Attenuation coefficient image processing method and device, computer equipment and storage medium

Abstract

The invention relates to an attenuation coefficient image processing method and device, computer equipment and a storage medium. Dividing each voxel into different attenuation coefficient intervals according to the attenuation coefficient value corresponding to each voxel in the attenuation coefficient image, adjusting the attenuation coefficient value of the voxel in each attenuation coefficient interval based on a preset linear piecewise function, and obtaining a preprocessed to-be-registered image based on the adjusted attenuation coefficient value; the image contrast ratios of different attenuation coefficient intervals are different, and the slope of the linear piecewise function of the attenuation coefficient interval with the minimum image contrast ratio is larger than that of the linear piecewise functions of other attenuation coefficient intervals. According to the embodiment of the invention, the slope of the linear piecewise function of the attenuation coefficient interval with the minimum image contrast is greater than the slopes of the linear piecewise functions of other attenuation coefficient intervals, so that the attenuation coefficient value of each voxel in the attenuation coefficient image is mapped according to the linear piecewise function corresponding to each attenuation coefficient interval. And the registration performance of the attenuation coefficient image is optimized.

Description

Technical Field

[0001] The present application relates to the field of medical technology, and in particular to an attenuation coefficient image processing method, device, computer equipment and storage medium. Background Art

[0002] Attenuation coefficient images are of great significance for positron emission tomography (PET) image reconstruction. Their accuracy directly affects the quality of PET reconstructed images. Inaccurate attenuation coefficient images will cause attenuation correction artifacts when reconstructing images. In order to solve the attenuation correction artifact problem, the registration of attenuation coefficient images is particularly important. Therefore, how to optimize the registration performance of attenuation coefficient images has become an urgent problem to be solved in the medical industry. Summary of the invention

[0003] Based on this, it is necessary to provide an attenuation coefficient image processing method, device, computer equipment and storage medium that can optimize the registration performance of the attenuation coefficient image in order to address the above technical problems.

[0004] In a first aspect, the present application provides a method for determining an attenuation coefficient map, the method comprising:

[0005] According to the attenuation coefficient value corresponding to each voxel in the attenuation coefficient image, each voxel is divided into different attenuation coefficient intervals, and the image contrast of the different attenuation coefficient intervals is different;

[0006] Based on a preset linear piecewise function, the attenuation coefficient value of the voxel in each attenuation coefficient interval is adjusted; the slope of the linear piecewise function of the attenuation coefficient interval with the minimum image contrast is greater than the slope of the linear piecewise function of other attenuation coefficient intervals;

[0007] Based on the adjusted attenuation coefficient value, the preprocessed image to be registered is obtained.

[0008] In one embodiment, the method further comprises:

[0009] Allocating a plurality of preset slopes to each of the attenuation coefficient intervals;

[0010] The corresponding linear piecewise function is determined according to the preset slope of each attenuation coefficient interval.

[0011] In one of the embodiments, the attenuation coefficient image includes a motion image and a reference image, and the images to be registered include a first image to be registered of the motion image and a second image to be registered of the reference image.

[0012] In one embodiment, after obtaining the pre-processed image to be registered based on the adjusted attenuation coefficient value, the method further includes:

[0013] determining a target deformation field according to the first image to be registered and the second image to be registered;

[0014] A registered attenuation coefficient image is determined according to the target deformation field and the motion image.

[0015] In one embodiment, determining the target deformation field according to the first image to be registered and the second image to be registered includes:

[0016] Acquire first position information of a plurality of control points on the reference image;

[0017] The target deformation field is determined according to an objective function, the first image to be registered, and the second image to be registered; the objective function includes first position information of the plurality of control points.

[0018] In one embodiment, determining the target deformation field according to the objective function, the first image to be registered, and the second image to be registered includes:

[0019] Iteratively optimize the first position information of the plurality of control points according to the first image to be registered and the second image to be registered to obtain the second position information of the plurality of control points that satisfies the minimization objective function;

[0020] The target deformation field is determined according to the second position information of the plurality of control points and an interpolation algorithm.

