Image reconstruction method, device, computer equipment and storage medium

Abstract

The present application relates to an image reconstruction method, device, computer equipment and storage medium. The motion trajectory of a DSA scanning device during scanning is obtained, and the target PI line of each pixel to be reconstructed in the image to be reconstructed is obtained according to the position of each moving point on the motion trajectory. Image reconstruction is performed according to the target PI line of each pixel to be reconstructed and the projection data of the DSA scanning device to obtain a reconstructed target image. Since the motion trajectory of the DSA scanning device is not a regular motion trajectory, the target PI line of each pixel to be reconstructed in the image to be reconstructed is obtained according to the position of each moving point on the motion trajectory in the embodiment of the present application. It does not depend on the representation form of the motion trajectory and can be applied to the determination of the target PI line of the irregular motion trajectory and the regular motion trajectory of the DSA scanning device, thereby reducing the difficulty of image reconstruction based on the target PI line and projection data of each pixel to be reconstructed.

Description

Technical Field

[0001] The present application relates to the technical field of image data processing, and in particular to an image reconstruction method, apparatus, computer equipment and storage medium. Background Art

[0002] Digital Substaction Angiograhy (DSA) imaging is that the tube collects the mask image before the injection of contrast agent and the full film image after the injection of contrast agent based on the motion trajectory, and subtracts the mask image and full film image collected at the same angle to obtain the subtraction image of each angle. The subtraction image of each angle is reconstructed to obtain a 3D DSA image, which can observe the details of the blood vessels more clearly. The PI line is the line connecting the two foci on the motion trajectory. The subtraction image of each pixel point is reconstructed based on the PI line corresponding to each pixel point, and the subtraction image corresponding to each pixel point is back-projected to obtain a 3D DSA.

[0003] However, the motion trajectory of the tube during DSA image scanning is not a regular trajectory, which increases the difficulty of image reconstruction based on the motion trajectory. Summary of the invention

[0004] Based on this, it is necessary to provide an image reconstruction method, apparatus, computer device and storage medium that can reduce the difficulty of image reconstruction in response to the above technical problems.

[0005] In a first aspect, the present application provides an image reconstruction method, comprising:

[0006] Obtain the motion trajectory of the DSA scanning device during the scanning process;

[0007] According to the position of each moving point on the motion trajectory, a target PI line of each pixel to be reconstructed in the image to be reconstructed is obtained;

[0008] Image reconstruction is performed according to the target PI line of each pixel to be reconstructed and the projection data of the DSA scanning device to obtain a reconstructed target image.

[0009] The step of obtaining a target PI line for each pixel to be reconstructed in the image to be reconstructed according to the position of each moving point on the moving trajectory comprises:

[0010] Determine a motion vector group corresponding to the motion trajectory according to the position of each motion point on the motion trajectory; each motion vector in the motion vector group is a motion vector composed of any two motion points on the motion trajectory;

[0011] A target PI line for each pixel to be reconstructed is determined according to the position of each pixel to be reconstructed and the motion vector group.

[0012] In one of the embodiments, determining the target PI line of each pixel to be reconstructed according to the position of each pixel to be reconstructed and the motion vector group includes:

[0013] Determine, according to the position of each pixel to be reconstructed, the distance between each pixel to be reconstructed and each motion vector in the motion vector group;

[0014] The PI line represented by the motion vector with the smallest distance is determined as the corresponding target PI line of each pixel to be reconstructed.

[0015] In one embodiment, determining the distance between each pixel to be reconstructed and each motion vector in the motion vector group according to the position of each pixel to be reconstructed includes:

[0016] Determine a first difference vector between each pixel to be reconstructed and a motion point on each motion vector;

[0017] Determine a projection vector of each of the first difference vectors on the corresponding motion vector;

[0018] A second difference vector between each of the first difference vectors and the corresponding projection vector is determined, and the distance represented by each of the second difference vectors is used as the distance between each of the pixel points to be reconstructed and each of the motion vectors.

[0019] In one embodiment, the method further comprises:

[0020] Performing vector deduplication processing on the motion vector group to obtain a processed motion vector group;

[0021] The step of determining a target PI line for each pixel to be reconstructed according to the position of each pixel to be reconstructed and the motion vector group includes:

[0022] According to the position of each pixel to be reconstructed and the processed motion vector group, a target PI line of each pixel to be reconstructed is determined.

