure of the laser device. This step realizes the mapping from image pixel coordinates to physical markers of the laser positioning and driving device, so that subsequent calculations are no longer simple digital geometric calculations, but physical geometric calculations based on the actual mechanical design of the device, which allows for the use of preset mechanical fixed parameters (angle α) and mechanical design constraints (H... The m-parallel x_loc axis provides the foundation; the entire calibration rule is designed based on the inherent physical geometric constraints of the marker array, rather than general pattern matching. Each calibration step has a clear geometric judgment basis, which can achieve unambiguous identification of the 8 marker points, avoid misinterpretations, and ensure that the identification results of the marker points are consistent under different imaging conditions and different installation postures, thus improving the robustness of the system; after the included angle calibration in steps S33 and S34, a 90° deviation threshold check is added, and in the moving reference point calibration in S35, a midpoint distance threshold check is added. If the deviation exceeds the preset value, the system records an error. The mechanism automatically filters out invalid calibration results caused by image noise, image blur, and partial occlusion of markers, preventing incorrect calibration coordinates from entering subsequent coordinate system calculations. During calibration, it clearly distinguishes between H-plane (upper plane), L-plane (lower plane) markers, and moving reference points (Hm, Lm), and the function of each plane marker precisely matches the subsequent calculation steps: H1 / H3 is used to calculate the x_loc axis direction of the machine coordinate system, and Hm / Lm is used to determine the origin of the machine coordinate system. This functional classification calibration allows subsequent axial and origin calculations to directly call the coordinates of the corresponding feature points, simplifying the calculation process. Simultaneously, it conforms to the actual mechanical design of the laser positioning drive device, ensuring the consistency between the calculation logic and the physical structure. After calibration, the obtained pixel coordinates are accurate with physical identity. When S4 calculates the axis of the mechanical coordinate system, it can directly call the pre-stored fixed angle α between H1-H3 and the x_loc axis, and calculate the direction vector by combining the calibration coordinates of H1 / H3. When S5 determines the origin, it can directly use the parallel mechanical constraints of Hm / Lm and x_loc / y_loc axes. The premise of these operations is that S3 has completed the accurate identity calibration of the marker point; otherwise, it is impossible to accurately call the mechanical design parameters and geometric constraints.

[0021] The coordinate system deviation correction method for the surgical positioning and navigation device provided in Embodiment 1 of this invention, step S4, is to calculate the true direction vectors of the local mechanical coordinate system x_loc and y_loc axes in the image pixel coordinate system based on the coordinates of the physically identified marker points calibrated in S3, combined with the fixed mechanical design parameters pre-stored in the laser positioning drive device. This eliminates the rotation angle deviation between the two coordinate systems caused by factors such as equipment installation and patient positioning, providing a precise axial reference for subsequently determining the coordinate system origin and establishing a complete coordinate transformation model. Specifically, this includes: retrieving the pixel coordinates of the marker points calibrated in S3, and simultaneously calling the pre-stored fixed angle α determined by the mechanical design of the laser device (this angle is an inherent constraint between the geometric relationship of the physical markers and the mechanical coordinate axes), binding the coordinate calculation at the image level with the actual mechanical structure design of the device, ensuring that the calculated coordinate system axis is completely consistent with the physical motion axis of the laser positioning drive device; selecting the calibrated feature point pairs H1 and H3, and calculating their connecting direction vector V_image in the image pixel coordinate system. The actual imaging direction of the physical marker under X-ray projection is the basic reference for the image side of the subsequent calculation of the true axis of the machine coordinate system, providing a calculable image dimension basis for eliminating rotational deviations. The connecting direction vector V_image in the image is rotated in the opposite direction by a fixed angle α to cancel the inherent angle between the geometric relationship of the physical marker and the machine coordinate axis, restoring the true direction vector V_xloc of the local machine coordinate system x_loc axis in the image pixel coordinate system. This step is to eliminate random rotational deviations between the two coordinate systems, so that the calculated x_loc axis direction is no longer affected by the equipment installation posture. Then, the calculated V_xloc is rotated by 90° to obtain the true direction vector V_yloc of the y_loc axis, and it is ensured that the x_loc and y_loc axes are perpendicular to each other, following the geometric definition of the rectangular coordinate system, ensuring the geometric rationality of subsequent coordinate projection and transformation calculations, and avoiding coordinate conversion errors caused by non-perpendicular axes. Finally, the true direction vectors (V_xloc, V_yloc) of the x_loc and y_loc axes in the image pixel coordinate system are output.

