Image reconstruction method and device

Abstract

The invention relates to an image reconstruction method and device. The method comprises the following steps: acquiring original scanning data of a scanning object; the original scanning data is obtained by scanning at different speeds by the scanning equipment; correcting the original scanning data according to the correction factor corresponding to the moving object; the moving object comprises a scanning object or scanning equipment; wherein different voxels correspond to different correction factors; and performing image reconstruction on the corrected original scanning data to obtain a scanning image of the scanning object. The method can improve the quality of the scanned image.

Description

Technical Field

[0001] The present application relates to the technical field of image reconstruction, and in particular to an image reconstruction method and device. Background Art

[0002] Single Photon Emission Computed Tomography (SPECT) is a relatively mature imaging technology in the field of nuclear medicine and has been widely used in clinical testing.

[0003] For scanning scenarios, in the related art, uniform scanning of the detection object is mainly achieved by moving the probe and the bed to obtain a scanned image of the detection object.

[0004] However, for non-uniform scanning requirements, the quality of the scanned image obtained by the related art method is poor. Summary of the invention

[0005] Based on this, it is necessary to provide an image reconstruction method and device that can improve the quality of scanned images in response to the above technical problems.

[0006] In a first aspect, the present application provides an image reconstruction method, the method comprising:

[0007] Acquire original scan data of the scanned object; the original scan data is obtained by scanning the scanning device at different speeds;

[0008] Correcting the original scan data according to the correction factor corresponding to the moving object; the moving object includes the scan object or the scanning device;

[0009] The corrected original scanning data is reconstructed to obtain a scanning image of the scanned object.

[0010] In one embodiment, the scanning device includes a scanning bed and a detector;

[0011] Get the original scan data of the scanned object, including:

[0012] The detector is controlled to scan the scanning object at a speed relative to the scanning bed to obtain raw scanning data.

[0013] In one embodiment, controlling the detector to scan the scan object at a speed relative to the scanning bed to obtain raw scan data includes:

[0014] When the detector is fixed, the scanning bed is controlled to move along the detector in a non-uniform plane to obtain the original scanning data.

[0015] In one embodiment, the correction factors corresponding to the moving object include correction factors corresponding to different voxels on the scanned object;

[0016] Before correcting the original scan data according to the correction factor corresponding to the moving object, the method further includes:

[0017] Obtaining a start scanning time and an end scanning time of a plurality of voxels on a scanning object during a non-uniform plane scanning process;

[0018] Based on each scanning start time and each scanning end time, correction factors corresponding to a plurality of voxels on the scanning object are determined.

[0019] In one embodiment, determining correction factors corresponding to a plurality of voxels on a scanned object based on each scan start time and each scan end time includes:

[0020] For any voxel, the average moving speed of the detector is calculated through the start scanning time and the end scanning time corresponding to the voxel;

[0021] A correction factor corresponding to the voxel is generated based on the start scanning time, the end scanning time, the average moving speed, and the nuclide half-life of the nuclide in the body of the scanned object.

[0022] In one embodiment, controlling the detector to scan the scan object at a speed relative to the scanning bed to obtain raw scan data includes:

[0023] When the scanning bed is fixed in position, the detector is controlled to move non-uniformly at different angles of the scanning bed to obtain raw scanning data.

[0024] In one embodiment, the correction factors corresponding to the moving object include correction factors corresponding to different pixels on the detector;

[0025] Correct the original scan data according to the correction factors corresponding to the moving object, including:

[0026] Obtaining the scanning time difference between the start scanning time and the end scanning time corresponding to any pixel on the detector;

[0027] Generate a likelihood function corresponding to the original scan data according to the scan time difference and the correction factor;

[0028] The original scan data is corrected based on the likelihood function to obtain corrected original scan data.

[0029] In one embodiment, correcting the original scan data based on the likelihood function to obtain the corrected original scan data includes:

[0030] When the likelihood function is at a maximum value, the predicted scan data corresponding to the original scan data is obtained, and the predicted scan data is used as the corrected original scan data.

[0031] In one embodiment, the method further comprises:

[0032] The scanning requirements of the scanning object are analyzed to obtain multiple scanning areas of the detector; and the speed of the scanning device in the multiple scanning areas is determined.

[0033] In a second aspect, the present application further provides an image reconstruction device, comprising:

[0034] The data acquisition module is used to acquire the original scanning data of the scanned object; the original scanning data is obtained by scanning the scanning device at different speeds;

[0035] A correction module, used to correct the original scan data according to the correction factor corresponding to the moving object; the moving object includes the scanning object or the scanning device;

[0036] The reconstruction module is used to reconstruct the image of the corrected original scanning data to obtain a scanned image of the scanned object.

[0037] In a third aspect, the present application further provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the content of any one embodiment of the image reconstruction method in the first aspect is implemented.

[0038] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the content of any one embodiment of the image reconstruction method in the first aspect above.

