Three-dimensional digital subtraction angiography method, device, electronic equipment and storage medium

Abstract

The embodiments of the present application provide a three-dimensional digital subtraction angiography method, device, electronic device and storage medium. First, a method is proposed to use an X-ray imaging system to shoot multiple frames of images of an object to be measured with markers, and by calculating the markers in the image, a high-precision imaging geometric relationship between the imaging system and the object to be measured is obtained, thereby obtaining a CT image reconstruction method for a three-dimensional image of the object to be measured. The CT image reconstruction method is used to reconstruct CT images of multiple frames of images shot under mask operation and filling operation respectively, and the grayscale of the corresponding coordinate pixels of the two three-dimensional images of filling operation and mask operation are subtracted to obtain a subtraction angiography image. Since the coordinate system is established on the object to be measured, the coordinate system of the object to be measured includes the movement or change of the object to be measured. Therefore, the three-dimensional image result of the object to be measured is highly accurately matched and aligned, and various movements and errors in the CT operation state are automatically and effectively eliminated, so that a three-dimensional digital subtraction angiography image is obtained with high precision.

Description

Technical Field

[0001] The present application relates to the field of image processing technology, and in particular to a three-dimensional digital subtraction angiography method, device, electronic equipment and storage medium. Background Art

[0002] 3D Digital Subtraction Angiography (3D-DSA) is a new angiography technology that has developed rapidly in recent years. It is used to detect and monitor the three-dimensional structure, size, working condition, etc. of blood vessels in the human heart, brain and other parts.

[0003] Its main principle is to use CT technology such as C-arm CT or spiral CT to perform 3D CT image reconstruction of the body part of interest under masking, obtaining a 3D CT image under masking. Contrast agent is then injected into the body and 3D image reconstruction is performed to obtain a 3D CT image under filling. The two 3D CT images are then registered and subtracted to obtain a 3D digital subtraction angiography image.

[0004] Currently, the accuracy of the geometric relationship between the imaging system and the object being measured, as well as the registration accuracy of image subtraction, is primarily determined by hardware performance, such as the structural rigidity, machining accuracy, and motion synchronization control precision of the CT imaging system. This often requires the object to remain stable, resulting in high cost and low accuracy. Therefore, improving the accuracy of the calibration of the imaging geometry in 3D DSA and the subsequent registration accuracy of image subtraction is a pressing issue. Summary of the Invention

[0005] The embodiments of the present application provide a three-dimensional digital subtraction angiography method, device, electronic device and storage medium to relax the processing and motion accuracy requirements of various types of CT machines, improve the calibration accuracy of the imaging system, and obtain three-dimensional digital subtraction angiography images conveniently, reliably and with high precision.

[0006] In a first aspect, an embodiment of the present application provides a three-dimensional digital subtraction angiography method, comprising:

[0007] Acquiring a plurality of frames of first projection images, wherein the plurality of frames of first projection images are obtained by emitting X-rays to a test object at a plurality of first imaging angles with the blood vessel in a masked state, the test object being provided with a plurality of markers, and the CT imaging system moving on a predetermined track;

[0008] Acquire at least one set of second projection images, wherein each set of second projection images includes multiple frames of second projection images, and the multiple frames of second projection images in each set of second projection images are obtained by the CT imaging system emitting X-rays to the object under test at multiple second imaging angles when the blood vessel is in a filled state;

[0009] determining an imaging geometric relationship corresponding to each frame of the first projection image according to pixel coordinates of a marker in each frame of the first projection image;

[0010] determining, according to pixel coordinates of the markers in the plurality of frames of second projection images in each group of second projection images, imaging geometric relationships corresponding to the plurality of frames of second projection images in the plurality of frames of second projection images;

[0011] performing CT three-dimensional image reconstruction on the multiple frames of first projection images according to imaging geometric relationships respectively corresponding to the multiple frames of first projection images to obtain a first CT three-dimensional image;

[0012] performing CT three-dimensional image reconstruction on the multiple frames of second projection images in each group of second projection images according to imaging geometric relationships corresponding to the multiple frames of second projection images in each group of second projection images to obtain at least one second CT three-dimensional image;

[0013] At least one three-dimensional digital subtraction angiography image is obtained based on the first CT three-dimensional image and the at least one second CT three-dimensional image.

[0014] In a second aspect, an embodiment of the present application provides a three-dimensional digital subtraction angiography device, comprising:

[0015] an acquisition unit, configured to acquire a plurality of frames of first projection images, wherein the plurality of frames of first projection images are obtained by a CT imaging system emitting X-rays to an object under test at a plurality of first imaging angles, with the blood vessel in a masked state, the object being provided with a plurality of markers, and the CT imaging system moving on a predetermined track;

[0016] Acquire at least one set of second projection images, wherein each set of second projection images includes multiple frames of second projection images, and the multiple frames of second projection images in each set of second projection images are obtained by the CT imaging system emitting X-rays to the object under test at multiple second imaging angles when the blood vessel is in a filled state;

[0017] a processing unit, configured to determine an imaging geometric relationship corresponding to each frame of the first projection image according to pixel coordinates of a marker in each frame of the first projection image;

[0018] determining, according to pixel coordinates of the markers in the plurality of frames of second projection images in each group of second projection images, imaging geometric relationships corresponding to the plurality of frames of second projection images in the plurality of frames of second projection images;

[0019] performing CT three-dimensional image reconstruction on the multiple frames of first projection images according to imaging geometric relationships respectively corresponding to the multiple frames of first projection images to obtain a first CT three-dimensional image;

[0020] performing CT three-dimensional image reconstruction on the multiple frames of second projection images in each group of second projection images according to imaging geometric relationships corresponding to the multiple frames of second projection images in each group of second projection images to obtain at least one second CT three-dimensional image;

[0021] At least one three-dimensional digital subtraction angiography image is obtained based on the first CT three-dimensional image and the at least one second CT three-dimensional image.

[0022] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a processor, the processor being connected to a memory, the memory being used to store a computer program and the projection ray image, the processor being used to execute the computer program stored in the memory so that the electronic device performs the method described in the first aspect.

[0023] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program enables a computer to execute the method described in the first aspect.

[0024] In a fifth aspect, an embodiment of the present application provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer is operable to enable the computer to execute the method described in the first aspect.

[0025] The implementation of the embodiments of the present application has the following beneficial effects:

[0026] In various traditional CT devices, the imaging geometric relationship between the object under test and the imaging system is mainly completed and the accuracy is guaranteed by mechanical devices or equipment hardware. The present application obtains the imaging geometric relationship between the imaging system and the object under test through algorithms such as photogrammetry, and optimizes the obtained imaging geometric relationship with high precision. Since the global coordinate system of the present application is fixedly connected to the object under test, the imaging geometric relationship automatically includes the position and posture of the imaging system, including the motion error of the predetermined orbit caused by vibration, shaking, etc. under actual working conditions. In particular, during the two three-dimensional CT image reconstruction processes of the mask state and the filling state in the digital subtraction angiography operation, the relative position of the markers on the object under test and the object under test is kept unchanged, so that the multiple projection imaging links have the same coordinate system, and the error of the imaging geometric relationship caused by the movement change of the object under test is automatically eliminated, thereby improving the calibration accuracy of the imaging geometric relationship and further improving the accuracy of CT image reconstruction. Due to the improvement of CT imaging reconstruction accuracy, especially the improvement of the correspondence accuracy of volume image matching in different states, the quality and accuracy of digital subtraction angiography images are effectively improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 A schematic flow chart of a three-dimensional digital subtraction angiography method provided in an embodiment of the present application;

[0028] Figure 2 A schematic diagram of obtaining multiple frames of first projection images provided in an embodiment of the present application;

[0029] Figure 3 A schematic diagram of intrinsic and extrinsic parameters of an imaging system provided in an embodiment of the present application;

[0030] Figure 4 A block diagram of the functional units of a three-dimensional digital subtraction angiography device provided in an embodiment of the present application;

[0031] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0033] The terms "first," "second," "third," and "fourth," etc., in the specification and claims of this application and the accompanying drawings are used to distinguish between different objects, rather than to describe a specific order. In addition, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or elements is not limited to the listed steps or elements, but may optionally include steps or elements not listed, or may optionally include other steps or elements inherent to the process, method, product, or apparatus.

[0034] In order to facilitate understanding of the embodiments of the present application, the relevant knowledge involved in the present application is first introduced.

[0035] In cone-beam CT (CBCT) imaging, the projection imaging process can be expressed by formula (1):

[0036] p=Sf Formula (1)

[0037] Wherein, S is the system matrix reflecting the imaging geometric relationship between the imaging system and the object, f is the three-dimensional object to be reconstructed, and p is the projection image.

[0038] The CT image reconstruction process can be expressed by formula (2):

[0039] f=S -1 p Formula (2);

[0040] However, due to the ill-conditioned nature of limited angle reconstruction, the generalized inverse process is ill-conditioned, and the estimation of the image to be reconstructed is It can be expressed as:

[0041]

[0042] From formula (3), we can see that obtaining the imaging geometric relationship between the imaging system and the object under inspection is the prerequisite for CT image reconstruction, and the accuracy of the imaging geometric relationship is a key factor affecting the quality of CT reconstruction.

[0043] Currently, one of the main conventional equipment for 3D DSA is the C-arm CT. However, this CT needs to move at high speed around the object being measured on a predetermined track. In addition, the CT device is heavy, moves quickly, and has a small track curvature radius, which easily causes errors such as vibration and shaking. These factors reduce the quality of the CT device's 3D CT image reconstruction and the alignment accuracy of 3D CT images in both masking and filling modes.

[0044] How to improve the calibration accuracy of the imaging geometry during the DSA process of the predetermined orbit CT to improve the image reconstruction quality and the accuracy of the subsequent image subtraction alignment, especially how to improve the accuracy of the alignment caused by the motion of the measured object, is an urgent problem to be solved.