[0021] In a second aspect, the present application also provides an attenuation coefficient image processing device, the device comprising:

[0022] A division module, used for dividing each voxel into different attenuation coefficient intervals according to the attenuation coefficient value corresponding to each voxel in the attenuation coefficient image, wherein the image contrast of the different attenuation coefficient intervals is different;

[0023] An adjustment module, used for adjusting the attenuation coefficient value of the voxel in each attenuation coefficient interval based on a preset linear piecewise function; the slope of the linear piecewise function of the attenuation coefficient interval with the minimum image contrast is greater than the slope of the linear piecewise function of other attenuation coefficient intervals;

[0024] The first determination module is used to obtain a preprocessed image to be registered based on the adjusted attenuation coefficient value.

[0025] In a third aspect, the present application further provides a computer device, the computer device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the following steps when executing the computer program:

[0026] According to the attenuation coefficient value corresponding to each voxel in the attenuation coefficient image, each voxel is divided into different attenuation coefficient intervals, and the image contrast of the different attenuation coefficient intervals is different;

[0027] Based on a preset linear piecewise function, the attenuation coefficient value of the voxel in each attenuation coefficient interval is adjusted; the slope of the linear piecewise function of the attenuation coefficient interval with the minimum image contrast is greater than the slope of the linear piecewise function of other attenuation coefficient intervals;

[0028] Based on the adjusted attenuation coefficient value, the preprocessed image to be registered is obtained.

[0029] In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0030] According to the attenuation coefficient value corresponding to each voxel in the attenuation coefficient image, each voxel is divided into different attenuation coefficient intervals, and the image contrast of the different attenuation coefficient intervals is different;

[0031] Based on a preset linear piecewise function, the attenuation coefficient value of the voxel in each attenuation coefficient interval is adjusted; the slope of the linear piecewise function of the attenuation coefficient interval with the minimum image contrast is greater than the slope of the linear piecewise function of other attenuation coefficient intervals;

[0032] Based on the adjusted attenuation coefficient value, the preprocessed image to be registered is obtained.

[0033] In a fifth aspect, the present application further provides a computer program product, the computer program product comprising a computer program, which implements the following steps when executed by a processor:

[0034] According to the attenuation coefficient value corresponding to each voxel in the attenuation coefficient image, each voxel is divided into different attenuation coefficient intervals, and the image contrast of the different attenuation coefficient intervals is different;

[0035] Based on a preset linear piecewise function, the attenuation coefficient value of the voxel in each attenuation coefficient interval is adjusted; the slope of the linear piecewise function of the attenuation coefficient interval with the minimum image contrast is greater than the slope of the linear piecewise function of other attenuation coefficient intervals;

[0036] Based on the adjusted attenuation coefficient value, the preprocessed image to be registered is obtained.

[0037] The above-mentioned attenuation coefficient image processing method, device, computer equipment and storage medium divide each voxel into different attenuation coefficient intervals according to the attenuation coefficient value corresponding to each voxel in the attenuation coefficient image, adjust the attenuation coefficient value of the voxel in each attenuation coefficient interval based on a preset linear piecewise function, and obtain the preprocessed image to be registered based on the adjusted attenuation coefficient value. The image contrast of different attenuation coefficient intervals is different, and the slope of the linear piecewise function of the attenuation coefficient interval with the smallest image contrast is greater than the slope of the linear piecewise function of other attenuation coefficient intervals. In the embodiment of the present application, the slope of the linear piecewise function of the attenuation coefficient interval with the smallest image contrast is greater than the slope of the linear piecewise function of other attenuation coefficient intervals, so that the attenuation coefficient value of each voxel in the attenuation coefficient image is mapped according to the linear piecewise function corresponding to each attenuation coefficient interval, and the attenuation coefficient value in the attenuation coefficient image is adjusted, thereby achieving a contrast enhancement effect and optimizing the registration performance of the attenuation coefficient image. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 is an application environment diagram of an attenuation coefficient image processing method in one embodiment;

[0039] Figure 2 is a schematic flow chart of an attenuation coefficient image processing method in one embodiment;

[0040] Figure 3 is a schematic diagram of the attenuation coefficient value of each voxel in one embodiment;

[0041] Figure 4 is a schematic diagram of an attenuation coefficient image in one embodiment;

[0042] Figure 5 is a schematic diagram of an image to be registered in an embodiment;

[0043] Figure 6 A schematic diagram of a process for determining a linear piecewise function in one embodiment;

[0044] Figure 7 A schematic diagram of a process for determining a registered attenuation coefficient image in one embodiment;

[0045] Figure 8 A schematic diagram of a process for determining a target deformation field in one embodiment;

[0046] Fig. 9 is a schematic diagram of a process for determining a target deformation field in another embodiment;

