A multi-viewpoint exposure X-ray image positioning method and system

Abstract

The present invention provides a multi-view exposure X-ray image positioning method and system, and the method specifically includes: acquiring volume data information of a target object, taking X-ray images corresponding to multiple views according to a time sequence based on a preset time period, implementing position positioning of an image of one view according to a first optimization algorithm, and in the case where the target object is in a non-static state, receiving a second image sequence in the time sequence order and performing auxiliary optimization based on different-view images in the first preset time periods before and after it, so as to implement pose optimization of the target object in the depth direction, eliminating the error of tracking and positioning only in one view and realizing precise positioning of the target object in dynamic time-sequence images.

Description

Technical Field

[0001] The present invention relates to the field of imaging technology processing, and particularly to a multi-view exposure X-ray image positioning method and system. Background Art

[0002] Currently, X-rays are commonly used in clinical and scientific research to quantitatively analyze the motion state of bones and joints. However, when using single-view X-ray images to obtain the spatial position information during the movement of bones and joints, it often causes positioning errors in the out-of-plane movement. Therefore, in the prior art, multi-view dynamic X-ray images are often used to accurately locate the position of bones and joints. However, in the currently common multi-view imaging tracking environment composed of multiple C-arm machines, the time when the X-ray emission light is emitted cannot be determined, and there must be a time sequence for the actual imaging exposure time of the same target. That is, the target objects captured in different-view images are not the target objects at the same moment. Simply treating multiple dynamic X-ray imaging devices of the same specification as synchronous imaging often makes it difficult to achieve convergence in automatic registration.

[0003] In the prior art, since only one view is used for tracking and positioning, there will be errors in depth calculation, resulting in the calculated position not being close to the true position. Therefore, it is urgent to use images from other views to overcome the positioning errors caused by a single view. Summary of the Invention

[0004] The present invention is based on a multi-view exposure X-ray image positioning method and system. By using a first optimization algorithm to locate the position information of the target object at different views, and then using a second optimization algorithm to locate the position information of the target object at each view, accurate positioning of the target object in the dynamic time-series images is achieved. Specifically, it includes:

[0005] The first aspect of the present invention provides a multi-view exposure X-ray image positioning method. A plurality of X-ray detectors and a plurality of receiving plates are arranged at relative positions between different shooting views, including:

[0006] Obtain the volume data information of the target object;

[0007] According to the volume data information, sequentially capture X-ray images corresponding to multiple views in time series based on a preset time period;

[0008] When the target object is in a static state, receive the X-ray images of all views at the corresponding moment of the static state to generate a first image sequence, and obtain a first rotation displacement matrix according to the first optimization algorithm;

[0009] When the target object is in a non-static state, receive the X-ray images of the first view to the last view in the preset time period in time series order as a second image sequence, and process the second image sequence to obtain a second rotation displacement matrix;

[0010] Based on the first rotation displacement matrix and a number of second rotation matrices corresponding to the image sequence in a non-stationary state, the dynamic positioning of the X-ray image of the target object is realized.

[0011] In a possible implementation manner of the present application, a number of X-ray detectors and a number of receiving plates are arranged at the relative positions between different shooting perspectives; the relative positions between different shooting perspectives are the relative positions of the emission sources of different groups of X-ray emitters and the receiving plates, and multi-perspective X-ray images are obtained by shooting with different groups of X-ray emitters and the receiving plates.

[0012] In a possible implementation manner of the present application, the situation where the target object is in a stationary state includes that the target object is correspondingly in the scanning start period or the scanning end period.

[0013] In a possible implementation manner of the present application, the processing of the second image sequence to obtain the second rotation matrix includes:

[0014] When the reception of the second image sequence is completed, secondary rotation displacement matrices for each perspective corresponding to a preset time period are generated according to the first optimization algorithm;

[0015] The secondary rotation displacement matrices in the preset time period are updated by using the second optimization algorithm to obtain the corresponding second rotation displacement matrix.

