A position adjustment method, device, and equipment of an imaging device and a storage medium

Abstract

The application belongs to the field of vascular intervention surgery, and relates to a position adjustment method and device of an imaging equipment, an equipment and a storage medium. The method comprises the following steps: constructing a three-dimensional image of a blood vessel; acquiring a lesion parameter, a lesion tangent angle, a lesion blood vessel angle and a current position of the imaging equipment according to the three-dimensional image; generating a target position of the imaging equipment according to the lesion parameter, the lesion tangent angle and the lesion blood vessel angle; and adjusting the imaging equipment according to the current position of the imaging equipment and the target position of the imaging equipment, so that the imaging equipment reaches the target position of the imaging equipment. The application can improve positioning accuracy, reduce surgery time and reduce radiation exposure of a patient.

Description

Technical Field

[0001] This application relates to the field of vascular interventional surgery technology, and in particular to a method, apparatus, computer device, and storage medium for adjusting the position of an imaging device. Background Technology

[0002] Currently, vascular interventional procedures are used to treat lesions, such as aneurysm embolization and dense mesh stenting. The procedure involves using a catheter to release consumables such as coils or stents into the lesion or to cover the aneurysm neck. When performing aneurysm embolization, it is necessary to know the angular relationship between the aneurysm neck and the artery. Specifically, when locating the lesion, it is necessary to find the lesion under multiple angiography. Then, through multiple rotations and table movements using DSA (Digital Subtraction Angiography), the surgical angle is found, and the aneurysm coil embolization or dense mesh stenting is performed from that angle.

[0003] In current technologies, CTA (Computed Tomography Angiography) is typically performed on patients before surgery. Using 2D images of the patient's blood vessels, doctors can determine and remember the approximate location of lesions. However, 2D images can only roughly determine the presence of lesions; they cannot determine the nature of the lesions or the angular relationship between the lesions and the blood vessels, thus failing to provide accurate information for surgical planning. This leads to the need for multiple adjustments to the machine positioning during DSA (Digital Subtraction Angiography) to locate and determine the nature of lesions, resulting in prolonged surgery time, high radiation doses to the patient, and low instrument positioning accuracy. Summary of the Invention

[0004] The purpose of this application is to propose a method, device, computer equipment and storage medium for adjusting the position of an imaging device, so as to solve the problems of long operation time, high radiation dose to patients and low instrument positioning accuracy in the interventional surgery process of the prior art.

[0005] To address the aforementioned technical problems, this application provides a method for adjusting the position of an imaging device, employing the following technical solution:

[0006] A method for adjusting the position of an imaging device includes:

[0007] Constructing three-dimensional images of blood vessels;

[0008] Based on the three-dimensional image, obtain the lesion parameters, lesion tangent angle, lesion blood vessel angle, and the current position of the imaging device.

[0009] The target position of the imaging device is generated based on the lesion parameters, the lesion tangent angle, and the lesion blood vessel angle.

[0010] The imaging device is adjusted according to its current position and its target position so that it reaches the target position.

[0011] Furthermore, the step of obtaining lesion parameters based on the three-dimensional image includes:

[0012] The lesion was identified based on the three-dimensional image;

[0013] Select the rectangle with the largest area on the cross-section of the three-dimensional image region of the lesion, and take its long side as the major axis of the lesion and its short side as the minor axis of the lesion.

[0014] The volume of a single voxel is obtained, and the volume of the voxel is predetermined during the construction of the three-dimensional image. The total number of voxels in the three-dimensional image region of the lesion is counted to obtain the number of voxels in the lesion. Based on the number of voxels in the lesion and the volume of a single voxel, the volume of the lesion is calculated.

[0015] Further, the step of identifying the lesion based on the three-dimensional image includes:

[0016] The vascular structure image data in the three-dimensional image is acquired and analyzed to identify the lesion in the vascular structure image data and determine the location information of the lesion in the three-dimensional image.

[0017] Furthermore, the step of obtaining the lesion tangent angle based on the three-dimensional image includes:

[0018] Identify the diseased blood vessel where the lesion is located based on the three-dimensional image;

[0019] Obtain the neck section of the lesion and determine the center point of the neck section, wherein the neck section is the surface where the junction of the lesion and the diseased blood vessel is located;

[0020] Two-dimensional images of multiple tangential positions of the lesion are obtained with the center line of the diseased blood vessel as the axis, and the tangential position of the neck section in the two-dimensional image that is straight or tends to be straight is selected as the target tangential position.

[0021] Obtain the outline of the lesion in the two-dimensional image of the target tangent position, and take the point on the outline that is farthest from the center point as the distal endpoint;

[0022] Determine the straight line connecting the center point and the distal point, and take the angle between the straight line and the center line as the tangent angle of the lesion.

[0023] Furthermore, the step of obtaining the angle of the lesion blood vessels based on the three-dimensional image includes:

[0024] Identify the diseased blood vessel where the lesion is located based on the three-dimensional image;

[0025] Establish the spatial coordinate system of the diseased blood vessel in the three-dimensional image;

[0026] Obtain the reference coordinate system of the three-dimensional human body model in a lying position, register the spatial coordinate system of the diseased blood vessel with the reference coordinate system, and determine the transformation matrix between the two coordinate systems.