[0047] Fig.10 is a structural block diagram of an attenuation coefficient image processing device in one embodiment;

[0048] Fig.11FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0050] Attenuation coefficient images are of great significance to PET reconstruction, and their accuracy directly affects the quality of PET reconstructed images. Inaccurate attenuation coefficient images will cause attenuation correction artifacts when reconstructing images. In order to solve the problem of attenuation correction artifacts, the registration of attenuation coefficient images is particularly important. However, the accuracy of the registration of attenuation coefficient images is usually related to the contrast of the attenuation coefficient images. When the boundaries of organs or tissues are clear and the attenuation coefficient values ​​differ greatly, the registration can achieve the best registration accuracy. Therefore, the use of registration algorithms to register areas with large differences in attenuation coefficient values ​​in attenuation coefficient images can achieve better results; while for the junctions of kidneys, fat, liver and other parts with close attenuation coefficient values, the registration accuracy is poor. Therefore, in order to solve the above problems, the present application proposes an attenuation coefficient image processing method, device, computer equipment and storage medium.

[0051] The attenuation coefficient image processing method provided in the embodiment of the present application can be applied to Figure 1 The application environment includes a computer device, which may be a server, and its internal structure diagram may be as shown in FIG. Figure 1 As shown. The computer device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store image processing related data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, an attenuation coefficient image processing method is implemented. Among them, the server can be implemented as an independent server or a server cluster composed of multiple servers.

[0052] In one embodiment, Figure 2 As shown, a method for processing an attenuation coefficient image is provided, and the method is applied to Figure 1 The computer device in the example is used to illustrate, including the following steps:

[0053] S201. According to the attenuation coefficient values corresponding to each voxel in the attenuation coefficient image, each voxel is divided into different attenuation coefficient intervals, and the image contrast of different attenuation coefficient intervals is different.

[0054] In this embodiment, after obtaining the attenuation coefficient values corresponding to each voxel and the preset attenuation coefficient intervals, the attenuation coefficient values corresponding to each voxel can be divided into different attenuation coefficient intervals. Optionally, the preset attenuation coefficient intervals can be three attenuation coefficient intervals, namely, the low-density attenuation coefficient interval, the medium-density attenuation coefficient interval, and the high-density attenuation coefficient interval, or can be four or more attenuation coefficient intervals, etc.

[0055] If the preset attenuation coefficient intervals are the low-density attenuation coefficient interval, the medium-density attenuation coefficient interval, and the high-density attenuation coefficient interval, each voxel is divided into different attenuation coefficient intervals according to the attenuation coefficient value corresponding to each voxel. For example, the low-density attenuation coefficient interval mainly includes voxels of tissues such as the lungs and cavities; the medium-density attenuation coefficient interval mainly includes voxels of tissues such as muscles, fat, kidneys, and livers, and the high-density attenuation coefficient interval is mainly voxels of tissues such as bones.

[0056] S202. Based on the preset piecewise linear function, the attenuation coefficient values of the voxels in each attenuation coefficient interval are adjusted; the slope of the piecewise linear function of the attenuation coefficient interval with the smallest image contrast is greater than the slopes of the piecewise linear functions of other attenuation coefficient intervals.

[0057] In this embodiment, the slope of the piecewise linear function of the attenuation coefficient interval with the smallest image contrast is greater than the slopes of the piecewise linear functions of other attenuation coefficient intervals. For each attenuation coefficient interval, the attenuation coefficient value of each voxel is substituted into the piecewise linear function corresponding to the corresponding attenuation coefficient interval to obtain the adjusted attenuation coefficient value of each voxel.

[0058] As Figure 3 shown, Figure 3 Figure 19 shows the attenuation coefficient values of each voxel with a 511 keV photon energy in an embodiment, where the abscissa is the attenuation coefficient value and the ordinate is the adjusted attenuation coefficient value. Figure 3 It includes a piecewise linear function with 3 attenuation coefficient intervals. The piecewise linear functions corresponding to the three attenuation coefficient intervals are: the piecewise linear function of the low-density attenuation coefficient interval is y1 = k1 * x (0 ≤ x < x1); the piecewise linear function of the medium-density attenuation coefficient interval is y2 = k2 * x + k1 * x1 - k2 * x1 (x1 ≤ x < x2); the piecewise linear function of the high-density attenuation coefficient interval is y3 = k3 * x + k2 * x2 + k1 * x1 - k2 * x1 - k3 * x2 (x2 ≤ x ≤ x3), where k1, k2, and k3 are all greater than 0, x is the attenuation coefficient value of each voxel, and y is the adjusted attenuation coefficient value of each voxel.