[0023] In one embodiment, the image reconstruction is performed according to the target PI line of each pixel to be reconstructed and the projection data of the DSA scanning device to obtain a reconstructed target image, including:

[0024] Determining projection data to be reconstructed corresponding to each pixel to be reconstructed according to the target PI line of each pixel to be reconstructed and the projection data of the DSA scanning device;

[0025] Image reconstruction is performed according to the projection data to be reconstructed corresponding to each pixel point to be reconstructed to obtain a reconstructed target image.

[0026] In one embodiment, determining the projection data to be reconstructed corresponding to each pixel to be reconstructed according to the target PI line of each pixel to be reconstructed and the projection data of the DSA scanning device includes:

[0027] Determining a back-projection angle range of each pixel to be reconstructed according to a target PI line of each pixel to be reconstructed;

[0028] The projection data of the DSA scanning device within the back-projection angle range of each pixel point to be reconstructed is used as the projection data to be reconstructed corresponding to each pixel point to be reconstructed.

[0029] In a second aspect, the present application further provides an image reconstruction device, comprising:

[0030] A first acquisition module is used to acquire the motion trajectory of the DSA scanning device during the scanning process;

[0031] A second acquisition module, used for acquiring a target PI line of each pixel to be reconstructed in the image to be reconstructed according to the position of each moving point on the motion trajectory;

[0032] The reconstruction module is used to perform image reconstruction according to the target PI line of each pixel to be reconstructed and the projection data of the DSA scanning device to obtain a reconstructed target image.

[0033] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0034] Obtain the motion trajectory of the DSA scanning device during the scanning process;

[0035] According to the position of each moving point on the motion trajectory, a target PI line of each pixel to be reconstructed in the image to be reconstructed is obtained;

[0036] Image reconstruction is performed according to the target PI line of each pixel to be reconstructed and the projection data of the DSA scanning device to obtain a reconstructed target image.

[0037] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0038] Obtain the motion trajectory of the DSA scanning device during the scanning process;

[0039] According to the position of each moving point on the motion trajectory, a target PI line of each pixel to be reconstructed in the image to be reconstructed is obtained;

[0040] Image reconstruction is performed according to the target PI line of each pixel to be reconstructed and the projection data of the DSA scanning device to obtain a reconstructed target image.

[0041] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0042] Obtain the motion trajectory of the DSA scanning device during the scanning process;

[0043] According to the position of each moving point on the motion trajectory, a target PI line of each pixel to be reconstructed in the image to be reconstructed is obtained;

[0044] Image reconstruction is performed according to the target PI line of each pixel to be reconstructed and the projection data of the DSA scanning device to obtain a reconstructed target image.

[0045] The above-mentioned image reconstruction method, device, computer equipment and storage medium obtain the motion trajectory of the DSA scanning device during the scanning process, obtain the target PI line of each pixel to be reconstructed in the image to be reconstructed according to the position of each moving point on the motion trajectory, and perform image reconstruction according to the target PI line of each pixel to be reconstructed and the projection data of the DSA scanning device to obtain a reconstructed target image. Since the motion trajectory of the DSA scanning device is not a regular motion trajectory, it is difficult to express it using a relational equation. In the embodiment of the present application, the target PI line of each pixel to be reconstructed in the image to be reconstructed is obtained according to the position of each moving point on the motion trajectory. It does not depend on the representation form of the motion trajectory and can be applied to the determination of the target PI line of the irregular motion trajectory of the DSA scanning device, and is also applicable to the determination of the target PI line of the regular motion trajectory of the DSA scanning device, thereby reducing the difficulty of image reconstruction based on the target PI line and projection data of each pixel to be reconstructed. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0047] Figure 1 A diagram showing an application environment of an image reconstruction method in an embodiment;

[0048] Figure 2 is a schematic flow chart of an image reconstruction method in one embodiment;

[0049] Figure 3 is a schematic diagram of a motion trajectory in one embodiment;

[0050] Figure 4 is a schematic diagram of a PI line in one embodiment;

[0051] Figure 5 A schematic diagram of a PI line in another embodiment;

[0052] Figure 6 is a schematic flow chart of an image reconstruction method in another embodiment;

[0053] Figure 7 Schematic diagram of a process of determining a target PI line in one embodiment;

[0054] Figure 8 It is a flowchart of a method for determining a target PI line in another embodiment;

[0055] Fig. 9 is a schematic diagram of a distance determination method in one embodiment;

[0056] Fig.10 is a schematic diagram of a distance determination method in another embodiment;

[0057] Fig.11 is a schematic flow chart of a method for determining a target image in one embodiment;

[0058] Fig.12 is a schematic flow chart of an image reconstruction method in another embodiment;

[0059] Fig.13 FIG. 4 is a structural block diagram of an image reconstruction device in an embodiment. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0061] The image reconstruction method provided in the embodiment of the present application can be applied to Figure 1 The application environment includes a computer device, which may be a server, and its internal structure diagram may be as shown in FIG. Figure 1As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store image reconstruction related data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, an image reconstruction method is implemented. The server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides cloud computing services.