[0039] In a fifth aspect, the present application further provides a computer program product, comprising a computer program, which, when executed by a processor, implements the content of any one embodiment of the image reconstruction method in the first aspect above.

[0040] The above-mentioned image reconstruction method and device obtain the original scanning data of the scanning object; the original scanning data is obtained by scanning the scanning device at different speeds; the original scanning data is corrected according to the correction factor corresponding to the moving object; the moving object includes the scanning object or the scanning device; the corrected original scanning data is reconstructed to obtain a scanning image of the scanning object. The original scanning data obtained by non-uniform scanning is inaccurate, so that the obtained scanning image is also inaccurate. Based on this, the method uses the moving object scanned at different speeds and obtains the correction factor corresponding to the moving object, which can accurately correct the original scanning data scanned at different speeds in a targeted manner, and the corrected original scanning data is made more accurate through correction. In this way, the quality of the reconstructed scanning image will also be higher. At the same time, it can also reduce the waiting time during the scanning process and improve the scanning efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0042] FIG1 is a diagram showing an application environment of an image reconstruction method according to an embodiment;

[0043] FIG2 is a schematic diagram of a flow chart of an image reconstruction method in one embodiment;

[0044] FIG3 is a schematic diagram of stepping plane scanning in one embodiment;

[0045] FIG4 is a schematic diagram of continuously variable speed scanning in one embodiment;

[0046] FIG5 is a schematic diagram of a flow chart of an image reconstruction method in one embodiment;

[0047] FIG6 is a schematic diagram of stepping plane scanning in one embodiment;

[0048] FIG7 is a schematic diagram of a curve of counting and scanning time in one embodiment;

[0049] FIG8 is a schematic diagram of continuously variable speed scanning in one embodiment;

[0050] FIG9 is a schematic diagram of a curve of counting and scanning time in one embodiment;

[0051] FIG10 is a schematic diagram of a flow chart of an image reconstruction method in one embodiment;

[0052] FIG11 is a schematic diagram of non-uniform tomography in one embodiment;

[0053] FIG12 is a schematic diagram of a flow chart of an image reconstruction method in one embodiment;

[0054] FIG13 is a schematic diagram of non-uniform tomography in one embodiment;

[0055] FIG14 is a schematic diagram of a curve showing pixel count and scanning time in one embodiment;

[0056] FIG15 is a schematic flow chart of an image reconstruction method in one embodiment;

[0057] FIG16 is a schematic diagram of a flow chart of an image reconstruction method in one embodiment;

[0058] FIG17 is a block diagram of an image reconstruction device in one embodiment;

[0059] FIG. 18 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

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

[0061] Before introducing the specific contents of this application in detail, a brief introduction to the background technology of this application is first given.

[0062] In clinical scanning scenarios, for common dual-probe SPECT, the movement of the detector and the scanning bed can be stepping motion or continuous motion. Stepping motion means that the same time is collected at each position; continuous motion means that the movement speed remains unchanged.

[0063] Whether it is stepping motion or continuous motion, the essence is to scan at the same scanning speed. For example, for a scanned object with a height of 180cm, if the scanning speed is 15cm / min, the required scanning time is 12min, which makes the scanned object's comfort and scanning efficiency low. However, during the scanning process, it is often hoped to increase the acquisition time or count for the lesion area, so that the scanning process of the lesion area can be more careful, and other areas except the lesion area can be scanned quickly. If a non-uniform speed method is used for clinical scanning, the image quality obtained by the scan is poor.

[0064] In view of the above problems, the present application provides an image reconstruction method and device, which corrects the non-uniform scanned data based on specific scanning requirements, and reconstructs the image based on the corrected non-uniform scanned data, thereby improving the quality of the scanned image. Of course, the technical solution provided in the embodiments of the present application is not limited to solving only the above problems, and there are other technical effects, which can be specifically referred to in the following embodiments. The technical solution of the present application is described in detail below.

[0065] The image reconstruction method provided in the embodiment of the present application can be applied in the application environment shown in FIG1. ​​The application environment includes a computer device 101 and a scanning device 102, and the computer device 101 and the scanning device 102 communicate with each other. The scanning device 102 performs non-uniform scanning on the scanned object at different moving speeds to obtain raw scan data, and sends the raw scan data to the computer device 101. The computer device 101 can correct the raw scan data according to the correction factors corresponding to different voxels on the scanned object; and reconstruct the image of the corrected raw scan data to obtain a scanned image of the scanned object.

[0066] In an exemplary embodiment, as shown in FIG2 , an image reconstruction method is provided, which is described by taking the method applied to the computer device in FIG1 as an example, and includes the following steps 201 to 203. Among them:

[0067] S201, obtaining original scanning data of a scanning object; the original scanning data is obtained by scanning a scanning device at different speeds.

