Image acquisition and reconstruction method, device, electronic device and storage medium

Abstract

The present invention provides a method, device, electronic device and storage medium for image acquisition and reconstruction, the method comprising: starting a tomographic fusion system, and controlling a flat panel detector to acquire multiple projection images of a target imaging object, the target imaging object being placed above the flat panel detector; performing a derivative operation on the projection image to obtain a first gradient projection image, performing a back-projection operation on the first gradient projection image to obtain a gradient reconstruction image, performing a Hilbert transform on the gradient reconstruction image to obtain a first intermediate image; performing a local artifact reduction operation on the projection image and the corresponding first gradient projection image to obtain a second gradient projection image, performing back-projection, global artifact reduction and Hilbert transform on the second gradient projection image to obtain a second intermediate image; and fusing the first and second intermediate images to obtain a reconstructed image. Thus, overshoot / undershoot artifacts can be corrected.

Description

Technical Field

[0001] The present invention relates to the field of medical imaging, and in particular to a method, device, electronic equipment and storage medium for image acquisition and reconstruction. Background Art

[0002] Tomosynthesis based on flat panel detectors 2 has a wide range of applications in the field of medical imaging. It is similar to traditional CT (Computed Tomography), CBCT (Cone beam CT), etc. Its basic principles are as follows: Figure 1 As shown, when in use, the light source 1 (eg, an X-ray tube, etc.) may be in different positions (eg, Figure 1 The flat panel detector 2 is a device that can detect position A, position B, and position C in the image, and emits X-rays to the target imaging object (for example, the patient's body, etc.) at each position. It can be understood that when the light source 1 is located at different positions, then for the same area of ​​the target imaging object, the angles of the X-rays emitted by the light source 1 are different. The flat panel detector 2 can obtain projections of the target imaging object at multiple angles. Therefore, based on the reconstruction algorithm, the projection data and the geometric structure information can be reconstructed into the original three-dimensional slice image of the object.

[0003] In practice, the position of light source 1 is limited, so the tomographic fusion system is limited-angle imaging, resulting in less data sampling. The FBP (Filtered Back Projection) image reconstruction algorithm is a common reconstruction algorithm, which can usually only obtain a stable numerical solution under the condition of full-angle scanning. However, in practice, limited-angle imaging will cause black or white edge artifacts to appear at the edges of high-density objects (such as bones, metals, etc.) and the junctions of tissues with different densities (such as lungs and diaphragms) in the reconstructed image, which are called upstroke or downstroke artifacts. Under the conventional observation window width, downstroke or upstroke artifacts will cause local grayscale shift of tissues and lesions, masking the lesions, increasing the difficulty of doctors' reading of the film, and leading to missed diagnosis.

[0004] Therefore, in the tomosynthesis system, how to correct the overshoot / undershoot artifacts becomes an urgent problem to be solved. Summary of the invention

[0005] The object of the present invention is to provide a method, device, electronic equipment and storage medium for image acquisition and reconstruction.

[0006] In order to achieve one of the above-mentioned purposes of the invention, an embodiment of the present invention provides an image acquisition and reconstruction method for a tomosynthesis system, wherein a flat panel detector is provided in the tomosynthesis system, and the flat panel detector can acquire projection images; the method comprises the following steps: starting the tomosynthesis system and controlling the flat panel detector to acquire multiple projection images of a target imaging object, wherein the target imaging object is placed above the flat panel detector; performing the following operations on each projection image: performing a derivative operation on the projection image to obtain a first gradient projection image, performing a back-projection operation on the first gradient projection image to obtain a gradient reconstruction image, and performing a Hilbert transform on the gradient reconstruction image to obtain a first intermediate image ; The following operations are performed on each projection image: the projection image and the corresponding first gradient projection image are subjected to a local artifact reduction operation to obtain a second gradient projection image, and the second gradient projection image is subjected to back-projection, global artifact reduction and Hilbert transformation to obtain a second intermediate image ; From the first intermediate image Extract the details of the target imaging object and combine the details with the second intermediate image Perform image fusion to obtain the reconstructed image .