[0062] Those skilled in the art will understand that Figure 1 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0063] In an exemplary embodiment, Figure 2 As shown, an image reconstruction method is provided, which is applied to Figure 1 The computer device in the example is used to illustrate, including the following S201 to S203. Among them:

[0064] S201, obtaining a motion trajectory of a DSA scanning device during a scanning process.

[0065] In this embodiment, after the DSA scanning device is calibrated according to the scanning requirements, the motion trajectory of the DSA scanning device can be obtained. Figure 3As shown, the motion trajectory of the focus of the tube of the DSA scanning device during the scanning process is an accurate circular motion trajectory or a spiral motion trajectory in space that can be expressed by a formula. However, when acquiring a panoramic 3D DSA image, due to the large long-axis scanning range of the DSA scanning device and the influence of vibration and inertia, the motion trajectory of the focus of the tube is often an inaccurate motion trajectory that cannot be expressed by a formula, for example, an inaccurate circular motion trajectory or an inaccurate spiral motion trajectory in space. After acquiring the motion trajectory and starting the scanning program of the DSA scanning device, the computer device can control the focus of the tube of the DSA scanning device to move along a predetermined motion trajectory, that is, the focus of the tube of the DSA scanning device is each motion point on the motion trajectory.

[0066] Therefore, the motion trajectory of the DSA scanning device obtained after correction can be sent to a computer device, or the motion trajectory of the DSA scanning device can be obtained by collecting the position information of the focus of the tube using a sensor during the scanning process of the DSA scanning device.

[0067] Optionally, the motion trajectory may also be a fault trajectory, such as a circular trajectory, an elliptical trajectory, etc.

[0068] S202, obtaining a target PI line of each pixel to be reconstructed in the image to be reconstructed according to the position of each moving point on the moving trajectory.

[0069] In this embodiment, multiple PI lines are determined according to the positions of each moving point on the motion trajectory. Figure 4 is a schematic diagram of a PI line in one embodiment, Figure 5 is a schematic diagram of a PI line in another embodiment, such as Figure 4 and Figure 5 As shown in the figure, the PI line is the line connecting any two moving points (i, j) on the motion trajectory. Corresponding to the only PI line.

[0070] In one possible implementation, multiple pairs of moving points can be obtained according to the motion trajectory, and the connecting line between each pair of moving points can be represented in vector form to obtain a motion vector group including multiple motion vectors. The target PI line of each pixel to be reconstructed can be determined according to the position of each pixel to be reconstructed and the motion vector group.

[0071] In another possible implementation, multiple moving point pairs can be obtained according to the motion trajectory, and the connecting line between each moving point pair can be expressed in the form of a parametric equation. According to the position of each pixel to be reconstructed and each parametric equation, the target PI line of each pixel to be reconstructed is determined.

[0072] S203, performing image reconstruction according to the target PI line of each pixel to be reconstructed and the projection data of the DSA scanning device to obtain a reconstructed target image.

[0073] The projection data of the DSA scanning device includes mask projection data of each acquisition angle and full film projection data of each acquisition angle.

[0074] In this embodiment, the mask projection data and the projection data of the film to be reconstructed corresponding to each pixel to be reconstructed can be determined from the mask projection data of each acquisition angle of the DSA scanning device and the projection data of the film to be reconstructed at each acquisition angle according to the target PI line of each pixel to be reconstructed, and the projection data of the film to be reconstructed and the mask projection data to be reconstructed of the corresponding acquisition angle are subtracted to obtain the subtraction data to be reconstructed, and the reconstruction of the pixel to be reconstructed can be realized by back-projecting the subtraction data to be reconstructed. For each pixel to be reconstructed in the image to be reconstructed, the above method is adopted to obtain the reconstructed target image.

[0075] In one possible implementation, Figure 6 As shown, after obtaining the mask projection data of each acquisition angle and the full film projection data of each acquisition angle, the mask projection data and the full film projection data of the corresponding acquisition angle are first subtracted to obtain the subtraction data corresponding to each acquisition angle. According to the target PI line of each pixel to be reconstructed, the subtraction data to be reconstructed is determined from the subtraction data corresponding to each acquisition angle, and the reconstruction of the pixel to be reconstructed can be achieved by back-projecting the subtraction data to be reconstructed. For each pixel to be reconstructed in the image to be reconstructed, the above method is adopted to obtain the reconstructed target image.