[0016] In a possible implementation manner of the present application, the first optimization algorithm includes:

[0017] Step 110: Preset a first position where the projection of the target object along the projection direction from the emission source to the receiving plate approaches the real image of the target object, and calculate the first similarity S1 between the projection of the target object and the real image X view_1 ;

[0018] Step 210: Select a second position, generate a matrix T first corresponding to the second position, and re-project according to the second position and calculate the second similarity S2; determine whether S1 is less than S2;

[0019] If so, accept the current position T first and enter step 310;

[0020] If not, enter step 410;

[0021] Step 310: Set the matrix T first as the matrix T second ;

[0022] Step 410: Obtain the number of times of updating and calculating T first and determine whether the preset iteration condition is satisfied;

[0023] If so, accept the current position T first ;

[0024] If not, return to step 210.

[0025] In a possible implementation manner of the present application, updating the secondary rotation displacement matrix of the preset time period by using the second optimization algorithm to obtain the corresponding second rotation displacement matrix includes:

[0026] Step 120: Based on the position perspective corresponding to the secondary rotation displacement matrix, take the poses of other perspectives as references, and calculate the displacement in the Z-axis direction and the rotation values N1 around the X and Y axes corresponding to the matrix T ave ;

[0027] Step 220: Fix the displacement in the Z-axis direction and the rotation values N1 around the X and Y axes, select the second position, and generate the matrix T' corresponding to the second position first , and re-project according to the second position and calculate the displacement in the Z-axis direction and the rotation values N2 around the X and Y axes; judge T ave The corresponding generated similarity S ave Whether it is less than the similarity S' first Correspondingly generated by T' first ;

[0028] If so, accept the displacement in the Z-axis direction and the rotation values N1 around the X and Y axes, and enter step 320;

[0029] If not, enter step 420;

[0030] Step 320: Set the matrix T' first As the matrix T' final ;

[0031] Step 420: Obtain the number of times of updating and calculating T' first , and judge whether it meets the preset iteration condition;

[0032] If so, accept the current position T' first ;

[0033] If not, return to step 220.

[0034] In a possible implementation manner of the present application, taking the poses of other perspectives as references includes:

[0035] According to the position of the first perspective in the current first preset time period, obtain the average value of the pose of the next perspective of the previous preset time of the current preset time and the pose of the next perspective of the current first preset time period;

[0036] Convert the average value to the first perspective and replace the displacement in the Z-axis direction and the rotations about the X and Y axes in the detector coordinate system of the first perspective of the secondary rotation displacement matrix.

[0037] In a possible implementation manner of the present application, the values of the displacement in the fixed Z-axis direction and the rotations about the X and Y axes include:

[0038] Based on the position in the current first preset time period, the matrix obtained is: T = T4×4,

[0039] That is This matrix includes six translation vectors and rotation elements (x, y, z, γ, α, β);

[0040] Among them, R 3×3 is the rotation matrix R related to three axes a × a = R γ *R α *R β ; V1x3 is the translation vector along three axes

[0041] The second aspect of the present application provides a multi-perspective exposure X-ray image positioning device, including:

[0042] Data acquisition module: used to acquire the volume data information of the target object;

[0043] Data collection module: According to the volume data information, sequentially capture X-ray images corresponding to multiple perspectives in time series based on a preset time period;

[0044] First data receiving module: When the target object is in a stationary state, receive the X-ray images of all perspectives at the corresponding time of the stationary state to generate a first image sequence, and obtain a first rotation displacement matrix according to the first optimization algorithm;

[0045] Second data receiving module: When the target object is in a non-stationary state, receive the X-ray images from the first perspective to the last perspective in the preset time period in time series order as a second image sequence, and perform optimization processing on the second image sequence to obtain a second rotation displacement matrix;

[0046] Positioning module:

[0047] According to the first rotation displacement matrix and a plurality of second rotation matrices corresponding to the image sequence in the non-stationary state, realize the dynamic positioning of the X-ray image of the target object.

[0048] Specifically, the second data receiving module further includes:

[0049] Second Data First Optimization Unit: When the reception of the second image sequence is completed, generate a secondary rotation displacement matrix corresponding to a preset time period according to the first optimization algorithm;

[0050] Second Data Second Optimization Unit: Update the secondary rotation displacement matrix of the preset time period by using the second optimization algorithm to obtain the corresponding second rotation displacement matrix.