[0045] In order to facilitate understanding of the technical solution of this application, the relevant concepts of this application are first explained and illustrated.

[0046] The CT imaging system of the present application is an imaging system that satisfies the imaging model of central perspective projection. The imaging system includes a radiation source and a radiation detector, wherein the radiation source is the focus of the central perspective projection, and in the present application, the relative distance between the radiation source and the radiation detector remains unchanged.

[0047] The imaging system of the present application can be any type of CT imaging system in which the relative distance between the radiation source and the radiation detector remains constant. This includes, but is not limited to, various types of predetermined-track C-arm CT, spiral CT, tomosynthesis CT, and DR-based cone beam computed tomography (CBCT).

[0048] The coordinate system of the present application includes a global coordinate system, a measured object coordinate system, an imaging system coordinate system, and an image coordinate system. Among them, the coordinate origin of the measured object coordinate system is established on the measured object or on a supporting device fixed to the measured object. For the convenience of calculation, the measured object coordinate system is used as the global coordinate system in this application. The coordinate origin of the imaging system coordinate system is established at the center of the ray source, and the z-axis coincides with the optical axis of the imaging system. The spatial coordinates of the marker are the three-dimensional spatial coordinates of the marker in the measured object coordinate system, and the pixel coordinates of the marker are the two-dimensional pixel coordinates of the marker in the image coordinate system.

[0049] In the present application, the multi-frame projection images of the object to be measured at multiple imaging angles, since a plurality of markers are provided on the object to be measured, each frame of the projection image contains a number of markers. The markers on each projection image are identified and extracted by an image processing method to obtain the pixel coordinates of the markers, and the markers (points with the same name) between different projection images are matched and numbered by an image processing mathematical method, such as an algorithm such as RANSAC. In order to facilitate the automatic matching of markers with the same name between these projection images, a plurality of markers can be made into different specific shapes, such as a triangle, a cross, etc. For each frame of projection image, when the markers of this specific shape are detected by image processing and pattern recognition algorithms, they can be automatically matched and paired with numbers, and the remaining markers can be matched and numbered by their relative positional relationship with the specific marker, so that the markers contained in each frame of projection image and the marker numbers are quickly and accurately identified, thereby quickly obtaining the same markers in different projection images.

[0050] Optionally, the spatial position relationship or relative distance of more than two markers among the multiple markers may be known.

[0051] Optionally, the material of the marker can be any material that is sensitive to X-rays, such as lead, steel, or bone material, and the shape can be beads or lines, etc. This application does not limit the material and shape of the marker.

[0052] It should be understood that the marker is set on the object to be measured, and the marker can be set directly on the object to be measured, or the marker can be set indirectly on the object to be measured. For example, the marker can be set on an accessory, and the accessory is set on the object to be measured, and the accessory is a freely detachable accessory. Therefore, the present application does not limit the manner in which the marker is set on the object to be measured. In addition, the positional relationship between the multiple markers can be arbitrary. For example, the multiple markers can be randomly fixedly placed on the object to be measured and move with the object to be measured; the relationship between the multiple markers can also be fixed, for example, the multiple markers are placed on a shelf, and the shelf is then fixed to the object to be measured.

[0053] In order to accurately obtain the pixel coordinates of the marker in the projection image, a sub-pixel positioning algorithm is usually used. For example, the grayscale surface or correlation coefficient matrix of the marker in the projection image is first fitted with a quadratic or cubic surface, and then the extreme value is calculated, and the extreme value point is used as the pixel coordinate of the marker.

[0054] To reduce the radiation-blocking effect of markers, after identifying and aligning the markers in the projected image using an image processing algorithm, the marker's pixel value can be interpolated with the pixel values of the surrounding area, replacing the original pixel value of the marker. This suppresses the effect of the radiation-sensitive marker on the radiographic image. Alternatively, the marker's pixel value can be set to null, meaning it is not included in the 3D image reconstruction calculations. This reduces the disturbance caused by the marker's radiation-sensitive material and thus does not affect the quality of the 3D image reconstruction.

[0055] See Figure 1 , Figure 1 The following is a flow chart of a three-dimensional digital subtraction angiography method provided in an embodiment of the present application. The method includes the following steps:

[0056] 101. Acquire multiple frames of first projection images.

[0057] The multiple frames of first projection images are obtained by emitting X-rays from the CT imaging system to the object under examination at multiple first imaging angles, with the blood vessels in a masked state (i.e., without the injection of a contrast agent). The CT imaging system moves along a predetermined trajectory, i.e., the relative distance between the radiation source and the radiation detector in the CT imaging system remains constant.

[0058] The multiple frames of first projection images correspond one-to-one to the multiple first imaging angles, and the multiple first imaging angles can be any imaging angles. For example, at any first imaging angle, the CT imaging system emits X-rays toward the object under test. The X-rays irradiate the object under test, and the radiation detector records a series of projection data at the corresponding position of the radiation source. Based on the series of projection data, a frame of first projection image corresponding to the imaging angle is generated, thereby obtaining multiple frames of first projection images.

[0059] Furthermore, a plurality of markers are provided on the object to be measured, and each frame of the first projection image includes part or all of the plurality of markers.

[0060] Specifically, the CT imaging system is controlled to rotate and / or translate multiple times, and each rotation and / or translation obtains an imaging angle, thereby obtaining a first imaging angle; and the CT imaging system is controlled to emit X-rays to the object under test at multiple first imaging angles after the object under test has been rotated and / or translated multiple times, thereby obtaining multiple frames of first projection images.

[0061] like Figure 2As shown, the object to be measured is placed on a carrying device, and the CT imaging system can be controlled to rotate and / or translate around the object to be measured on a predetermined track. After each rotation and / or translation, the radiation source is controlled to emit X-rays toward the object to be measured, and the radiation detector records a series of projection data at the corresponding position of the radiation source, generating a projection image after each rotation and / or translation, and obtaining multiple frames of first projection images.

[0062] It should be noted that the imaging system of the present application moves on a predetermined track. When the motion trajectory of the imaging system is known, the way to obtain multiple frames of first projection images is to control the CT imaging system to move on a preset track. When it reaches multiple preset positions or first imaging angles, X-rays are emitted to the object to be measured to obtain multiple frames of first projection images.

[0063] In one embodiment of the present application, the supporting device is a rotatable or translatable device, and the imaging system and the object to be inspected can be controlled to rotate and / or translate multiple times simultaneously, and after each rotation and / or translation, the radiation source is controlled to emit X-rays to the object to be inspected to obtain multiple frames of first projection images.

[0064] 102: Acquire at least one set of second projection images.

[0065] For example, similar to the method for acquiring the first projection images, for each set of second projection images, while the blood vessels of the subject are in a filled state (i.e., with contrast agent injected), the CT imaging system is controlled to emit X-rays toward the subject at multiple second imaging angles to obtain multiple frames of second projection images within the set of second projection images. It should be noted that the method for acquiring multiple frames of second projection images within any set of second projection images is similar to the method for acquiring multiple frames of first projection images described above and will not be further described.

[0066] It should be noted that the multiple second imaging angles corresponding to any two sets of second projection images can be the same or different; and the multiple second imaging angles corresponding to any set of projection images can be the same or different from the multiple first imaging angles. In other words, the imaging angles used in each 3D CT image reconstruction process can be the same or different, and this application does not impose any restrictions on this.

[0067] For example, four frames of first projection images are acquired at positions A, B, C, and D respectively. When acquiring any set of second projection images, imaging can be performed at the four positions A, B, C, and D, or imaging can not be performed at any of the four positions A, B, C, and D.

[0068] It should be noted that in different projection imaging links, the relative geometric relationship between the marker and the object being measured needs to be kept unchanged until several projection imaging links are completed, so that the multiple projection imaging links have the same coordinate system.

[0069] It should be noted that when the CT imaging system operates in both masking and filling modes, the CT imaging system acquires projection images around the object being measured, using the same C-arm X-ray imaging system to collect and record data sets. Optionally, the CT imaging system can also return to orbital operation between masking and filling modes, so that orbital operation can be restarted in filling mode from the same starting position as in masking mode. For example, operations are typically performed using a C-arm X-ray system in a cone-beam geometry (cone-beam CT operation). During the rotation of the C-arm around the object being measured, multiple projection images are recorded at different rotation angles. Optionally, the rotation is at least 200°.

[0070] 103: Determine the imaging geometric relationship corresponding to each frame of the first projection image according to the pixel coordinates of the marker in each frame of the first projection image.

[0071] Among them, the imaging geometric relationship corresponding to each frame of the first projection image is the imaging geometric relationship between the object to be measured and the imaging system when obtaining each frame of the first projection image, that is, the posture and position of the imaging system coordinate system relative to the coordinate system of the object to be measured, and the imaging geometric relationships of the first projection images mentioned later are similar to the explanation here and will not be described again.

[0072] Exemplarily, the imaging geometric relationship corresponding to each frame of the first projection image includes the intrinsic parameters and extrinsic parameters corresponding to each frame of the first projection image. Figure 3 As shown, the internal parameters of each frame projection include the focal length corresponding to the first projection image of each frame, that is, the distance D from the ray source C to the ray detector SD and the principal point coordinates (C x , C y ); wherein, the principal point is the perpendicular intersection of the ray source C and the imaging surface of the ray detector, the line connecting the ray source and the principal point is defined as the optical axis, and the coordinates of the principal point are the pixel coordinates of the central pixel of the first projection image of each frame; the external parameters are the posture and position relationship of the imaging system coordinate system relative to the coordinate system of the measured object when obtaining the first projection image of each frame, and the posture is represented by the rotation matrix, and the position relationship is represented by the translation matrix.

