Crystal position lookup table generation method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention discloses a crystal position lookup table generation method and device, electronic equipment and a storage medium. The method comprises the steps that a two-dimensional position map used for indicating the position of an incident photon event is obtained, the two-dimensional position map comprises a plurality of light spots, and the light spots correspond to a plurality of crystals of positron emission tomography equipment in a one-to-one mode; dividing the two-dimensional position map according to an arrangement mode of sensor units, coupled with a plurality of crystals, of positron emission tomography equipment so as to obtain at least two image blocks; the image position of the light spot contained in each image block of the at least two image blocks is determined, a crystal position lookup table is generated according to the image positions of the light spots contained in the at least two image blocks, and the crystal position lookup table is used for indicating the positions of crystal boundaries among the multiple crystals. According to the scheme, the crystal position lookup table can be automatically, efficiently and accurately generated, and manual intervention operation is less.

Description

Technical Field

[0001] The present invention relates to the technical field of medical equipment, and in particular to a method, device, electronic device, storage medium and computer program product for generating a crystal position lookup table. Background Art

[0002] Positron emission tomography (PET) is an imaging device used in nuclear medicine to visualize the internal structures of the human body using radioactive nuclide tracing. For PET devices, a precise crystal lookup table (CLT) is crucial for achieving high-quality image reconstruction. Traditional CLT generation typically requires performing a two-dimensional histogram analysis on the two-dimensional position map (also known as a "flood map") generated by the PET device, which indicates the location of incident photon events. Crystal boundaries are then determined by identifying peak values in the two-dimensional histogram and setting a threshold.

[0003] Currently, the generation of traditional crystal position lookup tables often relies on manual adjustment, which cannot meet the precise positioning requirements of complex crystal arrays. In particular, for some PET devices that need to meet portability and lightness requirements but cannot install large-volume cooling devices or have a small number of crystals, such as wearable brain PET devices, the two-dimensional position map (also known as "flood map") generated to indicate the location of incident photon events usually contains a lot of noise, and there will be adhesion and smear between the bright spots in the image. In this case, the traditional method of generating crystal position lookup tables often cannot generate accurate crystal position lookup tables. Other image processing methods, such as watershed method, edge detection algorithm or threshold analysis method, are very sensitive to noise and spot adhesion in the two-dimensional position map, and are also unable to accurately determine the crystal position, and accordingly cannot generate an accurate crystal position lookup table. Summary of the Invention

[0004] The present invention was developed in response to the aforementioned issues. It provides a method, apparatus, electronic device, storage medium, and computer program product for generating a crystal position lookup table. This solution can automatically, efficiently, and accurately generate a crystal position lookup table with minimal manual intervention.

[0005] According to one aspect of the present invention, a method for generating a crystal position lookup table is provided. The method includes: obtaining a two-dimensional position map for indicating the position of an incident photon event, the two-dimensional position map including a plurality of light spots, each of the plurality of light spots corresponding one-to-one to a plurality of crystals of a positron emission tomography device; dividing the two-dimensional position map according to the arrangement of sensor units of the positron emission tomography device coupled to the plurality of crystals to obtain at least two image blocks; determining the image position of the light spot contained in each of the at least two image blocks, and generating a crystal position lookup table based on the image position of the light spot contained in each of the at least two image blocks, the crystal position lookup table being used to indicate the positions of crystal boundaries between the plurality of crystals.

[0006] Optionally, before dividing the two-dimensional position map according to the arrangement of sensor units coupled to multiple crystals to obtain at least two image blocks, the method also includes: defining the arrangement of the sensor units in response to a user's arrangement customization operation; or, obtaining device type information and / or device identification information of the positron emission tomography device, and determining the arrangement of the sensor units based on the device type information and / or device identification information; or, determining the arrangement of the sensor units based on the distribution of multiple light spots in the two-dimensional position map.

[0007] Optionally, before dividing the two-dimensional position map according to the arrangement of sensor units connected to the plurality of crystals to obtain at least two image blocks, the method further comprises: updating the arrangement of the sensor units in response to an arrangement update operation by the user.

[0008] Optionally, determining the image position of the light spot included in each of the at least two image blocks includes: performing peak value detection of pixel values on each of the at least two image blocks to determine the image position of the light spot included in the image block.

[0009] Optionally, the arrangement of the sensor units is determined based on the distribution of multiple light spots in the two-dimensional position map, including: grouping the multiple light spots in the two-dimensional position map according to the preset number of light spots in the group and the preset distance information of the light spots in the group to determine at least two light spot groups; determining the arrangement of the sensor units according to the image positions of each of the at least two light spot groups in the two-dimensional position map, wherein each sensor unit in the determined arrangement corresponds to a unique light spot group, and the image positions of each of the at least two light spot groups in the two-dimensional position map are used to indicate the distribution situation.

[0010] Optionally, the two-dimensional position map is divided according to the arrangement of sensor units of a positron emission tomography device coupled to multiple crystals to obtain at least two image blocks, including: based on the row and column information of the sensor units, the two-dimensional position map is evenly divided into at least two image blocks according to the number of rows and columns corresponding to the row and column information, and the row and column information is used to indicate the arrangement of the sensor units.

[0011] Optionally, peak detection of pixel values is performed on each of the at least two image blocks to determine the image position of the light spot contained in the image block, including: for each of the at least two image blocks, summing the pixel values of each pixel point in the image block along a first direction to obtain first projection data, and summing the pixel values along a second direction to obtain second projection data, wherein the first projection data includes different summation result data distributed along the second direction, and the second projection data includes different summation result data distributed along the first direction. Peak detection is performed on each of the first and second projection data, and when the number of peak values in the first and second projection data both meet a preset first number requirement, the image position of the light spot contained in the image block is determined based on the peak position of the first and second projection data.