[0007] As a further improvement of an embodiment of the present invention, the tomographic fusion system further includes: a light source, which is located above the flat-panel detector and can move relative to the flat-panel detector; the three-dimensional coordinate system based on the tomographic fusion system is: the plane where the flat-panel detector is located is the XOY plane, the Z axis is perpendicular to the XOY plane, and the positive direction of the Z axis is the direction of the flat-panel detector toward the light source; the "starting the tomographic fusion system and controlling the flat-panel detector to obtain multiple projection images of the target imaging object" specifically includes: starting the tomographic fusion system, controlling the light source to move in the YOZ plane, and emitting X-rays to the target imaging object, and forming a projection on the flat-panel detector, and controlling the flat-panel detector to obtain multiple projection images ;in, is the angle between the line between the light source and point O and the Z axis, and when the position of the light source is different, the corresponding The method of “deriving the projection image to obtain a first gradient projection image, performing a back-projection operation on the first gradient projection image to obtain a gradient reconstruction image, and performing a Hilbert transform on the gradient reconstruction image to obtain a first intermediate image” is also different; "Specifically includes: along the movement direction of the light source, projecting the image Perform a derivative operation to obtain the first gradient projection map , where the projected image The angle between the line between the light source and point O and the Z axis is When the flat panel detector acquires the projection image, To project an image The projection value corresponding to the area with X coordinate u and Y coordinate v in the first gradient projection map By Angle Back-project to the image domain and obtain the gradient reconstruction map , where at the starting position, the angle between the line between the light source and point O and the Z axis is ; At the end position, the angle between the line between the light source and point O and the Z axis is ; Reconstruct the gradient map Perform Hilbert transform to get the first intermediate image .

[0008] As a further improvement of an embodiment of the present invention, the “performing a local artifact reduction operation on the projection image and the corresponding first gradient projection image to obtain a second gradient projection image” specifically includes: A set E of multiple edge points of the target soft tissue is extracted, and the set E and the first gradient projection map are Eliminate sharp edges to obtain the second gradient projection map .

[0009] As a further improvement of an embodiment of the present invention, the “set E and the first gradient projection map The operation of eliminating sharp edges specifically includes: based on the set E, the first gradient projection map The gradient of the corresponding pixel is set to 0.

[0010] As a further improvement of an embodiment of the present invention, the “from the projected image Extracting a set E of multiple edge points of the target soft tissue to be extracted specifically includes: segmenting the lung area from the projection image , from the lung area A set E of multiple edge points of the diaphragm, heart and aortic arch is extracted.

[0011] As a further improvement of an embodiment of the present invention, the “back-projecting, global artifact reduction and Hilbert transforming the second gradient projection image to obtain a second intermediate image” "Specifically includes: the second gradient projection map Back-projected to the image domain at an angle θ to obtain a gradient reconstruction map with local artifact reduction ; Generate gradient reconstruction map ,in, , Represents the input image Take the nth percentile; generate the second intermediate image .

[0012] As a further improvement of an embodiment of the present invention, the “from the first intermediate image Extract the details of the target imaging object and combine the details with the second intermediate image Perform image fusion to obtain the reconstructed image "Specifically includes: for the first intermediate image Perform smoothing to get the base layer , the second intermediate image Perform smoothing to get the base layer , get the detail layer , reconstruct the image .

[0013] The embodiment of the present invention further provides an apparatus for image acquisition and reconstruction of a tomosynthesis system, wherein the tomosynthesis system is provided with a flat panel detector, and the flat panel detector can acquire a projection image; the apparatus comprises the following modules:

[0014] A start module, used to start the tomosynthesis system and control the flat panel detector to acquire a plurality of projection images of a target imaging object, wherein the target imaging object is placed above the flat panel detector;

[0015] The first processing module is used to perform the following operations on each projection image: perform a derivative operation on the projection image to obtain a first gradient projection image, perform a back-projection operation on the first gradient projection image to obtain a gradient reconstruction image, and perform a Hilbert transform on the gradient reconstruction image to obtain a first intermediate image. ;

[0016] The second processing module is used to perform the following operations on each projection image: perform a local artifact reduction operation on the projection image and the corresponding first gradient projection image to obtain a second gradient projection image, and perform back-projection, global artifact reduction and Hilbert transformation on the second gradient projection image to obtain a second intermediate image ;

[0017] Fusion module, used to transform the first intermediate image Extract the details of the target imaging object and combine the details with the second intermediate image Perform image fusion to obtain the reconstructed image .