[0027] Based on the transformation matrix, calculate the spatial coordinates of the diseased blood vessel in the reference coordinate system;

[0028] The angle between the diseased blood vessel and the human body is calculated based on the spatial coordinates to obtain the angle of the lesion blood vessel.

[0029] Furthermore, the step of identifying the lesion's blood vessel based on the three-dimensional image includes:

[0030] Determine the location information of the lesion in the three-dimensional image;

[0031] Based on the location information, the blood vessels around the lesion are tracked to obtain the blood vessel segment connected to the lesion, and the blood vessel segment is identified as the diseased blood vessel where the lesion is located.

[0032] Furthermore, the imaging device includes a bed and an operating arm, and the target position of the imaging device includes a target position on the bed and a target position on the operating arm;

[0033] The step of generating the target position of the imaging device based on the lesion parameters, the lesion tangent angle, and the lesion blood vessel angle includes:

[0034] The geometric center point of the lesion is determined based on the lesion parameters, and the coordinates of the geometric center point in the reference coordinate system are calculated using the transformation matrix.

[0035] Obtain the coordinates of the interventional puncture point in the reference coordinate system, and calculate the operation path from the puncture point to the geometric center point by combining the coordinates of the geometric center point, the tangent angle of the lesion, and the angle of the lesion vessel.

[0036] The target position of the bed is determined according to the operation path;

[0037] Based on the target position of the bed, the target implementation angle of the operating arm relative to the human body is obtained, and the target implementation angle is used as the target position of the operating arm.

[0038] To address the aforementioned technical problems, this application also provides a position adjustment device for an imaging apparatus, comprising:

[0039] A position adjustment device for an imaging apparatus, comprising:

[0040] A building block for creating 3D images of blood vessels;

[0041] The parameter acquisition module is used to acquire lesion parameters, lesion tangent angle, lesion blood vessel angle and current position of imaging device based on the three-dimensional image;

[0042] A location generation module is used to generate a target location for the imaging device based on the lesion parameters, the lesion tangent angle, and the lesion blood vessel angle.

[0043] The control module is used to adjust the imaging device according to the current position and the target position of the imaging device to achieve the target position of the imaging device.

[0044] To address the aforementioned technical problems, this application also provides a computer device that employs the following technical solution:

[0045] A computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the position adjustment method of the imaging device described above.

[0046] To address the aforementioned technical problems, this application also provides a computer-readable storage medium, employing the technical solution described below:

[0047] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the position adjustment method for the imaging device described above.

[0048] Compared with the prior art, the embodiments of this application have the following main advantages:

[0049] This application automatically determines the lesion parameters, lesion tangent angle, and lesion vessel angle by reconstructing the three-dimensional image data of blood vessels. It then generates the target position of the imaging device based on this and adjusts the imaging device according to its current position to achieve the target position. This not only reduces the complexity of adjustment and improves the positioning accuracy and safety of the surgery, but also reduces the operation time, significantly improves the success rate and efficiency of interventional surgery, and reduces the radiation exposure of patients and doctors. Attached Figure Description

[0050] To more clearly illustrate the solutions in this application, the accompanying drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0051] Figure 1 A flowchart of an embodiment of the imaging device position adjustment method according to this application;

[0052] Figure 2 This is a flowchart illustrating the process of obtaining the lesion tangent angle in an embodiment of this application;

[0053] Figure 3 This is a schematic diagram of the neck section according to this application;

[0054] Figure 4 This is a schematic diagram of the neck section of the linear shape according to this application;

[0055] Figure 5 This is a flowchart illustrating the determination of the lesion vessel angle in an embodiment of this application;

[0056] Figure 6 yes Figure 1 A flowchart of a specific implementation of step S13;

[0057] Figure 7 This is a schematic diagram of the structure of the position adjustment device of the imaging device according to an embodiment of this application;

[0058] Figure 8 This is a schematic diagram of the structure of one embodiment of the computer device according to this application. Detailed Implementation

[0059] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein in the specification of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "comprising" and "having," and any variations thereof, in the specification, claims, and foregoing drawings of this application, are intended to cover non-exclusive inclusion. The terms "first," "second," etc., in the specification, claims, or foregoing drawings of this application are used to distinguish different objects, not to describe a particular order.

[0060] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0061] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0062] refer to Figure 1 The diagram illustrates a flowchart of an embodiment of the imaging device position adjustment method according to this application. The imaging device position adjustment method includes the following steps S11 to S14:

[0063] Step S11: Construct a three-dimensional image of the blood vessels;

[0064] Step S12: Obtain the lesion parameters, lesion tangent angle, lesion blood vessel angle, and current position of the imaging device based on the three-dimensional image;

[0065] Step S13: Generate the target position of the imaging device based on the lesion parameters, the lesion tangent angle, and the lesion blood vessel angle;

[0066] Step S14: Adjust the imaging device according to the current position and the target position of the imaging device so that the imaging device reaches the target position.