[0012] Optionally, performing pixel value peak detection on each of the at least two image blocks to determine the image position of the light spot contained in the image block further includes: when the number of peak values of the first projection data and the number of peak values of the second projection data do not meet a first number requirement, using a preset Hough circle detection algorithm to detect the image block; if the number of circle centers indicated by the detection result obtained by the current detection does not meet a preset second number requirement, adjusting preset algorithm parameters of the Hough circle detection algorithm, and returning to execute the operation of detecting the image block using the preset Hough circle detection algorithm until the number of circle centers indicated by the detection result obtained by the current detection meets the second number requirement, or the number of detections is greater than or equal to a preset number threshold; when the number of circle centers indicated by the detection result obtained by the current detection meets the second number requirement, determining the image position of the light spot contained in the image block according to the circle center position indicated by the detection result.

[0013] Optionally, the preset algorithm parameters include a minimum distance between detected circle centers and an accumulator threshold.

[0014] Optionally, the first quantity requirement includes: the peak number of the first projection data is equal to the preset number of light spots in the second direction, and the peak number of the second projection data is equal to the preset number of light spots in the first direction; the second quantity requirement includes: the number of detected circle centers is equal to the preset number of light spots in the image block.

[0015] Optionally, a crystal position lookup table is generated based on the image position of the light spot contained in each of the at least one image blocks, including: generating a Vero map based on the image position of the light spot contained in each of the at least one image blocks, the Vero map including multiple sub-regions, and the multiple sub-regions corresponding one-to-one to multiple crystals; generating a crystal position lookup table based on the Vero map, the crystal position lookup table including the crystal number and crystal boundary information corresponding to each of the multiple sub-regions.

[0016] Optionally, generating a crystal position lookup table according to the image positions of the light spots respectively included in at least one image block further includes: marking sub-regions of any two crystal boundaries at least partially overlapping with different colors.

[0017] According to another aspect of the present invention, a device for generating a crystal position lookup table is also provided, including: an acquisition module for acquiring a two-dimensional position map for indicating the position of an incident photon event, the two-dimensional position map including multiple light spots, and the multiple light spots corresponding one-to-one to multiple crystals of a positron emission tomography device; a division module for dividing the two-dimensional position map according to the arrangement of sensor units of the positron emission tomography device coupled to the multiple crystals to obtain at least two image blocks; a detection module for performing peak value detection of pixel values on each of the at least two image blocks to determine the image position of the light spot contained in the image block; a generation module for generating a crystal position lookup table based on the image positions of the light spots contained in each of the at least two image blocks, the crystal position lookup table being used to indicate the positions of crystal boundaries between the multiple crystals.

[0018] According to another aspect of the present invention, an electronic device is provided, comprising: a processor and a memory, wherein the memory stores computer program instructions, and the computer program instructions are used by the processor to execute the above-mentioned method for generating a crystal position lookup table when the processor is running.

[0019] According to yet another aspect of the present invention, a storage medium is provided, on which program instructions are stored. The program instructions are used to execute the above-mentioned method for generating a crystal position lookup table when running.

[0020] According to yet another aspect of the present invention, a computer program product is provided, comprising computer program instructions, which are used to execute the above-mentioned method for generating a crystal position lookup table when running.

[0021] By dividing the two-dimensional position map into multiple image blocks and determining the image position of the light spot contained in each image block, the above-mentioned technical solution can automatically, efficiently, and accurately generate a crystal position lookup table, with minimal manual intervention. Furthermore, by dividing the two-dimensional position map according to the arrangement of the sensor units of the positron emission tomography device, the differences between the pixel values and morphologies of the light spots corresponding to sensor units at different positions can be fully considered. Determining the image position of the light spot within each image block can better eliminate interference from other light spots with significantly different pixel values and morphologies from the light spot contained in the image block, compared to determining the image position of the light spot within the entire two-dimensional position map, thereby obtaining a more accurate image position of the light spot.

[0022] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are specifically listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The above and other objects, features, and advantages of the present invention will become more apparent through a more detailed description of the embodiments of the present invention with reference to the accompanying drawings. The accompanying drawings are provided to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and are not intended to limit the present invention. In the drawings, the same reference numerals generally represent the same components or steps.

[0024] Figure 1 A schematic flow chart of a method for generating a crystal position lookup table according to an embodiment of the present invention is shown;

[0025] Figure 2 shows a two-dimensional position diagram according to one embodiment of the present invention;

[0026] Figure 3 A schematic diagram showing image blocks obtained by dividing a two-dimensional position map according to an embodiment of the present invention is shown;

[0027] Figure 4 A schematic diagram showing the distribution of first projection data and second projection data according to an embodiment of the present invention is shown;

[0028] Figure 5 shows a schematic diagram of distribution of first projection data and second projection data according to another embodiment of the present invention;

[0029] Figure 6 shows a visualization of a crystal position lookup table according to one embodiment of the present invention;

[0030] Figure 7 A flow chart showing a specific process of generating a crystal position lookup table according to one embodiment of the present invention is shown;

[0031] Figure 8 A schematic diagram showing a device for generating a crystal position lookup table according to an embodiment of the present invention is shown;

[0032] Figure 9 A schematic block diagram of an electronic device according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0033] In order to make the purpose, technical solutions and advantages of the present invention more apparent, exemplary embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments of the present invention, and it should be understood that the present invention is not limited to the exemplary embodiments described herein. Based on the embodiments of the present invention described in the present invention, all other embodiments obtained by those skilled in the art without creative work should fall within the scope of protection of the present invention.