[0018] An embodiment of the present invention further provides an electronic device, comprising: a memory for storing executable instructions; and an operator for implementing the above-mentioned image acquisition and reconstruction method when executing the executable instructions stored in the memory.

[0019] The embodiment of the present invention further provides a computer-readable storage medium storing executable instructions for causing an operator to implement the steps of the above-mentioned image acquisition and reconstruction method when executed.

[0020] Compared with the prior art, the technical effect of the present invention is that: the embodiment of the present invention provides a method, device, electronic device and storage medium for image acquisition and reconstruction, the method comprising: starting a tomographic fusion system, and controlling a flat-panel detector to obtain multiple projection images of a target imaging object, the target imaging object being placed above the flat-panel detector; performing a derivative operation on the projection image to obtain a first gradient projection map, performing a back-projection operation on the first gradient projection map to obtain a gradient reconstruction map, performing a Hilbert transform on the gradient reconstruction map to obtain a first intermediate image; performing a local artifact reduction operation on the projection image and the corresponding first gradient projection map to obtain a second gradient projection map, performing back-projection, global artifact reduction and Hilbert transform on the second gradient projection map to obtain a second intermediate image; fusing the first and second intermediate images to obtain a reconstructed image. Thus, overshoot / undershoot artifacts can be corrected. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 is a schematic structural diagram of a tomosynthesis system in an embodiment of the present invention;

[0022] Figure 2 is a flow chart of the method for image acquisition and reconstruction in an embodiment of the present invention;

[0023] Figure 3 is an intermediate result image of global artifact reduction in an embodiment of the present invention;

[0024] Figure 4 is a reconstruction result diagram of the image fusion in an embodiment of the present invention;

[0025] Figure 5 is an intermediate result graph related to local artifact reduction in an embodiment of the present invention;

[0026] Figure 6 It is a comparison diagram of the effect of reducing local artifacts in the embodiment of the present invention. DETAILED DESCRIPTION

[0027] The present invention will be described in detail below in conjunction with the various embodiments shown in the accompanying drawings. However, these embodiments do not limit the present invention, and any structural, methodological, or functional changes made by a person skilled in the art based on these embodiments are all within the scope of protection of the present invention.

[0028] As used herein, terms indicating spatial relative positions such as "upper," "above," "lower," and "below" are used for the purpose of convenience to describe the relationship of one unit or feature relative to another unit or feature as shown in the accompanying drawings. Terms of spatial relative position may be intended to include different orientations of the device in use or operation in addition to the orientation shown in the drawings. For example, if the device in the figure is turned over, the units described as being "below" or "beneath" other units or features will be located "above" the other units or features. Thus, the exemplary term "below" can encompass both the above and below orientations. The device may be oriented in other ways (rotated 90 degrees or in other orientations), and the spatially relative descriptors used herein interpreted accordingly.

[0029] Embodiment 1 of the present invention provides an image acquisition and reconstruction method for a tomosynthesis system, wherein the tomosynthesis system is provided with a flat panel detector 2, and the flat panel detector 2 can acquire a projection image; here, the flat panel detector 2 can be an amorphous selenium flat panel detector or an amorphous silicon flat panel detector according to the principle, and can be an indirect conversion flat panel detector or a direct conversion flat panel detector according to the type. In the tomosynthesis system, a processor can be provided, and the image acquisition and reconstruction method can be executed by the processor;

[0030] like Figure 2 As shown, the following steps are included:

[0031] Step 201: Start the tomosynthesis system and control the flat panel detector 2 to obtain multiple projection images of a target imaging object, and the target imaging object is placed above the flat panel detector 2. Here, in the tomosynthesis system, a command input device can be provided, and a user can input a start command through the command input device. When the processor receives the start command, the tomosynthesis system will be started. It can be understood that when in use, the target imaging object (for example, a human body, etc.) needs to be placed above the flat panel detector 2.