[0076] In the above-mentioned image reconstruction method, the motion trajectory of the DSA scanning device during the scanning process is obtained, and the target PI line of each pixel to be reconstructed in the image to be reconstructed is obtained according to the position of each moving point on the motion trajectory, and image reconstruction is performed according to the target PI line of each pixel to be reconstructed and the projection data of the DSA scanning device to obtain a reconstructed target image. Since the motion trajectory of the DSA scanning device is not a regular motion trajectory, it is difficult to express it using a relational equation. In the embodiment of the present application, the target PI line of each pixel to be reconstructed in the image to be reconstructed is obtained according to the position of each moving point on the motion trajectory. It does not depend on the representation form of the motion trajectory, and can be applied to the determination of the target PI line of the irregular motion trajectory of the DSA scanning device, and is also applicable to the determination of the target PI line of the regular motion trajectory of the DSA scanning device, thereby reducing the difficulty of image reconstruction based on the target PI line and projection data of each pixel to be reconstructed.

[0077] Figure 7 FIG. 1 is a flow chart of a method for determining a target PI line in an embodiment. Figure 7As shown, the embodiment of the present application relates to a possible implementation method of how to obtain a target PI line for each pixel to be reconstructed in the image to be reconstructed according to the position of each moving point on the motion trajectory, including the following steps:

[0078] S701, determining a motion vector group corresponding to the motion trajectory according to the position of each motion point on the motion trajectory; each motion vector in the motion vector group is a motion vector formed by any two motion points on the motion trajectory.

[0079] In this embodiment, it is assumed that the motion trajectory of the tube in the DSA scanning device is ,in, , and are the coordinates of the focus of the tube in the x, y and z directions respectively, and n is the number of moving points on the motion trajectory, that is, the number of projection data or the number of focuses of the tube.

[0080] Since each motion vector in the motion vector group is a motion vector composed of any two motion points on the motion trajectory, two vectors with opposite directions can be obtained for any two motion points. Assuming that there are 10 motion points on the motion trajectory, a total of 90 motion vectors can be obtained.

[0081] S702, determining a target PI line for each pixel to be reconstructed according to the position of each pixel to be reconstructed and the motion vector group.

[0082] In this embodiment, assuming that for a pixel to be reconstructed, the distance between the pixel to be reconstructed and each motion vector can be determined according to the position of the pixel to be reconstructed, and the PI line represented by the motion vector with the smallest distance is used as the target PI line. According to the above analysis, for any two motion points, two vectors with opposite directions can be obtained, and two identical minimum distances will actually be obtained. Since two different motion vectors represent the same PI line, the PI line represented by any one of the two motion vectors is the target PI line of the reconstructed pixel.

[0083] In a possible implementation, partial motion vectors that meet the conditions can be screened out from the motion vector group based on a preset screening method, and the PI line represented by the motion vector with the smallest distance is used as the target PI line according to the distance between the position of each pixel to be reconstructed and the partial motion vector. The partial motion vector that meets the conditions can be a motion vector that retains only one direction among every two motion vectors with opposite directions; or a motion vector whose motion point time is within a certain time range, etc.

[0084] In another possible implementation, since the pixel to be reconstructed has a unique corresponding relationship with the PI line, after the target PI line is determined for the first pixel to be reconstructed, in order to distinguish, it is assumed that the target PI line corresponding to the first pixel to be reconstructed is the first target PI line. When determining the distance between the second pixel to be reconstructed and the motion vector, the distance between the second pixel to be reconstructed and the first target PI line is not calculated. Similarly, when determining the target PI line of the second pixel to be reconstructed, the first target PI line and the second target PI line are no longer considered, thereby obtaining the target PI line corresponding to each pixel to be reconstructed.

[0085] In an embodiment of the present application, the motion vector group corresponding to the motion trajectory is determined according to the position of each moving point on the motion trajectory, and the target PI line of each pixel to be reconstructed is determined according to the position and motion vector group of each pixel to be reconstructed. For motion trajectories of arbitrary shapes, the target PI line of the pixel to be reconstructed can be obtained, thereby improving the universality and accuracy of the determination of the target PI line.