[0051] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0052] By setting multiple multi-view exposure X-ray images, based on the fact that there must be a time sequence in the actual imaging exposure time of the same target object in actual X-ray imaging, it is realized that there is no need to synchronize multiple dynamic X-ray imaging devices of the same specification, that is, when the target objects captured from multiple different perspectives are not the target objects at the same moment, based on different perspectives, the position information is optimized respectively according to the first optimization algorithm. At the same time, when the target object is in a non-static state, the second optimization algorithm is used to optimize the position information of each perspective based on the time sequence. By collecting the images of the moments before and after the current preset time period perspective to optimize and compensate for the error of depth calculation, the error of tracking and positioning only from one perspective is eliminated, and the pose optimization of the target object in the depth direction is realized. Finally, the precise positioning of the target object in the dynamic time sequence images is realized. Description of the Drawings

[0053] Figure 1 According to an embodiment of the present application, a flowchart of multi-view shooting and positioning is shown;

[0054] Figure 2 According to an embodiment of the present application, a schematic diagram of obtaining an X-ray image sequence by multi-view shooting is shown;

[0055] Figure 3 According to an embodiment of the present application, a schematic diagram of the time sequence of multi-view shooting is shown;

[0056] Figure 4 According to an embodiment of the present application, a flowchart of the first optimization algorithm is shown;

[0057] Figure 5 According to an embodiment of the present application, a flowchart of the first optimization algorithm is shown.

[0058] Figure 6 According to an embodiment of the present application, a schematic diagram of X-ray shooting in the Z-axis direction of the detector's own coordinate system is shown.

[0059] Figure 7 According to an embodiment of the present application, a schematic diagram of a multi-view exposure X-ray image positioning device is shown. Detailed Embodiments

[0060] Unless otherwise defined, technical terms or scientific terms used in this specification and claims shall have the ordinary meanings as understood by those of ordinary skill in the technical field to which the present invention pertains.

[0061] In the description of the present invention, it should be understood that the orientation or positional relationships indicated by the terms "center", "longitudinal", "transverse", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. are based on the orientation or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as a limitation to the present invention.

[0062] In addition, the terms "first", "second", etc. are only used for descriptive purposes and should not be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first", "second", etc. may explicitly or implicitly include one or more of such features. In the description of the present invention, unless otherwise stated, the meaning of "a plurality of" is two or more.

[0063] The present invention will be described in detail below with reference to the drawings and in conjunction with embodiments. It should be noted that in the specific description of these embodiments, for the sake of concise description, this specification cannot describe all features of the actual embodiments in detail.

[0064] As Figure 1 shown, a flowchart of multi-view shooting and positioning is shown. Specifically, it includes the following steps:

[0065] Step 100: Obtain the volume data information of the target object. It can be understood that obtaining the volume data information of the target joint includes, but is not limited to, tomographic scan images (CT), magnetic resonance scan images (MR), three-dimensional surface models, etc. According to the volume data information, the static three-dimensional geometric structure features of the target joint or the internal bone texture information can be obtained simultaneously. This volume data information has nothing to do with multi-view shooting and is necessary preparatory data before tracking. As long as it meets the condition of the same target object, it can be a bone joint, etc., which is not limited herein.

[0066] Step 200: According to the volume data information, X-ray images corresponding to multiple perspectives are sequentially captured in time series based on a preset time period. It can be understood that in the case of capturing the same target object, the target object is set to be capable of being X-rayed at different times from different angles to capture different X-ray images corresponding to the same preset time period. The change in the angle of the target object can achieve the capture of X-ray images based on different positions, thereby collecting information of the target object at different angles and enabling precise positioning of the target object in space.

[0067] In the above step 200, a plurality of X-ray detectors and a plurality of receiving plates are arranged at the relative positions between different shooting perspectives; the relative positions between different shooting perspectives are the relative positions of the emission sources of different groups of X-ray emitters and the receiving plates. Multiple-perspective X-ray images are obtained by shooting with different groups of X-ray emitters and receiving plates. It can be understood that the number and positions of the X-ray generators and the receiving plates are in a spatially relative relationship, where each receiving plate can receive the light emitted by the X-ray generator corresponding to its position one by one. Within the same preset time period, each receiving plate receives an X-ray image of one perspective, and the images of each perspective may not be received at the same moment.