[0068] Among them, the scanning device can scan the scanning object in a uniform speed variation manner or a variable acceleration manner. For example, the uniform speed variation manner can be a manner in which the speed gradually increases or the speed gradually decreases; the variable acceleration manner can be a manner in which the acceleration gradually increases or the acceleration gradually decreases. Alternatively, the scanning device can be divided into different scanning areas, and the corresponding scanning areas are scanned at different speeds, and the scanning speed within each scanning area is the same. For example, the scanning area can be the head, abdomen, and lower limbs of the scanning object, which belong to different scanning areas respectively; the lesion area and non-lesion area of ​​the scanning object also belong to different scanning areas. That is, the original scanning data is obtained by non-uniform scanning.

[0069] In the embodiment of the present application, after the scanning device performs non-uniform scanning on the scanning object at different speeds, the scanned data is stored in the scanning database. At this time, the computer device can obtain the original scanning data of the scanning object from the scanning database based on the identification information of the scanning object.

[0070] Optionally, the computer device can determine multiple scanning speeds on the scanned object according to the doctor's scanning requirements for the scanned object. And generate a control instruction based on the scanning requirements and the multiple scanning speeds on the scanned object. The control instruction is used to control the scanning device to perform non-uniform scanning on the scanned object to obtain raw scanning data. The embodiment of the present application does not limit the method for obtaining the raw scanning data of the scanned object.

[0071] S202, correcting the original scan data according to the correction factor corresponding to the moving object; the moving object includes a scan object or a scanning device.

[0072] In the embodiment of the present application, before scanning the scanned object by the scanning device, a nuclide needs to be injected into the scanned object. The nuclide will decay in the scanned object, making the accuracy of the original scan data poor. Therefore, the original scan data needs to be corrected to ensure the accuracy of the original scan data. For example, when the scanning device is SPECT, the nuclide injected into the scanned object is the radioactive element technetium-99m (Tc-99m). The injection amount of this nuclide is small and can be excreted from the body through normal metabolism.

[0073] Specifically, there are two situations when the scanning device scans at different speeds. In one situation, the scanning object moves with the scanning bed at different scanning speeds, and in the other situation, the detector in the scanning device moves at different speeds. In either case, the moving object moves at different speeds to complete the scanning process. The quality of different pixels in the scanned image at different moving speeds is different. Therefore, in order to ensure that the quality of different pixels in the corrected scanned image is in the same dimension, the correction factors corresponding to the moving object at different moving speeds are also different. Based on this, the computer device can use the correction factor corresponding to the moving object to correct the original scan data to obtain the corrected original scan data.

[0074] S203, performing image reconstruction on the corrected original scan data to obtain a scanned image of the scanned object.

[0075] In the embodiment of the present application, after obtaining the corrected raw scan data, the computer device can input the corrected raw scan data into a preset image reconstruction model, and use the image reconstruction model to analyze the raw scan data to reconstruct a scanned image of the scanned object. The image reconstruction model can be a fully convolutional network (for example, a V-Net network, a U-Net network, etc.), a generative adversarial network (pix2pix network, a WGAN network, etc.).

[0076] Optionally, the computer device may also reconstruct the corrected raw scan data using an image reconstruction algorithm to obtain a scanned image of the scanned object. For example, the image reconstruction algorithm may be a back projection method, a Fourier transform reconstruction method, a filtered back projection reconstruction method, a convolution back projection method, or an iterative reconstruction algorithm, etc.

[0077] In the above-mentioned image reconstruction method, the original scanning data of the scanning object is obtained; the original scanning data is obtained by scanning the scanning device at different speeds; the original scanning data is corrected according to the correction factor corresponding to the moving object; the moving object includes the scanning object or the scanning device; the corrected original scanning data is reconstructed to obtain a scanning image of the scanning object. The original scanning data obtained by non-uniform scanning is inaccurate, so that the obtained scanning image is also inaccurate. Based on this, the method uses the moving object scanned at different speeds and obtains the correction factor corresponding to the moving object, which can accurately correct the original scanning data scanned at different speeds in a targeted manner, and the corrected original scanning data is made more accurate through correction. In this way, the quality of the reconstructed scanning image will also be higher. At the same time, it can also reduce the waiting time during the scanning process and improve the scanning efficiency.

[0078] Assuming that the scanning device includes a scanning bed and a detector, the specific content of obtaining the original scanning data of the scanning object is introduced in one embodiment, and the specific content includes:

[0079] The detector is controlled to scan the scanning object at a speed relative to the scanning bed to obtain raw scanning data.

[0080] In the embodiment of the present application, the scanning device needs to ensure that the scanning speed is different.

[0081] The detector and the scanning bed in the scanning device move at different relative speeds. In this case, the detector can be controlled to move along the scanning bed, or the scanning bed can be controlled to move along the detector to obtain raw scan data. It should be noted that in order to ensure the quality of the raw scan data, the detector and the scanning bed cannot be controlled to move at the same time.