[0086] Figure 8 FIG. 4 is a flow chart of a method for determining a target PI line in another embodiment. Figure 8 As shown, the embodiment of the present application relates to a possible implementation method of how to determine the target PI line of each pixel to be reconstructed according to the position and motion vector group of each pixel to be reconstructed, including the following steps:

[0087] S801, determining the distance between each pixel to be reconstructed and each motion vector in the motion vector group according to the position of each pixel to be reconstructed.

[0088] In this embodiment, for a pixel point to be reconstructed, the first difference vector between the pixel point to be reconstructed and the motion point on each motion vector can be determined, and the projection vector of each first difference vector on the corresponding motion vector can be further determined to obtain the first distance represented by the first difference vector and the projection distance represented by the corresponding projection vector. On the basis of the first distance and the projection distance, the distance between the pixel point to be reconstructed and each motion vector can be determined using the Pythagorean theorem.

[0089] In one possible implementation, for a pixel point to be reconstructed, a first difference vector between the pixel point to be reconstructed and the motion point on each motion vector can be determined, and the projection vector of each first difference vector on the corresponding motion vector can be further determined, thereby determining the second difference vector between each first difference vector and the corresponding projection vector, and the distance represented by each second difference vector is used as the distance between the pixel point to be reconstructed and each motion vector.

[0090] S802, determining the PI line represented by the motion vector with the smallest distance as the target PI line corresponding to each pixel to be reconstructed.

[0091] In this embodiment, for each pixel point to be reconstructed, the PI line represented by the motion vector with the smallest distance is determined as the target PI line of the reconstructed pixel point.

[0092] In an embodiment of the present application, according to the position of each pixel to be reconstructed, the distance between each pixel to be reconstructed and each motion vector is determined, the PI line represented by the motion vector with the smallest distance is determined as the target PI line corresponding to each pixel to be reconstructed, and the distance between each motion vector and the position of the pixel to be reconstructed is calculated, thereby ensuring the accuracy of the distance determination.

[0093] In one embodiment, according to the position of each pixel point to be reconstructed, the distance between each pixel point to be reconstructed and each motion vector is determined, including: determining a first difference vector between each pixel point to be reconstructed and a motion point on each motion vector; determining a projection vector of each first difference vector on the corresponding motion vector; determining a second difference vector between each first difference vector and the corresponding projection vector, and using the distance represented by each second difference vector as the distance between each pixel point to be reconstructed and each motion vector.

[0094] In this embodiment, if Fig. 9 As shown, taking a pixel to be reconstructed and a motion vector as an example, the motion vector is determined according to the position of the i-th motion point and the position of the j-th motion point. The position of the pixel to be reconstructed is expressed as a pixel vector To represent, set the position of the pixel to be reconstructed and the starting point of the motion vector to be located at the origin , then the motion vector can be expressed as The first difference vector between the position of the pixel to be reconstructed and the moving point on the motion vector , project the first difference vector onto the motion vector to obtain the projection vector , get the second difference vector of the first difference vector and the projection vector , taking the modulus of the second difference vector can obtain the distance between the reconstructed pixel point and the motion vector.

[0095] Since the motion vector is perpendicular to the second difference vector, we have ,Right now , let the projection vector ,but , the distance between the pixel to be reconstructed and the motion vector is , where · is the inner product of two vectors and || || is the modulus of the vectors.

[0096] Optionally, the first difference vector between the pixel to be reconstructed and the motion point on the motion vector can also be expressed as .

[0097] like Fig.10As shown, taking a pixel to be reconstructed and a motion vector as an example, the motion vector is determined according to the position of the i-th motion point and the position of the j-th motion point. The position of the pixel to be reconstructed is , the position of the pixel to be reconstructed and the starting point of the motion vector are set at ,Right now . Motion vector , the first difference vector between the position of the pixel to be reconstructed and the moving point on the motion vector , project the first difference vector onto the motion vector to obtain the projection vector , then ,Right now , let the projection vector ,but , the distance between the pixel to be reconstructed and the motion vector is .

[0098] In an embodiment of the present application, a first difference vector between each pixel point to be reconstructed and a motion point on each motion vector is determined, and a projection vector of each first difference vector on the corresponding motion vector is determined, thereby determining a second difference vector between each first difference vector and the corresponding projection vector, and the distance represented by each second difference vector is used as the distance between each pixel point to be reconstructed and each motion vector, and the distance between each pixel point to be reconstructed and each motion vector is obtained in a vector manner, thereby improving the accuracy of distance determination and facilitating implementation.