[0034] Currently, the detectors in commonly used positron emission tomography (PET) devices primarily utilize a crystal array coupled to a sensor unit (typically a photoelectric converter). Their operating principle is the annihilation effect between positrons produced by the decay of positron-emitting isotopes and negative electrons in the human body. When a gamma photon strikes a scintillation crystal, the interaction with the crystal deposits energy and generates a visible light signal. The sensor unit receives the resulting light signal and converts it into an electrical output. The resulting electrical signal can be used to calculate the incident photon event location. However, due to issues with the detector's design and the device's algorithms, the calculated incident photon event location is not the actual event location. Therefore, a crystal position lookup table is needed to accurately correlate the calculated incident photon event location with the crystal. During actual image acquisition, the calculated incident photon event location and the crystal position lookup table can be used to determine the crystal with which the gamma photon interacted. The actual physical location of the crystal can then be used to determine the actual incident photon event location, thereby obtaining an accurate image of the human body's internal structures.

[0035] As described above, in the related art, for some positron emission tomography (PET) devices that need to meet portability and lightness requirements but cannot install large cooling devices or have a small number of crystals, neither traditional methods for generating crystal position lookup tables nor methods based on other image processing algorithms often fail to generate accurate crystal position lookup tables. To at least partially address the above technical issues, embodiments of the present invention provide a method, apparatus, electronic device, storage medium, and computer program product for generating a crystal position lookup table. This solution can automatically, efficiently, and accurately generate a crystal position lookup table, requiring minimal human intervention.

[0036] See also Figure 1 FIG2 is a schematic flow chart of a method for generating a crystal position lookup table according to an embodiment of the present invention. According to one aspect of the present invention, a method for generating a crystal position lookup table is provided, the method comprising: step S110, step S120 and step S130.

[0037] In step S110 , a two-dimensional position map indicating the event position of an incident photon is acquired, where the two-dimensional position map includes a plurality of light spots, and the plurality of light spots correspond one-to-one to a plurality of crystals of a positron emission tomography device.

[0038] For example, a positron emission tomography (PET) device may include multiple detectors, each of which may include multiple sensor units. The sensor units may be, for example, photomultiplier tubes (PMTs), silicon photodiodes (SiPMs), or other photoelectric converters. Each sensor unit may be coupled to one or more crystals. The PET device may be used for data acquisition. By counting the incident photon event positions detected by the detectors, a two-dimensional position map indicating the incident photon event positions may be obtained. Specifically, each detector surface may have a corresponding preset image coordinate system. When a photon arrives at a certain position on the detector, that is, when the detector detects the incident photon event at that position, the coordinates of that position in the preset coordinate image system may be determined as an incident photon event position. A two-dimensional position map may be obtained based on the incident photon event positions. More specifically, during the data acquisition process, if the same detector position detects incident photon events multiple times, the count value at that position may be increased accordingly. These count values may be used to determine the pixel value at the corresponding coordinate in the two-dimensional position map. For example, the higher the count value, the larger the corresponding pixel value of the position in the two-dimensional position map.

[0039] For example, the two-dimensional position map may include multiple light spots, each of which corresponds to a plurality of crystals of the positron emission tomography device. Specifically, for each of the plurality of crystals, multiple photons may be incident on the crystal, thereby forming a light spot corresponding to the crystal on the two-dimensional position map. Figure 2As shown, it is a two-dimensional position map according to an embodiment of the present invention. Figure 2 In the illustrated embodiment, each detector of the positron emission tomography device may include nine sensor units, which may be arranged in a 3x3 matrix. Each sensor unit may be coupled to four crystals (which may be considered a crystal array), which may be arranged in a 2x2 matrix. Figure 2 The two-dimensional position map shown is based on a single detector and can include nine light spot arrays, each of which includes four light spots. It will be appreciated that each sensor unit corresponds to a light spot array. The light spots corresponding to sensor units at different locations have different pixel values and morphologies. Specifically, among the nine light spot arrays, the four light spot arrays at the four corners exhibit the most severe sticking and smearing, followed by the four light spot arrays at the midpoints of the four edges, and the light spot array at the center exhibits the clearest spots.

[0040] In step S120 , the two-dimensional position map is divided according to the arrangement of the sensor units of the positron emission tomography device coupled to the plurality of crystals to obtain at least two image blocks.

[0041] For example, the two-dimensional position map can be divided into multiple image blocks based on the arrangement of the sensor units. Each image block can correspond to one or more sensor units. Accordingly, each image block can include one or more light spot arrays corresponding to one or more sensor units. Figure 2 Taking the two-dimensional position map shown as an example, the two-dimensional position map can be divided into 9 image blocks in a 3*3 manner, and each image block can include a light spot array, that is, it can include four light spots arranged in a 2*2 arrangement. In another embodiment, the two-dimensional position map includes 16 light spot arrays arranged in a 4*4 matrix arrangement, and the two-dimensional position map can be divided into 9 image blocks, including 4 first image blocks, 4 second image blocks and 1 third image block. Among them, each of the 4 first image blocks can include a light spot array located at one of the four corners, each of the 4 second image blocks can include two light spot arrays located in the middle of one of the four edges, and the third image block can include four light spot arrays located at the center position in addition to the light spot arrays located at the edges and the four corners. Please refer to Figure 3 As shown in FIG, it is a schematic diagram of image blocks obtained after dividing a two-dimensional position map according to an embodiment of the present invention. Figure 3In the embodiment shown, the two-dimensional position map includes 9 light spot arrays, which are arranged in a 3*3 matrix arrangement, and each light spot array includes 4 light spots. The two-dimensional position map can obtain 9 image blocks by dividing it in a 3*3 matrix. Figure 3 It is shown as (a)-(i). Among them, Figure 3 The image blocks shown in (a), (c), (g) and (i) each contain a light spot array located at the four corners. Figure 3 The image blocks shown in (b), (d), (f) and (h) each contain four light spot arrays located at the midpoints of the four edges. Figure 3 The light spot array included in the image block shown in (e) is a light spot array located at the center.