[0073] Furthermore, the imaging geometric relationship between the measured object coordinate system, the imaging system coordinate system, and the image coordinate system can be expressed by formula (4):

[0074]

[0075] Among them, Z Cis a constant factor, (X, Y, Z) refers to the spatial coordinates of the marker P in the coordinate system of the object being measured, Refers to the pixel coordinates of the image point p obtained by the central perspective projection of the marker P, that is, the pixel coordinates of the marker P in the projected image; du and dv are the pixel sizes of the ray detector respectively; R0 is the rotation matrix, which is a 3×3 unit orthogonal matrix. Its elements are the trigonometric function combination of the rotation angle. The rotation angle is used to represent the Euler angle around the three coordinate axes when the posture of the coordinate system of the measured object is transformed to be consistent with the posture of the coordinate system of the imaging system. T0 is the translation matrix, T0=(T x ,T y ,T z ) is called the translation vector, T x , T y , T z They respectively represent the translation amounts on the three coordinate axes of moving the origin of the measured object coordinate system to the origin of the imaging system coordinate system. T0 can also be called the coordinates of the origin of the measured object coordinate system in the imaging system coordinate system, which is equivalent to the coordinates of the origin of the imaging system coordinate system in the measured object coordinate system.

[0076] From the above, it can be seen that the imaging geometric relationship corresponding to each frame of the first projection image to be obtained in this application is to obtain the principal point coordinates, the distance from the ray source to the ray detector, the rotation matrix, and the translation matrix corresponding to each frame of the first projection image. In addition, in this application, the initial value of the principal point coordinates (Cx, Cy) corresponding to each frame of the first projection image is set to the pixel coordinates of the center pixel point of the first projection image of the frame, so the principal point coordinates corresponding to each frame of the first projection image can be directly determined based on each frame of the first projection image. Moreover, without loss of generality, in the embodiment of this application, it is assumed that the distance D from the ray source C to the ray detector during the entire imaging process is SD Remains unchanged, so the focal lengths corresponding to any two frames of the first projection image are the same, so the distance D from the ray source C to the ray detector is determined for the first time SD After that, there is no need to confirm D again SD ; Then the multiple frames of the first projection image all use the D determined for the first time SD To simplify the calculation, the nominal D SD As D in the computational model SD The initial value of .

[0077] Exemplarily, the initial imaging geometric relationship corresponding to each frame of the first projection image is determined based on the motion position posture of the CT imaging system on a predetermined track (i.e., the nominal parameters of the CT imaging system); the imaging geometric relationship of each frame of the first projection image is determined based on the initial imaging geometric relationship of each frame of the first projection image and the pixel coordinates of the markers in each frame of the first projection image.

[0078] Four methods for obtaining the initial imaging geometric relationship of each frame of the first projection image and the spatial coordinates of the marker in each frame of the first projection image are introduced below.

[0079] Method 1: When the nominal parameters of the imaging system are known and the spatial coordinates of the markers in each frame of the first projection image are all known.

[0080] Since the nominal parameters of the imaging system are known, that is, the initial imaging geometric relationship of the imaging system at each first imaging angle is known, the initial imaging geometric relationship corresponding to each frame of the first projection image can be directly determined according to the nominal parameters of the imaging system;

[0081] The spatial coordinates of the so-called markers are known, that is, the relative position and posture relationship between the markers and the coordinate origin of the coordinate system of the measured object is set and does not change. Therefore, after the coordinate system of the measured object is established, the spatial coordinates of each marker can be directly obtained. For example, the relative position relationships between the coordinates of multiple markers with respect to the coordinate system of the measured object can be pre-set, so that the spatial coordinates of all markers in each frame of the first projection image are known.

[0082] Method 2: The nominal parameters of the imaging system are known, but some of the projection images in the multiple frames of first projection images contain markers with unknown spatial coordinates.

[0083] Exemplarily, there are markers with unknown spatial coordinates in k frames of the multiple first projection images, 0<k≤n (n is the number of multiple frames of first projection images), that is, there are markers with unknown spatial coordinates in some or all of the first projection images. For the first projection image with markers with unknown spatial coordinates, the spatial coordinates of all markers thereon may be unknown, or the spatial coordinates of some markers may be unknown, while the spatial coordinates of another part of the markers are known.

[0084] The following uses the first projection image A as an example to illustrate the process of acquiring the spatial coordinates of a landmark with unknown spatial coordinates in first projection image A. First projection image A is any one of the k frames of first projection images. It should be understood that the process of acquiring the spatial coordinates of a landmark with unknown spatial coordinates in other first projection images within the k frames of first projection images is similar and will not be further described.

[0085] Exemplarily, the first projection image B is selected from multiple frames of first projection images, and the imaging angle between the first projection image A and the first projection image B is greater than an angle threshold, wherein the first projection image B and the first projection image A have p identical markers, and the p identical markers include a marker whose spatial coordinates in the first projection image A are unknown.

[0086] In one embodiment of the present application, since the nominal parameters of the imaging system are known, the initial imaging geometric relationship corresponding to the first projection image A and the first projection image B can be determined based on the nominal parameters of the imaging system. Finally, the spatial coordinates of the p identical markers are determined based on the pixel coordinates of the p identical markers in the first projection image A and the first projection image B, respectively, and the initial imaging geometric relationship corresponding to the first projection image A and the first projection image B. If there are still markers with unknown spatial coordinates in the projection image, the spatial coordinates of the markers with unknown spatial coordinates in the first projection image A can be obtained by selecting the first projection image A and the first projection image B as described above. Furthermore, the number of markers with known spatial coordinates is set to be greater than or equal to a first threshold.

[0087] In another embodiment of the present application, the relative rotation and translation matrix between the imaging systems of the first projection image A and the first projection image B during imaging is determined based on the motion trajectory posture of the CT imaging system on a predetermined track; based on the relative rotation and translation matrix and the pixel coordinates of p identical markers in the first projection image A and the first projection image B, respectively, the spatial coordinates of the markers with unknown spatial coordinates among the p markers are obtained, that is, a triangulated intersection is performed to obtain the spatial coordinates of the p identical markers. Similarly, if there are still markers with unknown spatial coordinates in the projection image, the spatial coordinates of the markers with unknown spatial coordinates can be obtained by selecting the first projection image A and the first projection image B as described above, and the spatial coordinates of the markers with unknown spatial coordinates in the first projection image A can be obtained.

[0088] For the first projection images of other frames, the spatial coordinates of each marker in the first projection images of other frames can also be obtained according to the above method. It should be noted that when obtaining the spatial coordinates of a marker in any first projection image frame, if the spatial coordinates of a marker contained therein are already known (for example, when obtaining the three-dimensional coordinates of the marker in the first projection image of another frame, the spatial coordinates of the marker have already been obtained), there is no need to obtain the spatial coordinates of the marker again. It is only necessary to obtain the spatial coordinates of the marker with unknown spatial coordinates in the first projection image of the other frame. In this way, the spatial coordinates of the marker in each first projection image frame are known.

[0089] It should be noted that the spatial coordinates of the markers, derived from the relative rotation and translation matrices between the imaging systems, are those within the coordinate system of the specified imaging system. Based on application requirements, a global coordinate system fixed to the object under test is established to obtain the global spatial coordinates of each marker. Since the nominal parameters are known, the initial imaging geometry corresponding to the first projection image of each frame is also known.

[0090] Method 3: The nominal parameters of the imaging system are unknown, but the spatial coordinates of the markers in the first projection image of each frame are known.

[0091] Since the nominal parameters of the imaging system are unknown, the initial imaging geometric relationship of each frame of the first projection image cannot be directly obtained; however, the spatial coordinates of all markers are known, so the internal and external parameters corresponding to each frame of the first projection image (i.e., the initial imaging geometric relationship) can be directly calculated according to formula (4) using the spatial coordinates of the markers and the pixel coordinates contained in each frame of the first projection image to form a linear equation group of the projection matrix elements of the frame of projection image. The equation group is solved, and then according to the relationship between the projection matrix and the internal and external parameters of the imaging system, the initial imaging geometric relationship corresponding to the frame of projection image is obtained from the projection matrix decomposition.

[0092] Various mathematical methods, such as the PnP algorithm, can be used to solve the intrinsic and extrinsic parameters of the imaging geometry, depending on the number of known markers. Alternatively, when a distribution of markers with known spatial coordinates is specifically designed to satisfy certain constraints, only three markers with known spatial coordinates are required to solve the intrinsic and extrinsic parameters of the projection image frame. When the nominal parameter of the system's source-to-detector distance is directly used as the intrinsic parameter, the extrinsic parameters of the projection image frame can be solved directly using three markers with known spatial coordinates.

[0093] Method 4: The nominal parameters of the imaging system are unknown, and the number of landmarks with known spatial coordinates in each frame of projection image is less than a first threshold.

[0094] Exemplarily, a first projection image A and a first projection image B are selected from multiple frames of first projection images to form a first projection image pair, and the imaging angle difference between the first projection image A and the first projection image B is greater than an angle threshold, wherein the first projection image A and the first projection image B have w identical markers, and these w identical markers are used as w first markers, and w is greater than or equal to the second threshold.

[0095] Although the nominal parameters of the imaging system are unknown, since the imaging system moves on a predetermined orbit, the relative rotation and translation matrix between the imaging systems when the first projection image A and the first projection image B are imaged can be determined based on the imaging position of each frame of the first projection image and the motion trajectory of the imaging system on the predetermined orbit; then, the spatial coordinates of the w first markers are determined according to the pixel coordinates of the w first markers in the first projection image A and the first projection image B respectively and the relative rotation and translation matrix; the initial imaging geometric relationship of the first projection image A is determined according to the pixel coordinates of the w first markers in the first projection image A and the spatial coordinates of the w first markers; the initial imaging geometric relationship of the projection image B is determined according to the pixel coordinates of the w first markers in the first projection image B and the spatial coordinates of the w first markers.