[0099] In one embodiment, according to the position of each moving point on the motion trajectory, the target PI line of each pixel to be reconstructed in the image to be reconstructed is obtained, and it also includes: performing vector deduplication processing on the motion vector group to obtain a processed motion vector group; according to the position of each pixel to be reconstructed and the processed motion vector group, determining the target PI line of each pixel to be reconstructed.

[0100] In this embodiment, according to the above analysis, any two motion points may include two motion vectors with opposite directions. Since the direction will not affect the determination of the distance between the pixel point to be reconstructed and the motion vector, after obtaining the motion vector group, the motion vectors in the motion vector group can also be deduplicated to obtain the processed motion vector group.

[0101] In one possible implementation, the motion vectors in the processed motion vector group can be expressed as , or That is, the motion vectors are all moving in the same direction.

[0102] In another possible implementation, any one of the two motion vectors with opposite directions may be deduplicated to obtain a deduplicated motion vector group.

[0103] In an embodiment of the present application, vector deduplication processing is performed on the motion vector group to obtain a processed motion vector group, and the target PI line of each pixel to be reconstructed is determined based on the position of each pixel to be reconstructed and the processed motion vector group, thereby improving the efficiency of determining the target PI line.

[0104] Fig.11 FIG. 1 is a flow chart of a method for determining a target image in an embodiment. Fig.11 As shown, the embodiment of the present application relates to a possible implementation method of how to perform image reconstruction according to the target PI line of each pixel to be reconstructed and the projection data of the DSA scanning device to obtain a reconstructed target image, including the following steps:

[0105] S1101, determining projection data to be reconstructed corresponding to each pixel point to be reconstructed according to a target PI line of each pixel point to be reconstructed and projection data of a DSA scanning device.

[0106] The projection data are the mask projection data and the full film projection data of each acquisition angle, and the projection data to be reconstructed are the target PI line based on the pixel point to be reconstructed, and the mask projection data and the full film projection data to be reconstructed are selected from the projection data.

[0107] In this embodiment, the back-projection angle range of each pixel to be reconstructed can be determined according to the target PI line of the pixel to be reconstructed, and the projection data within the back-projection angle range of each pixel to be reconstructed is used as the projection data to be reconstructed for the pixel to be reconstructed.

[0108] In a possible implementation, partial projection data within the back-projection angle range of the target PI line of each pixel to be reconstructed may be used as the projection data to be reconstructed for the pixel to be reconstructed.

[0109] S1102, performing image reconstruction according to the projection data to be reconstructed corresponding to each pixel point to be reconstructed, to obtain a reconstructed target image.

[0110] In this embodiment, the mask projection data to be reconstructed and the projection data of the full film to be reconstructed at each acquisition angle corresponding to each pixel to be reconstructed are subtracted to obtain subtraction data to be reconstructed. The subtraction data to be reconstructed is processed using a back-projection algorithm to achieve reconstruction of each pixel to be reconstructed, thereby obtaining a reconstructed target image.

[0111] In an embodiment of the present application, the projection data to be reconstructed corresponding to each pixel to be reconstructed is determined based on the target PI line of each pixel to be reconstructed and the projection data of the DSA scanning device, and image reconstruction is performed based on the projection data to be reconstructed corresponding to each pixel to be reconstructed to obtain a reconstructed target image. Since the motion trajectory of the DSA scanning device is not a regular trajectory, it is difficult to determine the PI line from the motion trajectory of the DSA scanning device. Based on the method proposed in the present application, the target PI line of each pixel to be reconstructed is obtained, the projection data to be reconstructed is determined using the target PI line and projection data of each pixel to be reconstructed, and the projection data to be reconstructed is reconstructed, thereby reducing the complexity and difficulty of DSA image reconstruction.

[0112] In one embodiment, the projection data to be reconstructed corresponding to each pixel to be reconstructed is determined based on the target PI line of each pixel to be reconstructed and the projection data of the DSA scanning device, including: determining the back projection angle range of each pixel to be reconstructed based on the target PI line of each pixel to be reconstructed; and using the projection data of the DSA scanning device within the back projection angle range of each pixel to be reconstructed as the projection data to be reconstructed corresponding to each pixel to be reconstructed.

[0113] In this embodiment, the target PI line is determined according to the position of the moving point, and the back-projection angle range of each pixel to be reconstructed can be determined according to the two endpoints of the target PI line of each pixel to be reconstructed, that is, the positions of the two moving points corresponding to the target PI line. , directly change the starting position As the starting angle of the target PI line, the end position As the end angle of the target PI line, the position (angle) of the moving point within the range of the start angle and the end angle is used as the back-projection angle range.