[0022] The coordinate system deviation correction method for the surgical positioning and navigation device provided in Embodiment 1 of this invention, the core function of step S5 is to rely on the real axial vector of the mechanical coordinate system calculated in S4, combined with the coordinates of the moving reference point with physical identity calibrated in S3, and using the mechanical design constraints of the laser positioning drive device, to determine the position of the origin O_loc of the local mechanical coordinate system in the image pixel coordinate system, eliminate the translation offset between the two coordinate systems, and finally completely reconstruct the local mechanical coordinate system in the image that is completely corresponding to the physical structure of the laser positioning drive device. This provides the axial and origin coordinate system reference for subsequent coordinate transformation model establishment and coordinate conversion. Specifically, it includes retrieving the axial vectors (V_xloc, V_yloc) of the mechanical coordinate system in S4 and the pixel coordinates of the moving reference point (Hm, Lm) calibrated in S3, and combining the inherent mechanical design constraints that Hm is parallel to the x_loc axis and Lm is parallel to the y_loc axis, transforming from a semi-complete coordinate system that only determines the coordinate axis direction into a complete coordinate system. A complete Cartesian coordinate system with a clearly defined origin and direction is established to reconstruct the local mechanical coordinate system within the image pixel coordinate system. A geometric solution method is employed: drawing a straight line Lx along V_xloc through Hm and a straight line Ly along V_yloc through Lm, with the intersection of these two lines as the origin O_loc. This ensures that the origin of the mechanical coordinate system is entirely determined by the physical design constraints of the device, rather than being arbitrarily set. This eliminates translational offsets between the two coordinate systems caused by factors such as equipment installation and imaging position, allowing the origin of the mechanical coordinate system in the image to map to the physical mechanical origin of the laser positioning drive device. The Hm / Lm parallel constraints and axial vectors relied upon in this origin solution method are inherent calculation benchmarks for the laser positioning drive device, ensuring the uniqueness of the geometrically solved intersection point and avoiding calculation errors caused by arbitrariness in origin setting. After steps S4 and S5, the system finally obtains a complete local mechanical coordinate system in the image pixel coordinate system, including the x_loc / y_loc axes and the origin O_loc.

[0023] The coordinate system deviation correction method for the surgical positioning and navigation device provided in Embodiment 1 of this invention, in step S6, establishes a coordinate transformation model adaptable to any pixel in the image based on the mechanical coordinate system axis calculated in S4 and the mechanical coordinate system origin determined in S5. This mathematically unifies the two coordinate systems that originally had dual deviations in rotation and translation, eliminating the deviation between the two types of coordinate systems mathematically and achieving accurate conversion from pixel coordinates to mechanical motion coordinates. Specifically, it includes: using the x_loc / y_loc axial vectors of step S4 and the origin O_loc of step S5 as the core reference, and combining the geometric principles of rigid body transformation, designing a targeted transformation logic, first calculating the offset vector of the pixel relative to the origin O_loc, and then projecting the vector onto the two axes of the mechanical coordinate system. This ensures that the transformation logic conforms to the coordinate system reconstruction result of this system, rather than using a general coordinate transformation formula to project the offset vector to... The V_xloc and V_yloc axes are projected and the projected length is used as the mechanical coordinate value. This process is achieved by multiplying by the inverse of the rotation matrix, which mathematically cancels the rotation and translation deviations between the image pixel coordinate system and the local mechanical coordinate system. This ensures that the converted mechanical coordinates are no longer affected by any installation deviations and are determined only by the image resolution and electromechanical execution accuracy. Based on the projection calculation principle, a general coordinate transformation formula is extracted and solidified into a directly callable transformation model. This model is not only suitable for a single point but can cover any pixel in the X-ray image, whether it is a marker point, a lesion target point, or other points in the image. The image pixel coordinates that doctors can intuitively operate are transformed into local mechanical coordinates that can be recognized by the two-dimensional precision motion platform of the laser positioning drive device, so that the visual position in the image is mapped to the physical movement position of the device.