[0096] In this way, the initial imaging geometric relationship of the two frames of first projection images can be obtained based on the triangulation intersection method. After obtaining the first projection images with the initial imaging geometric relationship, one frame can be selected from the remaining first projection images with unknown imaging geometric relationships, and one frame can be selected from the first projection images with known imaging geometric relationships to form a new projection image pair. The two frames of first projection images have the same markers, and the number of markers with known spatial coordinates in the same markers is greater than or equal to a first threshold. In this way, based on the PNP method, the initial imaging geometric relationship of the first projection images with unknown imaging geometric relationships can be directly obtained. If there is a marker with unknown spatial coordinates among the same markers in the two frames of first projection images, the spatial coordinates of the marker with unknown spatial coordinates can be determined based on the initial imaging geometric relationship of the two frames of first projection images and the pixel coordinates of the marker with unknown spatial coordinates in the two frames of first projection images respectively. By repeating this process in sequence, the initial imaging geometric relationship corresponding to each frame of first projection images and the spatial coordinates of the marker in each frame of first projection images can be obtained.

[0097] Method 5: The nominal parameters of the imaging system are unknown, and the number of markers with known spatial coordinates in the partial projection image is greater than or equal to a first threshold.

[0098] Exemplarily, the spatial coordinates of some markers are known, which results in the number of markers with known spatial coordinates in some projection images being greater than or equal to a first threshold, and the number of markers with known spatial coordinates in another part of the projection images being less than the first threshold. Therefore, for the partially known case, a target projection image is obtained from multiple frames of projection images, wherein the number of markers with known spatial coordinates in the target projection image is greater than or equal to the first threshold. Based on the spatial coordinates and pixel coordinates of the markers with known spatial coordinates and the above formula (4), the initial imaging geometric relationship of the target projection image can be obtained.

[0099] After determining the initial imaging geometric relationship of the target projection image, the target projection image can be moved into a projection image set with a known imaging geometric relationship, and the remaining projection images except the target projection image can be moved into a projection image set with an unknown imaging geometric relationship, and multiple pose estimation operations can be performed, that is, the projection images in the projection image set with a known imaging geometric relationship and the projection images with an unknown imaging geometric relationship are used to re-form a projection image pair; based on the 2D-3D pose estimation method, the imaging geometric relationship of the projection images in the projection image set with an unknown imaging geometric relationship is estimated to obtain the initial imaging geometric relationship of the first projection image of each frame.

[0100] The i-th pose estimation operation in the above multiple pose estimation operations includes the following steps:

[0101] From the projected image set h i-1 Select the first projection image A from the projection image set w i-1 The first projection image B is selected from the first projection image A and the first projection image B, wherein the first projection image A and the first projection image B have p identical markers, and the p identical markers are used as p second markers, wherein the projection image set h i-1 and the projected image set w i-1 To perform the i-1th pose estimation operation, the projection image set h i It is composed of projection images with known imaging geometric relationships in multiple frames of first projection images; the projection image set w i Including the projection image set h in the multi-frame projection image i All projection images except i It is composed of projection images with unknown imaging geometry (mainly unknown external parameters) in multiple frames of projection images. When i = 1, the projection images contained in the projection image set h0 are the target projection images, and the projection image set w0 is the remaining projection images in the first projection image of the multiple frames except the target projection image.

[0102] When the number of second markers with known spatial coordinates among the p second markers is greater than or equal to the third threshold, for example, the third threshold can be set to 3, and based on the 2D-3D pose estimation method, the external parameters corresponding to the first projection image B are determined according to the intrinsic parameters of the imaging system, the spatial coordinates of the second markers with known spatial coordinates among the p second markers, and the pixel coordinates of the second markers with known spatial coordinates in the first projection image B.

[0103] So far, the initial imaging geometric relationship of the first projection image B has been obtained, so the first projection image B is removed from the projection image set w i-1 Removed from the projected image set h i-1, and obtain the projection image set h corresponding to the i-th pose estimation operation respectively i and the projected image set w i , that is, moving the projection image with known imaging geometry to the projection image set h i It should be understood that after performing N pose estimation operations, the projected image set w N is an empty set, that is, the initial imaging geometric relationship of the first projection image of each frame is obtained.

[0104] Furthermore, for a second marker whose spatial coordinates are unknown among the p second markers, the spatial coordinates of the second marker can be determined based on the initial imaging geometric relationship between the first projection image A and the first projection image B, thereby determining the spatial coordinates of the p second markers. Therefore, after performing each pose estimation operation, if there is a marker with unknown spatial coordinates among the same markers on the two projection images participating in the pose estimation operation, the spatial coordinates of the marker with unknown spatial coordinates can be calculated based on the imaging geometric relationship obtained by the pose estimation operation. In this way, as the number of pose estimation operations increases, the spatial coordinates of more markers on each frame of the first projection image will be calculated. Therefore, if any marker appears in at least two frames of projection images, the spatial coordinates of the marker on each frame of the first projection image can be calculated after multiple pose estimation operations are performed.

[0105] By way of example, the five processing methods described above can be used to obtain the initial imaging geometry of the first projection image and the spatial coordinates of each of the multiple markers. Furthermore, optimization processing is performed based on the initial imaging geometry corresponding to each frame of the first projection image, the pixel coordinates of the markers in each frame of the first projection image, and the spatial coordinates of each marker to obtain the imaging geometry of each frame of the first projection image.

[0106] For example, the bundle adjustment optimization method is used to optimize the imaging geometric relationship of the first projection image of each frame and the spatial coordinates of the markers on the measured object in the coordinate system of the measured object with high precision.

[0107] Specifically, in the bundle adjustment optimization method, based on the internal parameters, external parameters and spatial coordinates of each marker in the initial imaging geometric relationship of each frame of projection image, the projection of each marker in each frame of the first projection image (the pixel coordinates of the marker in the projection image) is recalculated according to the imaging model, that is, the reprojected image point, and the sum of the distances between the reprojection results and the actual projection results of each marker is minimized as the optimization objective function. For the optimal solution of the objective function, the observation equation and the constraint equation can be linearized by Taylor expansion, and then the correction values of each adjustment parameter can be calculated iteratively step by step. If the algorithm converges, the iteratively calculated correction value will gradually approach zero. When the final correction value is less than the threshold, it is determined that the imaging relationship has been well satisfied, and the optimized imaging geometric relationship and the optimized spatial coordinates of each marker are obtained.

[0108] Specifically, x ij is the actual projection result of the i-th marker among multiple markers in the j-th frame projection image. For the convenience of marking, it is assumed that each marker is visible in all projection images. Therefore, the objective function can be determined to minimize the sum of the squares of the distances between the reprojected image points and the actual projection image points of all markers. It should be understood that the sum of the squares of the distances between the reprojected image points and the actual projection image points of each marker in each frame of the first projection image is first calculated; then, the sum of the squares of the distances of the multiple frames of projection images is used as the objective function. Of course, the absolute value of the difference between the reprojected image points and the actual projection image points of each marker in each frame of the first projection image can also be calculated; then, the sum of the absolute values of the multiple frames of projection images is used as the objective function. This application mainly uses the sum of the squares of the distances as an example of the objective function.

[0109] Among them, the objective function can be expressed by formula (5):

[0110]

[0111] Where m is the number of multiple markers, n is the number of multiple frame projection images, and x ij and They represent the actual projected image point and the reprojected image point of the i-th marker in the j-th frame projection image, d(x, y) is the Euclidean distance between the two image points x and y represented by non-homogeneous coordinates, and k represents the column vector composed of the intrinsic parameters corresponding to the projection image. j The column vector of the external parameters corresponding to the j-th frame projection image, b i is a column vector consisting of the spatial coordinates of the i-th marker.

[0112] Furthermore, since multiple frames of first projection images are all generated by the same imaging system, the intrinsic parameters on the multiple frames of first projection images are the same, the above-mentioned objective function has a special parameter division form, and the corresponding normal equation has a special sparse block form. The sparse LM bundle method indirect adjustment in the form of common internal parameter multi-view object points can be used to optimize the intrinsic parameters, extrinsic parameters and spatial coordinates of each marker of each frame projection. The intrinsic parameters, extrinsic parameters and spatial coordinates of each marker of each frame of the first projection image when the above-mentioned objective function takes the minimum value are used as the imaging geometric relationship of each frame of the first projection image and the spatial coordinates of each marker. The above-mentioned process of determining the objective function by minimizing the sum of the squares of the distances between the reprojected image points and the actual projection image points of all markers can be performed both on the image side and on the object side.

[0113] During the actual optimization calculation process, the parameters involved in the optimization iteration can be different. For example, when the intrinsic parameters and / or the spatial coordinates of the markers are accurate, the intrinsic parameters and / or the spatial coordinates of the markers can be excluded from the optimization calculation. The optimization objective function here can have different specific forms. For example, the sum of squared distances can be replaced by the sum of absolute distances.

[0114] It should be understood that the above-mentioned method of using all the first projection images for optimization is given. In actual applications, some first projection images in multiple frames of first projection images can also be used for optimization. The optimization method is similar to the optimization method using all the first projection images and will not be described again.

[0115] It should be noted that when the spatial positional relationships or relative distances of two or more markers in multiple marker groups are known, these known conditional relationships can be used as one or more simultaneous constraints of the optimization objective function and jointly solved. This can make the optimal solution of the optimization process more stable and more accurate. Optionally, the CT imaging system has relatively precise special states for the imaging geometry, such as the state values of the initial and / or final positions of the CT imaging system. Using these special state values as simultaneous constraints of the optimization objective function can also make the optimization process more stable and more accurate.

[0116] 104 : Determine an imaging geometric relationship corresponding to the multiple frames of second projection images in each group of second projection images according to pixel coordinates of the marker in the multiple frames of second projection images in each group of second projection images.

