A geometric correction method, image reconstruction method and device

Abstract

The present application provides a geometric correction method, an image reconstruction method and a device, the geometric correction method comprising: obtaining the spatial coordinates of the marker, a bright field image set and a dark field image set, and the afterglow correction parameters and bad pixel correction parameters of the detector; the projection angles of the bright field projection image set and the dark field projection image set are the same; based on the bright field image set, the dark field image set, the afterglow correction parameters and the bad pixel correction parameters, the corrected projection image of the marker is determined; based on the corrected projection image, the projection coordinates of the marker in the corrected projection image are determined; based on the spatial coordinates and the projection coordinates, the geometric correction parameters of the detector at the projection angle are determined. The present application can correct the geometric distortion of the detector, and the obtained imaging geometric correction relationship has high accuracy, meets actual clinical needs, and can avoid missed diagnosis and misdiagnosis.

Description

Technical Field

[0001] The present application relates to the field of image processing technology, and in particular to a geometric correction method, an image reconstruction method and a device. Background Art

[0002] Tomosynthesis is a new technology of X-ray imaging and an improvement on full digital X-ray photography. Figure 1 Tomographic fusion photography obtains multiple projection data at multiple angles, reduces the overlap of human tissue, and reconstructs photographic images of all levels, which can detect some hidden lesions.

[0003] For medical imaging equipment, the accuracy of the spatial geometric position relationship between the radiation source and the detector plays a vital role in the accuracy of the results of tomographic fusion reconstruction. However, the actual spatial position of the radiation source and the detector will always introduce errors due to installation accuracy, feedback accuracy, measurement accuracy, etc. In addition, as the medical imaging equipment ages, the accuracy of the spatial position of the radiation source and the detector will also decrease. The above reasons may cause the final reconstructed image to have large noise, blurred edges or artifacts. If the reconstructed image is used for diagnosis, it is likely to lead to missed diagnosis or misdiagnosis.

[0004] In order to make the quality of the reconstructed image meet the actual clinical needs, it is necessary to perform geometric correction on the geometric position relationship between the ray source and the detector. Therefore, how to correct the geometric position relationship between the ray source and the detector, obtain the geometric correction relationship, and then use the geometric correction relationship to reconstruct in the reconstruction process to improve the quality of the reconstructed image so that it meets the actual clinical needs has become one of the problems that need to be solved. Summary of the invention

[0005] In view of the above problems, the present application is proposed to provide a geometric correction method, an image reconstruction method and a device that overcome the above problems or at least partially solve the above problems, including:

[0006] A geometric correction method for tomosynthesis reconstruction is used to correct the geometric distortion of a detector, comprising:

[0007] Acquire the spatial coordinates of the marker, a bright field image set and a dark field image set, and the afterglow correction parameters and bad pixel correction parameters of the detector; wherein the projection angles of the bright field projection image set and the dark field projection image set are the same;

[0008] Determining a corrected projection image of the marker according to the bright field image set, the dark field image set, the afterglow correction parameter, and the bad pixel correction parameter;

[0009] Determining the projection coordinates of the marker in the corrected projection image according to the corrected projection image;

[0010] According to the space coordinates and the projection coordinates, a geometric correction parameter of the detector at the projection angle is determined.

[0011] Preferably, the step of determining the corrected projection image of the marker according to the bright field image set, the dark field image set, the afterglow correction parameter and the bad pixel correction parameter comprises:

[0012] Generating a first projection image after afterglow correction according to the bright field image set and the afterglow correction parameter;

[0013] Generating a second projection image after dark field correction according to the first projection image and the dark field image set;

[0014] Generate a third projection image after bright field correction according to the second projection image, the dark field image set and the bright field image set;

[0015] The corrected projection image after bad pixel correction is generated according to the third projection image and the bad pixel correction parameters.

[0016] Preferably, the step of generating the first projection image after afterglow correction based on the bright field image set and the afterglow correction parameter comprises:

[0017] Determining a grayscale persistence correspondence relationship according to the bright field image set and the persistence correction parameter;

[0018] According to the bright field image set, a projection image to be processed and a previous projection image are determined; wherein the projection image to be processed is any bright field projection image except the first frame in the bright field projection image set; and the previous projection image is a bright field projection image in the bright field projection image set corresponding to a frame before the projection image to be processed;

[0019] Determining a persistence value of the preceding projection image according to a corresponding relationship between the preceding projection image and the grayscale persistence;

[0020] The first projection image is determined according to the projection image to be processed and the afterglow value.

[0021] Preferably, the step of determining the second projection image after dark field correction based on the first projection image and the dark field image set includes:

[0022] Determining dark field correction parameters of the detector according to the dark field image set;

[0023] The second projection image is determined according to the first projection image and the dark field correction parameter.