[0068] In some embodiments of the present application, as Figure 2 shown, a schematic diagram of obtaining an X-ray image sequence by multi-perspective shooting is shown. Specifically, under a multi-perspective shooting device, taking the automatic registration and positioning of a target object as an example, first, it is necessary to obtain the X-ray image and CT volume data of the imaging area of the subject target object. This process can use two C-arm X-ray machines to shoot the imaging part of the subject to obtain multiple emission sources and receiving plates to achieve multi-perspective synchronous dynamic X-ray images. Among them, there are multiple shootings at multiple angles of multiple receiving plates in space to obtain X-ray images of multiple different shooting perspectives;

[0069] According to the time range of the preset time period, the emission sources and receiving plates are set to achieve shooting of all perspectives, so that each group of several X-ray images are taken within the same time period after each X-ray machine is started; the dynamic shooting can be continuous shooting of multiple X-ray images to obtain the image sequence data information of the target object.

[0070] Using several sets of X-ray generators and receiving plates, multi-perspective X-ray images of the target object are taken, and the image sequence (X view_1 , X view_1 , …, X view_end ) is obtained, and the time information (t view_1 , t view_1 , …, t view_end ) of each perspective image is obtained. For devices with the same shooting rate specification, their images can be divided into image groups under different time periods, that is, {X t_0 , X1, … Xt_1 , …, X t_end}, where the i-th group of images for the preset time period includes That is, the images of the last receiving plate from view 1 to view_end taken at different times in the i-th time period, where view_1 to view_end are arranged in the order of shooting in each time period.

[0071] Specifically, X t_0 The preset time period is in the initial scanning period, and the target object is in a stationary state during this preset period. The X-ray image taken at this time is the position positioning of the target object at the initial moment.

[0072] Specifically, X t_end The preset time period is in the end scanning period, and the target object is in a stationary state during this preset period. The X-ray image taken at this time is the position positioning of the target object at the end moment.

[0073] Specifically, In any preset time period, the target object is in a non-stationary state, and the target object can rotate or move along various angles of the device.

[0074] Step 300: When the target object is in a stationary state, receive the X-ray images of all views corresponding to the stationary state moment to generate a first image sequence, and obtain a first rotation displacement matrix according to the first optimization algorithm. It can be understood that when the target object is in a stationary state, the imaging of the target object can be realized within the same preset time period, that is, within the initial period or the end period, and the imaging of the target object is realized along all views of the set receiving plate of the target object to generate a first X-ray image sequence.

[0075] In some embodiments of the present application, the first image sequence includes the image sequences of the initial period and the end period. The first image sequences for the preset time periods of t_0 and t_end are respectively: Image sequence, the target object is at the current position and in a stationary state. The X-ray images of all receiving plates are collected in this part to form a first image sequence. The rotation displacement matrix T at the initial moment is located by using the first optimization algorithm t_0 and T t_end .

[0076] Specifically, as Figure 3 shown, a schematic diagram of a time sequence of multi-view shooting is shown. In all preset time periods corresponding to t_0 to t_end, multi-view shooting is realized sequentially according to the time sequence and the order of shooting views.

[0077] In some embodiments of the present application, set T t_0 and T 1_end to be 4X4 matrices respectively, that is In the formula, R is the rotation matrix and V is the displacement matrix. Specifically, T t_0 and T t_end For each image sequence at any moment, the rotation displacement matrix of the object needs to be finally calculated, T = T4×4,

[0078] That is This matrix contains six translation vectors and rotation elements (x, y, z, γ, α, β);

[0079] Among them, R 3×3 is the rotation matrix R related to three axes a × a = R γ *R α *R β ; V1x3 is the translation vector along three axes

[0080] Step 400: When the target object is in a non - stationary state, receive the X - ray images from the first perspective to the last perspective of a preset time period in chronological order as the second image sequence, and process the second image sequence to obtain the second rotation matrix. It can be understood that when the target object is in a non - stationary state, the corresponding preset time period is to obtain the dynamic target pose at the perspectives from t_2 to t_end - 1 to achieve the tracking and positioning of the target object.