[0032] Step 202: Perform the following operations on each projection image: perform a derivative operation on the projection image to obtain a first gradient projection image, perform a back-projection operation on the first gradient projection image to obtain a gradient reconstruction image, perform a Hilbert transform on the gradient reconstruction image to obtain a first intermediate image ;

[0033] Here, the Sobel operator, Robert operator, Prewitt operator, Laplacian operator or Canny operator can be used to implement the derivative operation. The principle of the back-projection operation is to evenly distribute the measured projection value to each point along the original projection path. After back-projecting the projection values ​​in all directions, the back-projected images at each angle are accumulated to infer the original image. The principle of the Hilbert transform is to convolve the signal s(t) with 1 / (πt) to obtain s'(t).

[0034] Here, in this step, the projection image will be subjected to derivative, backprojection and Hilbert transform operations. The order of these three operations can be determined according to actual needs, that is, the order of the three operations can be variable, for example, derivative → backprojection → Hilbert transform, derivative → Hilbert transform → backprojection, backprojection → derivative → Hilbert transform, backprojection → Hilbert transform → derivative, Hilbert transform → derivative → backprojection or Hilbert transform → backprojection → derivative.

[0035] Here, it can be understood that the first intermediate image is not artifact corrected, so in the first intermediate image Will include details in the target image.

[0036] Step 203: Perform the following operations on each projection image: perform a local artifact reduction operation on the projection image and the corresponding first gradient projection image to obtain a second gradient projection image, perform back-projection, global artifact reduction and Hilbert transform on the second gradient projection image to obtain a second intermediate image ;

[0037] Here, it can be understood that the second intermediate image After local and global artifact correction, in the second intermediate image In the process, details in the target image may be lost.

[0038] Step 204: From the first intermediate image Extract the details of the target imaging object and combine the details with the second intermediate image Perform image fusion to obtain the reconstructed image Here, the details in the target image are compared with the second intermediate image. The fusion is performed to reduce artifacts (including overshoot and undershoot) without losing details.

[0039] In this embodiment, the tomosynthesis system further includes: a light source 1, which is located above the flat panel detector 2 and can move relative to the flat panel detector 2;

[0040] The three-dimensional coordinate system based on the tomosynthesis system is: the plane where the flat panel detector 2 is located is the XOY plane, the Z axis is perpendicular to the XOY plane, and the positive direction of the Z axis is the direction of the flat panel detector 2 toward the light source 1;

[0041] The “starting the tomosynthesis system and controlling the flat panel detector 2 to acquire multiple projection images of the target imaging object” specifically includes: starting the tomosynthesis system, controlling the light source 1 to move in the YOZ plane, and emitting X-rays to the target imaging object, and forming a projection on the flat panel detector 2, and controlling the flat panel detector 2 to acquire multiple projection images ;in, is the angle between the line between light source 1 and point O and the Z axis, and when the position of the light source 1 is different, the corresponding are also different; here, in practice, a preset motion trajectory is first planned for light source 1 (the trajectory is located in the YOZ plane). In this trajectory, when light source 1 is located at different positions, the corresponding Also different, that is, you can use parameters , the position of light source 1 can be determined.

[0042] The method of “deriving the projection image to obtain a first gradient projection image, back-projecting the first gradient projection image to obtain a gradient reconstruction image, and performing Hilbert transform on the gradient reconstruction image to obtain a first intermediate image” "Specifically includes: along the movement direction of the light source 1, the projected image Perform a derivative operation to obtain the first gradient projection map , where the projected image The angle between the line between light source 1 and point O and the Z axis is When the projection image acquired by the flat panel detector 2 is To project an image The projection value corresponding to the area with X coordinate u and Y coordinate v in ;

[0043] The first gradient projection map By Angle Back-project to the image domain and obtain the gradient reconstruction map , where at the starting position, the angle between the line between light source 1 and point O and the Z axis is ; At the end position, the angle between the line between light source 1 and point O and the Z axis is Here, the light source 1 will move along a preset motion trajectory. It can be understood that the light source will move from the starting position to the end position.