[0024] Preferably, the step of determining the third projection image after bright field correction based on the second projection image, the dark field image set and the bright field image set comprises:

[0025] Determining a bright field correction parameter of the detector according to the bright field image set and the dark field correction parameter;

[0026] The third projection image is determined according to the second projection image and the bright field correction parameter.

[0027] Preferably, the step of determining the projection coordinates of the marker in the corrected projection image based on the corrected projection image comprises:

[0028] Determining the edge of the marker according to the corrected projection image;

[0029] The projection coordinates are determined according to the edge.

[0030] Preferably, the step of determining the edge of the marker based on the corrected projection image comprises:

[0031] Binarizing the corrected projection image to obtain a binary projection image;

[0032] Determining the initial edge of the marker according to the binary projection image;

[0033] The edge is determined based on the initial edge and a preset marker matching template.

[0034] A tomosynthesis image reconstruction method, comprising:

[0035] Acquire at least two target projection images and their corresponding target projection angles; wherein different target projection images correspond to different target projection angles;

[0036] Using any of the geometric correction methods described above, obtaining geometric correction parameters of the detector at each target projection angle;

[0037] Performing geometric correction on each of the target projection images according to the geometric correction parameters corresponding to the target projection images to obtain a set of corrected images;

[0038] The corrected image set is subjected to tomographic fusion reconstruction to obtain a target composite image.

[0039] A geometric correction device for tomosynthesis reconstruction, used for correcting the geometric distortion of a detector, comprising:

[0040] A data acquisition module, used to acquire the spatial coordinates of the marker, a bright field image set and a dark field image set, and afterglow correction parameters and bad pixel correction parameters of the detector; wherein the projection angles of the bright field projection image set and the dark field projection image set are the same;

[0041] An image processing module, used for determining a corrected projection image of the marker according to the bright field image set, the dark field image set, the afterglow correction parameter and the bad pixel correction parameter;

[0042] A coordinate determination module, used to determine the projection coordinates of the marker in the corrected projection image based on the corrected projection image;

[0043] A parameter determination module is used to determine the geometric correction parameters of the detector at the projection angle according to the space coordinates and the projection coordinates.

[0044] A tomosynthesis image reconstruction device, comprising:

[0045] A target acquisition module, used to acquire at least two target projection images and their corresponding target projection angles; wherein different target projection images correspond to different target projection angles;

[0046] A geometric correction module, used to obtain geometric correction parameters of the detector at each target projection angle by using any of the geometric correction methods described above;

[0047] A correction processing module, used for performing geometric correction on each of the target projection images according to the geometric correction parameters corresponding to the target projection images to obtain a set of corrected images;

[0048] The image reconstruction module is used to perform tomographic fusion reconstruction on the correction image set to obtain a target composite image.

[0049] This application has the following advantages:

[0050] In an embodiment of the present application, by acquiring the spatial coordinates, bright field image set and dark field image set of the marker, as well as the afterglow correction parameters and bad pixel correction parameters of the detector; wherein the projection angles of the bright field projection image set and the dark field projection image set are the same; based on the bright field image set, the dark field image set, the afterglow correction parameters and the bad pixel correction parameters, the corrected projection image of the marker is determined; based on the corrected projection image, the projection coordinates of the marker in the corrected projection image are determined; based on the spatial coordinates and the projection coordinates, the geometric correction parameters of the detector at the projection angle are determined, the geometric distortion of the detector can be corrected, and the obtained imaging geometric correction relationship has high accuracy, meets actual clinical needs, and can avoid the occurrence of missed diagnosis and misdiagnosis. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solution of the present application, the drawings required for use in the description of the present application 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 drawings can be obtained based on these drawings without paying any creative work.

[0052] Figure 1 It is a schematic diagram of the operation of tomographic fusion photography according to the prior art;

[0053] Figure 2 is a flowchart of a geometric correction method for tomosynthesis reconstruction provided in an embodiment of the present application;

[0054] Figure 3 is a schematic diagram of a three-dimensional coordinate system and a two-dimensional coordinate system provided in one embodiment of the present application;

[0055] Figure 4 It is a structural schematic diagram of a membrane provided in one embodiment of the present application;

[0056] Figure 5 is a flowchart of the steps of a tomosynthesis image reconstruction method provided in one embodiment of the present application;

[0057] Figure 6 It is a structural schematic diagram of a geometric correction device for tomosynthesis reconstruction provided by an embodiment of the present application;

[0058] Figure 7 is a structural schematic diagram of a tomosynthesis image reconstruction device provided in one embodiment of the present application;

[0059] Figure 8 It is a structural diagram of a computer device provided in one embodiment of the present application.