[0082] In the above-mentioned image reconstruction method, the detector is controlled to scan the scanned object at a speed relative to the scanning bed to obtain raw scan data. This method controls the relative movement of the detector and the scanning bed to achieve the detector scanning the scanned object at different speeds, thereby ensuring that the original scan data is obtained after non-uniform scanning of the scanning device.

[0083] The above embodiments mentioned that the non-uniform scanning methods include non-uniform plane scanning and non-uniform tomographic scanning. Next, these two scanning methods are introduced one by one through different embodiments.

[0084] First, the non-uniform plane scanning method is introduced. In one embodiment, the specific content of obtaining the original scanning data of the scanning object includes:

[0085] When the detector is fixed, the scanning bed is controlled to move along the detector in a non-uniform plane to obtain the original scanning data.

[0086] For the plane scanning process, it is necessary to fix the position of the detector in the scanning device, and scan the scanning object on the scanning bed by moving the scanning bed to obtain the original scanning data of the scanning object. It should be noted that the non-uniform plane scanning method can also be subdivided into step plane scanning and continuous variable speed scanning. Figure 3 is a schematic diagram of step plane scanning, in which the detector is set at a fixed position, and the scanning bed moves below the detector. The upper body and lower body of the scanning object correspond to a scanning area respectively. Taking each scanning area corresponding to a scanning speed as an example, the scanning speed of the upper body is completely different from the scanning speed of the lower body. Alternatively, whether it is the upper body or the lower body, it can also be scanned at different speeds. Figure 4 is a schematic diagram of continuous variable speed scanning. Similarly, the fixed position of the detector, the movement process of the scanning bed, and the moving speeds of different scanning areas are the same as those in Figure 3.

[0087] In the embodiment of the present application, the control instruction sent by the computer device to the scanning device carries the control instruction corresponding to the detector and the control instruction of the scanning bed. Therefore, in the case where the non-uniform scanning is a non-uniform plane scanning, after the detector receives the control instruction, the position of the detector is fixed. At this time, the computer device sends a control instruction to the scanning bed to control the scanning bed to move within the scannable range of the detector, and the movement process refers to the non-uniform plane movement. The detector collects the scanning data of the scanned object during the movement of the scanning bed. After the scanning bed moves, the collection process of the detector ends, and the detector sends the collected raw scanning data to the computer device.

[0088] In the above image reconstruction method, when the detector position is fixed, the scanning bed is controlled to move along the detector in a non-uniform plane to obtain the original scanning data. In the process of non-uniform plane scanning, the position of the detector is fixed, and by limiting the movement speed of the scanning bed, the detector can scan different scanning parts of the scanned object in a non-uniform acquisition manner, and the original scanning data of the scanned object can be accurately obtained.

[0089] Assuming that the correction factors corresponding to the moving object include correction factors corresponding to different voxels on the scanned object, in one embodiment, as shown in FIG5 , before correcting the original scanned data according to the correction factors corresponding to the moving object, the method for obtaining the correction factors corresponding to different voxels on the scanned object includes the following steps:

[0090] S301, obtaining a start scanning time and an end scanning time of a plurality of voxels on a scanning object during a non-uniform plane scanning process.

[0091] The start scanning time refers to the time when the voxel of the scanning object moves to the start position of the detector, and the end scanning time refers to the time when the voxel of the scanning object moves to the end position of the detector.

[0092] In the embodiment of the present application, the scanning device can record the scanning position and the corresponding scanning time during the scanning of the scanning object, and store the recorded information and the original scanning data in the scanning database. Therefore, the computer device can search from the scanning database according to the identification information of the scanning object to obtain the start scanning time and the end scanning time of multiple voxels on the scanning object during the non-uniform plane scanning process.

[0093] FIG6 is a schematic diagram of step-by-step plane scanning. It can be seen from the figure that any unit volume on the scanned object can be used as a voxel i. FIG7 is a schematic diagram of the curve of count and scanning time. The ordinate represents the count of the detector on the voxel, and the abscissa represents the time change during the detector scanning process. The starting scanning time of the voxel is t ia The scanning end time is t ib , then the scanning time difference D of voxel i i It can be expressed as:

[0094] D i =t ib -t ia

[0095] FIG8 is a schematic diagram of continuously variable speed scanning, from which we can see the position of voxel i, and the length of the detector is L. FIG9 is a schematic diagram of the curve of count and scanning time, in which the horizontal and vertical coordinates are the same as those in FIG7. For any voxel i on the scanned object, the start scanning time when the detector just passes over voxel i is t ia , the end scanning time just leaving voxel i is t ib .

[0096] S302: Determine correction factors corresponding to a plurality of voxels on the scan object based on each scan start time and each scan end time.