[0024] The coordinate system deviation correction method for the surgical positioning and navigation device provided in Embodiment 1 of the present invention, step S7 is to rely on the high-precision coordinate transformation model established in S6 to convert the surgical target position selected by the doctor on the image into a physical motion command for the laser positioning drive device, and finally form an indicator spot on the patient's body surface that precisely corresponds to the lesion through the laser emitter. On the interactive interface of the image processing and control unit, the doctor can intuitively click on the surgical target location (such as lesion or surgical approach point) in the X-ray image. The system automatically extracts the pixel coordinates P_target(x_p,y_p) of that location. Then, using the universal coordinate transformation model fixed in S6, the extracted target pixel coordinates P_target(x_p,y_p) are automatically converted into local mechanical coordinates P_loc(x_l,y_l) that can be recognized by the laser positioning drive device. The control unit of the laser positioning drive device converts the mechanical coordinates P_loc(x_l,y_l) into motor drive commands adapted to the two-dimensional precision motion platform. These commands directly correspond to the precise X and Y movement of the platform, transforming abstract coordinate values ​​into physical motion execution parameters of the device. The two-dimensional precision motion platform drives the laser emitter according to the drive commands, moving it to the physical position on the patient's body surface that precisely corresponds to the target point in the image. The light spot emitted by the laser emitter forms a visual, precise positioning mark on the patient's body surface, providing the doctor with a clear reference for the surgical approach.

[0025] Example 2: Embodiment 2 of the present invention provides a detailed description of the steps for implementing a coordinate system deviation correction method for a surgical positioning and navigation device. Specifically, it includes the following steps: Step 1: Image Acquisition and Input After the system starts, the C-arm is operated to perform fluoroscopic imaging of the surgical area. Ensure that the marker array on the laser navigation device is completely visible within the image field of view. The imaging device transmits a single frame of two-dimensional X-ray image to the processing unit, where the image format is converted to 8-bit grayscale for processing.

[0026] Step 2: Adaptive Recognition of Marker Points The system employs a circular detection algorithm to locate all markers in the image. To adapt to different imaging conditions (such as brightness and contrast), the algorithm adopts an adaptive strategy: Starting from the center region of the image, set an initial small circular detection radius parameter.

[0027] Perform the detection and count the number of circular outlines found.

[0028] If the number of circles found is not equal to the preset 8, the detection radius parameter will be automatically adjusted (increased or decreased) and the detection will be repeated.

[0029] Repeat the above process until exactly 8 circular areas are identified.

[0030] Record the center pixel coordinates of these 8 circular regions from P1(x1, y1) to P8(x8, y8).

[0031] This adaptive process ensures that all marker points can be reliably found regardless of image quality.

[0032] Step 3: Automatic identification and sorting of marker identities After obtaining the coordinates of the eight points, it is necessary to determine which specific marker on the physical device each point corresponds to. This is accomplished through a set of deterministic rules based on coordinates and geometric relationships: Rule 1: Determine reference points L3 and H3 From the 8 points, find the point with the smallest X-coordinate value and label it as L3 (a specific point in the lower plane).

[0033] Find the point with the smallest Y-coordinate value (Note: In digital images, the Y-axis is usually positive downwards, so the point with the smallest Y-coordinate is the topmost point in the image), and label it as H3 (a specific point on the upper plane).

[0034] Rule 2: Preliminary planar classification Find the two points with the largest X-coordinate values; these two points belong to the lower plane point set (L plane).

[0035] Find the two points with the largest Y-coordinate values; these two points belong to the upper plane point set (H plane).

[0036] The remaining two points are classified as moving reference points (point M).

[0037] Rule 3: Define the points (L1, L2) in the L-plane. Given point L3 and two points in the L-plane (let's call them A and B).

[0038] Calculate the angle between vectors L3→A and L3→B respectively.