[0059] It should be noted that the linear piecewise function is a continuous and monotonically increasing function, such as the linear piecewise function y1 in the low-density attenuation coefficient interval, the linear piecewise function y2 in the medium-density attenuation coefficient interval, and the linear piecewise function y3 in the high-density attenuation coefficient interval. y1, y2 and y3 are continuous and monotonically increasing.

[0060] Since the image contrast in the medium-density attenuation coefficient interval is the smallest, and the image contrast in the low-density attenuation coefficient interval is greater than the image contrast in the high-density attenuation coefficient interval, k2 can be set to be greater than k1, and k1 can be set to be greater than k3. If the image contrast in the low-density attenuation coefficient interval and the image contrast in the high-density attenuation coefficient interval are not particularly obvious, it is sufficient to satisfy the maximum k2 value, and the size relationship between k1 and k3 is not specifically limited.

[0061] Figure 3 The attenuation coefficient values ​​of the voxels of several major tissues are marked at the same time. It can be seen that the attenuation coefficient value of the voxels in the kidney is very close to the attenuation coefficient value of the voxels in the fat, that is, the projections of the voxels in the kidney and the voxels in the fat in the x-axis direction are very close. After being processed by the linear piecewise function, the difference between the projections of the voxels in the kidney and the voxels in the fat in the y-axis direction becomes larger.

[0062] It should be noted that the main purpose of using the linear piecewise function is to increase the difference in the attenuation coefficient values ​​of the voxels that are closer. Therefore, in the process of mapping the attenuation coefficient values ​​of each voxel using the linear piecewise function, the voxels with originally large attenuation coefficient values ​​may have a smaller difference in the new attenuation coefficient values ​​after the mapping process, as long as the difference in the new attenuation coefficient values ​​is greater than the preset difference. For example, the voxels of kidney tissue and the voxels of bone tissue.

[0063] S203: Obtain a pre-processed image to be registered based on the adjusted attenuation coefficient value.

[0064] Repeat the above operation for the attenuation coefficient value of each voxel, and replace the attenuation coefficient value of each voxel in the attenuation coefficient map with the mapped new attenuation coefficient value, thereby obtaining the preprocessed image to be registered. Figure 4 and Figure 5 As shown, Figure 4 is an attenuation coefficient image in one embodiment, Figure 5 is an image to be registered in an embodiment, through Figure 4 and Figure 5 It can be clearly seen from the comparison that the edges of the liver and kidneys become clearer, and the contrast between different tissues becomes greater.

[0065] In the above-mentioned attenuation coefficient image processing method, each voxel is divided into different attenuation coefficient intervals according to the attenuation coefficient value corresponding to each voxel in the attenuation coefficient image, and the attenuation coefficient value of the voxel in each attenuation coefficient interval is adjusted based on a preset linear piecewise function, and the preprocessed image to be registered is obtained based on the adjusted attenuation coefficient value. The image contrast of different attenuation coefficient intervals is different, and the slope of the linear piecewise function of the attenuation coefficient interval with the smallest image contrast is greater than the slope of the linear piecewise function of other attenuation coefficient intervals. In the embodiment of the present application, the slope of the linear piecewise function of the attenuation coefficient interval with the smallest image contrast is greater than the slope of the linear piecewise function of other attenuation coefficient intervals, so that the attenuation coefficient value of each voxel in the attenuation coefficient image is mapped according to the linear piecewise function corresponding to each attenuation coefficient interval, and the attenuation coefficient value in the attenuation coefficient image is adjusted, thereby achieving a contrast enhancement effect and optimizing the registration performance of the attenuation coefficient image.

[0066] Figure 6 FIG. 1 is a flow chart of determining a linear piecewise function in one embodiment. Figure 6 As shown, the following steps are included:

[0067] S601: Allocate multiple preset slopes to each attenuation coefficient interval.

[0068] Optionally, the preset slope may be 0.2, 0.5, etc., and the preset slope may be determined based on a large number of attenuation coefficient images.

[0069] In this embodiment, the largest preset slope may be allocated to the attenuation coefficient interval with the smallest image contrast, and other preset slopes may be randomly allocated to other attenuation coefficient intervals.