[0060] The reference numerals in the drawings of the specification are as follows:

[0061] 12. Computer equipment; 14. External devices; 16. Processing unit; 18. Bus; 20. Network adapter; 22. I / O interface; 24. Display; 28. Memory; 30. Random access memory; 32. Cache memory; 34. Storage system; 40. Program / utility; 42. Program module. DETAILED DESCRIPTION

[0062] In order to make the objects, features and advantages of the present application more obvious and understandable, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods. Obviously, the described embodiments are part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0063] It should be noted that in any embodiment of the present application, the geometric correction method is used to obtain the geometric correction parameters of the detector at a specified projection angle, and the geometric correction parameters are used to correct the geometric distortion of the detector, that is, to correct the geometric position deviation between the detector and the radiation source. The detector can be any X-ray imaging device, such as a digital breast tomosynthesis (DBT) device.

[0064] Reference Figure 2 , showing a geometric correction method for tomosynthesis reconstruction provided by an embodiment of the present application, comprising:

[0065] S110, acquiring the spatial coordinates of the marker, a bright field image set and a dark field image set, and an afterglow correction parameter and a bad pixel correction parameter of the detector; wherein the projection angles of the bright field projection image set and the dark field projection image set are the same;

[0066] S120, determining a corrected projection image of the marker according to the bright field image set, the dark field image set, the afterglow correction parameter, and the bad pixel correction parameter;

[0067] S130, determining the projection coordinates of the marker in the corrected projection image according to the corrected projection image;

[0068] S140. Determine geometric correction parameters of the detector at the projection angle according to the spatial coordinates and the projection coordinates.

[0069] In an embodiment of the present application, by acquiring the spatial coordinates, bright field image set and dark field image set of the marker, as well as the afterglow correction parameters and bad pixel correction parameters of the detector; wherein the projection angles of the bright field projection image set and the dark field projection image set are the same; based on the bright field image set, the dark field image set, the afterglow correction parameters and the bad pixel correction parameters, the corrected projection image of the marker is determined; based on the corrected projection image, the projection coordinates of the marker in the corrected projection image are determined; based on the spatial coordinates and the projection coordinates, the geometric correction parameters of the detector at the projection angle are determined, the geometric distortion of the detector can be corrected, and the obtained imaging geometric correction relationship has high accuracy, meets actual clinical needs, and can avoid the occurrence of missed diagnosis and misdiagnosis.

[0070] Next, a geometric correction method for tomosynthesis reconstruction in this exemplary embodiment will be further described.

[0071] As described in step S110, the spatial coordinates of the marker, the bright field image set and the dark field image set, as well as the afterglow correction parameters and bad pixel correction parameters of the detector are obtained; wherein the projection angles of the bright field projection image set and the dark field projection image set are the same.

[0072] A three-dimensional coordinate system is established with the rotation center of the detector as the origin, and the two-dimensional coordinate system of the detector is associated with this coordinate system. The three-dimensional coordinate system is defined as follows: Figure 3 As shown, a right-handed coordinate system is formed with O as the origin, vertical upward as the positive direction of the Z axis, the direction from the chest wall to the gantry as the positive direction of the X axis, and from left to right as the positive direction of the Y axis when the gantry looks at the chest wall (from right to left as the positive direction of the Y axis when the chest wall looks at the gantry). The coordinates of the ray source (i.e., S) in the three-dimensional coordinate system are [Xs, Ys, Zs]. The figure shows a special case when the gantry angle is 0 degrees, and S is on the Z axis at this time. The position of S will change with each shot. The three-dimensional coordinate system is scaled in mm and is used to calibrate real-world objects. The definition of the detector's two-dimensional coordinate system in the three-dimensional coordinate system is as follows Figure 3 As shown in the figure, when looking at the detector from the top of the rack, the coordinate origin is at the lower left corner of the detector, the detector plane is parallel to the XY plane, and the intersection with the Z axis is O', the V axis is parallel to the Y axis, and the U axis is antiparallel to the X axis. The detector coordinate system has been discretized, and the measurement unit of (u, v) is pixel, not physical length.

[0073] A membrane body for testing is provided, the membrane body comprising a substrate and the marker embedded in the middle of the substrate. The marker may be a steel ball or a filament. The substrate is usually made of a uniform material, and the material of the marker has a different absorption coefficient from the material of the substrate, so that the marker can be more easily detected from the projection image during imaging. In addition, the markers must be arranged so that at the same projection angle, the position of each marker in the projection image of the phantom does not overlap. The number of markers can be determined according to actual needs, and the greater the number of markers, the more conducive it is to improving the accuracy of the final imaging geometric correction relationship. Reference Figure 4 , shows a schematic diagram of the structure of a phantom provided in this embodiment, wherein the substrate is a cuboid, 15 steel balls in 5 rows and 3 columns are embedded in the upper surface of the cuboid, 8 steel balls in 2 rows and 4 columns are embedded in the lower surface of the cuboid, and the projection image of the steel balls in 5 rows and 3 columns does not overlap with the projection image of the steel balls in 2 rows and 4 columns in the projection image obtained by photographing the phantom. It should be noted that in other embodiments, the marker may not be embedded in the substrate, but may be directly composed of a plurality of steel balls or filaments.