[0039] According to the physical design, the lines connecting point L3 to the right-angled point in plane L (denoted as L2) and another point (denoted as L1) should be nearly perpendicular. Therefore, the point whose angle with the line connecting to point L3 is closest to 90 degrees is L2, and the other point is L1.

[0040] Verification: The deviation of the calculated included angle from 90 degrees. If the deviation exceeds a preset threshold (e.g., 2.0 degrees), the system will record an error.

[0041] Rule 4: Define the points (H1, H2) in the H-plane. The same logic as in Rule 3 is used to process point H3 and the two H-plane points.

[0042] Mark the right-angle point H2 and another point H1.

[0043] Perform the same angle threshold check.

[0044] Rule 5: Define the moving reference point (Lm, Hm) Calculate the coordinates of the midpoint Mid_H of the line connecting the calibrated points H2 and H3.

[0045] Calculate the distances from the two moving reference points (M1, M2) to Mid_H.

[0046] The moving point that is closer to Mid_H is identified as Hm (moving point on the upper plane).

[0047] Calculate the coordinates of the midpoint Mid_L of the line connecting the calibrated points L2 and L3.

[0048] The remaining moving point should be relatively close to Mid_L, and its identity should be marked as Lm (moving point in the lower plane).

[0049] Verification: Check the distances from Hm to Mid_H and from Lm to Mid_L. If either distance exceeds a preset threshold (e.g., 2.0 pixels), the system will record an error.

[0050] At this point, the eight unordered points in the image have been uniquely assigned identities: {L1, L2, L3, Lm, H1, H2, H3, Hm}, and each corresponds to a physical marker. For example... Figure 2 As shown.

[0051] Step 4: Calculate the orientation of the local machine coordinate system (to resolve rotational deviations) Based on the correct identification of the point, the system begins to calculate the coordinate system of the laser device itself, namely the local mechanical coordinate system, whose coordinate axes are denoted as x_loc and y_loc.

[0052] Select a computational reference: Use a pre-labeled pair of points, such as H1 and H3 on the upper plane. Calculate the direction vector V_image of the line connecting these two points in the image.

[0053] Introducing known mechanical parameters: According to the mechanical design drawings of the laser navigation device, the angle between the H1-H3 sides and the x_loc axis of the device in the physical world is a fixed known value α. For example, if the ratio of the legs of the right triangle formed by the markers is 31:80, then α = arctan(31 / 80).

[0054] Solve for coordinate axis directions: The direction V_image observed in the image is rotated in the opposite direction by an angle α. The resulting direction is the true direction of the x_loc axis in the image pixel coordinate system, denoted as vector V_xloc.

[0055] The direction of the y_loc axis, V_yloc, can be obtained by rotating V_xloc by 90 degrees (ensuring that the two are perpendicular).

[0056] The V_xloc and V_yloc output in this step are the mechanical coordinate axes after eliminating rotational deviations.

[0057] Step 5: Determine the origin of the local machine coordinate system (to resolve translational deviations) In addition to direction, a coordinate system also needs to define an origin.

[0058] Mechanical constraints using moving reference points: According to the design, point Hm is located on a mechanical reference line that is strictly parallel to the x_loc axis; point Lm is located on a reference line that is strictly parallel to the y_loc axis.

[0059] Geometric solution in the image: Draw an infinitely extending straight line Lx through point Hm along the direction of V_xloc calculated in step four.

[0060] Draw an infinitely extending straight line Ly through point Lm along the direction of V_yloc calculated in step four.

[0061] Calculate the intersection point of lines Lx and Ly.

[0062] Define the origin: This intersection point is defined as the origin of the local machine coordinate system (x_loc, y_loc), denoted as O_loc.

[0063] Through steps four and five, the system completely "reconstructs" the local mechanical coordinate system in the image that perfectly corresponds to the physical device: the position of its origin O_loc and the directions of the x_loc and y_loc axes are known. For example... Figure 3 As shown.

[0064] Step Six: Coordinate Transformation and Laser Navigation Execution Once a precise coordinate mapping relationship is established, high-precision navigation can be performed.