[0044] Reconstructing the gradient map Perform Hilbert transform to get the first intermediate image .

[0045] In this embodiment, the “performing a local artifact reduction operation on the projection image and the corresponding first gradient projection image to obtain a second gradient projection image” specifically includes: A set E of multiple edge points of the target soft tissue is extracted, and the set E and the first gradient projection map are Eliminate sharp edges to obtain the second gradient projection map .

[0046] Here, sharp edges between soft tissues (e.g., diaphragm, heart, aortic arch, and lungs, etc.) can introduce large overshoot / undershoot artifacts in the reconstructed images.

[0047] This image acquisition and reconstruction method performs targeted local operations on such edges in the projection domain rather than the image domain, which has at least two advantages: (1) it can make the edges of soft tissues (especially the lungs, etc.) highly consistent in projection images at different angles and relatively easy to identify; (2) if back-projected into the image domain, due to the existence of limited-angle artifacts, these edges exist in a series of continuous layers in the Z direction and are difficult to completely remove.

[0048] Sharp edges in the first gradient projection Therefore, the sharp edges between soft tissues are eliminated (for example, the gradient is set to 0, etc.) in combination with the extracted edge E, and the second gradient projection image with local artifacts weakened is obtained. .

[0049] In this embodiment, the “set E and the first gradient projection map The operation of eliminating sharp edges specifically includes: based on the set E, the first gradient projection map The gradient of the corresponding pixel is set to 0.

[0050] In this embodiment, the “from the projected image Extracting a set E of multiple edge points of the target soft tissue to be extracted specifically includes: segmenting the lung area from the projection image , from the lung area A set E of multiple edge points of the diaphragm, heart and aortic arch is extracted.

[0051] Here, the lungs contain a large amount of extremely low-density air, and in the projection image, the boundary between the lungs and soft tissues is often accompanied by a sharp change in grayscale value.

[0052] Here, we can use the prior knowledge of lung morphology to classify the lung regions The operation is performed and the edges of the diaphragm, heart and aortic arch are extracted, and then the points on the edges are obtained and formed into a set E.

[0053] Here, the projection domain weakens the sharp edges around the lungs (the edges between the diaphragm, heart, aortic arch and lungs). Such edges are easy to identify and have strong consistency in the projection domain. At the same time, there are no limited angle artifacts in the projection domain. Furthermore, the overlapping sharp edges on the projection map (strong edges around bones / blood vessels / organs) are globally weakened in the image domain. Such edges are difficult to extract in the projection map due to the overlap of the front and back layer information. Back-projecting the gradient projection map to the image domain can effectively separate the information.

[0054] In this embodiment, the “back-projecting, global artifact reduction and Hilbert transforming the second gradient projection image to obtain a second intermediate image” Specifically include:

[0055] The second gradient projection Back-projected to the image domain at an angle θ to obtain a gradient reconstruction map with local artifact reduction ;

[0056] Generate gradient reconstruction map ,in, , Represents the input image Take the nth percentile; here, since the information in the projection image overlaps front and back, such as the ribs and the trachea / blood vessels in the lungs overlap each other in the projection image, it is difficult to accurately extract this part of the sharp edge in the projection domain. Therefore, we further weaken this part of the strong edge with a large degree of overlap in the reconstruction image of the gradient projection image. Here, the nth percentile means: if a set of data is sorted from small to large and the corresponding cumulative percentile is calculated, the value of the data corresponding to a certain percentile is called the percentile of this percentile. For example, a set of m observations are arranged according to numerical size, and the value at the n% position is called the nth percentile.

[0057] Generate the second intermediate image .

[0058] Here, since the information in the projection image overlaps front and back, for example, the ribs and the trachea / blood vessels in the lungs overlap with each other in the projection image, it is difficult to accurately extract these sharp edges in the projection domain. Therefore, we further weaken these strong edges with a large degree of overlap in the reconstructed image of the gradient projection image.