[0067] In step S11, initial angiographic data of the blood vessels in the diseased vascular region is acquired, and a three-dimensional image of the blood vessels in the diseased vascular region is constructed based on the initial angiographic data. The initial angiographic data is a two-dimensional angiographic image. In this embodiment, a preset algorithm is used to construct a three-dimensional image of the diseased vascular region based on the two-dimensional angiographic image. In this embodiment, the diseased vascular region mainly refers to the area where the lesion is located. In a specific embodiment, the lesion can be an aneurysm, and the corresponding diseased blood vessel is the aneurysm-bearing artery.

[0068] In one embodiment, the step of constructing a three-dimensional image of a blood vessel specifically includes: acquiring multiple two-dimensional tomographic images obtained by scanning the blood vessel; forming a two-dimensional contour of the blood vessel based on the multiple two-dimensional tomographic images; generating a three-dimensional surface model of the blood vessel based on the two-dimensional contour of the blood vessel, and constructing a three-dimensional image of the blood vessel. This embodiment, by performing three-dimensional reconstruction of the complete intraluminal contour of the blood vessel, can construct a refined three-dimensional image of the diseased blood vessel region, providing support for subsequent positioning adjustments of the imaging equipment.

[0069] In this embodiment, multiple two-dimensional tomographic images are obtained by scanning the diseased blood vessel region with CT or MRI. When scanning the diseased blood vessel region with CT or MRI, in order to obtain more accurate three-dimensional images, as many two-dimensional tomographic images as possible can be obtained. For example, the scanning parameters are set to a slice thickness of 1 mm and an interslice spacing of 5 mm to obtain a series of two-dimensional tomographic images. Then, a three-dimensional reconstruction algorithm, such as the Marching Cubes algorithm, is used to reconstruct the blood vessels in the diseased blood vessel region based on the two-dimensional tomographic images. For example, the voxel size is set to 5 mm × 5 mm × 5 mm to generate a triangular mesh model of the blood vessel, that is, the three-dimensional surface model, and smoothing is performed to obtain a three-dimensional image of the real and smooth inner contour of the blood vessel lumen, which intuitively displays the three-dimensional morphological features of the diseased blood vessel region.

[0070] In some embodiments, the step of forming a two-dimensional vascular contour based on multiple two-dimensional tomographic images includes: aligning the multiple two-dimensional tomographic images to eliminate positional deviations between them, obtaining a registered two-dimensional tomographic image; and performing image segmentation on the registered two-dimensional tomographic image to extract vascular regions from each segmented image, obtaining a segmented vascular two-dimensional contour. This embodiment can obtain a clear vascular two-dimensional contour, facilitating subsequent three-dimensional image construction. The two-dimensional tomographic images can be aligned using an image registration algorithm, such as a mutual information-based image registration algorithm. By maximizing the mutual information between adjacent layers, the registration transformation parameters are optimized to register the two-dimensional tomographic images, eliminating inter-layer positional deviations caused by patient breathing movements, etc. Similarly, vascular regions can be extracted using a threshold segmentation algorithm to obtain a segmented vascular two-dimensional contour. For example, a region growing method can be used to segment the vascular region, setting the CT value threshold of the seed point to 150 HU, and the growth criterion being that the difference in CT values ​​between adjacent pixels is less than 50 HU, thus extracting the vascular two-dimensional contour.

[0071] Furthermore, after constructing the three-dimensional image, techniques such as lighting rendering and texture mapping can be used to improve the realism and three-dimensionality of the three-dimensional image, making it closer to the real morphology of blood vessels. For example, Phong lighting model and Gouraud shading technology can be used to visualize the refined three-dimensional image and generate a realistic three-dimensional blood vessel model.

[0072] For step S12, the lesion parameters are calculated based on the three-dimensional image constructed in step S11. The lesion parameters generally include parameters related to the size of the lesion, specifically the long and short diameters and volume of the lesion. Taking an aneurysm as an example, the lesion parameters include at least the long and short diameters and the volume of the aneurysm.

[0073] In one embodiment, the step of obtaining lesion parameters based on the three-dimensional image includes: identifying the lesion based on the three-dimensional image; selecting the rectangle with the largest area on the cross-section of the three-dimensional image region of the lesion, using its long side as the major axis and its short side as the minor axis of the lesion; obtaining the volume of a single voxel, the volume of which is predetermined when the three-dimensional image is constructed; counting the total number of voxels in the three-dimensional image region of the lesion to obtain the number of voxels of the lesion; and calculating the volume of the lesion based on the number of voxels and the volume of a single voxel.

[0074] In this embodiment, when identifying lesions based on the three-dimensional image, the method includes: acquiring and analyzing vascular structure image data in the three-dimensional image, identifying lesions in the vascular structure image data, and determining the location information of the lesions in the three-dimensional image.