[0042] In step S130, the image position of the light spot contained in each of the at least two image blocks is determined, and a crystal position lookup table is generated according to the image position of the light spot contained in each of the at least two image blocks. The crystal position lookup table is used to indicate the positions of crystal boundaries between multiple crystals.

[0043] Exemplarily, each image block may include at least one light spot, and each included light spot may correspond to a crystal. For each of the at least two image blocks, the image position of the light spot included in the image block may be determined using methods such as threshold segmentation and connected domain analysis, machine learning, and peak detection. In one specific embodiment, a pixel value threshold may be set for each image block, and connected domains with pixel values greater than the pixel value threshold may be determined as the light spots included in the image block. Feature extraction may be used to determine the centroid of the connected domain, and the image position of the centroid of the connected domain in the image block may be used as the image position of the light spot. In another specific embodiment, a trained convolutional neural network may be used to detect the light spots included in each image block, thereby determining the image position of the light spots included in the image block. In yet another specific embodiment, pixel value peak detection may be performed on each image block, and the image position of the light spots included in each image block may be determined based on the peak detection results. Exemplarily, based on the image positions of the light spots in the corresponding image blocks, the positions of the crystal boundaries between the crystals may be determined, thereby generating a crystal position lookup table indicating the positions of the crystal boundaries between the multiple crystals.

[0044] By dividing the two-dimensional position map into multiple image blocks and determining the image position of the light spot contained in each image block based on the peak detection results of the image blocks, the above-mentioned technical solution can automatically, efficiently, and accurately generate a crystal position lookup table with minimal manual intervention. Furthermore, dividing the two-dimensional position map according to the arrangement of the sensor units of the positron emission tomography device can fully account for the differences between the pixel values and morphologies of the light spots corresponding to sensor units at different positions. Determining the image position of the light spot within each image block can better eliminate interference from other light spots with significantly different pixel values and morphologies from the light spot contained in the image block, compared to determining the image position of the light spot within the entire two-dimensional position map, thereby obtaining a more accurate image position of the light spot.

[0045] Optionally, before dividing the two-dimensional position map according to the arrangement of sensor units coupled to multiple crystals to obtain at least two image blocks, the method also includes: defining the arrangement of the sensor units in response to a user's arrangement customization operation; or, obtaining device type information and / or device identification information of the positron emission tomography device, and determining the arrangement of the sensor units based on the device type information and / or device identification information; or, determining the arrangement of the sensor units based on the distribution of multiple light spots in the two-dimensional position map.

[0046] Exemplarily, before dividing the two-dimensional position map according to the arrangement of the sensor units, the arrangement of the sensor units may be first obtained. In some embodiments, the user may customize the arrangement of the sensor units. For example, the user may customize the arrangement of the sensor units to a 3*3 matrix arrangement. In response to the user's arrangement customization operation, the processor may define the arrangement of the sensor units as the arrangement indicated by the customization operation. In other embodiments, the positron emission tomography device may have corresponding device type information and / or device identification information. The device type information (e.g., model number) may indicate the device type of the positron emission tomography device, and the device identification information (e.g., serial number) may indicate a specific positron emission tomography device. For some positron emission tomography devices, the device type information and / or device identification information may be mapped to a preset arrangement of the sensor units. The processor may obtain the device type information and / or device identification information of the current positron emission tomography device and determine the arrangement of the sensor units of the current positron emission tomography device based on the device type information and / or device identification information. In some other embodiments, the arrangement of the sensor units may be determined based on the distribution of multiple light spots in the two-dimensional position map. The specific process of determining the arrangement of the sensor units will be described in detail below.

[0047] The above technical solution can define the arrangement of sensor units in response to user customized operations, which is highly flexible and can be well adapted to actual conditions. When the arrangement of sensors is relatively irregular, or when the performance of the sensor units of the current positron emission tomography device is relatively special, resulting in a large difference between the pixel values and morphology of each light spot in the two-dimensional position map and the pixels and morphology of the light spots at the corresponding positions in the two-dimensional position map obtained by other positron emission tomography devices with the same arrangement of sensor units, the user can divide the sensor units according to the actual situation to customize the arrangement of the sensor units, and the determined arrangement of the sensor units is consistent with the arrangement of each current positron emission tomography device. There is high consistency between tomography devices; in addition, the embodiment of the present invention can also automatically determine the arrangement of sensor units based on the device type information of the current positron emission tomography device or the device identification information unique to the current device. The arrangement of sensor units determined in this way can also accurately match the current positron emission tomography device in a targeted manner and reduce manual operation; in addition, the embodiment of the present invention can also determine the arrangement of sensor units based on the distribution of light spots in the two-dimensional position map. The determined arrangement of sensor units has high accuracy, can reduce manual operation, and does not need to determine the type and identification of each current positron emission tomography device, and has strong versatility.

[0048] Optionally, before dividing the two-dimensional position map according to the arrangement of sensor units connected to the plurality of crystals to obtain at least two image blocks, the method further comprises: updating the arrangement of the sensor units in response to an arrangement update operation by the user.