[0074] The spatial coordinates of the marker are measured by the bracket provided by the phantom. Specifically, the phantom with the bracket is placed at a predetermined position on the detector, and the position of the phantom in the three-dimensional coordinate system can be obtained according to the scale marked on the bracket. In addition, when designing the phantom, the position of the marker in the membrane can also be obtained in advance, so the spatial coordinates of the marker can also be directly obtained according to the position of the phantom set during design.

[0075] The detector collects a set of bright field images and a set of dark field images of the marker; wherein the set of bright field images includes a set of bright field projection images obtained by the detector continuously collecting the marker when the radiation source is turned on, and the set of dark field images includes a set of dark field projection images obtained by the detector continuously collecting the marker when the radiation source is turned off. Specifically, the phantom is placed on a flat plate so that one surface of the membrane body is close to the edge of the flat plate, and the phantom is placed in the middle of the edge of the flat plate. Ensure that the phantom and the flat plate are stationary, the rack starts to rotate, and according to the set clinical scanning angle range (for example, -8 degrees to +8 degrees), a set of bright field projection images and a set of dark field projection images are collected every 1 degree to obtain the set of bright field images and the set of dark field images of the marker at the projection angle. In addition, the bad point correction parameters and the afterglow correction parameters of the detector at the projection angle are respectively obtained; wherein the bad point correction parameters are used to correct the abnormal points on the detector glass, and can be obtained through the flat plate SDK template; the afterglow correction parameters are used to eliminate the afterglow interference caused by the continuous exposure of the detector, and are generally provided by the manufacturer of the detector.

[0076] As described in step S120, a corrected projection image of the marker is determined based on the bright field image set, the dark field image set, the afterglow correction parameter, and the bad pixel correction parameter.

[0077] An image is selected from the bright field image set as a projection image to be processed, and afterglow correction, dark field correction, bright field correction and bad pixel correction are sequentially performed on the projection image to be processed to obtain a corrected projection image of the marker. Specifically, afterglow correction is performed on the projection image to be processed according to the bright field image set and the afterglow correction parameters to obtain a first projection image after afterglow correction; dark field correction is performed on the first projection image according to the dark field image set to obtain a second projection image after dark field correction; bright field correction is performed on the second projection image according to the dark field image set and the bright field image set to obtain a third projection image after bright field correction; bad pixel correction is performed on the third projection image according to the bad pixel correction parameters to obtain the corrected projection image after bad pixel correction.

[0078] As described in step S130, the projection coordinates of the marker in the calibrated projection image are determined based on the calibrated projection image.

[0079] The corrected projection image is binarized according to preset threshold segmentation parameters to obtain a binary projection image; the binary projection image is identified by an edge detection algorithm to determine the initial edge of the marker in the corrected projection image; the initial edge is further fitted and denoised by template recognition and other methods to obtain the edge of the marker in the corrected projection image; based on the edge, the two-dimensional coordinates of the center of the marker in the corrected projection image are calculated as the projection coordinates of the marker.

[0080] As described in step S140, the geometric correction parameters of the detector at the projection angle are determined according to the space coordinates and the projection coordinates.

[0081] The spatial coordinates of the marker are sequentially associated with the projection coordinates. Specifically, the projection coordinates of the 25 steel balls are sorted in the order of bottom layer first, top layer second, Y first, then X to obtain a projection coordinate list of the marker. For each projection coordinate in the projection coordinate list, the projection coordinate (u, v) is associated with the spatial coordinate (X, Y, Z) of the corresponding steel ball using the pre-established projection matrix Proj_Matrix, as shown in formula (1):

[0082]

[0083] in, k = 1, 2, ..., 17;

[0084] From (1), we can get:

[0085]

[0086] Eliminating the homogeneous matrix weight w, the projection coordinates (u, v) of each steel ball in two directions are obtained:

[0087]

[0088] After solving the equation, P is the geometric correction parameter of the detector at the projection angle.

[0089] In one embodiment of the present application, the specific process of "determining the corrected projection image of the marker based on the bright field image set, the dark field image set, the afterglow correction parameters and the bad pixel correction parameters" in step S120 can be further explained in combination with the following description.