[0070] In one possible implementation, the preset slopes can be sorted in ascending order to obtain a first sorting result, and the contrasts corresponding to each attenuation coefficient interval can be sorted in descending order to obtain a second sorting result. The first sorting result and the second sorting result can be matched one by one, that is, the largest preset slope is assigned to the attenuation coefficient interval corresponding to the smallest contrast in the sorting result, and the smallest preset slope is assigned to the attenuation coefficient interval corresponding to the largest contrast in the sorting result.

[0071] S602: Determine a corresponding linear piecewise function according to a preset slope of each attenuation coefficient interval.

[0072] In this embodiment, the corresponding linear piecewise function is determined according to the preset slope of each attenuation coefficient interval. Exemplarily, there are the above three attenuation coefficient intervals, and the three attenuation coefficient intervals are [0, x1], [x1, x2], [x2, x3], and the preset slopes are k1, k2, and k3 respectively.

[0073] Then the expression of the linear piecewise function corresponding to each attenuation coefficient interval is:

[0074] y1=k1*x(0≤x <x1)

[0075] y2=k2*x+k1*x1-k2*x1(x1≤x <x2)

[0076] y3=k3*x+k2*x2+k1*x1-k2*x1-k3*x2(x2≤x≤x3)

[0077] If there are two attenuation coefficient intervals, the expression of the linear piecewise function corresponding to each attenuation coefficient interval is:

[0078] y1=k1*x(0≤x <x1)

[0079] y2=k2*x+k1*x1-k2*x1(x1≤x≤x2)

[0080] In the embodiment of the present application, multiple preset slopes are assigned to each attenuation coefficient interval, and the corresponding linear piecewise function is determined according to the preset slope of each attenuation coefficient interval. In this embodiment, multiple preset slopes are assigned to each attenuation coefficient interval according to the image contrast of different attenuation coefficient intervals, and the linear piecewise function is determined according to the preset slope, which improves the efficiency of determining the linear piecewise function.

[0081] Figure 7 FIG. 1 is a schematic diagram of a process for determining a registered attenuation coefficient image in one embodiment. Figure 7 As shown, the following steps are included:

[0082] S701, determining a target deformation field according to a first image to be registered and a second image to be registered.

[0083] Optionally, the attenuation coefficient image includes a motion image and a reference image, and the image to be registered includes a first image to be registered of the motion image and a second image to be registered of the reference image.

[0084] In this embodiment, the moving image and the reference image are respectively Figure 2-Figure 7 The motion image and the reference image are preprocessed by a method to obtain a first image to be registered corresponding to the motion image and a second image to be registered corresponding to the reference image. Optionally, the motion image and the reference image may be attenuation coefficient images obtained using a computed tomography image, or an attenuation coefficient image obtained using a magnetic resonance image; the reference image may be an attenuation coefficient image obtained using a PET image.

[0085] The first image to be registered and the second image to be registered are registered to obtain a target deformation field. For example, the first image to be registered and the second image to be registered are registered using a non-rigid image registration algorithm based on B-splines to obtain a target deformation field.

[0086] S702, determining a registered attenuation coefficient image according to the target deformation field and the motion image.

[0087] In this embodiment, the target deformation field is applied to the motion image to obtain the deformed motion image, and thus the registered attenuation coefficient image is obtained according to the deformed motion image.

[0088] In the embodiment of the present application, the target deformation field is determined based on the first image to be registered and the second image to be registered, and the registered attenuation coefficient image is determined based on the target deformation field and the motion image. In the present embodiment, the target deformation field is determined based on the first image to be registered and the second image to be registered, and the first image to be registered and the second image to be registered are subjected to contrast enhancement processing, so that the determination of the target deformation field is more accurate, thereby improving the accuracy of attenuation coefficient image registration.

[0089] Figure 8 FIG. 1 is a schematic diagram of a process for determining a target deformation field in an embodiment. Figure 8 As shown, the embodiment of the present application relates to a possible implementation method of how to determine a target deformation field according to a first image to be registered and a second image to be registered, including the following steps:

[0090] S801: Acquire first position information of a plurality of control points on a reference image.

[0091] In this embodiment, the first position information of the plurality of control points may be acquired at equal intervals on the reference image, or the first position information of the plurality of control points may be acquired arbitrarily on the reference image.

[0092] S802, determining a target deformation field according to an objective function, a first image to be registered, and a second image to be registered; the objective function includes first position information of a plurality of control points.