[0117] The imaging geometric relationship corresponding to any one frame of the second projection images in each group of second projection images is the relative imaging geometric relationship between the object under test and the CT imaging system when acquiring the frame of the second projection image.

[0118] For each set of second projection images, the imaging geometry of any one second projection image within that set is obtained in a similar manner to the imaging geometry of each first projection image frame described above, and will not be further described. In practice, since the spatial coordinates of the markers in the filled state remain unchanged relative to the spatial coordinates of the markers in the masked state, the spatial coordinates of the multiple markers can be considered known. In other words, the spatial coordinates of the markers in any second projection image within any set of second projection images are also known.

[0119] Therefore, when the nominal parameters of the imaging system are known, the initial imaging geometric relationship of any frame of the second projection image can be obtained by the above-mentioned method 1, and then the imaging geometric relationship of each frame of the second projection image can be determined by the above-mentioned optimization method; when the nominal parameters of the imaging system are unknown, the initial imaging geometric relationship of any frame of the second projection image can be obtained by the above-mentioned method 3, and then the imaging geometric relationship of each frame of the second projection image can be determined by the above-mentioned optimization method.

[0120] It should be noted that even if the spatial coordinates of the markers in any frame of the second projection image in any set of second projection images are all known, they can be regarded as unknown. According to the above-mentioned methods 2 and 4, the initial imaging geometric relationship of any frame of the second projection image can be determined, and then the imaging geometric relationship of each frame of the second projection image can be determined through the above-mentioned optimization method.

[0121] 105: Perform CT three-dimensional image reconstruction on the multiple frames of first projection images according to the imaging geometric relationships corresponding to the multiple frames of first projection images, to obtain a first CT three-dimensional image.

[0122] For example, after determining the imaging geometric relationship corresponding to each frame of the first projection image, each frame of the first projection image and the imaging geometric relationship corresponding to each frame of the first projection image can be used as input data of the CT reconstruction algorithm. The multiple frames of the first projection images are processed by the CT reconstruction algorithm to realize three-dimensional reconstruction of the CT image of the object under test and obtain the first CT three-dimensional image.

[0123] 106 : Perform CT three-dimensional image reconstruction on the multiple frames of second projection images in each group of second projection images according to the imaging geometric relationship corresponding to the multiple frames of second projection images in each group of second projection images to obtain at least one second CT three-dimensional image.

[0124] Similarly, after determining the imaging geometric relationship corresponding to each frame of the second projection image in each group of second projection images, each frame of the second projection image in each group of second projection images and the imaging geometric relationship of the frame of the second projection image can be used as input data of the reconstruction algorithm. The multiple frames of the second projection images in each group of second projection images are processed by the CT reconstruction algorithm to achieve three-dimensional reconstruction of the CT image of the object under test, thereby obtaining a second CT three-dimensional image corresponding to each group of second projection images, and further obtaining at least one second CT three-dimensional image.

[0125] 107: Obtain at least one three-dimensional digital subtraction angiography image based on the first three-dimensional CT image and the at least one second three-dimensional CT image.

[0126] Exemplarily, the spatial coordinates of each voxel in the first CT three-dimensional image are obtained, wherein the spatial coordinates of each voxel in the first CT three-dimensional image are spatial coordinates in a coordinate system with a fixed marker of the object to be measured, that is, the position of each voxel in the first CT three-dimensional image relative to the origin of the coordinate system of the object to be measured; the spatial coordinates of each voxel in each second CT three-dimensional image are obtained, wherein the spatial coordinates of each voxel in each second CT three-dimensional image are spatial coordinates in a coordinate system with a fixed marker of the object to be measured, that is, the position of each voxel in the second CT three-dimensional image relative to the origin of the coordinate system of the object to be measured; based on the spatial coordinates of each voxel in the first CT three-dimensional image and the spatial coordinates of each voxel in each second CT three-dimensional image, the corresponding voxels in the first CT three-dimensional image and each second CT three-dimensional image are determined, that is, the voxels with the same spatial coordinates are regarded as corresponding voxels; the grayscale values of the corresponding voxels in each second CT three-dimensional image are subtracted from the grayscale values of the corresponding voxels in the first CT three-dimensional image to obtain at least one three-dimensional digital subtraction angiography image.

[0127] It can be understood that when only one set of second projection images is acquired, a three-dimensional digital subtraction angiography image can be acquired, and based on this three-dimensional digital subtraction angiography image, the structure, morphology, size, etc. of the blood vessel can be observed; when multiple sets of second projection images are acquired, multiple three-dimensional digital subtraction angiography images can be acquired, that is, a three-dimensional digital subtraction angiography image sequence is acquired, and based on this three-dimensional digital subtraction angiography image sequence, the flow state of the contrast agent in the blood vessel and the surgical status of the medical interventional treatment can be displayed.

[0128] It can be seen that in the embodiment of the present application, the CT imaging system captures the object to be measured with a marker, and uses the pixel coordinates of the marker in the image and the spatial coordinates of the marker to obtain the imaging geometric relationship between the CT imaging system and the object to be measured with high precision using camera measurement technology. Since the coordinate system is established on the object to be measured, the imaging geometric relationship automatically includes the position and posture state of the imaging system, including various errors such as vibration and shaking. As long as the relative relationship between the markers of the object to be measured set in the two shooting and projection links remains unchanged, the obtained CT three-dimensional imaging result of the object to be measured is the same object in the same coordinate system, which is highly accurately matched and aligned, effectively eliminating rigid motion or changes during each CT operating state, and improving the alignment accuracy of the CT three-dimensional image in the mask state and the three-dimensional CT image in the filling state.

[0129] In one embodiment of the present application, when the CT imaging system operates in both the mask state and the filling state modes, and emits X-rays at the same position, that is, when multiple first imaging angles and multiple second imaging angles are identical in one-to-one correspondence, it can be understood that after determining the imaging geometric relationship corresponding to each frame of the first projection image, there is no need to further determine the imaging geometric relationship with each frame of the second projection image in each group of second projection images. The initial imaging geometric relationship of each frame of the first projection image can be used as the initial imaging geometric relationship of the second projection image corresponding to the frame of the first projection image, and directly participate in the subsequent optimization calculation. Similarly, only the initial imaging geometric relationship of each frame of the second projection image in a group of second projection images can be determined, without determining the imaging geometric relationship of other projection images. The initial imaging geometric relationship of each frame of the second projection image can be used as the initial imaging geometric relationship of the projection image corresponding to it, and directly participate in the subsequent optimization calculation to ensure high precision.

[0130] See Figure 4 , Figure 4 The present invention provides a block diagram of the functional units of a 3D digital subtraction angiography device. The 3D digital subtraction angiography device 400 includes: an acquisition unit 401 and a processing unit 402, wherein:

[0131] An acquisition unit 401 is configured to acquire multiple frames of first projection images, wherein the multiple frames of first projection images are obtained by a CT imaging system emitting X-rays to an object under test at multiple first imaging angles, with a blood vessel in a masked state, the object under test being provided with multiple markers, and the CT imaging system moving on a predetermined track; and acquire at least one set of second projection images, wherein each set of second projection images includes multiple frames of second projection images, and the multiple frames of second projection images in each set of second projection images are obtained by the CT imaging system emitting X-rays to the object under test at multiple second imaging angles, with the blood vessel in a filled state.

[0132] The processing unit 402 is configured to determine an imaging geometric relationship corresponding to each frame of the first projection image according to pixel coordinates of the marker in each frame of the first projection image;

[0133] determining, according to pixel coordinates of the markers in the plurality of frames of second projection images in each group of second projection images, imaging geometric relationships corresponding to the plurality of frames of second projection images in the plurality of frames of second projection images;

[0134] performing CT three-dimensional image reconstruction on the multiple frames of first projection images according to imaging geometric relationships respectively corresponding to the multiple frames of first projection images to obtain a first CT three-dimensional image;

[0135] performing CT three-dimensional image reconstruction on the multiple frames of second projection images in each group of second projection images according to imaging geometric relationships corresponding to the multiple frames of second projection images in each group of second projection images to obtain at least one second CT three-dimensional image;

[0136] At least one three-dimensional digital subtraction angiography image is obtained based on the first CT three-dimensional image and the at least one second CT three-dimensional image.

[0137] In some possible implementations, in obtaining at least one three-dimensional digital subtraction angiography image based on the first three-dimensional CT image and the at least one second three-dimensional CT image, the processing unit 402 is specifically configured to:

[0138] Acquire the spatial coordinates of each voxel in the first CT three-dimensional image, wherein the spatial coordinates of each voxel in the first CT three-dimensional image are spatial coordinates in the coordinate system of the object being measured;

[0139] Acquiring the spatial coordinates of each voxel in each second CT three-dimensional image, wherein the spatial coordinates of each voxel in each second CT three-dimensional image are spatial coordinates in the coordinate system of the object being measured;

[0140] determining corresponding voxels in the first CT three-dimensional image and each of the second CT three-dimensional images according to the spatial coordinates of each voxel in the first CT three-dimensional image and the spatial coordinates of each voxel in each of the second CT three-dimensional images;

[0141] The at least one three-dimensional digital subtraction angiography image is obtained by subtracting the grayscale values of the corresponding voxels in each second CT three-dimensional image and the first CT three-dimensional image.

[0142] In some possible implementations, in determining the imaging geometric relationship corresponding to each frame of the first projection image based on the pixel coordinates of the marker in each frame of the first projection image, the processing unit 402 is specifically configured to:

[0143] determining an initial imaging geometric relationship corresponding to each frame of the first projection image according to a movement position and posture of the CT imaging system on the predetermined track;

[0144] The imaging geometric relationship of each frame of the first projection image is determined according to the initial imaging geometric relationship of each frame of the first projection image and the pixel coordinates of the marker in each frame of the first projection image.