[0090] Determine a first projection image after afterglow correction according to the bright field image set and the afterglow correction parameters. Specifically, select an image from the bright field image set as a projection image to be processed, perform afterglow correction on the projection image to be processed according to the bright field image set and the afterglow correction parameters, and obtain a first projection image after afterglow correction;

[0091] Determine a second projection image after dark field correction based on the first projection image and the dark field image set. Specifically, perform dark field correction on the first projection image based on the dark field image set to obtain a second projection image after dark field correction;

[0092] Determine a third projection image after bright field correction according to the second projection image, the dark field image set and the bright field image set. Specifically, perform bright field correction on the second projection image according to the dark field image set and the bright field image set to obtain a third projection image after bright field correction;

[0093] According to the third projection image and the bad pixel correction parameters, the corrected projection image after bad pixel correction is determined. Specifically, the third projection image is subjected to bad pixel correction according to the bad pixel correction parameters to obtain the corrected projection image after bad pixel correction.

[0094] In this embodiment, the step of determining the first projection image after afterglow correction based on the bright field image set and the afterglow correction parameter includes:

[0095] According to the bright field image set and the persistence correction parameters, the grayscale persistence correspondence is determined. Specifically, assuming that the lowest effective grayscale of the detector is Dmin, the highest effective grayscale is Dmax, and the grayscale of a single-frame projection image is Di∈[Dmin,Dmax], the persistence value Hi of each frame of projection image Di in the bright field image set to the next frame of projection image is calculated, and the grayscale persistence correspondence is established and stored: first solve the equation h(t)=Di, where h(t) is the persistence attenuation function related to the persistence correction parameters, and obtain the number of frames t(Di) with grayscale Di, and then calculate the persistence value according to Hi=h(t(Di)+l);

[0096] According to the bright field image set, a projection image to be processed and a preceding projection image are determined; wherein the projection image to be processed is any bright field projection image in the bright field projection image set except the first frame; the preceding projection image is the bright field projection image in the bright field projection image set that is located in a frame before the projection image to be processed;

[0097] According to the previous projection image and the grayscale persistence correspondence, the persistence value of the previous projection image is determined. Specifically, for a pixel P' of the previous projection image, its grayscale value is set to Dp', and its corresponding persistence value Hp is obtained by searching through the grayscale persistence correspondence.

[0098] The first projection image is determined according to the projection image to be processed and the persistence value. Specifically, for a pixel P of the image to be processed, its grayscale value is set to Dp, then the grayscale value of P after persistence correction is

[0099] In this embodiment, the step of determining the second projection image after dark field correction based on the first projection image and the dark field image set includes:

[0100] The dark field correction parameters of the detector are determined based on the dark field image set. Specifically, all dark field projection images in the dark field image set are averaged to obtain the dark field correction parameters of the detector:

[0101] The second projection image is determined according to the first projection image and the dark field correction parameter. Specifically, the grayscale value of the first projection image is corrected according to the dark field correction parameter to obtain the second projection image after dark field correction.

[0102] In this embodiment, the step of determining the third projection image after bright field correction based on the second projection image, the dark field image set and the bright field image set includes:

[0103] The bright field correction parameters of the detector are determined according to the bright field image set and the dark field correction parameters. Specifically, the bright field correction parameters of the detector are obtained by taking the average of all bright field projection images in the bright field image set and subtracting the dark field correction parameters:

[0104] The third projection image is determined according to the second projection image and the bright field correction parameter. Specifically, the grayscale value of the second projection image is corrected according to the bright field correction parameter to obtain the second projection image after bright field correction.

[0105] In this embodiment, the step of determining the projection coordinates of the marker in the corrected projection image based on the corrected projection image includes:

[0106] The edge of the marker is determined based on the corrected projection image. Specifically, the corrected projection image is binarized based on a preset threshold segmentation parameter to obtain a binarized projection image; the binarized projection image is identified by an edge detection algorithm to determine the initial edge of the marker in the corrected projection image; the initial edge is further fitted and denoised by template recognition or other methods to obtain the edge of the marker in the corrected projection image.

[0107] The projection coordinates are determined based on the edge. Specifically, based on the edge, the two-dimensional coordinates of the center of the marker in the corrected projection image are calculated as the projection coordinates of the marker.

[0108] In this embodiment, the step of determining the edge of the marker according to the corrected projection image includes:

[0109] The corrected projection image is binarized to obtain a binarized projection image. Specifically, the corrected projection image is subjected to an adaptive threshold binarization process to obtain a binarized projection image after the binarization process. The threshold in the adaptive threshold binarization process is variable, rather than a fixed threshold. The threshold in the adaptive threshold binarization process is calculated based on each small area on the corrected projection image to obtain a threshold corresponding to it. Therefore, different thresholds are used in different areas of the corrected projection image, so that better results can be obtained under different brightness conditions. Therefore, by performing an adaptive threshold binarization process on the corrected projection image, the binarization effect of the corrected projection image can be effectively improved.