[0093] In this embodiment, the objective function can be optimized for the first position information of the control point according to the first image to be registered and the second image to be registered, and the second position information of the control point can be obtained when the objective function converges. The second position information of the control point is interpolated using an interpolation algorithm to obtain a target deformation field.

[0094] In a possible implementation, after obtaining the second position information of the control point, the second position information of the control point may be processed using a matrix decomposition-based method or a matrix approximation-based method to obtain the target deformation field.

[0095] In the embodiment of the present application, the first position information of the plurality of control points on the reference image is obtained, and the target deformation field is determined according to the objective function, the first image to be registered, and the second image to be registered. In the present embodiment, the contrast of the first image to be registered and the second image to be registered are both enhanced, thereby improving the accuracy of the target deformation field obtained based on the first image to be registered and the second image to be registered.

[0096] Fig. 9 FIG. 1 is a schematic diagram of a process for determining a target deformation field in an embodiment. Fig. 9 As shown, the embodiment of the present application relates to a possible implementation method of how to determine the target deformation field according to the objective function, the first image to be registered and the second image to be registered, including the following steps:

[0097] S901, iteratively optimizing first position information of a plurality of control points according to a first image to be registered and a second image to be registered, to obtain second position information of the plurality of control points satisfying a minimization objective function.

[0098] In this embodiment, the first position information of the plurality of control points is iteratively optimized according to the first image to be registered and the second image to be registered until the second position information of the plurality of control points is obtained when the objective function converges. For example, the parameter information of the first image to be registered and the second image to be registered are substituted into the objective function, and according to the direction of descent of the objective function, the first position information of the control points is iteratively optimized using a gradient descent method, a least squares method, a genetic algorithm, etc. so as to minimize the objective function.

[0099] S902: Determine a target deformation field according to second position information of a plurality of control points and an interpolation algorithm.

[0100] In this embodiment, since the first position information of the control point is the position information of multiple control points obtained in the reference image, and the second position information of the control point is obtained by iteratively optimizing the first position information of the control point, the second position information of the control point can be restored to a target deformation field consistent with the size of the reference image using an interpolation algorithm. Optionally, a B-spline interpolation algorithm, a nearest neighbor interpolation algorithm, a bilinear interpolation algorithm, etc. can be used.

[0101] In the embodiment of the present application, the first position information of multiple control points is iteratively optimized based on the first image to be registered and the second image to be registered to obtain the second position information of multiple control points that satisfies the minimization objective function, and the target deformation field is determined based on the second position information of the multiple control points and the interpolation algorithm. In this embodiment, the second position information of the control points is obtained by iteratively optimizing the minimization objective function of the first position information of multiple control points, so that the accuracy of the target deformation field obtained based on the second position information of the control points is achieved, which lays the foundation for the subsequent determination of the attenuation coefficient image after registration based on the target deformation field and the motion image.

[0102] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0103] Based on the same inventive concept, the embodiment of the present application also provides an attenuation coefficient image processing device for implementing the attenuation coefficient image processing method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the one or more attenuation coefficient image processing device embodiments provided below can refer to the limitations of the attenuation coefficient image processing method above, and will not be repeated here.

[0104] In one embodiment, Fig.10 As shown, an attenuation coefficient image processing device is provided, comprising: a division module 11, an adjustment module 12 and a first determination module 13, wherein:

[0105] A division module 11 is used to divide each voxel into different attenuation coefficient intervals according to the attenuation coefficient value corresponding to each voxel in the attenuation coefficient image, and the image contrast of different attenuation coefficient intervals is different;

[0106] An adjustment module 12, configured to adjust the attenuation coefficient value of the voxels in each attenuation coefficient interval based on a preset linear piecewise function; the slope of the linear piecewise function of the attenuation coefficient interval with the minimum image contrast is greater than the slopes of the linear piecewise functions of other attenuation coefficient intervals;

[0107] The first determination module 13 is used to obtain the pre-processed image to be registered based on the adjusted attenuation coefficient value.

[0108] In one embodiment, the attenuation coefficient image processing device further includes:

[0109] An allocation module, used for allocating a plurality of preset slopes to each attenuation coefficient interval;

[0110] The second determination module is used to determine the corresponding linear piecewise function according to the preset slope of each attenuation coefficient interval.

[0111] In one embodiment, the attenuation coefficient image includes a motion image and a reference image, and the images to be registered include a first image to be registered of the motion image and a second image to be registered of the reference image.