[0145] In some possible implementations, when the nominal parameters of the imaging system are known and a marker with unknown spatial coordinates exists in k frames of the multiple frames of first projection images, in determining the imaging geometric relationship of each frame of the first projection images based on the initial imaging geometric relationship of each frame of the first projection images and the pixel coordinates of the marker in each frame of the first projection images, the processing unit 402 is specifically configured to:

[0146] For a first projection image A, selecting a first projection image B from the multiple frames of first projection images, wherein the first projection image A is any one of the k frames of first projection images, the first projection image A and the first projection image B are different projection images, and the first projection image A and the first projection image B have p identical markers, and the p markers include a marker with unknown spatial coordinates in the first projection image A;

[0147] Obtaining spatial coordinates of markers with unknown spatial coordinates among the p markers based on the initial imaging geometric relationship of the first projection image A, the initial imaging geometric relationship of the first projection image B, and the pixel coordinates of the p markers in the first projection image A and the first projection image B, respectively;

[0148] Optimization processing is performed based on the initial imaging geometric relationship corresponding to each frame of the first projection image, the pixel coordinates of the marker in each frame of the first projection image, and the spatial coordinates of the marker in each frame of the first projection image to obtain the imaging geometric relationship corresponding to each frame of the first projection image.

[0149] In some possible implementations, when the nominal parameters of the imaging system are known and a marker with unknown spatial coordinates exists in k frames of the multiple frames of first projection images, in determining the imaging geometric relationship of each frame of the first projection images based on the initial imaging geometric relationship of each frame of the first projection images and the pixel coordinates of the marker in each frame of the first projection images, the processing unit 402 is specifically configured to:

[0150] For a first projection image A, selecting a first projection image B from the multiple frames of first projection images, wherein the first projection image A is any one of the k frames of first projection images, the first projection image A and the first projection image B are different projection images, and the first projection image A and the first projection image B have p identical markers, and the p markers include a marker with unknown spatial coordinates;

[0151] Determining, according to the motion trajectory, position, and posture of the imaging system, a relative rotation and translation matrix between the imaging systems when the first projection image A and the first projection image B are formed;

[0152] Obtaining the spatial coordinates of the markers with unknown spatial coordinates among the p markers according to the relative rotation and translation matrix and the pixel coordinates of the p markers in the first projection image A and the first projection image B respectively;

[0153] Optimization processing is performed based on the initial imaging geometric relationship corresponding to each frame of the first projection image, the pixel coordinates of the marker in each frame of the first projection image, and the spatial coordinates of the marker in each frame of the first projection image to obtain the imaging geometric relationship corresponding to each frame of the first projection image.

[0154] In some possible implementations, when the nominal parameters of the imaging system are unknown and the number of markers with known spatial coordinates in each frame of the first projection image is less than a first threshold, in determining the initial imaging geometric relationship corresponding to each frame of the first projection image based on the motion position and posture of the imaging system on the predetermined track, the processing unit 402 is specifically configured to:

[0155] determining, according to the motion position and posture of the imaging system, a relative rotation and translation matrix between a first projection image A and a first projection image B during imaging, wherein the first projection image A and the first projection image B are two frames of projection images having w identical markers in the multiple frames of first projection images, and w is greater than or equal to a second threshold;

[0156] Using the w identical markers as w first markers;

[0157] determining the spatial coordinates of the w first markers according to the pixel coordinates of the w first markers in the first projection image A and the first projection image B, respectively, and the relative rotation and translation matrix;

[0158] determining an initial imaging geometric relationship of the first projection image A according to the pixel coordinates of the w first markers in the first projection image A and the spatial coordinates of the w first markers;

[0159] determining an initial imaging geometric relationship of the first projection image B according to the pixel coordinates of the w first markers in the first projection image B and the spatial coordinates of the w first markers;

[0160] According to the spatial coordinates of the w first markers, the initial imaging geometric relationship of the first projection image A or the initial imaging geometric relationship of the first projection image B, the initial imaging geometric relationship of each frame of the first projection image and the spatial coordinates of the markers in each frame of the first projection image are determined.

[0161] In some possible implementations, in determining the imaging geometric relationship of each frame of the first projection image based on the initial imaging geometric relationship corresponding to each frame of the first projection image and the pixel coordinates of the marker in each frame of the first projection image, the processing unit 402 is specifically configured to:

[0162] Optimization processing is performed based on the initial imaging geometric relationship corresponding to each frame of the first projection image, the pixel coordinates of the marker in each frame of the first projection image, and the spatial coordinates of the marker in each frame of the first projection image to obtain the imaging geometric relationship corresponding to each frame of the first projection image.

[0163] See Figure 5 , Figure 5 This is a schematic diagram of the structure of a three-dimensional digital subtraction angiography device provided in an embodiment of the present application. Figure 5 As shown, the electronic device 500 includes a transmitter 501, a processor 502, and a memory 503. These are connected via a bus 504. The memory 503 is used to store computer programs and data, and can transmit the data stored in the memory 503 to the processor 502.

[0164] The processor 502 is configured to read the computer program in the memory 503 and perform the following operations:

[0165] Controlling the emitter 501 to emit X-rays toward the object to be measured to obtain multiple frames of first projection images, wherein the multiple frames of first projection images are obtained by emitting X-rays toward the object to be measured at multiple first imaging angles with the blood vessels in a masked state, wherein the CT imaging system moves along a predetermined track and has multiple markers disposed on the object to be measured;

[0166] Controlling the emitter 501 to emit X-rays toward the object to be measured to obtain at least one set of second projection images, wherein each set of second projection images includes multiple frames of second projection images, and the multiple frames of second projection images in each set of second projection images are obtained by the CT imaging system emitting X-rays toward the object to be measured at multiple second imaging angles when the blood vessels are in a filled state;

[0167] determining an imaging geometric relationship corresponding to each frame of the first projection image according to pixel coordinates of a marker in each frame of the first projection image;

[0168] determining, according to pixel coordinates of the markers in the plurality of frames of second projection images in each group of second projection images, imaging geometric relationships corresponding to the plurality of frames of second projection images in the plurality of frames of second projection images;

[0169] performing CT three-dimensional image reconstruction on the multiple frames of first projection images according to imaging geometric relationships respectively corresponding to the multiple frames of first projection images to obtain a first CT three-dimensional image;

[0170] performing CT three-dimensional image reconstruction on the multiple frames of second projection images in each group of second projection images according to imaging geometric relationships corresponding to the multiple frames of second projection images in each group of second projection images to obtain at least one second CT three-dimensional image;

[0171] At least one three-dimensional digital subtraction angiography image is obtained based on the first CT three-dimensional image and the at least one second CT three-dimensional image.

[0172] The specific implementation functions of the processor 502 are similar to those of the processing unit 402 and will not be described again.

[0173] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. The computer program is executed by a processor to implement part or all of the steps of any three-dimensional digital subtraction angiography method described in the above method embodiments.

[0174] An embodiment of the present application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute part or all of the steps of any three-dimensional digital subtraction angiography method described in the above method embodiments.

[0175] It should be noted that for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in this specification are all optional embodiments, and the actions and modules involved are not necessarily required by this application.

[0176] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0177] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0178] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0179] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or in the form of software program modules.

[0180] If the integrated unit is implemented in the form of a software program module and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a memory, including a number of instructions for enabling a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: various media that can store program codes, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0181] Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program. The program can be stored in a computer-readable memory, and the memory can include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0182] The above is a detailed introduction to the embodiments of the present application. Specific examples are used herein to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of the present application. At the same time, for those skilled in the art, according to the idea of the present application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A three-dimensional digital subtraction angiography method, characterized in that: include: Acquiring a plurality of frames of first projection images, wherein the plurality of frames of first projection images are obtained by emitting X-rays to an object under test at a plurality of first imaging angles, with the blood vessel in a masked state, the object under test being provided with a plurality of markers, and the CT imaging system moving on a predetermined track; Acquire at least one set of second projection images, wherein each set of second projection images includes multiple frames of second projection images, and the multiple frames of second projection images in each set of second projection images are obtained by the CT imaging system emitting X-rays to the object under test at multiple second imaging angles when the blood vessel is in a filled state; Determining an imaging geometric relationship corresponding to each frame of the first projection image according to the pixel coordinates of the marker in each frame of the first projection image; when the nominal parameters of the imaging system are known and the spatial coordinates of the marker in each frame of the first projection image are all known; comprising: determining an initial imaging geometric relationship corresponding to each frame of the first projection image according to the motion position and posture of the CT imaging system on the predetermined track and the nominal parameters; Performing optimization processing based on the initial imaging geometric relationship corresponding to each frame of the first projection image, as well as the pixel coordinates of the markers in each frame of the first projection image and the spatial coordinates of each marker, to obtain the imaging geometric relationship of each frame of the first projection image; determining, according to pixel coordinates of the markers in the plurality of frames of second projection images in each group of second projection images, imaging geometric relationships corresponding to the plurality of frames of second projection images in the plurality of frames of second projection images; Performing CT three-dimensional image reconstruction on the multiple frames of first projection images according to imaging geometric relationships respectively corresponding to the multiple frames of first projection images to obtain a first CT three-dimensional image; performing CT three-dimensional image reconstruction on the multiple frames of second projection images in each group of second projection images according to imaging geometric relationships corresponding to the multiple frames of second projection images in each group of second projection images to obtain at least one second CT three-dimensional image; At least one three-dimensional digital subtraction angiography image is obtained based on the first CT three-dimensional image and the at least one second CT three-dimensional image.