[0110] Based on the binary projection image, the initial edge of the marker is determined. Specifically, edge detection is performed on the marker in the binary projection image to obtain the initial edge of the marker. The edge detection can be understood as a technical means for detecting the clear edge contour of the steel ball in the binary projection image. Since the projections left by several steel balls on the binary projection image appear circular or quasi-circular, the detection result of the initial edge is the circular or quasi-circular edge contour in the binary projection image.

[0111] The edge is determined based on the initial edge and a preset marker matching template. Specifically, based on the detection result of the initial edge, the image of the calibration object is fitted with a contour shape to obtain a candidate area where the marker is located. The contour shape fitting may include ellipse fitting, circle fitting, rectangle fitting or square fitting, etc., and the present embodiment is preferably ellipse fitting. The basic idea of ​​ellipse fitting is to find an ellipse for a set of sample points on a given initial edge, so that it is as close to these sample points as possible. In other words, a set of data in the initial edge is fitted with an ellipse equation as a model, so that a certain ellipse equation satisfies these data as much as possible, and the various parameters of the ellipse equation are calculated. The best ellipse finally determined is the edge fitting result of the marker.

[0112] Reference Figure 5 , shows a tomosynthesis image reconstruction method provided by an embodiment of the present application, comprising:

[0113] S210, acquiring at least two target projection images and their corresponding target projection angles; wherein different target projection images correspond to different target projection angles;

[0114] S220, using any of the geometric correction methods described above to obtain geometric correction parameters of the detector at each of the target projection angles;

[0115] S230, performing geometric correction on each of the target projection images according to the geometric correction parameters corresponding to the target projection images to obtain a set of corrected images;

[0116] S240: Perform tomosynthesis reconstruction on the corrected image set to obtain a target composite image.

[0117] In an embodiment of the present application, the geometric correction parameters of the detector at each target projection angle are obtained by the image reconstruction method, and the projection coordinates of the target tissue in the target projection images at different target projection angles can be correctly mapped to the three-dimensional space coordinates in the theoretical coordinate system, and the corrected target images of the target tissue at different target projection angles are obtained to form the corrected image set. The step of geometrically correcting each target projection image is conducive to improving the quality of the reconstructed image, meets actual clinical needs, and avoids the occurrence of missed detection or false detection to a certain extent.

[0118] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0119] Reference Figure 6 , showing a geometric correction device for tomosynthesis reconstruction provided by an embodiment of the present application, comprising:

[0120] The data acquisition module 310 is used to acquire the spatial coordinates of the marker, the bright field image set and the dark field image set, and the afterglow correction parameters and bad pixel correction parameters of the detector; wherein the projection angles of the bright field projection image set and the dark field projection image set are the same;

[0121] An image processing module 320, configured to determine a corrected projection image of the marker according to the bright field image set, the dark field image set, the afterglow correction parameter, and the bad pixel correction parameter;

[0122] A coordinate determination module 330, configured to determine the projection coordinates of the marker in the calibrated projection image based on the calibrated projection image;

[0123] The parameter determination module 340 is used to determine the geometric correction parameters of the detector at the projection angle according to the space coordinates and the projection coordinates.

[0124] Reference Figure 7 , shows a tomosynthesis image reconstruction device provided by an embodiment of the present application, comprising:

[0125] The target acquisition module 410 is used to acquire at least two target projection images and their corresponding target projection angles; wherein different target projection images correspond to different target projection angles;

[0126] A geometric correction module 420, configured to obtain geometric correction parameters of the detector at each target projection angle by using any of the geometric correction methods described above;

[0127] A correction processing module 430, configured to perform geometric correction on each of the target projection images according to the geometric correction parameters corresponding to the target projection images to obtain a set of corrected images;

[0128] The image reconstruction module 440 is used to perform tomosynthesis reconstruction on the corrected image set to obtain a target composite image.

[0129] Reference Figure 8 , shows a computer device for a geometric correction method for tomosynthesis reconstruction of the present application, which may specifically include the following:

[0130] The computer device 12 is in the form of a general-purpose computing device, and the components of the computer device 12 may include but are not limited to: one or more processors or processing units 16, a memory 28, and a bus 18 connecting different system components (including the memory 28 and the processing unit 16).

[0131] The bus 18 represents one or more of several types of bus 18 structures, including a memory bus 18 or memory controller, a peripheral bus 18, an accelerated graphics port, a processor or a local bus 18 using any of a variety of bus 18 architectures. These architectures include, by way of example, but are not limited to, an Industry Standard Architecture (ISA) bus 18, a Micro Channel Architecture (MAC) bus 18, an Enhanced ISA bus 18, an Audio Video Electronics Standards Association (VESA) local bus 18, and a Peripheral Component Interconnect (PCI) bus 18.