[0097] In the embodiment of the present application, after obtaining the start scanning time and the end scanning time corresponding to each voxel on the scanned object, for any voxel, the computer device can calculate the scanning speed of the voxel based on the time difference between the start scanning time and the end scanning time of the voxel. And based on the theoretical relationship between the scanning speed and the correction factor, the correction factor corresponding to the voxel is determined. In the above manner, the correction factor corresponding to each voxel on the scanned object can be obtained.

[0098] It should be noted that for long half-life nuclides (scanning time is very short relative to half-life), if a certain scanning area is scanned uniformly, the scanning speed of all voxels in the scanning area is the same, and the corresponding correction factors are also the same. If a certain scanning area is scanned non-uniformly, the scanning speeds of different voxels in the scanning area are different, and the corresponding correction factors are also different.

[0099] In the above-mentioned image reconstruction method, the start scanning time and the end scanning time of multiple voxels on the scanned object in the process of non-uniform plane scanning are obtained; based on each start scanning time and each end scanning time, the correction factors corresponding to the multiple voxels on the scanned object are determined. By analyzing the start scanning time and the end scanning time of each voxel on the scanned object, the method can accurately determine the scanning speed of the voxel based on the analysis result, and thus can accurately determine the correction factor corresponding to each voxel based on the scanning speed.

[0100] In one embodiment, as shown in FIG. 10 , the correction factors corresponding to the plurality of voxels on the scanned object are determined based on each start scan time and each end scan time, including:

[0101] S401 , for any voxel, calculate the average moving speed of the detector through the start scanning time and the end scanning time corresponding to the voxel.

[0102] In the embodiment of the present application, for any voxel, the moving distance of the voxel during the non-uniform plane scanning process is the length L of the detector, and the moving time is the time difference between the start scanning time and the end scanning time. Therefore, the computer device can calculate the time difference between the start scanning time and the end scanning time, and use the ratio of the length of the detector to the time difference as the average moving speed of the detector. The average moving speed V i It can be expressed as:

[0103] V i =L / (t ib -t ia )

[0104] S402, generating a correction factor corresponding to a voxel based on the start scanning time, the end scanning time, the average moving speed, and the nuclide half-life of the nuclide in the scanned object.

[0105] In the embodiment of the present application, each voxel corresponds to a correction factor. After the start scanning time, end scanning time and average moving speed of the voxel are obtained, the correction factor corresponding to the voxel can be determined based on the calculation formula of the correction factor. The correction factor f corresponding to any voxel i The calculation formula can be expressed as:

[0106]

[0107] Among them, T cal Indicates the initial scanning time of the detector; T 1 / 2 Represents the half-life of the nuclide.

[0108] In the above-mentioned image reconstruction method, for any voxel, the average moving speed of the detector is calculated through the start scanning time and the end scanning time corresponding to the voxel; based on the start scanning time, the end scanning time, the average moving speed and the nuclide half-life of the nuclide in the scanned object, the correction factor corresponding to the voxel is generated. For any voxel, this method can accurately obtain the time when the voxel passes through the detector based on the start scanning time and the end scanning time of the voxel, so that the average moving speed of the detector can be accurately determined based on the length and time of the detector, so that the correction factor corresponding to the voxel can be accurately generated.

[0109] Next, the specific content of the non-uniform tomography is introduced. In one embodiment, the non-uniform scanning includes non-uniform tomography. The specific content of obtaining the original scanning data of the scanning object includes:

[0110] When the scanning bed is fixed in position, the detector is controlled to move non-uniformly at different angles of the scanning bed to obtain raw scanning data.

[0111] For the tomography process, the position of the scanning bed in the scanning device needs to be fixed, and the scanning object on the scanning bed is scanned by rotating the detector to obtain the original scanning data of the scanning object. FIG11 is a schematic diagram of non-uniform tomography. It can be seen from the figure that the detector rotates around the scanning object, and the rotation speed at different angles is different. The rotation speed at each angle can be the same or different. The dark area in the figure represents the area of ​​interest.

[0112] In the embodiment of the present application, the control instruction sent by the computer device to the scanning device carries the control instruction corresponding to the detector and the control instruction of the scanning bed. Therefore, in the case where the non-uniform scanning is a non-uniform tomography scan, after the scanning bed receives the control instruction, the position of the scanning bed is fixed. At this time, the computer device sends a control instruction to the detector to control the detector to rotate around the scanning bed, and the rotation process refers to a non-uniform rotation. During the rotation of the detector, the scanning data of the scanning object on the scanning bed is collected. After the movement of the detector is completed, the collection process of the detector is also terminated, and the detector sends the collected raw scanning data to the computer device.

[0113] In the above image reconstruction method, when the scanning bed is fixed in position, the detector is controlled to move non-uniformly at different angles of the scanning bed to obtain the original scanning data. In the process of non-uniform tomography scanning, the method fixes the position of the scanning bed and limits the moving speed of the detector so that the detector can scan the scanning object at different scanning angles in a non-uniform acquisition manner, thereby accurately obtaining the original scanning data of the scanning object.