[0081] In the above step 400, when the reception of the second image sequence is completed, generate the secondary rotation displacement matrices for each perspective of the corresponding preset time period according to the first optimization algorithm; use the second optimization algorithm to update the secondary rotation displacement matrices of the preset time period to obtain the corresponding second rotation displacement matrix. It can be understood that for the process of dynamically photographing the image sequence of the target object, at least two optimizations are used to obtain the position information of the target object. Among them, in the first optimization process, only the image of one perspective is used for optimization, and in the second optimization, the images at the previous and subsequent moments are used to optimize the pose in the depth direction.

[0082] In a possible implementation manner of the present application, generate the matrix T corresponding to the second position first It can be realized by simulated annealing or particle swarm optimization algorithm or other existing algorithms that can realize positioning, which is not limited here.

[0083] In some embodiments of the present application, such as Figure 4As shown, a flowchart of a first optimization algorithm is presented, specifically including: implementing single-view X-ray image tracking according to the first optimization algorithm when the target object is in a stationary state or a non-stationary state. Taking view1 as an example during the preset time period t_i, when the target object is in a non-stationary state during the preset time period t_i, the optimization process can be achieved as follows:

[0084] Step 110: Preset that the target object moves closer to the target position marked as the first position, such that the projection of the target object along the projection direction from the emission source to the receiving plate approaches the true image X of the target object view_1 , and calculate the first similarity S1 between the projection of the target object and the true image X view_1 ;

[0085] Step 210: Select a second position that does not coincide with the previous position, generate a primary rotation displacement matrix T corresponding to the second position first , and re-project according to the second position and calculate the second similarity S2; determine whether S1 is less than S2;

[0086] If so, accept the current position T first , and enter Step 310;

[0087] If not, enter Step 410;

[0088] Step 310: Generate a secondary rotation displacement matrix T according to T first ; second ;

[0089] Step 410: Obtain the number of times of re-calculating T_ first , and determine whether the preset iteration condition is met;

[0090] If so, accept the current position T_ first， and enter Step 310;

[0091] If not, return to Step 210.

[0092] In some embodiments of the present application, the preset iteration conditions include being greater than or equal to exceeding the preset calculation duration, or the similarity meeting the preset similarity threshold condition, or the number of repeated calculations reaching the preset threshold, etc., which are not limited herein. Through the first optimization algorithm, the final T first is the displacement matrix obtained by the initial positioning under the view1 perspective during the preset time period t_i.

[0093] In some embodiments of the present application, the comparison between S1 and S2 can be achieved by calculating the contour coincidence degree, feature point information similarity, normalized mutual information, and image structure similarity extracted, which are not limited herein.

[0094] In some embodiments of the present application, the generation of several point positions is implemented based on simulated annealing or particle swarm optimization algorithms, or it can also be other algorithms that can achieve position generation, which are not limited herein.

[0095] In step 300 above, when the target object is in a stationary state, based on the Figure 4 first optimization algorithm flowchart as shown, the generation of T t_0 and T t_end of the first rotation displacement matrix is achieved.

[0096] In step 400 above, the secondary rotation displacement matrix for a preset time period is updated using a second optimization algorithm to obtain the corresponding second rotation displacement matrix. Among them, the second optimization algorithm.

[0097] Specifically, as Figure 5 shown, a schematic diagram of the second optimization algorithm is shown, which is applicable to the positioning of the target object at any perspective during any time period from t_1 to t_end-1, that is, when the target object is in a non-stationary state.

[0098] Step 120: Based on the position perspective corresponding to the secondary rotation displacement matrix, taking the poses of other perspectives as references, calculate the displacement in the Z-axis direction and the rotation values N1 around the X and Y axes corresponding to matrix T ave ;

[0099] Step 220: Fix the displacement in the Z-axis direction and the rotation values N1 around the X and Y axes, select a second position, generate the matrix T` first corresponding to the second position, and re-project according to the second position and calculate the displacement in the Z-axis direction and the rotation values N2 around the X and Y axes; determine whether the similarity S ave corresponding to the generated T ave is less than the similarity S` first corresponding to T` firs ;

[0100] If so, accept the displacement in the Z-axis direction and the rotation values N1 around the X and Y axes, and enter step 320;

[0101] If not, enter step 420;

[0102] Step 320: Set the matrix T` first to the matrix T` final ;

[0103] Step 420: Obtain the number of times of updating and calculating T` first , and determine whether the preset iteration condition is satisfied;

[0104] If so, accept the current position T` first , and enter step 320;

[0105] Otherwise, return to step 220.