[0075] When identifying lesions, it is necessary to perform image analysis on the three-dimensional images. Specifically, the constructed three-dimensional images need to be preprocessed, and noise and artifacts in the three-dimensional images need to be removed by image filtering algorithms. For example, anisotropic diffusion filtering algorithm can be used to smooth the image and remove noise and artifacts. Then, the Otsu threshold segmentation algorithm is used to binarize the image and extract high-density vascular structure image data.

[0076] After preprocessing, this embodiment can identify lesions by analyzing the vascular structure image data in the three-dimensional image. Specifically, taking an aneurysm as an example, morphological analysis methods are used to analyze the vascular structure image data to identify spherical or cystic structures in the vascular structure image data; spherical or cystic structures that meet preset conditions are determined as aneurysms, and the location information of the aneurysm in the three-dimensional image is determined; for example, in the process of identifying spherical or cystic structures based on vascular structure image data, morphological opening operations are first performed on the vascular structure, such as setting the structural element to a sphere with a radius of 2 pixels to remove small protrusions and spurs on the vessel wall, and then morphological closing operations are performed, setting the structural element to a sphere with a radius of 5 pixels to fill small cavities and breaks in the vessel lumen, thus improving the recognition accuracy of spherical or cystic structures. Based on the vascular structure obtained after the aforementioned binarization process, a three-dimensional connected component labeling algorithm is used to mark different regions in the vascular structure. The volume and surface area of ​​each connected region are calculated, and whether it is an aneurysm is determined according to preset conditions, such as preset thresholds. For example, regions with a volume greater than 500 cubic millimeters and a surface area to volume ratio less than 2 are considered aneurysms.

[0077] In this embodiment, the minimum bounding rectangle of the identified lesion region is calculated using a rotating caliper algorithm. Specifically, the rotation angle step size and maximum number of iterations can be set. By rotating the convex hull of the lesion region, the bounding box with the smallest area is found, which is the minimum bounding rectangle. The long and short sides of the minimum bounding rectangle are obtained, and the long side is taken as the major diameter of the lesion, and the short side as the minor diameter. This embodiment, through minimum bounding rectangle measurement and voxel counting, can quantitatively analyze the size of the lesion, providing reliable imaging indicators for lesion grading diagnosis and assessment of surgical resection difficulty.

[0078] In some embodiments, after identifying the lesion, the method further includes: performing a first annotation process on the area where the lesion is located in the three-dimensional image. For example, using red to annotate the lesion area in the three-dimensional image can clearly and intuitively display the location of the lesion in the three-dimensional image.

[0079] Furthermore, for the identified lesions, a fast matching algorithm can be used to perform region registration and localization in the original 3D image to determine the location information of the lesions.

[0080] In one embodiment, such as Figure 2 As shown, in step S12, the step of obtaining the lesion tangent angle based on the three-dimensional image includes:

[0081] S21, Identify the diseased blood vessel where the lesion is located based on the three-dimensional image;

[0082] S22, Obtain the neck section of the lesion and determine the center point of the neck section, wherein the neck section is the surface where the junction of the lesion and the diseased blood vessel is located;

[0083] S23, acquire two-dimensional images of multiple tangential positions of the lesion with the center line of the diseased blood vessel as the axis, and select the tangential position of the neck section in the two-dimensional image that is straight or tends to be straight as the target tangential position.

[0084] S24, Obtain the outline of the lesion in the two-dimensional image of the target tangent position, and take the point on the outline that is farthest from the center point as the distal endpoint;

[0085] S25, determine the straight line connecting the center point and the distal end point, and take the angle between the straight line and the center line as the tangent angle of the lesion.

[0086] In this embodiment, step S21, the step of identifying the lesion vessel where the lesion is located based on the three-dimensional image, includes: determining the location information of the lesion in the three-dimensional image; tracking the blood vessels around the lesion based on the location information to obtain the blood vessel segment connected to the lesion, and determining the blood vessel segment as the lesion vessel where the lesion is located.

[0087] Specifically, based on the identified lesions, a fast matching algorithm can be used to perform region registration and localization in the original 3D image to determine the location information of the lesions. Then, starting from the location of the lesion, a depth-first search strategy is used to track the surrounding connected blood vessel segments to obtain the diseased blood vessels connected to the lesion.

[0088] In one embodiment, after identifying the diseased blood vessel, the method further includes: performing a second annotation process on the area where the diseased blood vessel is located in the three-dimensional image; wherein the second annotation process uses a different annotation method than the first annotation process to distinguish the lesion from the diseased blood vessel. Unlike the first annotation process on the lesion area, which uses red for example, the second annotation process on the diseased blood vessel in the three-dimensional image uses yellow for example, which can clearly and intuitively display the position of the diseased blood vessel in the three-dimensional image and intuitively display the spatial relationship between the lesion and the diseased blood vessel.

[0089] In this embodiment, for step S22, the Canny edge detection algorithm is used to perform edge detection on the regions where the segmented lesions and diseased blood vessels are located. By setting high and low thresholds, the interface between the lesion and the diseased blood vessel is extracted, that is, the surface where the intersection line of the lesion and the diseased blood vessel is located. The interface is determined as the neck section, and the obtained neck section can be as follows: Figure 3 As shown. In a specific embodiment, when the lesion is an aneurysm, the neck section is the aneurysm neck section.