[0114] Assuming that the correction factors corresponding to the moving object include correction factors corresponding to different pixels on the detector, in one embodiment, as shown in FIG. 12 , the specific content of correcting the raw scan data according to the correction factors corresponding to the moving object is described, and the specific content includes the following steps:

[0115] S501, obtaining a scanning time difference between a start scanning time and an end scanning time corresponding to any pixel on the detector.

[0116] In the embodiment of the present application, for any pixel on the detector, the computer device can calculate the difference between the start scanning time and the end scanning time of the pixel, and use the difference as the scanning time difference of the pixel. Assume that the start scanning time of the pixel is t ia The scanning end time is t ib , then, the scanning time difference D of pixel i i It can be expressed as:

[0117] D i =t ib -t ia

[0118] FIG13 is a schematic diagram of non-uniform tomography, from which the projection of the region of interest on the detector can be seen. FIG14 is a schematic diagram of the curve of pixel count and scanning time. Similarly, the horizontal and vertical coordinates in the figure are the same as those in FIG7. For any pixel i on the scanned object, the starting scanning time of pixel i on the detector is t ia , the end scanning time of pixel i is tib .

[0119] S502: Generate a likelihood function corresponding to the original scan data according to the scan time difference and the correction factor.

[0120] In the embodiment of the present application, for any pixel, the correction factor a corresponding to the pixel is i It can be expressed as:

[0121]

[0122] Among them, T cal represents the initial scanning time of any pixel on the detector; T 1 / 2 represents the half-life of the nuclide; represents the initial activity; for uniform tomography, D i can be a constant; for inhomogeneous tomography, D i Can be any value.

[0123] The likelihood function L corresponding to the original scan data can be expressed as:

[0124]

[0125] Where x represents the scanned image; y represents the projection; represents the true value of the i-th projection; represents the expected value of the i-th projection, which can be expressed as:

[0126]

[0127] in, represents the jth pixel; represents the system matrix, that is, the probability that the gamma ray emitted by the jth voxel is received by the i-th projection.

[0128] The total number of pixels in the scanned image is N, the total number of projection data is M, and the product of the scan time of the i-th projection and the correction factor is A i It can be expressed as:

[0129]

[0130] S503, correcting the original scan data based on the likelihood function to obtain corrected original scan data.

[0131] In an embodiment of the present application, after obtaining the likelihood function, the computer device can determine the predicted scan data corresponding to the original scan data under the preset conditions of the likelihood function based on preset constraints, and use the predicted scan data as the corrected original scan data.

[0132] In the above-mentioned image reconstruction method, the scanning time difference between the start scanning time and the end scanning time corresponding to any pixel on the detector is obtained; the likelihood function corresponding to the original scanning data is generated according to the scanning time difference and the correction factor; the original scanning data is corrected based on the likelihood function to obtain the corrected original scanning data. This method can accurately obtain the likelihood function corresponding to the original scanning data by calculating the scanning time difference of each pixel on the detector, and based on the scanning time difference and the correction factor, so that the correction can be accurately performed based on the likelihood function, so that the accuracy of the corrected original scanning data is higher.

[0133] Next, the specific process of correction is introduced through an embodiment. The specific content of the corrected original scan data obtained by correcting the original scan data based on the likelihood function includes:

[0134] When the likelihood function is at a maximum value, the predicted scan data corresponding to the original scan data is obtained, and the predicted scan data is used as the corrected original scan data.

[0135] In the embodiment of the present application, assuming that the likelihood function L is the largest, the estimated value of the scan data, that is, the predicted scan data, can be obtained. The predicted scan data can be expressed as:

[0136]

[0137] In the above-mentioned image reconstruction method, when the likelihood function is at a maximum value, the predicted scan data corresponding to the original scan data is obtained, and the predicted scan data is used as the corrected original scan data. When the likelihood function is at a maximum value, this method can accurately analyze the original scan data to accurately obtain the predicted scan data corresponding to the original scan data, so that the corrected original scan data can be accurately obtained.

[0138] Next, a process of obtaining the speeds of multiple scanning areas of a scanning object is described through an embodiment, and the process includes the following contents:

[0139] The scanning requirements of the scanning object are analyzed to obtain multiple scanning areas of the detector; and the speed of the scanning device in the multiple scanning areas is determined.

[0140] The scanning requirement of the scanned object refers to the clinical scanning requirement determined by the doctor after preliminary analysis of the scanned object. For example, the clinical scanning requirement may be: since the anatomical structure of the lower limb of the scanned object is simple, it is only necessary to see the general lesion, that is, the lower limb needs to be scanned faster.