[0114] The projection data within the back-projection angle range is extracted as the projection data to be reconstructed corresponding to the pixel to be reconstructed.

[0115] In an embodiment of the present application, the back-projection angle range of each pixel to be reconstructed is determined based on the target PI line of each pixel to be reconstructed, and the projection data of the DSA scanning device within the back-projection angle range of each pixel to be reconstructed is used as the projection data to be reconstructed corresponding to each pixel to be reconstructed, thereby improving the accuracy of acquiring the projection data to be reconstructed.

[0116] Fig.12 FIG. 1 is a flow chart of an image reconstruction method in another embodiment. Fig.12 As shown, the following steps are included:

[0117] S1201, obtaining a motion trajectory of the DSA scanning device during the scanning process;

[0118] S1202, determining a motion vector group corresponding to the motion trajectory according to the positions of each motion point on the motion trajectory; each motion vector in the motion vector group is a motion vector formed by any two motion points on the motion trajectory;

[0119] S1203, determining a first difference vector between each pixel to be reconstructed and a motion point on each motion vector;

[0120] S1204, determining a projection vector of each first difference vector on the corresponding motion vector;

[0121] S1205, determining a second difference vector between each first difference vector and the corresponding projection vector, and using the distance represented by each second difference vector as the distance between each pixel to be reconstructed and each motion vector;

[0122] S1206, determining the PI line represented by the motion vector with the smallest distance as the target PI line corresponding to each pixel to be reconstructed;

[0123] S1207, determining a back-projection angle range of each pixel to be reconstructed according to a target PI line of each pixel to be reconstructed;

[0124] S1208, using the projection data of the DSA scanning device within the back-projection angle range of each pixel point to be reconstructed as the projection data to be reconstructed corresponding to each pixel point to be reconstructed;

[0125] S1209, performing image reconstruction according to the projection data to be reconstructed corresponding to each pixel point to be reconstructed, to obtain a reconstructed target image.

[0126] Since the motion trajectory of the DSA scanning device is not a regular motion trajectory, it is difficult to express it using a relational equation. In the embodiment of the present application, the target PI line of each pixel to be reconstructed in the image to be reconstructed is obtained according to the position of each moving point on the motion trajectory. This is independent of the representation form of the motion trajectory and can be applied to the determination of the target PI line of the irregular motion trajectory of the DSA scanning device, as well as the determination of the target PI line of the regular motion trajectory of the DSA scanning device, thereby reducing the difficulty of image reconstruction based on the target PI line and projection data of each pixel to be reconstructed.

[0127] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0128] Based on the same inventive concept, the embodiment of the present application also provides an image reconstruction device for implementing the above-mentioned image reconstruction method. The implementation solution provided by the device to solve the problem is similar to the implementation solution recorded in the above-mentioned method, so the specific limitations in one or more image reconstruction device embodiments provided below can refer to the limitations on the image reconstruction method above, and will not be repeated here.

[0129] In an exemplary embodiment, Fig.13 As shown, an image reconstruction device is provided, comprising: a first acquisition module 11, a second acquisition module 12 and a reconstruction module 13, wherein:

[0130] A first acquisition module 11 is used to acquire the motion trajectory of the DSA scanning device during the scanning process;

[0131] A second acquisition module 12 is used to acquire a target PI line of each pixel to be reconstructed in the image to be reconstructed according to the position of each moving point on the motion trajectory;

[0132] The reconstruction module 13 is used to perform image reconstruction according to the target PI line of each pixel to be reconstructed and the projection data of the DSA scanning device to obtain a reconstructed target image.

[0133] In one embodiment, the second acquisition module 12 is used to determine a motion vector group corresponding to the motion trajectory according to the position of each motion point on the motion trajectory; each motion vector in the motion vector group is a motion vector composed of any two motion points on the motion trajectory;

[0134] According to the position of each pixel to be reconstructed and the motion vector group, a target PI line of each pixel to be reconstructed is determined.

[0135] In one embodiment, the second acquisition module 12 is used to determine the distance between each pixel to be reconstructed and each motion vector in the motion vector group according to the position of each pixel to be reconstructed;

[0136] The PI line represented by the motion vector with the smallest distance is determined as the target PI line of each corresponding pixel to be reconstructed.