[0112] In one embodiment, an attenuation coefficient image processing device is provided, further comprising:

[0113] A third determination module, used to determine a target deformation field according to the first image to be registered and the second image to be registered;

[0114] The fourth determination module is used to determine the registered attenuation coefficient image according to the target deformation field and the motion image.

[0115] In one embodiment, the fourth determining module includes:

[0116] An acquiring unit, used for acquiring first position information of a plurality of control points on a reference image;

[0117] The first determining unit is used to determine the target deformation field according to the target function, the first image to be registered and the second image to be registered; the target function includes first position information of multiple control points.

[0118] In one embodiment, the first determination unit is also used to iteratively optimize the first position information of multiple control points according to the first image to be registered and the second image to be registered to obtain the second position information of the multiple control points that satisfies the minimization objective function; and determine the target deformation field according to the second position information of the multiple control points and the interpolation algorithm.

[0119] Each module in the attenuation coefficient image processing device can be implemented in whole or in part by software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module.

[0120] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Fig.11As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, an attenuation coefficient image processing method is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0121] Those skilled in the art will understand that Fig.11 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0122] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0123] According to the attenuation coefficient value corresponding to each voxel in the attenuation coefficient image, each voxel is divided into different attenuation coefficient intervals, and the image contrast of different attenuation coefficient intervals is different;

[0124] Based on a preset linear piecewise function, the attenuation coefficient value of the voxel in each attenuation coefficient interval is adjusted; the slope of the linear piecewise function of the attenuation coefficient interval with the minimum image contrast is greater than the slope of the linear piecewise function of other attenuation coefficient intervals;

[0125] Based on the adjusted attenuation coefficient value, the preprocessed image to be registered is obtained.

[0126] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0127] Allocating a plurality of preset slopes to each attenuation coefficient interval;

[0128] The corresponding linear piecewise function is determined according to the preset slope of each attenuation coefficient interval.

[0129] In one embodiment, the attenuation coefficient image includes a motion image and a reference image, and the images to be registered include a first image to be registered of the motion image and a second image to be registered of the reference image.

[0130] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0131] Determine a target deformation field according to the first image to be registered and the second image to be registered;

[0132] According to the target deformation field and the motion image, the registered attenuation coefficient image is determined.

[0133] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0134] Acquire first position information of a plurality of control points on a reference image;

[0135] The target deformation field is determined according to the target function, the first image to be registered and the second image to be registered; the target function includes first position information of a plurality of control points.

[0136] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0137] Iteratively optimize first position information of multiple control points according to the first image to be registered and the second image to be registered to obtain second position information of the multiple control points that satisfies the minimization objective function;

[0138] The target deformation field is determined according to the second position information of the plurality of control points and an interpolation algorithm.

[0139] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0140] According to the attenuation coefficient value corresponding to each voxel in the attenuation coefficient image, each voxel is divided into different attenuation coefficient intervals, and the image contrast of different attenuation coefficient intervals is different;

[0141] Based on a preset linear piecewise function, the attenuation coefficient value of the voxel in each attenuation coefficient interval is adjusted; the slope of the linear piecewise function of the attenuation coefficient interval with the minimum image contrast is greater than the slope of the linear piecewise function of other attenuation coefficient intervals;

[0142] Based on the adjusted attenuation coefficient value, the preprocessed image to be registered is obtained.

[0143] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0144] Allocating multiple preset slopes to each attenuation coefficient interval; allocating the largest preset slope to the attenuation coefficient interval corresponding to the smallest image contrast;

[0145] The corresponding linear piecewise function is determined according to the preset slope of each attenuation coefficient interval.

[0146] In one embodiment, the attenuation coefficient image includes a motion image and a reference image, and the images to be registered include a first image to be registered of the motion image and a second image to be registered of the reference image.

[0147] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0148] Determine a target deformation field according to the first image to be registered and the second image to be registered;

[0149] According to the target deformation field and the motion image, the registered attenuation coefficient image is determined.

[0150] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0151] Acquire first position information of a plurality of control points on a reference image;

[0152] The target deformation field is determined according to the target function, the first image to be registered and the second image to be registered; the target function includes first position information of a plurality of control points.

[0153] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0154] Iteratively optimize first position information of multiple control points according to the first image to be registered and the second image to be registered to obtain second position information of the multiple control points that satisfies the minimization objective function;

[0155] The target deformation field is determined according to the second position information of the plurality of control points and an interpolation algorithm.