[0065] Coordinate transformation model: For any point P_pixel(x_p, y_p) in the image pixel coordinate system, its coordinates P_loc(x_l, y_l) in the local machine coordinate system can be calculated using the following principle: First, calculate the offset vector of point P_pixel relative to the origin O_loc.

[0066] Then, this offset vector is projected onto the x_loc and y_loc axes respectively, with projection lengths being x_l and y_l. This calculation is mathematically equivalent to multiplying by the inverse of a rotation matrix consisting of V_xloc and V_yloc.

[0067] Navigation execution: The doctor clicks on the target location (such as a lesion) in the image on the navigation software interface to obtain its pixel coordinates P_target.

[0068] The system uses the above transformation model to convert P_target into mechanical coordinates P_loc.

[0069] The control unit converts the P_loc coordinates into motor drive commands, which control the two-dimensional motion platform to move the laser emitter to the corresponding physical position.

[0070] The laser emits a laser beam that projects an indicator spot onto the patient's body surface that precisely corresponds to the target image.

[0071] Example 3: The laser emitting component for a surgical laser positioning and navigation device provided in Embodiment 3 of the present invention allows for better adjustment of coaxiality, such as... Figure 4 As shown, it includes an outer sleeve 1 and a laser module 2; the outer sleeve 1 has a vertically oriented cavity 11; the laser module 2 is disposed in the cavity 11; the outer sleeve 1 has three centering holes 12 and three coaxiality adjustment holes 13 horizontally oriented on its side wall; the centering holes 12 are positioned above the coaxiality adjustment holes 13; a centering screw 3 is disposed in the centering hole 12; the end of the centering screw 3 can be pressed against the laser module 2; a coaxiality adjustment screw 4 is disposed in the coaxiality adjustment hole 13; the end of the coaxiality adjustment screw 4 can be pressed against the laser module 2.

[0072] The laser emitting assembly for surgical laser positioning and navigation device provided in Embodiment 1 of this invention, which allows for better adjustment of coaxiality, is used in practice by the operator who rotates the centering screws 3 in each centering hole 12. This causes the ends of the centering screws 3 to gradually extend radially and abut against the outer wall of the laser module 2. By simultaneously adjusting the three circumferentially distributed centering screws 3, the radial center of the laser module 2 is adjusted to the central axis of the outer sleeve 1 using the geometric principle of three points defining a circle. The three coaxiality adjustment holes 13 on the lower side wall of the outer sleeve 1 are circumferentially corresponding to the upper centering holes 12. After centering is completed, the coaxiality adjustment screws 4 in each coaxiality adjustment hole 13 are rotated to finely adjust the axial attitude of the laser module 2. By differentially adjusting the extension length of the three coaxiality adjustment screws 4, they abut against the lower outer wall of the laser module 2 to slightly adjust its spatial attitude, correcting the slight angle between the axis of the laser module 2 and the axis of the outer sleeve 1, thus achieving complete parallelism between the laser beam axis and the axis of the outer sleeve 1. The structure provided in this embodiment is designed to improve the accuracy of the coaxiality of the laser emission in the surgical laser positioning and navigation device. Compared with the existing cylindrical shaft adjustment method (such as the prior art provided in the background art which only uses a single screw 38 for adjustment), this embodiment divides the centering and coaxiality adjustment into two independent steps: the upper adjustment of the centering hole 12 and the centering set screw 3, and the lower adjustment of the coaxiality adjustment hole 13 and the coaxiality adjustment set screw 4. First, the laser beam center point is accurately aligned by the upper three-point centering, and then the laser axis is completely parallel to the axis of the outer sleeve 1 by the lower three-point fine adjustment. This eliminates the positioning deviation caused by the laser beam skew from a hardware physical perspective. There are three centering holes 12 and three coaxiality adjustment holes 13, which are evenly distributed circumferentially on the side wall of the outer sleeve 1. The corresponding centering set screw 3 and coaxiality adjustment set screw 4 form a three-point radial contact structure. The geometric characteristics of the three-point circular alignment ensure that the laser module 2 does not wobble radially during the adjustment process and can uniquely determine the center position and attitude of the laser module 2, avoiding the problems of positional deviation and unstable attitude during the adjustment process.