[0049] For example, the user can update the current arrangement of the current sensor units. In response to the user's arrangement update operation, the current arrangement of the current sensor units can be updated to the arrangement indicated by the arrangement update operation. For example, the current arrangement of the current sensor units may be a 4*4 matrix, and the arrangement of the sensor units of the new positron emission tomography device for which the crystal position lookup table is to be generated is a 3*3 matrix. In this case, the user can update the current arrangement of the current sensor units. In response to the user's arrangement update operation, the current arrangement of the current sensor units can be updated to a 3*3 matrix.

[0050] The above technical solution allows the user to update the arrangement of the sensor units, which is helpful to ensure the consistency between the currently set arrangement of the sensor units and the actual arrangement of the sensor units.

[0051] Optionally, the arrangement of the sensor units is determined based on the distribution of multiple light spots in the two-dimensional position map, including: grouping the multiple light spots in the two-dimensional position map according to the preset number of light spots in the group and the preset distance information of the light spots in the group to determine at least two light spot groups; determining the arrangement of the sensor units according to the image positions of each of the at least two light spot groups in the two-dimensional position map, wherein each sensor unit in the determined arrangement corresponds to a unique light spot group, and the image positions of each of the at least two light spot groups in the two-dimensional position map are used to indicate the distribution situation.

[0052] Exemplarily, the preset intra-group light spot quantity information may indicate the number of light spots contained in each light spot group (i.e., the "light spot array" in the aforementioned embodiment). For example, the number of light spots contained in each light spot group is 4. The preset intra-group light spot distance information may indicate the spacing range between the light spots contained in each light spot group. For example, the spacing range between the light spots contained in each light spot group is greater than or equal to 20 and less than or equal to 50. According to the preset intra-group light spot quantity information and the preset intra-group light spot quantity information, multiple light spots in the two-dimensional position map can be grouped to determine at least two light spot groups. It can be understood that the number of light spots determined in each light spot group is equal to the number of light spots indicated by the preset intra-group light spot quantity information, and the spacing between the light spots in each light spot group is within the spacing range indicated by the preset intra-group light spot distance information. After determining the light spot groups, the arrangement of the sensor units can be determined based on the image positions of each light spot group in the two-dimensional position map. Specifically, the image position of each light spot group in the two-dimensional position map can indicate the distribution of each light spot group. Each light spot group can correspond to a sensor unit. Accordingly, the arrangement of each sensor unit can be determined based on the image position of each light spot group in the two-dimensional position map.

[0053] The above technical solution groups the light spots in the two-dimensional position map according to the preset number of light spots in the group and the preset distance between the light spots in the group. This can quickly and accurately obtain a light spot group that is highly matched with the crystal arrangement of each sensor unit, which is conducive to ensuring that each determined light spot group corresponds to each sensor unit one-to-one. Based on the image position of each light spot group, the arrangement of the sensor units can be quickly and accurately determined.

[0054] Optionally, the two-dimensional position map is divided according to the arrangement of sensor units of a positron emission tomography device coupled to multiple crystals to obtain at least two image blocks, including: based on the row and column information of the sensor units, the two-dimensional position map is evenly divided into at least two image blocks according to the number of rows and columns corresponding to the row and column information, and the row and column information is used to indicate the arrangement of the sensor units.

[0055] For example, for each detector of a positron emission tomography device, the sensor units of the detector can be divided into rows and columns. The row and column information can describe the number of rows and columns of the sensor units, which can indicate the arrangement of the sensor units. For example, if a detector has 3 rows of sensor units and 4 columns, it can be understood that the number of sensor units in the detector is 12. In other words, the detector has 3 rows of sensor units, and the number of sensor units in each row is 4. The two-dimensional position map can be evenly divided into at least two image blocks according to the number of rows and columns corresponding to the row and column information of the sensor units. Still taking the example of 3 rows and 4 columns of sensor units, the corresponding two-dimensional position map can be evenly divided into 3 rows and 4 columns, resulting in 12 image blocks.

[0056] The above technical solution can quickly and accurately divide the two-dimensional position map into equal parts according to the row and column information of the sensor units. In particular, for some sensor units arranged in a matrix, this method of dividing the image blocks is simple and efficient.

[0057] Optionally, determining an image position of a light spot included in each of the at least two image blocks includes:

[0058] A peak value detection of pixel values is performed on each of the at least two image blocks to determine an image position of a light spot included in the image block.

[0059] For example, for each of the at least two image blocks, pixel value peak detection may be performed on the image block. Peak detection methods may employ, for example, a local maximum method, a non-maximum suppression method, a two-dimensional Gaussian fitting method, etc. The peak detection result may indicate the image position of the light spot contained in the image block.

[0060] The above technical solution performs peak value detection on each image block separately. It can take advantage of the fact that the pixel value of the light spot is significantly higher than the pixel value of other areas to quickly and accurately detect the brightest position (that is, the position with the largest pixel value) of each light spot contained in the image block to determine the image position of the light spot.

[0061] Optionally, after performing pixel value peak detection on each of the at least two image blocks to determine the image position of the light spot contained in the image block, determining the image position of the light spot contained in each of the at least two image blocks further includes: when the number of peaks contained in the peak detection result does not meet a first quantity requirement, using a preset Hough circle detection algorithm to detect the image block; if the number of circle centers indicated by the detection result obtained by the current detection does not meet a preset second quantity requirement, adjusting preset algorithm parameters of the Hough circle detection algorithm, and returning to execute the operation of detecting the image block using the preset Hough circle detection algorithm until the number of circle centers indicated by the detection result obtained by the current detection meets the second quantity requirement, or the number of detections is greater than or equal to a preset number threshold; when the number of circle centers indicated by the detection result obtained by the current detection meets the second quantity requirement, determining the image position of the light spot contained in the image block according to the circle center position indicated by the detection result.