[0090] In this embodiment, a skeleton extraction algorithm is used. The neck section is continuously eroded until its skeleton is reached. Then, for each pixel on the skeleton, the Euclidean distance from the edge of the neck section is calculated. The pixel with the largest distance is found and determined as the center point of the neck section.

[0091] In this embodiment, for steps S23 to S25, the centerline of the lesion vessel can be segmented using a three-dimensional region growing method, and then the centerline of the lesion vessel can be extracted using a 3D thinning algorithm. Using the extracted centerline as the rotation axis, the vessel is rotated within a preset angle range (e.g., ±30°) at preset angle intervals (e.g., 1°) to obtain multiple tangent positions. For each tangent position, the three-dimensional model is projected onto a two-dimensional plane along a set direction to obtain a two-dimensional image of the lesion at each tangent position. Then, Canny edge detection is performed on the two-dimensional image to extract the neck section contour. By fitting the contour point set, it is determined whether the neck section is a straight line or tends to be a straight line. For example, the least squares method is used to fit the contour points as a straight line, and the average distance between the fitted straight line and the contour points is calculated. If the average distance is less than 5mm, the neck section is considered to be a straight line. A straight neck section is as follows: Figure 4 The colored lines shown indicate that the lesion is in the optimal imaging position. For example, the slope of the fitted straight line is calculated. If the absolute value of the slope is less than 2, the neck section is considered to be close to a straight line. Finally, the tangent position that satisfies the condition of being a straight line or close to a straight line is taken as the target tangent position. Finally, the lesion tangent angle is obtained by calculating the angle between the straight line connecting the center point and the distal point in three-dimensional space and the center line of the neck section. This embodiment can automatically and quickly determine the lesion tangent angle.

[0092] In one embodiment, such as Figure 5 As shown, in step S12, the step of obtaining the angle of the lesion blood vessel based on the three-dimensional image includes: registering the three-dimensional image with the human body coordinate system, and calculating the angle between the lesion blood vessel and the human body in the corresponding reference coordinate system to obtain the angle of the lesion blood vessel; specifically, the method includes:

[0093] S51, Identify the diseased blood vessel where the lesion is located based on the three-dimensional image;

[0094] S52, Establish the spatial coordinate system of the diseased blood vessel in the three-dimensional image;

[0095] S53, obtain the reference coordinate system of the three-dimensional human body model in a lying position, register the spatial coordinate system of the diseased blood vessel with the reference coordinate system, and determine the transformation matrix between the two coordinate systems;

[0096] S54, Calculate the spatial position coordinates of the diseased blood vessel in the reference coordinate system according to the transformation matrix;

[0097] S55, calculate the angle between the diseased blood vessel and the human body based on the spatial location coordinates to obtain the angle of the lesion blood vessel.

[0098] In this embodiment, step S51 can refer to step S21 of the above embodiment.

[0099] For steps S52 to S54, after acquiring the three-dimensional image model of the lesion and the diseased blood vessel, the system automatically establishes a three-dimensional spatial coordinate system with the origin located at the center of the lesion. The X-axis, Y-axis, and Z-axis are parallel to the left-right, front-back, and up-down directions of the human body, respectively. At the same time, a standard three-dimensional human body model is acquired, with the model in a supine position. A corresponding reference coordinate system is constructed, with the origin located at the geometric center of the human body. The X-axis, Y-axis, and Z-axis are also parallel to the left-right, front-back, and up-down directions of the human body, respectively. By using an iterative nearest-point algorithm, the spatial coordinate system is registered with the reference coordinate system. Through continuous iteration, the optimal transformation matrix between the two coordinate systems is found, so that the registered position of the lesion and the diseased blood vessel in the human body model is closest to the actual position.

[0100] Assuming the transformation matrix is ​​T, and the coordinates of a point in the lesion coordinate system are (x1, y1, z1), then the coordinates of this point in the human body model coordinate system (x2, y2, z2) can be calculated by matrix multiplication, that is, (x2, y2, z2) = T × (x1, y1, z1).

[0101] Using this transformation matrix, the system can calculate the coordinates of any point on the center line of the diseased blood vessel in the reference coordinate system, and thus obtain its relative positional relationship with the human body.

[0102] In step S55, the system calculates the angular relationship between the centerline of the diseased blood vessel and the sagittal or coronal plane of the human body. Through coordinate registration and vector calculation, the spatial positional relationship between the diseased blood vessel and the three-dimensional model of the human body is determined, providing an important reference for subsequent surgical planning. This embodiment uses this method to accurately obtain the angular relationship between the diseased blood vessel and the human body.

[0103] For step S13, in this embodiment, the imaging device includes a bed and an operating arm. The current state of the device includes the current state of the bed and the current state of the operating arm, and the target state of the device includes the target state of the bed and the target state of the operating arm. The state of the bed and the operating arm is monitored by sensors built into the imaging device. Taking the C-arm of a digital subtraction angiography device as an example, the C-arm works in conjunction with the bed. The sensor monitors the operating angle of the C-arm to obtain the rotation angle information of the C-arm in the horizontal and vertical planes. The position sensor on the bed collects the tilt angle and position information of the bed. This information can be used to determine the current position of the imaging device.