[0073] The preferred embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and the devices and structures not described in detail should be understood as being implemented in a manner common to the art; any possible variations and modifications made by those skilled in the art without departing from the technical solution of the present invention, or equivalent embodiments with equivalent changes, do not affect the essential content of the present invention. Therefore, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. A method for correcting coordinate system deviation in a surgical positioning and navigation device, comprising a mobile C-shaped X-ray machine; characterized in that, Including the following steps: S1: Obtain a grayscale two-dimensional X-ray image containing the patient's lesion and the projection of 8 physical markers; S2: Identify 8 physical markers from the grayscale 2D X-ray image obtained in step S1, extract their center pixel coordinates, and obtain a set of 8 unordered pixel coordinates; S3: The 8 unordered pixel coordinate sets obtained in step S2 are identified to obtain the 8 marked pixel coordinates of the identified points, and correspond one-to-one with the 8 preset physical markers on the laser device; S4: By analyzing the pixel coordinates of the 8 marker points obtained in step S3 to complete the identity verification, the coordinate system of the local mechanical coordinates of the laser device is calculated to obtain the true direction vector in the pixel coordinate system of the image captured in step S1. S5: Calculate and determine the origin of the local machine coordinate system based on the mechanical design constraints; S6: Based on the true direction vector obtained in step S4 and the origin obtained in step S5, establish the coordinate transformation relationship, derive and solidify the general transformation formula, and output the transformation model from the image pixel coordinate system to the local machine coordinate system. S7: Extract the pixel coordinates of the surgical target position on the two-dimensional X-ray image, convert them into local mechanical coordinates through the transformation model obtained in step S6, drive the laser device to move the laser emitter to the corresponding position and emit laser to form an indicator spot; Step S3 specifically includes: the image processing and control unit takes the set of pixel coordinates of the 8 unordered marker points obtained in step S2, and performs identity calibration and angle and distance threshold verification on the 8 unordered points in the set in sequence to obtain the pixel coordinates of the 8 marker points that have completed identity calibration; the 8 calibrated points correspond one-to-one with the 8 preset physical markers on the laser device; the physical markers are divided into H plane markers {H1, H2, H3, Hm} and L plane markers {L1, L2, L3, Lm}, where Hm and Lm are moving reference points M; Step S3, which involves identifying the eight unordered points using an image processing system, specifically includes the following steps: S31: Select the point with the smallest X coordinate from 8 unordered points and label it L3; select the point with the smallest Y coordinate and label it H3. S32: Select the two points with the largest X coordinates from the eight unordered points and assign them to the L plane point set; select the two points with the largest Y coordinates and assign them to the H plane point set; the remaining two are the moving reference points M. S33: Based on the already marked L3 point and two points on the L plane, calculate the angle between L3 and the line connecting these two points respectively. Mark the point whose angle with the line connecting to L3 is closest to 90° as L2, and the other as L1; and check the deviation of the calculated angle from 90°. If the deviation exceeds the preset threshold, the system records the error. S34: Based on the already calibrated point H3 and two points on the H plane, calculate the angle between H3 and the line connecting these two points respectively. Mark the point whose angle with H3 is closest to 90° as H2 and the other as H1. Verify the deviation of the calculated angle from 90°. If the deviation exceeds the preset threshold, the system records the error. S35: Calculate the coordinates of the midpoint of the line connecting the calibrated points H2 and H3, and mark the point closer to the midpoint of the two moving reference points M as Hm. At the same time, calculate the coordinates of the midpoint of the line connecting the calibrated points L2 and L3, and mark the remaining moving reference point M as Lm. The distance of this point to the midpoint of the line connecting L2 and L3 must meet the preset threshold requirement. Step S4 specifically includes: the image processing system of the image processing and control unit retrieves the pixel coordinates of the 8 marker points for identity verification completed in step S3, and simultaneously calls the fixed angle α pre-stored in the system and determined by the mechanical design of the laser positioning drive device; selects the calibrated feature point pair H1 and H3, and calculates the connection direction vector V_image of the point pair in the image pixel coordinate system; rotates the direction vector V_image in the opposite direction by the fixed angle α to obtain the true direction vector V_xloc of the local mechanical coordinate system x_loc axis in the image pixel coordinate system; rotates V_xloc by 90° to obtain the true direction vector V_yloc of the local mechanical coordinate system y_loc axis in the image pixel coordinate system, ensuring that the x_loc axis and y_loc axis are perpendicular to each other; finally, the true direction vectors V_xloc and V_yloc of the local mechanical coordinate system x_loc and y_loc axes in the image pixel coordinate system are obtained. The specific steps of step S5 include: the image processing system of the image processing and control unit retrieves the local mechanical coordinate system axis direction vectors V_xloc and V_yloc obtained in step S4, as well as the pixel coordinates of the moving reference points Hm and Lm that were used for identity calibration in step S3; Based on the mechanical design constraint that Hm is parallel to the x_loc axis and Lm is parallel to the y_loc axis, draw an infinitely extending straight line Lx through point Hm along the V_xloc direction, and draw an infinitely extending straight line Ly through point Lm along the V_yloc direction; calculate the intersection point of the straight lines Lx and Ly, and determine the intersection point as the origin O_loc of the local mechanical coordinate system. Step S6 specifically includes: the image processing system of the image processing and control unit establishes a coordinate transformation relationship based on the local machine coordinate system axes V_xloc and V_yloc output in step S4 and the origin O_loc of the local machine coordinate system output in step S5; for any pixel in the image pixel coordinate system, the offset vector of the point relative to the origin O_loc is first calculated, and then the offset vector is projected onto the V_xloc and V_yloc axes respectively, and the projection length is used as the coordinate value of the point in the local machine coordinate system. The projection calculation is achieved by multiplying the pixel coordinates by the inverse matrix of the rotation matrix composed of V_xloc and V_yloc; based on the above projection calculation principle, a general coordinate transformation formula is derived and solidified, and a transformation model from the image pixel coordinate system to the local machine coordinate system that can be adapted to any pixel in the image is output, realizing the coordinate conversion between the two coordinate systems.