[0062] For example, due to the potential for light spot adhesion and smearing, the number of peaks included in the peak detection result may not meet the first quantity requirement. The first quantity requirement may include that the number of peaks in the current image block is consistent with a preset number of peaks. For example, if the preset number of peaks in the image block is 4 and the number of peaks included in the peak detection result is 6, then the first quantity requirement may be considered to be not met. In this case, a preset Hough circle detection algorithm may be used to detect the image block. For example, the second quantity requirement may include that the number of circle centers indicated by the detection result is equal to the total number of crystals coupled to the sensor unit corresponding to the image block. It is understood that the preset number of peaks may be consistent with the total number of crystals coupled to the sensor unit. When detecting an image block using the Hough circle detection algorithm, if the number of circle centers indicated by the current detection result does not meet the preset second quantity requirement, the preset algorithm parameters of the Hough circle detection algorithm may be adjusted, and the process may return to executing the detection operation for the image block using the preset Hough circle detection algorithm. If the number of circle centers indicated by the detection result still does not meet the second quantity requirement after each detection operation, the preset algorithm parameters may be further adjusted. The detection and parameter adjustment process can be repeated until the number of circle centers indicated by the detection result obtained in the current detection meets the second number requirement, or the number of detections is greater than or equal to a preset number threshold. When the number of circle centers indicated by the detection result obtained in the current detection meets the second number requirement, the position of the circle center indicated by the detection result can be determined as the image position of the light spot included in the image block.

[0063] When the number of peaks does not meet the first quantity requirement, that is, when the number of peaks does not match the number of light spots contained in the image block, the above technical solution can use the Hough circle detection algorithm to detect the image block. This can quickly and accurately determine the image position of the light spot when the adhesion and smear of the light spot have a significant impact on the peak detection result.

[0064] Optionally, peak detection of pixel values is performed on each of the at least two image blocks to determine the image position of the light spot contained in the image block, including: for each of the at least two image blocks, summing the pixel values of each pixel point in the image block along a first direction to obtain first projection data, and summing the pixel values along a second direction to obtain second projection data, wherein the first projection data includes different summation result data distributed along the second direction, and the second projection data includes different summation result data distributed along the first direction. Peak detection is performed on each of the first and second projection data, and when the number of peak values in the first and second projection data both meet a preset first number requirement, the image position of the light spot contained in the image block is determined based on the peak position of the first and second projection data.

[0065] Exemplarily, for each image block obtained by partitioning based on the two-dimensional position map, the pixel values of each pixel in the image block can be summed along a first direction to obtain first projection data, and summed along a second direction to obtain second projection data. It can be understood that the first direction and the second direction are perpendicular to each other. For example, the first direction can be a horizontal direction, and the second direction can be a vertical direction. Taking the first direction as a horizontal direction and the second direction as an example, if the image resolution of an image block is a*b (e.g., 200*150), it can be considered that the number of pixel rows in the image block is b and the number of columns is a. The first projection data can be obtained by summing each pixel in the image block along the first direction (i.e., the horizontal direction). The first projection data includes b pixel sum values, that is, each row of pixels corresponds to one pixel sum value. Similarly, the second projection data can be obtained by summing each pixel in the image block along the second direction (i.e., the vertical direction). The second projection data includes a pixel sum values, that is, each column of pixels can correspond to one pixel sum value. In other words, the first projection data includes different summation result data (i.e., pixel sum values) distributed along the second direction, and the second projection data includes different summation result data distributed along the first direction. Exemplarily, peak detection can be performed on the first projection data and the second projection data respectively, and the number of peaks of the first projection data and the number of peaks of the second projection data can be obtained. When both peak numbers meet the preset first quantity requirement, the image position of the light spot included in the corresponding image block can be determined based on the peak position of the first projection data and the peak position of the second projection data. Specifically, the preset first quantity requirement can be determined based on the number of crystals coupled to the sensor unit and the crystal arrangement. For example, each sensor unit is coupled to a crystal arranged in a 2*2 matrix, then the preset first quantity requirement may include: the number of peaks of the first projection data is equal to 2, and the number of peaks of the second projection data is equal to 2. For another example, the current image block includes 4 light spot groups corresponding to 4 sensor units, and each light spot group includes light spots arranged in a 2*2 matrix, then the preset first quantity requirement may include the number of peaks of the first projection data is equal to 4 and the number of peaks of the second projection data is equal to 4.

[0066] In a specific embodiment, the image block may have a corresponding xy image coordinate system, wherein the first direction is the direction of the x-axis, the second direction is the direction of the y-axis, and the coordinate origin may be any vertex of the image block. For the image block, the number of peak values of the first projection data and the number of peak values of the second projection data both meet the preset first quantity requirement. The coordinates of the peak values of the first projection data on the y-axis are y1 and y2, and the coordinates of the peak values of the second projection data on the x-axis are x1 and x2. It can be obtained that the image positions of the light spots contained in the image block are (x1, y1), (x1, y2), (x2, y1), and (x2, y2). Please refer to Figure 4As shown, it is a schematic diagram of the distribution of the first projection data and the second projection data according to one embodiment of the present invention. Figure 4 In the illustrated embodiment, each sensor unit is coupled to a crystal arranged in a 2*2 matrix, and the preset first quantity requirement may include: the number of peaks of the first projection data is equal to 2, and the number of peaks of the second projection data is equal to 2. Figure 4 In the illustrated embodiment, the image block has an xy coordinate system, and the coordinate range of the coordinate system is from (0, 0) to (175, 175). Figure 4 (a) shows the distribution of the first projection data obtained by summing along the x-direction (i.e., the first direction). In this set of first projection data, the peak values are the ordinates of points A and B, respectively. The peak positions are represented by the abscissas of points A (denoted as Y1) and B (denoted as Y2), respectively. Figure 4 (b) shows the distribution of the second projection data, obtained by summing along the y-direction (i.e., the first direction). In this set of second projection data, the peak values are the ordinates of points C and D, respectively. The peak positions are represented by the abscissas of points C (denoted as X1) and D (denoted as X2), respectively. The image positions of the light spots contained in the corresponding image blocks are (X1, Y1), (X1, Y2), (X2, Y1), and (X2, Y2), respectively.