2. A three-dimensional digital subtraction angiography method, characterized in that: include: Acquiring a plurality of frames of first projection images, wherein the plurality of frames of first projection images are obtained by emitting X-rays to an object under test at a plurality of first imaging angles, with the blood vessel in a masked state, the object under test being provided with a plurality of markers, and the CT imaging system moving on a predetermined track; Acquire at least one set of second projection images, wherein each set of second projection images includes multiple frames of second projection images, and the multiple frames of second projection images in each set of second projection images are obtained by the CT imaging system emitting X-rays to the object under test at multiple second imaging angles when the blood vessel is in a filled state; Determining an imaging geometric relationship corresponding to each frame of the first projection image according to pixel coordinates of a marker in each frame of the first projection image; when the nominal parameters of the imaging system are known, and there are markers with unknown spatial coordinates in k frames of the first projection image among the multiple frames of the first projection image; comprising: determining an initial imaging geometric relationship corresponding to each frame of the first projection image according to a movement position and posture of the CT imaging system on the predetermined track; For a first projection image A, selecting a first projection image B from the multiple frames of first projection images, wherein the first projection image A is any one of the k frames of first projection images, the first projection image A and the first projection image B are different projection images, and the first projection image A and the first projection image B have p identical markers, and the p markers include a marker with unknown spatial coordinates in the first projection image A; Obtaining spatial coordinates of markers with unknown spatial coordinates among the p markers based on the initial imaging geometric relationship of the first projection image A, the initial imaging geometric relationship of the first projection image B, and the pixel coordinates of the p markers in the first projection image A and the first projection image B, respectively; Performing optimization processing based on the initial imaging geometric relationship corresponding to each frame of the first projection image, the pixel coordinates of the marker in each frame of the first projection image, and the spatial coordinates of the marker in each frame of the first projection image to obtain the imaging geometric relationship corresponding to each frame of the first projection image; determining, according to pixel coordinates of the markers in the plurality of frames of second projection images in each group of second projection images, imaging geometric relationships corresponding to the plurality of frames of second projection images in the plurality of frames of second projection images; Performing CT three-dimensional image reconstruction on the multiple frames of first projection images according to imaging geometric relationships respectively corresponding to the multiple frames of first projection images to obtain a first CT three-dimensional image; performing CT three-dimensional image reconstruction on the multiple frames of second projection images in each group of second projection images according to imaging geometric relationships corresponding to the multiple frames of second projection images in each group of second projection images to obtain at least one second CT three-dimensional image; At least one three-dimensional digital subtraction angiography image is obtained based on the first CT three-dimensional image and the at least one second CT three-dimensional image.

3. A three-dimensional digital subtraction angiography method, characterized in that: include: Acquiring a plurality of frames of first projection images, wherein the plurality of frames of first projection images are obtained by emitting X-rays to an object under test at a plurality of first imaging angles, with the blood vessel in a masked state, the object under test being provided with a plurality of markers, and the CT imaging system moving on a predetermined track; Acquire at least one set of second projection images, wherein each set of second projection images includes multiple frames of second projection images, and the multiple frames of second projection images in each set of second projection images are obtained by the CT imaging system emitting X-rays to the object under test at multiple second imaging angles when the blood vessel is in a filled state; Determining an imaging geometric relationship corresponding to each frame of the first projection image according to pixel coordinates of a marker in each frame of the first projection image; when the nominal parameters of the imaging system are known, and there are markers with unknown spatial coordinates in k frames of the first projection image among the multiple frames of the first projection image; comprising: determining an initial imaging geometric relationship corresponding to each frame of the first projection image according to a movement position and posture of the CT imaging system on the predetermined track; For a first projection image A, selecting a first projection image B from the multiple frames of first projection images, wherein the first projection image A is any one of the k frames of first projection images, the first projection image A and the first projection image B are different projection images, and the first projection image A and the first projection image B have p identical markers, and the p markers include a marker with unknown spatial coordinates; determining, according to the motion trajectory, position and posture of the imaging system, a relative rotation and translation matrix between the imaging systems when the first projection image A and the first projection image B are formed; Obtaining spatial coordinates of markers with unknown spatial coordinates among the p markers according to the relative rotation and translation matrix and the pixel coordinates of the p markers in the first projection image A and the first projection image B respectively; Performing optimization processing based on the initial imaging geometric relationship corresponding to each frame of the first projection image, the pixel coordinates of the marker in each frame of the first projection image, and the spatial coordinates of the marker in each frame of the first projection image to obtain the imaging geometric relationship corresponding to each frame of the first projection image; determining, according to pixel coordinates of the markers in the plurality of frames of second projection images in each group of second projection images, imaging geometric relationships corresponding to the plurality of frames of second projection images in the plurality of frames of second projection images; Performing CT three-dimensional image reconstruction on the multiple frames of first projection images according to imaging geometric relationships respectively corresponding to the multiple frames of first projection images to obtain a first CT three-dimensional image; performing CT three-dimensional image reconstruction on the multiple frames of second projection images in each group of second projection images according to imaging geometric relationships corresponding to the multiple frames of second projection images in each group of second projection images to obtain at least one second CT three-dimensional image; At least one three-dimensional digital subtraction angiography image is obtained based on the first CT three-dimensional image and the at least one second CT three-dimensional image.

4. A three-dimensional digital subtraction angiography method, characterized in that: include: Acquiring a plurality of frames of first projection images, wherein the plurality of frames of first projection images are obtained by emitting X-rays to an object under test at a plurality of first imaging angles, with the blood vessel in a masked state, the object under test being provided with a plurality of markers, and the CT imaging system moving on a predetermined track; Acquire at least one set of second projection images, wherein each set of second projection images includes multiple frames of second projection images, and the multiple frames of second projection images in each set of second projection images are obtained by the CT imaging system emitting X-rays to the object under test at multiple second imaging angles when the blood vessel is in a filled state; Determining, based on pixel coordinates of markers in each frame of the first projection image, an imaging geometric relationship corresponding to each frame of the first projection image; when nominal parameters of the imaging system are unknown and the number of markers with known spatial coordinates in each frame of the first projection image is less than a first threshold; comprising: determining, according to the motion position and posture of the imaging system, a relative rotation and translation matrix between a first projection image A and a first projection image B during imaging, wherein the first projection image A and the first projection image B are two frames of projection images having w identical markers in the multiple frames of first projection images, and w is greater than or equal to a second threshold; Using the w identical markers as w first markers; determining the spatial coordinates of the w first markers according to the pixel coordinates of the w first markers in the first projection image A and the first projection image B, respectively, and the relative rotation and translation matrix; determining an initial imaging geometric relationship of the first projection image A according to the pixel coordinates of the w first markers in the first projection image A and the spatial coordinates of the w first markers; determining an initial imaging geometric relationship of the first projection image B according to the pixel coordinates of the w first markers in the first projection image B and the spatial coordinates of the w first markers; Determining the initial imaging geometric relationship of each frame of the first projection image and the spatial coordinates of the markers in each frame of the first projection image according to the spatial coordinates of the w first markers, the initial imaging geometric relationship of the first projection image A or the initial imaging geometric relationship of the first projection image B; Performing optimization processing based on the initial imaging geometric relationship corresponding to each frame of the first projection image, the pixel coordinates of the marker in each frame of the first projection image, and the spatial coordinates of the marker in each frame of the first projection image to obtain the imaging geometric relationship corresponding to each frame of the first projection image; determining, according to pixel coordinates of the markers in the plurality of frames of second projection images in each group of second projection images, imaging geometric relationships corresponding to the plurality of frames of second projection images in the plurality of frames of second projection images; Performing CT three-dimensional image reconstruction on the multiple frames of first projection images according to imaging geometric relationships respectively corresponding to the multiple frames of first projection images to obtain a first CT three-dimensional image; performing CT three-dimensional image reconstruction on the multiple frames of second projection images in each group of second projection images according to imaging geometric relationships corresponding to the multiple frames of second projection images in each group of second projection images to obtain at least one second CT three-dimensional image; At least one three-dimensional digital subtraction angiography image is obtained based on the first CT three-dimensional image and the at least one second CT three-dimensional image.

5. The method according to any one of claims 1 to 4, characterized in that Obtaining at least one three-dimensional digital subtraction angiography image based on the first three-dimensional CT image and the at least one second three-dimensional CT image includes: Acquire the spatial coordinates of each voxel in the first CT three-dimensional image, wherein the spatial coordinates of each voxel in the first CT three-dimensional image are spatial coordinates in the coordinate system of the object being measured; Acquiring the spatial coordinates of each voxel in each second CT three-dimensional image, wherein the spatial coordinates of each voxel in each second CT three-dimensional image are spatial coordinates in the coordinate system of the object being measured; determining corresponding voxels in the first CT three-dimensional image and each of the second CT three-dimensional images according to the spatial coordinates of each voxel in the first CT three-dimensional image and the spatial coordinates of each voxel in each of the second CT three-dimensional images; The at least one three-dimensional digital subtraction angiography image is obtained by subtracting the grayscale values of the corresponding voxels in each second CT three-dimensional image and the first CT three-dimensional image.