[0137] In one embodiment, the second acquisition module 12 is used to determine a first difference vector between each pixel to be reconstructed and a motion point on each motion vector;

[0138] Determine a projection vector of each first difference vector on the corresponding motion vector;

[0139] A second difference vector between each first difference vector and the corresponding projection vector is determined, and the distance represented by each second difference vector is used as the distance between each pixel point to be reconstructed and each motion vector.

[0140] In one embodiment, the second acquisition module 12 is used to perform vector deduplication processing on the motion vector group to obtain a processed motion vector group;

[0141] According to the position of each pixel to be reconstructed and the processed motion vector group, a target PI line of each pixel to be reconstructed is determined.

[0142] In one embodiment, the reconstruction module 13 is used to determine the projection data to be reconstructed corresponding to each pixel to be reconstructed according to the target PI line of each pixel to be reconstructed and the projection data of the DSA scanning device;

[0143] Image reconstruction is performed according to the projection data to be reconstructed corresponding to each pixel point to be reconstructed to obtain a reconstructed target image.

[0144] In one embodiment, the reconstruction module 13 is used to determine the back-projection angle range of each pixel to be reconstructed according to the target PI line of each pixel to be reconstructed;

[0145] The projection data of the DSA scanning device within the back-projection angle range of each pixel point to be reconstructed is used as the projection data to be reconstructed corresponding to each pixel point to be reconstructed.

[0146] Each module in the above-mentioned image reconstruction device can be implemented in whole or in part by software, hardware or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each module above.

[0147] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps of any of the above method embodiments when executing the computer program.

[0148] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of any of the above method embodiments are implemented.

[0149] In one embodiment, a computer program product is provided, including a computer program, which implements the steps of any of the above method embodiments when executed by a processor.

[0150] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0151] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0152] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0153] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. An image reconstruction method, characterized in that: The method comprises: Obtain the motion trajectory of the DSA scanning device during the scanning process; According to the position of each moving point on the motion trajectory, determine the motion vector group corresponding to the motion trajectory, determine the first difference vector between each pixel point to be reconstructed in the image to be reconstructed and the moving point on each motion vector in the motion vector group, determine the projection vector of each first difference vector on the corresponding motion vector, determine the second difference vector between each first difference vector and the corresponding projection vector, use the distance represented by each second difference vector as the distance between each pixel point to be reconstructed and each motion vector, and determine the PI line represented by the motion vector with the smallest distance as the corresponding target PI line of each pixel point to be reconstructed; Image reconstruction is performed according to the target PI line of each pixel to be reconstructed and the projection data of the DSA scanning device to obtain a reconstructed target image.

2. The method according to claim 1, characterized in that The method further comprises: Perform vector deduplication processing on the motion vector group to obtain a processed motion vector group.

3. The method according to claim 1 or 2, characterized in that: The image reconstruction is performed according to the target PI line of each pixel to be reconstructed and the projection data of the DSA scanning device to obtain a reconstructed target image, including: Determining projection data to be reconstructed corresponding to each pixel to be reconstructed according to the target PI line of each pixel to be reconstructed and the projection data of the DSA scanning device; Image reconstruction is performed according to the projection data to be reconstructed corresponding to each pixel point to be reconstructed to obtain a reconstructed target image.

4. The method according to claim 3, characterized in that Determining the projection data to be reconstructed corresponding to each pixel to be reconstructed according to the target PI line of each pixel to be reconstructed and the projection data of the DSA scanning device includes: Determining a back-projection angle range of each pixel to be reconstructed according to a target PI line of each pixel to be reconstructed; The projection data of the DSA scanning device within the back-projection angle range of each pixel point to be reconstructed is used as the projection data to be reconstructed corresponding to each pixel point to be reconstructed.

5. An image reconstruction device, characterized in that: The device comprises: A first acquisition module is used to acquire the motion trajectory of the DSA scanning device during the scanning process; A second acquisition module is used to determine the motion vector group corresponding to the motion trajectory according to the position of each moving point on the motion trajectory, determine the first difference vector between each pixel point to be reconstructed in the image to be reconstructed and the moving point on each motion vector in the motion vector group, determine the projection vector of each first difference vector on the corresponding motion vector, determine the second difference vector between each first difference vector and the corresponding projection vector, use the distance represented by each second difference vector as the distance between each pixel point to be reconstructed and each motion vector, and determine the PI line represented by the motion vector with the smallest distance as the corresponding target PI line of each pixel point to be reconstructed; The reconstruction module is used to perform image reconstruction according to the target PI line of each pixel to be reconstructed and the projection data of the DSA scanning device to obtain a reconstructed target image.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 4 are implemented.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 4 are implemented.

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