[0104] In one embodiment, such as Figure 6 As shown, the step of generating the target position of the imaging device based on the lesion parameters, the lesion tangent angle, and the lesion blood vessel angle includes:

[0105] S61, determine the geometric center point of the lesion based on the lesion parameters, and calculate the coordinates of the geometric center point in the reference coordinate system using the transformation matrix;

[0106] S62, obtain the coordinates of the interventional puncture point in the reference coordinate system, and calculate the operation path from the puncture point to the geometric center point by combining the coordinates of the geometric center point, the tangent angle of the lesion, and the angle of the lesion blood vessel;

[0107] S63, determine the target position of the bed body according to the operation path;

[0108] S64, Based on the target position of the bed, obtain the target implementation angle of the operating arm relative to the human body, and use the target implementation angle as the target position of the operating arm.

[0109] In this embodiment, the position of the bed will affect the angle setting of the operating arm, so the position of the bed needs to be adjusted before the operating arm is adjusted.

[0110] When obtaining the target position of the bed, the direction and length of the operation path are obtained to determine the position and inclination of the bed to be reached, so as to ensure that the doctor can successfully reach the geometric center of the lesion for treatment.

[0111] The lesion tangent angle can be used to determine the optimal projection direction of the manipulator because it can help reduce the overlap between the lesion and the diseased blood vessel. The principle of the above formula is based on this. Combined with the lesion blood vessel angle, it can determine the target implementation angle of the manipulator, so that the imaging device can clearly display the structure of the lesion.

[0112] In step S64, specifically based on the target position of the bed, the target implementation angle of the operating arm relative to the human body is calculated by combining geometric projection with the tangent angle of the lesion and the angle of the blood vessel in the lesion. The target implementation angle is taken as the target position of the operating arm. The target implementation angle of the operating arm relative to the human body can be obtained by the following formula:

[0113]

[0114] Wherein, β is the target implementation angle, θ1 is the tangent angle of the lesion, and θ2 is the vascular angle of the lesion.

[0115] For step S14, this embodiment compares the current position of the bed with the target position of the bed to obtain the distance the bed needs to be translated or raised, and obtains the angle the bed needs to rotate with respect to the horizontal or vertical axis as the reference, as the first adjustment parameter. At the same time, the target implementation angle (target position of the operating arm) and the current implementation angle (current position of the operating arm) of the operating arm are compared to obtain the horizontal translation distance, horizontal rotation angle and vertical tilt angle of the operating arm, as the second adjustment parameter. An adjustment command is generated based on the first adjustment parameter and the second adjustment parameter, and the adjustment command is sent to the control system of the imaging device, such as the digital subtraction angiography device, through the digital communication interface. After receiving the adjustment command, the control system of the imaging device determines the validity and safety of the command, such as whether the command will cause the operating arm to collide with the bed. If the command is valid and safe, the adjustment command is executed. The actuator of the imaging device adjusts the spatial position and angle of the operating arm and the bed according to the adjustment command to meet the surgical requirements. For example, the first adjustment parameter includes the angles that need to be rotated around the X-axis, Y-axis and Z-axis respectively, so that the position of the bed matches the human body model. By transmitting these angle values ​​as the first adjustment parameter to the control module of the bed, the motor is controlled to drive the bed to rotate around the three axes by the corresponding angles until the target position is reached. Another example is that the second adjustment parameter includes the angles that the operating arm needs to rotate around the X-axis, Y-axis and Z-axis in space, such as rotating -8 degrees around the X-axis, rotating 15 degrees around the Y-axis and rotating 3 degrees around the Z-axis, so that the implementation angle of the operating arm matches the target tangent position. By transmitting the angle values ​​to the control module of the operating arm, the motor is controlled to drive the operating arm to rotate to the target irradiation angle.

[0116] In this embodiment, the position of the operating table is first adjusted using the first adjustment parameter, and then the angle of the operating arm is adjusted using the second adjustment parameter. After adjustment, the imaging device will provide feedback on the actual position parameters of the operating arm and the operating table to confirm that the adjustment is in place, and fine-tuning will be performed as necessary until the surgical requirements are met. In this embodiment, the method monitors the position and posture of the operating table and the operating arm in real time. Once a deviation exceeds a threshold, the adjustment parameters will be automatically calculated and sent to the control module to ensure that the relative position between the imaging device and the human body always meets the surgical requirements, providing reliable hardware support for the smooth progress of the surgery.

[0117] This application automatically determines the lesion parameters, lesion tangent angle, and lesion vessel angle by reconstructing the three-dimensional image data of blood vessels. It then generates the target position of the imaging device based on this and adjusts the imaging device according to its current position to achieve the target position. This not only reduces the complexity of adjustment and improves the positioning accuracy and safety of the surgery, but also reduces the operation time, significantly improves the success rate and efficiency of interventional surgery, and reduces the radiation exposure of patients and doctors.