[0059] This image acquisition and reconstruction method can adaptively reduce overshoot / undershoot artifacts. In local artifact reduction, the anatomical structure information of the lungs is used. These feature information are highly consistent between different people and can robustly extract the corresponding features. In global artifact reduction, strong edges are regarded as outliers, and the threshold of gradient truncation is set according to the percentile to avoid differences in the processing of different images caused by setting absolute thresholds.

[0060] In this embodiment, the “from the first intermediate image Extract the details of the target imaging object and combine the details with the second intermediate image Perform image fusion to obtain the reconstructed image Specifically include:

[0061] For the first intermediate image Perform smoothing to get the base layer , the second intermediate image Perform smoothing to get the base layer , get the detail layer , reconstruct the image .

[0062] This image acquisition and reconstruction method can act on the edges of high-density tissue and soft tissue, and restore details obscured by overshoot / undershoot artifacts; then, the image fusion method is used to extract detail information from the initial reconstructed image, maintaining the faint edges and detail information of the soft tissue boundaries (such as the pulmonary blood vessels near the diaphragm).

[0063] Here, in the process of global artifact reduction, the tissue information in the projection image overlaps front and back. For example, the ribs and lungs overlap front and back, and the trachea / blood vessels in the lungs also overlap with each other. It is difficult to accurately extract these sharp edges in the projection domain. Therefore, we back-project the gradient projection image to obtain a reconstructed image to separate the overlapping information front and back, and then further reduce these separated strong edges. Figure 3 The projection and reconstruction of a phantom are shown. Unprocessed gradient reconstruction Strong gradient information can be seen in the image. The corresponding first reconstructed image has serious black undershoot artifacts near the diaphragm and blood vessels, as shown by the arrows in the first intermediate image. The gradient image is truncated according to the adaptive threshold (n=5) to obtain a gradient reconstruction image with reduced global artifacts. , after Hilbert transform, the second intermediate image is obtained The corresponding undershoot artifact near the diaphragm is well suppressed, and the black and white edge artifacts at the clavicle and blood vessel edges are weakened, improving the overall image quality. However, the details within the artifact are lost and the image is distorted (as shown by the arrow in the second middle image).

[0064] In the process of detail fusion, we perform edge suppression operations on the gradient map. These operations force the gradient values ​​of sharp edges to be constant values, while ignoring the slow gradient changes caused by other overlapping tissues superimposed on the sharp edges. Therefore, in the image with reduced artifacts, the details of the area where the artifacts are located are distorted, such as Figure 4 As shown by the arrow in the reconstruction image with global artifact reduction. Through the smoothing operation, we can extract the base layer of the artifact reduction reconstruction image, which represents the correct general grayscale fluctuation of the tissue structure in the reconstructed image. After the same smoothing operation and subtracting it from the original image, we get the second intermediate image The detail layer represents the local grayscale changes of the image. By adding it to the base layer with reduced artifacts, we can fuse the detail information of the same scale back, such as Figure 4 As shown by the arrows in the fusion image with global artifact reduction, the vascular details within the diaphragm undershoot artifact are restored.

[0065] In the process of local artifact reduction, there are two benefits of reducing local artifacts in the projection domain: first, the lung edges are highly consistent in the projection images at different angles and are relatively easy to identify and extract; second, if back-projected into the image domain, these strong edges will form serious limited-angle artifacts, which exist in a series of continuous images in the z direction and are difficult to completely remove. Figure 5 The intermediate results of local artifact reduction are shown. The arrow points to the boundary between the right diaphragm and lung. The projection image can be seen. There are strong sharp edges at the edge of the inner lung, which are reflected in the gradient projection image. The pixel value of the corresponding area on is large, and we combine the extracted edge E in Eliminate sharp edges on the gradient map, thereby reducing local artifacts Eliminate sharp edges, and then reconstruct the fusion image at the output Reduces overshoot / undershoot artifacts caused by sharp edges. Figure 6 The effect of local artifact reduction of a subject is shown. The first column is the first intermediate image. The second column is the reconstruction image after global artifact reduction and detail fusion, and the third column is the reconstruction image after global and local artifact reduction and detail fusion, where the parameter n of global artifact reduction is set to 1. Compare the first intermediate image Although the reconstruction image with global artifact reduction has improved the white upstroke and black downstroke artifacts at the edges of blood vessels, diaphragm and bones to a certain extent, the local downstroke artifacts are still very serious, such as the artifacts at the edges of the left and right diaphragms, heart and aortic arch pointed out by the arrows. After local artifact reduction, the artifacts pointed out by the arrows have been greatly improved, and the image looks more natural.