[0132] The computer device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the computer device 12, including volatile and non-volatile media, removable and non-removable media.

[0133] Memory 28 may include computer system readable media in the form of volatile memory, such as random access memory 30 and / or cache memory 32. Computer device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 34 may be used to read and write to non-removable, non-volatile magnetic media (commonly referred to as a "hard drive"). Although Figure 8 Not shown, a disk drive for reading and writing to a removable non-volatile disk (such as a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (such as a CD-ROM, DVD-ROM or other optical medium) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The memory may include at least one program product having a set (e.g., at least one) of program modules 42, which are configured to perform the functions of the various embodiments of the present application.

[0134] A program / utility 40 having a set (at least one) of program modules 42 may be stored in, for example, a memory, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules 42, and program data, each of which or some combination may include an implementation of a network environment. The program modules 42 generally perform the functions and / or methods of the embodiments described herein.

[0135] The computer device 12 may also communicate with one or more external devices 14 (e.g., keyboards, pointing devices, displays 24, cameras, etc.), one or more devices that enable an operator to interact with the computer device 12, and / or any device that enables the computer device 12 to communicate with one or more other computing devices (e.g., network cards, modems, etc.). Such communication may be performed through the I / O interface 22. Furthermore, the computer device 12 may also communicate with one or more networks (e.g., local area networks (LANs)), wide area networks (WANs), and / or public networks (e.g., the Internet) through a network adapter 20. Figure 8 As shown, the network adapter 20 communicates with other modules of the computer device 12 via the bus 18. It should be understood that although Figure 8 Not shown, other hardware and / or software modules may be used in conjunction with the computer device 12, including but not limited to: microcode, device drivers, redundant processing units 16, external disk drive arrays, RAID systems, tape drives, and data backup storage systems 34, etc.

[0136] The processing unit 16 executes various functional applications and data processing by running the programs stored in the memory 28, for example, implementing a geometric correction method for tomosynthesis reconstruction provided in an embodiment of the present application.

[0137] That is, when the processing unit 16 executes the program, it realizes: obtaining the spatial coordinates of the marker, a bright field image set and a dark field image set, as well as the afterglow correction parameters and bad pixel correction parameters of the detector; wherein the projection angles of the bright field projection image set and the dark field projection image set are the same; determining the corrected projection image of the marker based on the bright field image set, the dark field image set, the afterglow correction parameters and the bad pixel correction parameters; determining the projection coordinates of the marker in the corrected projection image based on the corrected projection image; and determining the geometric correction parameters of the detector at the projection angle based on the spatial coordinates and the projection coordinates.

[0138] In one embodiment of the present application, a computer-readable storage medium is further provided, on which a computer program is stored. When the program is executed by a processor, a geometric correction method for tomosynthesis reconstruction provided in all embodiments of the present application is implemented.

[0139] That is, when the program is executed by the processor, it is implemented as follows: obtaining the spatial coordinates of the marker, a bright field image set and a dark field image set, as well as the afterglow correction parameters and bad pixel correction parameters of the detector; wherein the projection angles of the bright field projection image set and the dark field projection image set are the same; determining the corrected projection image of the marker based on the bright field image set, the dark field image set, the afterglow correction parameters and the bad pixel correction parameters; determining the projection coordinates of the marker in the corrected projection image based on the corrected projection image; and determining the geometric correction parameters of the detector at the projection angle based on the spatial coordinates and the projection coordinates.

[0140] Any combination of one or more computer-readable media may be used. A computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, device, or device.

[0141] Computer-readable signal media may include a data signal propagated in baseband or as part of a carrier wave, which carries a computer-readable program code. Such propagated data signals may take a variety of forms, including, but not limited to, electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0142] The computer program code for performing the operation of the present application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the operator's computer, partially on the operator's computer, as an independent software package, partially on the operator's computer, partially on the remote computer, or entirely on the remote computer or server. In the case of a remote computer, the remote computer can be connected to the operator's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet). The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same and similar parts between the various embodiments can be referred to each other.

[0143] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present application.

[0144] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0145] The above is a detailed introduction to a geometric correction method, image reconstruction method and device provided by the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A geometric correction method for tomosynthesis reconstruction, used to correct the geometric distortion of a detector, characterized in that: include: Acquire the spatial coordinates, bright field image set and dark field image set of the marker, as well as afterglow correction parameters and bad pixel correction parameters of the detector; wherein the bright field image set includes a set of bright field projection images continuously acquired by the detector of the marker when the ray source is turned on, and the dark field image set includes a set of dark field projection images continuously acquired by the detector of the marker when the ray source is turned off; the projection angles of the bright field projection image set and the dark field projection image set are the same; Determine the corrected projection image of the marker according to the bright field image set, the dark field image set, the afterglow correction parameters and the bad pixel correction parameters; including: generating a first projection image after afterglow correction according to the bright field image set and the afterglow correction parameters; generating a second projection image after dark field correction according to the first projection image and the dark field image set; generating a third projection image after bright field correction according to the second projection image, the dark field image set and the bright field image set; generating the corrected projection image after bad pixel correction according to the third projection image and the bad pixel correction parameters; Determining the projection coordinates of the marker in the corrected projection image according to the corrected projection image; According to the space coordinates and the projection coordinates, a geometric correction parameter of the detector at the projection angle is determined.