[0118] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, optical disk, or read-only memory (ROM), or random access memory (RAM).

[0119] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0120] Further reference Figure 7 As a response to the above Figure 1 The implementation of the method shown in this application provides an embodiment of a position adjustment device for an imaging apparatus, which is similar to... Figure 1 Corresponding to the method embodiments shown, this device can be specifically applied to various electronic devices.

[0121] like Figure 7 As shown, the position adjustment device 7 of the imaging equipment described in this embodiment includes: a construction module 71, a parameter acquisition module 72, a position generation module 73, and a control module 74. Wherein:

[0122] The construction module 71 is used to construct a three-dimensional image of the blood vessel and identify the lesion and the diseased blood vessel where the lesion is located based on the three-dimensional image; the parameter acquisition module 72 is used to acquire the lesion parameters, lesion tangent angle, lesion blood vessel angle, and current device status of the lesion; the position generation module 73 is used to generate a target device status based on the lesion parameters, lesion tangent angle, and lesion blood vessel angle; the control module 74 is used to adjust the device based on the current device status and the target device status to achieve the target device status.

[0123] This embodiment, by setting up a device module corresponding to the position adjustment method of the imaging device, can reconstruct the three-dimensional image data of the blood vessel through the construction module 71, and then automatically determine the lesion parameters, lesion tangent angle, and lesion blood vessel angle through the parameter acquisition module 72. Then, the position generation module 73 generates the target position of the imaging device based on this. Finally, the control module 74 adjusts the imaging device in combination with the current position of the imaging device to achieve the target position of the imaging device. This not only reduces the complexity of adjustment and improves the positioning accuracy and safety of the surgery, but also reduces the operation time, significantly improves the success rate and efficiency of interventional surgery, and reduces the radiation exposure of patients and doctors.

[0124] To address the aforementioned technical problems, embodiments of this application also provide a computer device. Please refer to [link / reference needed]. Figure 8 , Figure 8 This is a basic structural block diagram of the computer device in this embodiment.

[0125] The computer device 8 includes a memory 81, a processor 82, and a network interface 83 that are interconnected via a system bus. It should be noted that only the computer device 8 with components 81-83 is shown in the figure; however, it should be understood that it is not required to implement all the shown components, and more or fewer components can be implemented alternatively. Those skilled in the art will understand that the computer device described here is a device capable of automatically performing numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes, but is not limited to, microprocessors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0126] The computer device can be a desktop computer, laptop, handheld computer, or cloud server, etc. The computer device can interact with the user via a keyboard, mouse, remote control, touchpad, or voice control.

[0127] The memory 81 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 81 may be an internal storage unit of the computer device 8, such as the hard disk or memory of the computer device 8. In other embodiments, the memory 81 may also be an external storage device of the computer device 8, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the computer device 8. Of course, the memory 81 may also include both the internal storage unit and its external storage device of the computer device 8. In this embodiment, the memory 81 is typically used to store the operating system and various application software installed on the computer device 8, such as the program code for the position adjustment method of the imaging device. In addition, the memory 81 can also be used to temporarily store various types of data that have been output or will be output.

[0128] In some embodiments, the processor 82 may be a central processing unit (CPU), controller, microcontroller, microprocessor, or other data processing chip. The processor 82 is typically used to control the overall operation of the computer device 8. In this embodiment, the processor 82 is used to run program code stored in the memory 81 or process data, for example, to run program code for the position adjustment method of the imaging device.

[0129] The network interface 83 may include a wireless network interface or a wired network interface, which is typically used to establish communication connections between the computer device 8 and other electronic devices.

[0130] This embodiment, by setting up a computer device corresponding to the position adjustment method of the imaging device, can effectively and accurately adjust the position of the camera device, making the display position of the interventional instruments in the interventional surgery images easier to observe.

[0131] This application also provides another embodiment, namely, a computer-readable storage medium storing a position adjustment program for an imaging device, the position adjustment program for the imaging device being executable by at least one processor to cause the at least one processor to perform the steps of the position adjustment method for the imaging device as described above.

[0132] This embodiment, by setting a computer-readable storage medium corresponding to the position adjustment method of the imaging device, can effectively and accurately adjust the position of the camera device, making the display position of interventional instruments in interventional surgical images easier to observe.

[0133] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0134] Obviously, the embodiments described above are only some embodiments of this application, not all embodiments. The accompanying drawings show preferred embodiments of this application, but do not limit the patent scope of this application. This application can be implemented in many different forms; rather, the purpose of providing these embodiments is to provide a more thorough and comprehensive understanding of the disclosure of this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing specific embodiments, or make equivalent substitutions for some of the technical features. Any equivalent structures made using the content of this application's specification and drawings, directly or indirectly applied to other related technical fields, are similarly within the scope of patent protection of this application.