[0067] The above technical solution sums the pixel values of the pixel points of the image block along the first direction and the second direction, and performs peak detection on the summed result data to determine the image position of the light spot. When the number of peaks matches the number of light spots, the peak detection result can be considered accurate, so that the image position of the light spot can be located quickly and accurately. The image position of the light spot obtained by this peak detection method can be used to preliminarily determine the position of crystals with obvious crystal boundaries and regular spacing.

[0068] Optionally, performing pixel value peak detection on each of the at least two image blocks to determine the image position of the light spot contained in the image block further includes: when the number of peak values of the first projection data and the number of peak values of the second projection data do not meet a first number requirement, using a preset Hough circle detection algorithm to detect the image block; if the number of circle centers indicated by the detection result obtained by the current detection does not meet a preset second number requirement, adjusting preset algorithm parameters of the Hough circle detection algorithm, and returning to execute the operation of detecting the image block using the preset Hough circle detection algorithm until the number of circle centers indicated by the detection result obtained by the current detection meets the second number requirement, or the number of detections is greater than or equal to a preset number threshold; when the number of circle centers indicated by the detection result obtained by the current detection meets the second number requirement, determining the image position of the light spot contained in the image block according to the circle center position indicated by the detection result.

[0069] For example, since the light spots may be stuck and smeared, the number of peaks in the first projection data and the number of peaks in the second projection data may not meet the first number requirement. Figure 5 , which is a schematic diagram of the distribution of the first projection data and the second projection data according to another embodiment of the present invention. Figure 5 In the illustrated embodiment, each sensor unit is coupled to a crystal arranged in a 2*2 matrix, and the preset first quantity requirement may include: the number of peaks of the first projection data is equal to 2, and the number of peaks of the second projection data is equal to 2. Figure 5 In the illustrated embodiment, the image block has an xy coordinate system, and the coordinate range of the coordinate system is from (0, 0) to (175, 175). Figure 5 (a) shows the distribution of the first projection data obtained by summing along the x direction (ie, the first direction). In this set of first projection data, the peak values are the ordinates of point E and point F, respectively. Figure 5 (b) shows the distribution of the second projection data obtained by summing along the y direction (i.e., the first direction). In this set of second projection data, the peak values are the ordinates of point G, point H, and point I, respectively. The second projection data contains three peak values, which does not meet the preset first quantity requirement. In this case, a preset Hough circle detection algorithm can be used to detect the image block. Exemplarily, the second quantity requirement can be, for example, that the number of circle centers indicated by the detection result is equal to the total number of crystals coupled to the sensor unit corresponding to the image block. The specific process of using the Hough circle detection algorithm to detect each image block can refer to the relevant description of the aforementioned embodiment and will not be repeated here.

[0070] In the above technical solution, when the number of peaks in the first projection data and the second projection data does not meet the first number requirement, that is, when the number of peaks does not match the number of light spots contained in the image block, the Hough circle detection algorithm can be used to detect the image block. This can quickly and accurately determine the image position of the light spot when the adhesion and smear of the light spot have a significant impact on the peak detection result.

[0071] Optionally, the preset algorithm parameters include a minimum distance between detected circle centers and an accumulator threshold.

[0072] For example, the preset algorithm parameters that are adjusted may include the minimum distance between detected circle centers (minDist) and the voting threshold in the accumulator (parm2). Adjusting minDist and param2 can help optimize the Hough circle detection algorithm's detection performance, ensuring that the algorithm is adaptable to situations where light spots have smearing and adhesion.

[0073] Optionally, the first quantity requirement includes: the peak number of the first projection data is equal to the preset number of light spots in the second direction, and the peak number of the second projection data is equal to the preset number of light spots in the first direction; the second quantity requirement includes: the number of detected circle centers is equal to the preset number of light spots in the image block.

[0074] Exemplarily, the summed data included in the first projection data are arranged along the second direction. Therefore, the number of peaks in the first projection data can represent the number of spots distributed along the second direction determined based on peak detection. When the determined number of spots is the same as the preset number of spots in the second direction, the number of peaks in the first projection data can be considered to meet the second quantity requirement. Similarly, the summed data included in the second projection data are arranged along the first direction. Therefore, the number of peaks in the second projection data can represent the number of spots distributed along the first direction determined based on peak detection. When the determined number of spots is the same as the preset number of spots in the first direction, the number of peaks in the second projection data can be considered to meet the second quantity requirement. The preset number can be determined based on the number of crystals coupled to the sensor unit and the crystal arrangement. The specific determination method can be referred to the aforementioned embodiment and will not be repeated here. Exemplarily, the second quantity requirement can include that the number of detected circle centers is equal to the preset number of spots in the corresponding image block. The preset number of spots can, for example, be equal to the total number of crystals coupled to the sensor unit corresponding to the image block.