[0106] In some embodiments of the present application, taking the poses of other perspectives as references includes: obtaining the average value of the pose of the next perspective at the previous preset time and the pose of the next perspective at the current first preset time period according to the position of the first perspective in the current first preset time period;

[0107] Convert the average value to the first perspective and replace the displacement in the Z-axis direction and the rotations around the X and Y axes in the detector coordinate system of the first perspective of the secondary rotation displacement matrix. It can be understood that, in some embodiments of the present application, for the image of view_1, the average pose of view_2 is determined as the pose in the view_2 perspective, and this pose is fixed and the rotation displacement matrix in view_1 is iteratively optimized again using the first optimization algorithm For view_i (where view_i < view_end), the average pose of view_i + 1 is determined as the pose in the view_2 perspective, and this pose is fixed and the rotation displacement matrix in view_i is iteratively optimized again using the optimization algorithm For the view_end perspective, the average pose of view_1 is determined as the pose in the view_1 perspective, and this pose is fixed and the rotation displacement matrix in view_end is iteratively optimized again using the first optimization algorithm As Figure 6 shown, a schematic diagram of X-ray shooting in the Z-axis direction of the detector's own coordinate system is shown. Specifically, fixing the displacement in the Z-axis direction and the rotations around the X and Y axes includes: obtaining the matrix based on the position in the first preset time period as: T = T4×4, that is: This matrix contains six translation and rotation elements (x, y, z, γ, α, β);

[0108] Among them, R 3×3 is the rotation matrix R related to the three axes R a × a = R γ *R α *R β ; V1x3 is the translation vector along the three axes

[0109] It can be understood that the second optimization algorithm is used to optimize the displacement in the X and Y axis directions and the rotation around the Z axis until the preset iteration condition is met.

[0110] Step 500: Based on the first rotation displacement matrix and several second rotation matrices corresponding to the image sequence in the non - stationary state, achieve the dynamic positioning of the X - ray image of the target object. It can be understood that the first rotation displacement matrix corresponds to the position information of the target object in the stationary state, that is, at the start and end of the scanning period. The several second rotation matrices include the non - stationary image sequences after the first image sequence. Processed according to the second image sequence, finally achieve the multi - sequence and multi - perspective X - ray image positioning in the stationary and non - stationary states.

[0111] In some embodiments of the present application, a multi - perspective exposure X - ray image positioning device is also proposed, which specifically includes:

[0112] Data acquisition module: used to acquire the volume data information of the target object;

[0113] Data collection module: According to the volume data information, take synchronous dynamic X - ray images corresponding to multiple perspectives through time series shooting within a preset time period;

[0114] The first data receiving module: When the target object is in a stationary state, receive the X - ray images of all perspectives at the corresponding moment in the stationary state to generate a first image sequence, and obtain the first rotation displacement matrix according to the first optimization algorithm;

[0115] The second data receiving module: When the target object is in a non - stationary state, receive the X - ray images from the first perspective to the last perspective in the preset time period in the order of time series as the second image sequence, and perform optimization processing on the second image sequence to obtain the second rotation displacement matrix;

[0116] Positioning module: Based on the first rotation displacement matrix and several second rotation matrices corresponding to the image sequence in the non - stationary state, achieve the dynamic positioning of the X - ray image of the target object.

[0117] Specifically, the second data receiving module further includes:

[0118] The first optimization unit of the second data: When the reception of the second image sequence is completed, generate a secondary rotation displacement matrix corresponding to the preset time period according to the first optimization algorithm;

[0119] The second optimization unit of the second data: Use the second optimization algorithm to update the secondary rotation displacement matrix of the preset time period to obtain the corresponding second rotation displacement matrix.