[0066] Embodiment 2 of the present invention provides an image acquisition and reconstruction device for a tomosynthesis system. The tomosynthesis system is provided with a flat panel detector 2, and the flat panel detector 2 can acquire a projection image; the device comprises the following modules:

[0067] A start module, used to start the tomosynthesis system and control the flat panel detector 2 to obtain a plurality of projection images of a target imaging object, wherein the target imaging object is placed above the flat panel detector 2;

[0068] The first processing module is used to perform the following operations on each projection image: perform a derivative operation on the projection image to obtain a first gradient projection image, perform a back-projection operation on the first gradient projection image to obtain a gradient reconstruction image, and perform a Hilbert transform on the gradient reconstruction image to obtain a first intermediate image. ;

[0069] The second processing module is used to perform the following operations on each projection image: perform a local artifact reduction operation on the projection image and the corresponding first gradient projection image to obtain a second gradient projection image, and perform back-projection, global artifact reduction and Hilbert transformation on the second gradient projection image to obtain a second intermediate image ;

[0070] Fusion module, used to transform the first intermediate image Extract the details of the target imaging object and combine the details with the second intermediate image Perform image fusion to obtain the reconstructed image .

[0071] Embodiment 3 of the present invention provides an electronic device, including:

[0072] A memory for storing executable instructions;

[0073] The operator is used to implement the image acquisition and reconstruction method in the first embodiment when executing the executable instructions stored in the memory.

[0074] Embodiment 4 of the present invention provides a computer-readable storage medium storing executable instructions for causing an operator to execute the steps of the image acquisition and reconstruction method in embodiment 1.

[0075] It should be understood that although this specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each implementation mode may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

[0076] The series of detailed descriptions listed above are only specific descriptions of feasible implementation methods of the present invention. They are not intended to limit the scope of protection of the present invention. Any equivalent implementation methods or changes that do not deviate from the technical spirit of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for image acquisition and reconstruction for a tomosynthesis system, wherein the tomosynthesis system is provided with a flat panel detector (2), the flat panel detector (2) being capable of acquiring a projection image; the tomosynthesis system include: A light source (1), the light source (1) being located above a flat panel detector (2) and being capable of moving relative to the flat panel detector (2); the tomosynthesis system being based on a three-dimensional coordinate system in which the plane in which the flat panel detector (2) is located is the XOY plane, the Z axis is perpendicular to the XOY plane, and the positive direction of the Z axis is the direction in which the flat panel detector (2) is directed toward the light source (1); and characterized in that the system comprises the following steps: The tomosynthesis system is started, the light source (1) is controlled to move in the YOZ plane, emit X-rays to the target imaging object, and form a projection on the flat panel detector (2), and the flat panel detector (2) is controlled to acquire a plurality of projection images. ;in, is the angle between the line between the light source (1) and point O and the Z axis, and when the position of the light source (1) is different, the corresponding Also different; the target imaging object is placed above the flat panel detector (2); The following operations are performed on each projected image: along the moving direction of the light source (1), the projected image Perform a derivative operation to obtain the first gradient projection map , where the projected image The angle between the line between the light source (1) and point O and the Z axis is When the flat panel detector (2) acquires the projection image, To project an image The projection value corresponding to the area with X coordinate u and Y coordinate v in the first gradient projection map By Angle Back-project to the image domain and obtain the gradient reconstruction map , where, at the starting position, the angle between the line between the light source (1) and point O and the Z axis is ; At the end position, the angle between the line connecting the light source (1) and point O and the Z axis is ; Reconstruct the gradient map Perform Hilbert transform to get the first intermediate image ; The following operations are performed for each projected image: A set E of multiple edge points of the target soft tissue is extracted, and the set E and the first gradient projection map are Eliminate sharp edges to obtain the second gradient projection map , the second gradient projection map Back-projected to the image domain at an angle θ to obtain a gradient reconstruction map with local artifact reduction ; Generate gradient reconstruction map ,in, , Represents the input image Take the nth percentile; generate the second intermediate image ; For the first intermediate image Perform smoothing to get the base layer , the second intermediate image Perform smoothing to get the base layer , get the detail layer , reconstruct the image .