[0141] In the embodiment of the present application, after obtaining the scanning requirements of the scanning object, the computer device can divide the scanning area according to the number of different scanning speeds in the scanning requirements to obtain multiple scanning areas. And obtain the scanning speed corresponding to each scanning area, and use the scanning speed as the moving speed of the scanning area. For example, in the scanning requirements, the scanning speed of the upper body is V1, and the scanning speed of the lower body is V2, then the scanning object can be divided into two scanning areas, namely the upper body and the lower body.

[0142] Alternatively, the scanning object may be scanned in a uniformly variable speed or variable acceleration manner, and the computer device may determine the scanning speeds at different positions of the scanning object based on the scanning rule. In the case of uniformly variable speed or variable acceleration, the scanning speeds at different positions are completely different.

[0143] In the above image reconstruction method, the scanning requirements of the scanned object are analyzed to obtain multiple scanning areas of the detector; and the speed of the scanning device in the multiple scanning areas is determined. Starting from the scanning requirements, the method can accurately divide the scanning object corresponding to the detector based on the scanning requirements, accurately obtain multiple scanning areas, and accurately obtain the speed of the scanning device in each scanning area.

[0144] As a specific embodiment of the present application, the image reconstruction process is described in detail below. In one embodiment, as shown in FIG15 , the image reconstruction method includes:

[0145] S601, analyzing the scanning requirements of the scanning object, obtaining multiple scanning areas of the detector; and determining the speed of the scanning device in the multiple scanning areas;

[0146] S602, when the detector is fixed, controlling the scanning bed to move along the detector in a non-uniform plane to obtain original scanning data;

[0147] S603, when the scanning bed is fixed, controlling the detector to move non-uniformly at different angles of the scanning bed to obtain original scanning data;

[0148] S604, correcting the original scan data according to the correction factor corresponding to the moving object; the moving object includes the scan object or the scanning device;

[0149] S605, performing image reconstruction on the corrected original scan data to obtain a scanned image of the scanned object.

[0150] Figure 16 is a flow chart of an image reconstruction method, which includes: S1: dividing the scanning area of ​​the scanning object, where the scanning object is divided into three areas, namely range 1, range 2 and range 3; S2: setting a corresponding scanning speed for each scanning range; S3: controlling the scanning device to perform non-uniform scanning based on the scanning speed to obtain original scanning data; S4: correcting the original scanning data using a correction factor, and reconstructing the corrected original scanning data to obtain a scanning image of the scanning object.

[0151] 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.

[0152] Based on the same inventive concept, the embodiment of the present application also provides an image reconstruction device for implementing the above-mentioned image reconstruction method. The implementation solution provided by the device to solve the problem is similar to the implementation solution recorded in the above-mentioned method, so the specific limitations in one or more image reconstruction device embodiments provided below can refer to the limitations on the image reconstruction method above, and will not be repeated here.

[0153] In an exemplary embodiment, as shown in FIG17 , an image reconstruction device is provided, comprising: a data acquisition module 11, a correction module 12 and a reconstruction module 13, wherein:

[0154] The data acquisition module 11 is used to acquire the original scanning data of the scanned object; the original scanning data is obtained by scanning the scanning device at different speeds;

[0155] A correction module, used to correct the original scan data according to the correction factor corresponding to the moving object; the moving object includes the scanning object or the scanning device;

[0156] The reconstruction module 13 is used to perform image reconstruction on the corrected original scan data to obtain a scanned image of the scanned object.

[0157] In one embodiment, the scanning module comprises a control unit, wherein:

[0158] The control unit is used to control the detector to scan the scan object at a speed relative to the scanning bed to obtain original scanning data.

[0159] In one embodiment, the control unit is further used to control the scanning bed to move along the detector in a non-uniform plane to obtain raw scanning data when the detector is fixed.

[0160] In one embodiment, the above-mentioned image reconstruction device further includes: a time acquisition module and a factor determination module, wherein:

[0161] A time acquisition module, used to acquire the start scanning time and the end scanning time of multiple voxels on the scanned object during the non-uniform plane scanning process;

[0162] The factor determination module is used to determine the correction factors corresponding to a plurality of voxels on the scan object based on each start scan time and each end scan time.

[0163] In one embodiment, the factor determination module includes: a calculation unit and a factor generation unit, wherein:

[0164] A calculation unit, for calculating, for any voxel, an average moving speed of the detector through a start scanning time and an end scanning time corresponding to the voxel;

[0165] The factor generating unit is used to generate the correction factor corresponding to the voxel based on the start scanning time, the end scanning time, the average moving speed and the nuclide half-life of the nuclide in the body of the scanned object.

[0166] In one embodiment, the control unit is further used to control the detector to move non-uniformly at different angles of the scanning bed when the scanning bed is fixed, so as to obtain original scanning data.