[0120] A multi - perspective exposure X - ray image positioning method provided by an embodiment of the present invention is applied to a multi - perspective exposure X - ray image positioning system, which will not be elaborated here.

[0121] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram may represent a module, a segment of a program, or a portion of an instruction, which contains one or more executable instructions for implementing the specified logical function. In some alternative implementations, the functions noted in the blocks may occur in a different order than that noted in the accompanying drawings. For example, two consecutive blocks may actually be executed substantially in parallel, or they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system that performs the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0122] The above are only the preferred embodiments of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions falling within the idea of the present invention belong to the protection scope of the present invention. It should be pointed out that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. A multi-view exposure X-ray image positioning method, characterized in that, The method described above includes: Obtaining the volume data information of the target object; According to the volume data information, taking X-ray images corresponding to multiple perspectives in sequence based on a preset time period according to the time series; When the target object is in a static state, receiving the X-ray images of all perspectives corresponding to the static state moment to generate a first image sequence, and obtaining a first rotation displacement matrix according to the first optimization algorithm; When the target object is in a non-static state, receiving the X-ray images of the first perspective to the last perspective of the preset time period in sequence according to the time series as a second image sequence, and processing the second image sequence to obtain a number of second rotation matrices; according to the first rotation displacement matrix and the number of second rotation matrices corresponding to the image sequence in the non-static state, realizing the dynamic positioning of the X-ray images of the target object; wherein, processing the second image sequence to obtain a second rotation displacement matrix includes: when the reception of the second image sequence is completed, generating secondary rotation displacement matrices corresponding to each perspective of the preset time period based on the first optimization algorithm; Updating the secondary rotation displacement matrix of the preset time period by using a second optimization algorithm to obtain the corresponding second rotation displacement matrix; The first optimization algorithm includes: Step 110: Preset a first position where the projection of the target object along the projection direction from the emission source to the receiving flat plate approaches the true image of the target object, and calculate the first similarity S1 between the projection of the target object and the true image X view_1 of the first similarity S1; Step 210: Select a second position that does not coincide with the aforementioned position, generate a matrix T corresponding to the second position first , and re-project according to the second position and calculate a second similarity S2; determine whether S1 is less than S2; If so, accept the current position T first , and proceed to step 310; If not, then enter step 410; Step 310: Set the matrix T first to matrix T second ; Step 410: Obtain the number of times of updated calculation of T first and determine whether it meets the preset iteration condition; If so, accept the current position T first； If not, then return to step 210; Updating the secondary rotation displacement matrix of the preset time period by using a second optimization algorithm to obtain the corresponding second rotation displacement matrix includes: Step 120: Based on the position perspective corresponding to the secondary rotation displacement matrix, take the poses of other perspectives as references, and calculate the matrix T corresponding to the displacement in the Z-axis direction and the rotation values N1 around the X and Y axes ave ; Step 220: Fix the displacement in the Z-axis direction and the rotation values N1 about the X and Y axes, select a second position, and generate a matrix T` corresponding to the second position first , and re-project according to the second position and calculate the displacement in the Z-axis direction and the rotation values N2 about the X and Y axes; determine whether the similarity S ave correspondingly generated by T ave is less than the similarity S` first correspondingly generated by T` first ; If so, then accept the displacement in the Z-axis direction and the rotation values N1 around the X and Y axes, and enter step 320; If not, then enter step 420; Step 320: Set the matrix T` first to the matrix T` final ; Step 420: Obtain the number of times of updated calculation of T` first , and determine whether the preset iteration condition is satisfied; If so, accept the current position T` first ; If not, then return to step 220.

2. The multi-perspective exposure X-ray image positioning method according to claim 1, wherein, Before taking X-ray images corresponding to multiple perspectives in sequence based on the preset time period includes: Setting a number of X-ray detectors and a number of receiving plates at the relative positions between different shooting perspectives; The relative positions between different shooting perspectives are the relative positions of the emission sources of different groups of X-ray emitters and the receiving plates, and the X-ray images of multiple perspectives are obtained by shooting with different groups of X-ray emitters and the receiving plates.

3. A multi-view exposure X-ray image positioning method according to claim 1, characterized in that The situation where the target object is in a static state includes that the target object corresponds to being in the scanning start period or the scanning end period.