2. The method for image acquisition and reconstruction according to claim 1, It is characterized in that The "set E and the first gradient projection map The operation of eliminating sharp edges specifically includes: based on the set E, the first gradient projection map The gradient of the corresponding pixel is set to 0.

3. The method for image acquisition and reconstruction according to claim 2, It is characterized in that The "from the projected image Extracting a set E of multiple edge points of the target soft tissue to be extracted specifically includes: segmenting the lung area from the projection image , from the lung area A set E of multiple edge points of the diaphragm, heart and aortic arch is extracted.

4. A device for image acquisition and reconstruction of a tomosynthesis system, wherein the tomosynthesis system is provided with a flat panel detector (2), the flat panel detector (2) being capable of acquiring a projection image; the tomosynthesis system include: A light source (1), the light source (1) being located above a flat panel detector (2) and being capable of moving relative to the flat panel detector (2); the tomosynthesis system being based on a three-dimensional coordinate system in which the plane in which the flat panel detector (2) is located is the XOY plane, the Z axis is perpendicular to the XOY plane, and the positive direction of the Z axis is the direction in which the flat panel detector (2) is directed toward the light source (1); and characterized in that it comprises the following modules: A start module, used to start the tomosynthesis system, control the light source (1) to move in the YOZ plane, emit X-rays to the target imaging object, form a projection on the flat panel detector (2), and control the flat panel detector (2) to acquire a plurality of projection images ;in, is the angle between the line between the light source (1) and point O and the Z axis, and when the position of the light source (1) is different, the corresponding Also different; the target imaging object is placed above the flat panel detector (2); The first processing module is used to perform the following operations on each projection image: along the movement direction of the light source (1), Perform a derivative operation to obtain the first gradient projection map , where the projected image The angle between the line between the light source (1) and point O and the Z axis is When the flat panel detector (2) acquires the projection image, To project an image The projection value corresponding to the area with X coordinate u and Y coordinate v in the first gradient projection map By Angle Back-project to the image domain and obtain the gradient reconstruction map , where, at the starting position, the angle between the line between the light source (1) and point O and the Z axis is ; At the end position, the angle between the line connecting the light source (1) and point O and the Z axis is ; Reconstruct the gradient map Perform Hilbert transform to get the first intermediate image ; The second processing module is used to perform the following operations on each projection image: A set E of multiple edge points of the target soft tissue is extracted, and the set E and the first gradient projection map are Eliminate sharp edges to obtain the second gradient projection map , the second gradient projection map Back-projected to the image domain at an angle θ to obtain a gradient reconstruction map with local artifact reduction ; Generate gradient reconstruction map ,in, , Represents the input image Take the nth percentile; generate the second intermediate image ; Fusion module, used to fusion the first intermediate image Perform smoothing to get the base layer , the second intermediate image Perform smoothing to get the base layer , get the detail layer , reconstruct the image .

5. An electronic device, It is characterized in that include: A memory for storing executable instructions; An operator is used to implement the image acquisition and reconstruction method according to any one of claims 1 to 3 when executing the executable instructions stored in the memory.

6. A computer-readable storage medium, It is characterized in that Executable instructions are stored, which are used to cause an operator to implement the steps of the method for image acquisition and reconstruction according to any one of claims 1 to 3 when executed.

Images