[0156] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0157] According to the attenuation coefficient value corresponding to each voxel in the attenuation coefficient image, each voxel is divided into different attenuation coefficient intervals, and the image contrast of different attenuation coefficient intervals is different;

[0158] Based on a preset linear piecewise function, the attenuation coefficient value of the voxel in each attenuation coefficient interval is adjusted; the slope of the linear piecewise function of the attenuation coefficient interval with the minimum image contrast is greater than the slope of the linear piecewise function of other attenuation coefficient intervals;

[0159] Based on the adjusted attenuation coefficient value, the preprocessed image to be registered is obtained.

[0160] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0161] Allocating a plurality of preset slopes to each attenuation coefficient interval;

[0162] The corresponding linear piecewise function is determined according to the preset slope of each attenuation coefficient interval.

[0163] In one embodiment, the attenuation coefficient image includes a motion image and a reference image, and the images to be registered include a first image to be registered of the motion image and a second image to be registered of the reference image.

[0164] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0165] Determine a target deformation field according to the first image to be registered and the second image to be registered;

[0166] According to the target deformation field and the motion image, the registered attenuation coefficient image is determined.

[0167] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0168] Obtaining position information of a plurality of control points on a reference image;

[0169] The target deformation field is determined according to the target function, the first image to be registered and the second image to be registered; the target function includes first position information of a plurality of control points.

[0170] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0171] Iteratively optimize first position information of multiple control points according to the first image to be registered and the second image to be registered to obtain second position information of the multiple control points that satisfies the minimization objective function;

[0172] The target deformation field is determined according to the second position information of the plurality of control points and an interpolation algorithm.

[0173] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0174] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0175] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0176] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for processing an attenuation coefficient image, characterized in that: The method comprises: According to the attenuation coefficient value corresponding to each voxel in the attenuation coefficient image, each voxel is divided into different attenuation coefficient intervals, and the image contrast of the different attenuation coefficient intervals is different; Based on a preset linear piecewise function, the attenuation coefficient value of the voxel in each attenuation coefficient interval is adjusted; the slope of the linear piecewise function of the attenuation coefficient interval with the minimum image contrast is greater than the slope of the linear piecewise function of other attenuation coefficient intervals; Based on the adjusted attenuation coefficient value, the preprocessed image to be registered is obtained.

2. The method according to claim 1, characterized in that: The method further comprises: Allocating a plurality of preset slopes to each of the attenuation coefficient intervals; The corresponding linear piecewise function is determined according to the preset slope of each attenuation coefficient interval.

3. The method according to claim 1, characterized in that The attenuation coefficient image includes a motion image and a reference image, and the images to be registered include a first image to be registered of the motion image and a second image to be registered of the reference image.

4. The method according to claim 3, characterized in that: After obtaining the preprocessed image to be registered based on the adjusted attenuation coefficient value, the method further includes: determining a target deformation field according to the first image to be registered and the second image to be registered; A registered attenuation coefficient image is determined according to the target deformation field and the motion image.

5. The method according to claim 4, characterized in that The step of determining a target deformation field according to the first image to be registered and the second image to be registered includes: Acquire first position information of a plurality of control points on the reference image; The target deformation field is determined according to an objective function, the first image to be registered, and the second image to be registered; the objective function includes first position information of the plurality of control points.

6. The method according to claim 5, characterized in that The determining the target deformation field according to the objective function, the first image to be registered, and the second image to be registered comprises: Iteratively optimize the first position information of the plurality of control points according to the first image to be registered and the second image to be registered to obtain the second position information of the plurality of control points that satisfies the minimization objective function; The target deformation field is determined according to the second position information of the plurality of control points and an interpolation algorithm.

7. An attenuation coefficient image processing device, characterized in that: The device comprises: A division module, used for dividing each voxel into different attenuation coefficient intervals according to the attenuation coefficient value corresponding to each voxel in the attenuation coefficient image, wherein the image contrast of the different attenuation coefficient intervals is different; An adjustment module, used for adjusting the attenuation coefficient value of the voxel in each attenuation coefficient interval based on a preset linear piecewise function; the slope of the linear piecewise function of the attenuation coefficient interval with the minimum image contrast is greater than the slope of the linear piecewise function of other attenuation coefficient intervals; The first determination module is used to obtain a preprocessed image to be registered based on the adjusted attenuation coefficient value.

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

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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