[0167] In one embodiment, the correction module comprises: a time difference acquisition unit, a function generation unit and a correction unit, wherein:

[0168] A time difference acquisition unit, used to acquire a scanning time difference between a start scanning moment and an end scanning moment corresponding to any pixel on the detector;

[0169] A function generating unit, used for generating a likelihood function corresponding to the original scanning data according to the scanning time difference and the correction factor;

[0170] The correction unit is used to correct the original scan data based on the likelihood function to obtain corrected original scan data.

[0171] In one embodiment, the correction unit is further configured to obtain predicted scan data corresponding to the original scan data when the likelihood function is at a maximum value, and use the predicted scan data as the corrected original scan data.

[0172] In one embodiment, the image reconstruction device further includes: an analysis module, wherein:

[0173] The analysis module is used to analyze the scanning requirements of the scanning object, obtain multiple scanning areas of the detector; and determine the moving speed of the scanning device in the multiple scanning areas.

[0174] Each module in the above-mentioned image reconstruction device can be implemented in whole or in part by software, hardware or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each module above.

[0175] In an exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be shown in FIG18. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data in the image reconstruction process. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, an image reconstruction method is implemented.

[0176] Those skilled in the art will understand that the structure shown in FIG. 18 is merely a block diagram of a partial structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0177] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the content of any one embodiment of the above-mentioned image reconstruction method is implemented.

[0178] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the content of any one embodiment of the above-mentioned image reconstruction method is implemented.

[0179] In one embodiment, a computer program product is provided, comprising a computer program, which implements the content of any one of the embodiments of the above-mentioned image reconstruction method when executed by a processor.

[0180] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0181] 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 memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0182] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0183] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. An image reconstruction method, characterized in that: The method comprises: Acquire original scan data of the scanned object; the original scan data is obtained by scanning the scanning device at different speeds; Correcting the original scan data according to a correction factor corresponding to a moving object; the moving object includes the scan object or the scanning device; The corrected original scan data is reconstructed to obtain a scanned image of the scanned object.

2. The method according to claim 1, characterized in that The scanning device includes a scanning bed and a detector; The obtaining of original scan data of the scanned object comprises: The detector is controlled to scan the scanning object at a speed relative to the scanning bed to obtain the original scanning data.

3. The method according to claim 2, characterized in that The step of controlling the detector to scan the scan object at a speed relative to the scanning bed to obtain the raw scan data includes: When the position of the detector is fixed, the scanning bed is controlled to move along the detector in a non-uniform plane to obtain the original scanning data.

4. The method according to claim 3, characterized in that The correction factors corresponding to the moving object include correction factors corresponding to different voxels on the scanned object; Before correcting the original scan data according to the correction factor corresponding to the moving object, the method further includes: Acquiring a start scanning time and an end scanning time of a plurality of voxels on the scanning object during a non-uniform plane scanning process; Based on each of the start scanning time and each of the end scanning time, correction factors corresponding to a plurality of voxels on the scanned object are determined.

5. The method according to claim 4, characterized in that The determining, based on each of the start scanning time and each of the end scanning time, the correction factors corresponding to the plurality of voxels on the scanned object comprises: For any voxel, the average moving speed of the detector is calculated through the start scanning time and the end scanning time corresponding to the voxel; A correction factor corresponding to the voxel is generated based on the start scanning time, the end scanning time, the average moving speed, and the nuclide half-life of the nuclide in the scanned object body.

6. The method according to claim 2, characterized in that The step of controlling the detector to scan the scan object at a speed relative to the scanning bed to obtain the raw scan data includes: When the scanning bed is fixed, the detector is controlled to move non-uniformly at different angles of the scanning bed to obtain the original scanning data.

7. The method according to claim 6, characterized in that The correction factors corresponding to the moving object include correction factors corresponding to different pixels on the detector; The correcting the original scan data according to the correction factor corresponding to the moving object includes: Obtaining a scanning time difference between a start scanning moment and an end scanning moment corresponding to any pixel on the detector; generating a likelihood function corresponding to the original scan data according to the scan time difference and the correction factor; The original scan data is corrected based on the likelihood function to obtain the corrected original scan data.

8. The method according to claim 7, characterized in that The correcting the original scan data based on the likelihood function to obtain the corrected original scan data includes: When the likelihood function is at a maximum value, predicted scan data corresponding to the original scan data is acquired, and the predicted scan data is used as the corrected original scan data.

9. The method according to claim 1 or 2, characterized in that: The method further comprises: The scanning requirements of the scanning object are analyzed to obtain a plurality of scanning areas of the detector; and the speed of the scanning device in the plurality of scanning areas is determined.

10. An image reconstruction device, characterized in that: The device comprises: A data acquisition module, used to acquire original scan data of the scanned object; the original scan data is obtained by scanning the scanning device at different speeds; A correction module, configured to correct the original scan data according to a correction factor corresponding to a moving object; the moving object includes the scan object or the scanning device; The reconstruction module is used to perform image reconstruction on the corrected original scan data to obtain a scanned image of the scanned object.

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