6. A three-dimensional digital subtraction angiography device, characterized in that: include: an acquisition unit, configured to acquire a plurality of frames of first projection images, wherein the plurality of frames of first projection images are obtained by a CT imaging system emitting X-rays to an object under test at a plurality of first imaging angles, with the blood vessel in a masked state, the object under test being provided with a plurality of markers, and the CT imaging system moving on a predetermined track; Acquire at least one set of second projection images, wherein each set of second projection images includes multiple frames of second projection images, and the multiple frames of second projection images in each set of second projection images are obtained by the CT imaging system emitting X-rays to the object under test at multiple second imaging angles when the blood vessel is in a filled state; A processing unit, configured to determine, based on the pixel coordinates of the marker in each frame of the first projection image, an imaging geometric relationship corresponding to each frame of the first projection image; when the nominal parameters of the imaging system are known and the spatial coordinates of the marker in each frame of the first projection image are all known; comprising: determining an initial imaging geometric relationship corresponding to each frame of the first projection image according to the motion position and posture of the CT imaging system on the predetermined track and the nominal parameters; Performing optimization processing based on the initial imaging geometric relationship corresponding to each frame of the first projection image, as well as the pixel coordinates of the markers in each frame of the first projection image and the spatial coordinates of each marker, to obtain the imaging geometric relationship of each frame of the first projection image; determining, according to pixel coordinates of the markers in the plurality of frames of second projection images in each group of second projection images, imaging geometric relationships corresponding to the plurality of frames of second projection images in the plurality of frames of second projection images; Performing CT three-dimensional image reconstruction on the multiple frames of first projection images according to imaging geometric relationships respectively corresponding to the multiple frames of first projection images to obtain a first CT three-dimensional image; performing CT three-dimensional image reconstruction on the multiple frames of second projection images in each group of second projection images according to imaging geometric relationships corresponding to the multiple frames of second projection images in each group of second projection images to obtain at least one second CT three-dimensional image; At least one three-dimensional digital subtraction angiography image is obtained based on the first CT three-dimensional image and the at least one second CT three-dimensional image.

7. A three-dimensional digital subtraction angiography device, characterized in that: include: an acquisition unit, configured to acquire a plurality of frames of first projection images, wherein the plurality of frames of first projection images are obtained by a CT imaging system emitting X-rays to an object under test at a plurality of first imaging angles, with the blood vessel in a masked state, the object under test being provided with a plurality of markers, and the CT imaging system moving on a predetermined track; Acquire at least one set of second projection images, wherein each set of second projection images includes multiple frames of second projection images, and the multiple frames of second projection images in each set of second projection images are obtained by the CT imaging system emitting X-rays to the object under test at multiple second imaging angles when the blood vessel is in a filled state; A processing unit, configured to determine an imaging geometric relationship corresponding to each frame of the first projection image based on pixel coordinates of a marker in each frame of the first projection image; when the nominal parameters of the imaging system are known and there are markers with unknown spatial coordinates in k frames of the first projection image among the multiple frames of the first projection image; comprising: determining an initial imaging geometric relationship corresponding to each frame of the first projection image according to a movement position and posture of the CT imaging system on the predetermined track; For a first projection image A, selecting a first projection image B from the multiple frames of first projection images, wherein the first projection image A is any one of the k frames of first projection images, the first projection image A and the first projection image B are different projection images, and the first projection image A and the first projection image B have p identical markers, and the p markers include a marker with unknown spatial coordinates in the first projection image A; Obtaining spatial coordinates of markers with unknown spatial coordinates among the p markers based on the initial imaging geometric relationship of the first projection image A, the initial imaging geometric relationship of the first projection image B, and the pixel coordinates of the p markers in the first projection image A and the first projection image B, respectively; Performing optimization processing based on the initial imaging geometric relationship corresponding to each frame of the first projection image, the pixel coordinates of the marker in each frame of the first projection image, and the spatial coordinates of the marker in each frame of the first projection image to obtain the imaging geometric relationship corresponding to each frame of the first projection image; determining, according to pixel coordinates of the markers in the plurality of frames of second projection images in each group of second projection images, imaging geometric relationships corresponding to the plurality of frames of second projection images in the plurality of frames of second projection images; Performing CT three-dimensional image reconstruction on the multiple frames of first projection images according to imaging geometric relationships respectively corresponding to the multiple frames of first projection images to obtain a first CT three-dimensional image; performing CT three-dimensional image reconstruction on the multiple frames of second projection images in each group of second projection images according to imaging geometric relationships corresponding to the multiple frames of second projection images in each group of second projection images to obtain at least one second CT three-dimensional image; At least one three-dimensional digital subtraction angiography image is obtained based on the first CT three-dimensional image and the at least one second CT three-dimensional image.

8. A three-dimensional digital subtraction angiography device, characterized in that: include: an acquisition unit, configured to acquire a plurality of frames of first projection images, wherein the plurality of frames of first projection images are obtained by a CT imaging system emitting X-rays to an object under test at a plurality of first imaging angles, with the blood vessel in a masked state, the object under test being provided with a plurality of markers, and the CT imaging system moving on a predetermined track; Acquire at least one set of second projection images, wherein each set of second projection images includes multiple frames of second projection images, and the multiple frames of second projection images in each set of second projection images are obtained by the CT imaging system emitting X-rays to the object under test at multiple second imaging angles when the blood vessel is in a filled state; A processing unit, configured to determine an imaging geometric relationship corresponding to each frame of the first projection image based on pixel coordinates of a marker in each frame of the first projection image; when the nominal parameters of the imaging system are known and there are markers with unknown spatial coordinates in k frames of the first projection image among the multiple frames of the first projection image; comprising: determining an initial imaging geometric relationship corresponding to each frame of the first projection image according to a movement position and posture of the CT imaging system on the predetermined track; For a first projection image A, selecting a first projection image B from the multiple frames of first projection images, wherein the first projection image A is any one of the k frames of first projection images, the first projection image A and the first projection image B are different projection images, and the first projection image A and the first projection image B have p identical markers, and the p markers include a marker with unknown spatial coordinates; determining, according to the motion trajectory, position and posture of the imaging system, a relative rotation and translation matrix between the imaging systems when the first projection image A and the first projection image B are formed; Obtaining spatial coordinates of markers with unknown spatial coordinates among the p markers according to the relative rotation and translation matrix and the pixel coordinates of the p markers in the first projection image A and the first projection image B respectively; Performing optimization processing based on the initial imaging geometric relationship corresponding to each frame of the first projection image, the pixel coordinates of the marker in each frame of the first projection image, and the spatial coordinates of the marker in each frame of the first projection image to obtain the imaging geometric relationship corresponding to each frame of the first projection image; determining, according to pixel coordinates of the markers in the plurality of frames of second projection images in each group of second projection images, imaging geometric relationships corresponding to the plurality of frames of second projection images in the plurality of frames of second projection images; Performing CT three-dimensional image reconstruction on the multiple frames of first projection images according to imaging geometric relationships respectively corresponding to the multiple frames of first projection images to obtain a first CT three-dimensional image; performing CT three-dimensional image reconstruction on the multiple frames of second projection images in each group of second projection images according to imaging geometric relationships corresponding to the multiple frames of second projection images in each group of second projection images to obtain at least one second CT three-dimensional image; At least one three-dimensional digital subtraction angiography image is obtained based on the first CT three-dimensional image and the at least one second CT three-dimensional image.

9. A three-dimensional digital subtraction angiography device, characterized in that: include: an acquisition unit, configured to acquire a plurality of frames of first projection images, wherein the plurality of frames of first projection images are obtained by a CT imaging system emitting X-rays to an object under test at a plurality of first imaging angles, with the blood vessel in a masked state, the object under test being provided with a plurality of markers, and the CT imaging system moving on a predetermined track; Acquire at least one set of second projection images, wherein each set of second projection images includes multiple frames of second projection images, and the multiple frames of second projection images in each set of second projection images are obtained by the CT imaging system emitting X-rays to the object under test at multiple second imaging angles when the blood vessel is in a filled state; A processing unit, configured to determine, based on pixel coordinates of markers in each frame of the first projection image, an imaging geometric relationship corresponding to each frame of the first projection image; when the nominal parameters of the imaging system are unknown and the number of markers with known spatial coordinates in each frame of the first projection image is less than a first threshold; comprising: determining, according to the motion position and posture of the imaging system, a relative rotation and translation matrix between a first projection image A and a first projection image B during imaging, wherein the first projection image A and the first projection image B are two frames of projection images having w identical markers in the multiple frames of first projection images, and w is greater than or equal to a second threshold; Using the w identical markers as w first markers; determining the spatial coordinates of the w first markers according to the pixel coordinates of the w first markers in the first projection image A and the first projection image B, respectively, and the relative rotation and translation matrix; determining an initial imaging geometric relationship of the first projection image A according to the pixel coordinates of the w first markers in the first projection image A and the spatial coordinates of the w first markers; determining an initial imaging geometric relationship of the first projection image B according to the pixel coordinates of the w first markers in the first projection image B and the spatial coordinates of the w first markers; Determining the initial imaging geometric relationship of each frame of the first projection image and the spatial coordinates of the markers in each frame of the first projection image according to the spatial coordinates of the w first markers, the initial imaging geometric relationship of the first projection image A or the initial imaging geometric relationship of the first projection image B; Performing optimization processing based on the initial imaging geometric relationship corresponding to each frame of the first projection image, the pixel coordinates of the marker in each frame of the first projection image, and the spatial coordinates of the marker in each frame of the first projection image to obtain the imaging geometric relationship corresponding to each frame of the first projection image; determining, according to pixel coordinates of the markers in the plurality of frames of second projection images in each group of second projection images, imaging geometric relationships corresponding to the plurality of frames of second projection images in the plurality of frames of second projection images; performing CT three-dimensional image reconstruction on the multiple frames of first projection images according to imaging geometric relationships respectively corresponding to the multiple frames of first projection images to obtain a first CT three-dimensional image; performing CT three-dimensional image reconstruction on the multiple frames of second projection images in each group of second projection images according to imaging geometric relationships corresponding to the multiple frames of second projection images in each group of second projection images to obtain at least one second CT three-dimensional image; At least one three-dimensional digital subtraction angiography image is obtained based on the first CT three-dimensional image and the at least one second CT three-dimensional image.

10. An electronic device, characterized in that: include: A processor and a memory, wherein the processor is connected to the memory, the memory is used to store a computer program and multiple frames of projection images, and the processor is used to execute the computer program stored in the memory to perform the method according to any one of claims 1 to 5.

11. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program and a plurality of frames of projection images, and the computer program is executed by a processor to implement the method according to any one of claims 1 to 5.

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