4. A multi-view exposure X-ray image positioning method according to claim 1, characterized in that Taking the poses of other perspectives as references includes: According to the position of the first perspective of the current first preset time period, obtaining the average value of the pose of the next perspective of the previous preset time period of the current first preset time period and the pose of the next perspective of the current first preset time period; Converting the average value to the first perspective and replacing the displacement in the Z-axis direction and the rotation around the X and Y axes in the detector coordinate system of the first perspective of the secondary rotation displacement matrix.

5. A multi-view exposure X-ray image positioning method according to claim 1, characterized in that Fixing the displacement in the Z-axis direction and the rotation values around the X and Y axes includes: Based on the position of the current first preset time period, the obtained matrix is: T = T4×4, that is This matrix contains six translation vectors and rotation elements (x, y, z, γ, α, β); where R 3×3 is the rotation matrix R related to three axes a × a =R γ *R α *R β ; V 1x3 is the translation vector along three axes 6. A multi-view exposure X-ray image positioning device, characterized in that, The device described above includes: A data acquisition module: used to obtain the volume data information of the target object; Data acquisition module: According to the volume data information, sequentially capture X-ray images corresponding to multiple perspectives in a time series based on a preset time period; First data receiving module: When the target object is in a static state, receive the X-ray images of all perspectives at the corresponding moment of the static state to generate a first image sequence, and obtain a first rotation displacement matrix based on the first optimization algorithm; Second data receiving module: When the target object is in a non-static state, receive the X-ray images of the first perspective to the last perspective in the preset time period in time series order as a second image sequence, and perform optimization processing on the second image sequence to obtain a plurality of the second rotation displacement matrices; Positioning module: According to the first rotation displacement matrix and the plurality of the second rotation matrices corresponding to the image sequence in the non-static state, realize the dynamic positioning of the X-ray images of the target object to realize the dynamic positioning of the X-ray images of the target object; Wherein, the second data receiving module further includes: First second-data optimization unit: When the reception of the second image sequence is completed, generate a secondary rotation displacement matrix corresponding to the preset time period based on the first optimization algorithm; Second second-data optimization unit: Update the secondary rotation displacement matrix of the preset time period by using a second optimization algorithm to obtain the corresponding second rotation displacement matrix; The first optimization algorithm includes: Step 110: Preset a first position where the projection of the target object along the projection direction from the emission source to the receiving flat plate approaches the real image of the target object, and calculate the first similarity S1 between the projection of the target object and the real image X view_1 of the first similarity S1; Step 210: Select a second position that does not coincide with the foregoing position, generate a matrix T corresponding to the second position first , and re-project according to the second position and calculate a second similarity S2; determine whether S1 is less than S2; If so, accept the current position T first , and proceed to step 310; Otherwise, go to step 410; Step 310: Set the matrix T first as matrix T second ; Step 410: Obtain the number of times of updated calculation T first and determine whether a preset iteration condition is met; If so, accept the current position T first； Otherwise, return to step 210; Updating the secondary rotation displacement matrix of the preset time period by using a second optimization algorithm to obtain the corresponding second rotation displacement matrix includes: Step 120: Based on the position perspective corresponding to the secondary rotation displacement matrix, taking the poses of other perspectives as references, calculate the matrix T corresponding to the displacement in the Z-axis direction and the rotation values N1 around the X and Y axes ave ; Step 220: Fix the displacement in the Z-axis direction and the rotation values N1 around the X and Y axes, select a second position, and generate a corresponding matrix T` first , and re-project according to the second position and calculate the displacement in the Z-axis direction and the rotation values N2 around the X and Y axes; determine whether the similarity S ave correspondingly generated by T ave is less than the similarity S` first correspondingly generated by T` first ; If so, accept the displacement in the Z-axis direction and the rotation values N1 around the X and Y axes, and go to step 320; Otherwise, go to step 420; Step 320: Set the matrix T` first to the matrix T` final ; Step 420: Obtain the number of times of updated calculation of T` first , and determine whether the preset iteration condition is satisfied; If so, accept the current position T` first ; Otherwise, return to step 220.

Images