2. The method according to claim 1, characterized in that The step of generating a first projection image after afterglow correction according to the bright field image set and the afterglow correction parameter comprises: Determining a grayscale persistence correspondence relationship according to the bright field image set and the persistence correction parameter; According to the bright field image set, a projection image to be processed and a previous projection image are determined; wherein the projection image to be processed is any bright field projection image except the first frame in the bright field projection image set; and the previous projection image is a bright field projection image in the bright field projection image set corresponding to a frame before the projection image to be processed; Determining a persistence value of the preceding projection image according to a corresponding relationship between the preceding projection image and the grayscale persistence; The first projection image is determined according to the projection image to be processed and the afterglow value.

3. The method according to claim 1, characterized in that The step of generating a second projection image after dark field correction based on the first projection image and the dark field image set comprises: Determining dark field correction parameters of the detector according to the dark field image set; The second projection image is determined according to the first projection image and the dark field correction parameter.

4. The method according to claim 1, characterized in that: The step of generating a third projection image after bright field correction according to the second projection image, the dark field image set and the bright field image set comprises: Determining a bright field correction parameter of the detector according to the bright field image set and the dark field correction parameter; The third projection image is determined according to the second projection image and the bright field correction parameter.

5. The method according to claim 1, characterized in that The step of determining the projection coordinates of the marker in the corrected projection image based on the corrected projection image comprises: Determining the edge of the marker according to the corrected projection image; The projection coordinates are determined according to the edge.

6. The method according to claim 5, characterized in that The step of determining the edge of the marker according to the corrected projection image comprises: Binarizing the corrected projection image to obtain a binary projection image; Determining the initial edge of the marker according to the binary projection image; The edge is determined based on the initial edge and a preset marker matching template.

7. A tomosynthesis image reconstruction method, characterized in that: include: Acquire at least two target projection images and their corresponding target projection angles; wherein different target projection images correspond to different target projection angles; Adopting the geometric correction method according to any one of claims 1 to 6, obtaining the geometric correction parameters of the detector at each target projection angle; Performing geometric correction on each of the target projection images according to the geometric correction parameters corresponding to the target projection images to obtain a set of corrected images; The corrected image set is subjected to tomographic fusion reconstruction to obtain a target composite image.

8. A geometric correction device for tomosynthesis reconstruction, used for correcting the geometric distortion of a detector, characterized in that: include: A data acquisition module, used to acquire the spatial coordinates of the marker, a bright field image set and a dark field image set, and afterglow correction parameters and bad pixel correction parameters of the detector; wherein the bright field image set includes a set of bright field projection images continuously acquired by the detector for the marker when the ray source is turned on, and the dark field image set includes a set of dark field projection images continuously acquired by the detector for the marker when the ray source is turned off; the projection angles of the bright field projection image set and the dark field projection image set are the same; An image processing module is used to determine the corrected projection image of the marker according to the bright field image set, the dark field image set, the afterglow correction parameters and the bad pixel correction parameters; including: generating a first projection image after afterglow correction according to the bright field image set and the afterglow correction parameters; generating a second projection image after dark field correction according to the first projection image and the dark field image set; generating a third projection image after bright field correction according to the second projection image, the dark field image set and the bright field image set; generating the corrected projection image after bad pixel correction according to the third projection image and the bad pixel correction parameters; A coordinate determination module, used to determine the projection coordinates of the marker in the corrected projection image based on the corrected projection image; A parameter determination module is used to determine the geometric correction parameters of the detector at the projection angle according to the space coordinates and the projection coordinates.

9. A tomosynthesis image reconstruction device, characterized in that: include: A target acquisition module, used to acquire at least two target projection images and their corresponding target projection angles; wherein different target projection images correspond to different target projection angles; A geometric correction module, configured to obtain geometric correction parameters of the detector at each target projection angle by using the geometric correction method according to any one of claims 1 to 6; A correction processing module, used for performing geometric correction on each of the target projection images according to the geometric correction parameters corresponding to the target projection images to obtain a set of corrected images; The image reconstruction module is used to perform tomographic fusion reconstruction on the correction image set to obtain a target composite image.

Images