Claims

1. A method for adjusting the position of an imaging device, characterized in that, include: Constructing three-dimensional images of blood vessels; Based on the three-dimensional image, obtain the lesion parameters related to the lesion size, the lesion tangent angle, the lesion blood vessel angle, and the current position of the imaging device. The step of obtaining the lesion tangent angle based on the three-dimensional image includes: Identify the diseased blood vessel where the lesion is located based on the three-dimensional image; Obtain the neck section of the lesion and determine the center point of the neck section, wherein the neck section is the surface where the junction of the lesion and the diseased blood vessel is located; Using the centerline of the diseased blood vessel as the axis of rotation, the system rotates within a preset angle range at preset angle intervals to obtain multiple tangential positions. For each tangential position, the three-dimensional model is projected onto a two-dimensional plane along a set direction to obtain a two-dimensional image of the lesion at each tangential position. The tangential position in the two-dimensional image where the neck section is straight or tends to be straight is selected as the target tangential position. Obtain the outline of the lesion in the two-dimensional image of the target tangent position, and take the point on the outline that is farthest from the center point as the distal endpoint; Determine the straight line connecting the center point and the distal point, and take the angle between the straight line and the center line as the tangent angle of the lesion; The target position of the imaging device is generated based on the lesion parameters related to the lesion size, the lesion tangent angle, and the lesion blood vessel angle; The imaging device is adjusted according to its current position and its target position so that it reaches the target position.

2. The method for adjusting the position of an imaging device according to claim 1, characterized in that, The step of obtaining lesion parameters related to lesion size based on the three-dimensional image includes: The lesion was identified based on the three-dimensional image; Select the rectangle with the largest area on the cross-section of the three-dimensional image region of the lesion, and take its long side as the major axis of the lesion and its short side as the minor axis of the lesion. The volume of a single voxel is obtained, and the volume of the voxel is predetermined during the construction of the three-dimensional image. The total number of voxels in the three-dimensional image region of the lesion is counted to obtain the number of voxels in the lesion. Based on the number of voxels in the lesion and the volume of a single voxel, the volume of the lesion is calculated.

3. The method for adjusting the position of an imaging device according to claim 2, characterized in that, The step of identifying the lesion based on the three-dimensional image includes: The vascular structure image data in the three-dimensional image is acquired and analyzed to identify the lesion in the vascular structure image data and determine the location information of the lesion in the three-dimensional image.

4. The method for adjusting the position of an imaging device according to claim 1, characterized in that, The step of obtaining the angle of the lesion blood vessels based on the three-dimensional image includes: Identify the diseased blood vessel where the lesion is located based on the three-dimensional image; Establish the spatial coordinate system of the diseased blood vessel in the three-dimensional image; Obtain the reference coordinate system of the three-dimensional human body model in a lying position, register the spatial coordinate system of the diseased blood vessel with the reference coordinate system, and determine the transformation matrix between the two coordinate systems; Based on the transformation matrix, calculate the spatial coordinates of the diseased blood vessel in the reference coordinate system; The angle between the diseased blood vessel and the human body is calculated based on the spatial coordinates to obtain the angle of the lesion blood vessel.

5. The method for adjusting the position of an imaging device according to claim 4, characterized in that, The step of identifying the lesion's blood vessel based on the three-dimensional image includes: Determine the location information of the lesion in the three-dimensional image; Based on the location information, the blood vessels around the lesion are tracked to obtain the blood vessel segment connected to the lesion, and the blood vessel segment is identified as the diseased blood vessel where the lesion is located.

6. The method for adjusting the position of an imaging device according to claim 4, characterized in that, The imaging device includes a bed and an operating arm, and the target position of the imaging device includes the target position of the bed and the target position of the operating arm. The step of generating the target position of the imaging device based on the lesion parameters related to the lesion size, the lesion tangent angle, and the lesion blood vessel angle includes: The geometric center point of the lesion is determined based on the lesion parameters related to the lesion size, and the coordinates of the geometric center point in the reference coordinate system are calculated using the transformation matrix. Obtain the coordinates of the interventional puncture point in the reference coordinate system, and calculate the operation path from the puncture point to the geometric center point by combining the coordinates of the geometric center point, the tangent angle of the lesion, and the angle of the lesion blood vessel. The target position of the bed is determined according to the operation path; Based on the target position of the bed, the target implementation angle of the operating arm relative to the human body is obtained, and the target implementation angle is used as the target position of the operating arm.

7. A position adjustment device for an imaging apparatus, characterized in that, A method for adjusting the position of an imaging device according to any one of claims 1 to 6, comprising: A building block for creating 3D images of blood vessels; The parameter acquisition module is used to acquire lesion parameters related to lesion size, lesion tangent angle, lesion blood vessel angle and current position of imaging device based on the three-dimensional image; The location generation module is used to generate the target location of the imaging device based on the lesion parameters related to the lesion size, the lesion tangent angle, and the lesion blood vessel angle; The control module is used to adjust the imaging device according to the current position and the target position of the imaging device to achieve the target position of the imaging device.

8. A computer device, characterized in that, The device includes a memory and a processor, wherein the memory stores computer-readable instructions, and the processor executes the computer-readable instructions to implement the position adjustment method of the imaging device according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-readable instructions, which, when executed by a processor, implement the position adjustment method of the imaging device according to any one of claims 1 to 6.

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