2. The coordinate system deviation correction method for the surgical positioning and navigation device as described in claim 1, characterized in that, The specific steps of step S1 include: the user operates the mobile C-arm X-ray machine for clinical surgery to ensure that the eight physical markers of the laser positioning drive device are fully visible in the image field of view; the imaging device transmits a single frame of two-dimensional X-ray image to the image processing and control unit in DICOM format; the control unit converts it into an 8-bit grayscale image to obtain an 8-bit grayscale two-dimensional X-ray image containing the patient's lesion and the projection of the eight physical markers.

3. The coordinate system deviation correction method for the surgical positioning and navigation device as described in claim 1, characterized in that, Step S2 specifically includes: the image processing and control unit inputs the grayscale two-dimensional X-ray image obtained in step S1 into its built-in image processing system. The system adopts a circular detection algorithm, sets an initial circular detection radius with the image center as the starting point, performs detection and counts the number of circular contours; if the number is not 8, the detection radius is automatically increased or decreased and the detection is repeated until exactly 8 circular regions are identified; finally, the center pixel coordinates of each circular region are extracted to obtain an unordered set of pixel coordinates of 8 marker points in the image, denoted as {P1(x1,y1), P2(x2,y2)……P8(x8,y8)}.

4. The coordinate system deviation correction method for the surgical positioning and navigation device as described in claim 1, characterized in that, Step S7 specifically includes: based on the coordinate transformation model output in step S6, the doctor clicks on the surgical target location on the X-ray image in the interactive interface of the image processing and control unit; the image processing system of the image processing and control unit extracts the pixel coordinates P_target(x_p,y_p) of the target location, and uses the coordinate transformation model to convert P_target into local mechanical coordinates P_loc(x_l,y_l) that can be recognized by the laser positioning drive device; the control unit of the laser positioning drive device receives the local mechanical coordinates P_loc and converts them into motor drive commands; the two-dimensional precision motion platform of the laser positioning drive device executes the movement action according to the drive command, driving the laser emitter to move to the physical position corresponding to the patient's body surface, and the laser emitter emits laser light and forms an indicator spot on the patient's body surface.

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