[0075] The first quantity requirement and the second quantity requirement in the above technical solution can be adapted to the number of light spots in the image block, thereby ensuring that the image position of the detected light spot is consistent with the actual image position of the light spot under the premise that the number of peaks meets the first quantity requirement or the detection center meets the second quantity requirement.

[0076] Optionally, a crystal position lookup table is generated based on the image position of the light spot contained in each of the at least one image blocks, including: generating a Vero map based on the image position of the light spot contained in each of the at least one image blocks, the Vero map including multiple sub-regions, and the multiple sub-regions corresponding one-to-one to multiple crystals; generating a crystal position lookup table based on the Vero map, the crystal position lookup table including the crystal number and crystal boundary information corresponding to each of the multiple sub-regions.

[0077] Exemplarily, after determining the image position of each light spot, a Vero map can be generated based on the image position of each light spot. The Vero map can include multiple sub-areas, each sub-area can correspond to a light spot, and correspondingly can correspond to a crystal. A crystal position lookup table can be generated based on the Vero map. Specifically, each sub-area in the Vero map can be numbered, and the number can be used as the crystal number of the corresponding crystal. The crystal position lookup table can include the crystal number and crystal boundary information corresponding to each sub-area. It can be understood that the crystal boundary information of the corresponding crystal can be determined based on the image position of the boundary of each sub-area in the Vero map in the Vero map.

[0078] In the above technical solution, a Vero map is generated based on the image position of the light spot, and the position range of the crystal can be quickly and accurately determined based on the Vero map, thereby obtaining accurate crystal boundary information.

[0079] Optionally, generating a crystal position lookup table according to the image positions of the light spots respectively included in at least one image block further includes: marking sub-regions of any two crystal boundaries at least partially overlapping with different colors.

[0080] See also Figure 6 As shown in FIG, it is a visualization view of the crystal position lookup table according to one embodiment of the present invention. Figure 6 In the illustrated embodiment, the visual view of the crystal position lookup table can include 36 sub-regions, each of which can include a light spot corresponding to a crystal. Any two sub-regions with overlapping crystal boundaries can be marked with different colors. This method can visually distinguish the sub-regions, especially when users view the crystal position lookup table, and can clearly and intuitively display crystal location information to users.

[0081] See also Figure 7The figure shows a flowchart of the specific process for generating a crystal position lookup table according to one embodiment of the present invention. First, a two-dimensional position map can be obtained and divided into multiple image blocks based on the row and column information of the sensor units. For each image block, the pixel values of each pixel in the image block can be summed along the x-direction to obtain first projection data and summed along the y-direction to obtain second projection data. Peak detection is performed on each of the first and second projection data. When the number of peaks in the first and second projection data both meet a preset first quantity requirement, the image position of the light spot contained in the image block is determined based on the peak position of the first and second projection data. In this embodiment, each image block corresponds to a sensor unit, each sensor unit is coupled to four crystals, and the crystals are arranged in a 2x2 matrix. The first quantity requirement includes: the number of peaks in the first and second projection data equal to 2, and the number of peaks in the second projection data equal to 2. Peak detection is performed on each of the first and second projection data. When the number of peaks in the first and second projection data both equals 2, the peak position can be recorded and saved. The peak position can be represented by the coordinates in the image coordinate system of the image block. When any one of the peak numbers of the first projection data and the peak number of the second projection data is not equal to 2, the image block can be detected using the Hough circle detection algorithm. When the number of circle centers detected matches the number of crystals coupled to a single sensor, the position of the circle center detected can be recorded and saved. Similarly, the position of the circle center can be represented by the coordinates in the image coordinate system of the image block. If the number of circle centers detected does not match the number of crystals coupled to a single sensor and does not exceed the preset number of detections, the preset algorithm parameters, such as minDist and param2, can be automatically and randomly modified. If the number of circle centers detected does not match the number of crystals coupled to a single sensor and exceeds the preset number of detections, the algorithm parameters in the Hough circle detection algorithm can be manually modified by the user. A Vero diagram can be drawn based on the saved peak position or circle center position, and a crystal number can be set for the crystal corresponding to each sub-area in the Vero diagram. The crystal boundary information of the corresponding crystal can be determined based on the position of the boundary of each sub-area in the Vero diagram in the image. It can be understood that a crystal position lookup table can be generated based on the crystal number and crystal boundary information.

[0082] See also Figure 8 , which is a schematic diagram of a device for generating a crystal position lookup table according to an embodiment of the present invention. According to another aspect of the present invention, a device for generating a crystal position lookup table is also provided. The device 800 includes:

[0083] An acquisition module 810 is configured to acquire a two-dimensional position map indicating a position of an incident photon event, wherein the two-dimensional position map includes a plurality of light spots, and the plurality of light spots correspond one-to-one to a plurality of crystals of a positron emission tomography device;

[0084] a dividing module 820 for dividing the two-dimensional position map according to an arrangement of sensor units coupled to a plurality of crystals of a positron emission tomography device to obtain at least two image blocks;

[0085] The generation module 830 is used to determine the image position of the light spot contained in each of the at least two image blocks, and generate a crystal position lookup table based on the image position of the light spot contained in each of the at least two image blocks, wherein the crystal position lookup table is used to indicate the positions of the crystal boundaries between multiple crystals.

[0086] See also Figure 9 As shown, it is a schematic block diagram of an electronic device according to an embodiment of the present invention. On the other hand, an electronic device is also provided according to the present invention. The electronic device 900 includes: a processor 910 and a memory 920, wherein the memory 920 stores computer program instructions, and the computer program instructions are used by the processor 910 to execute the above-mentioned method for generating the crystal position lookup table when the processor 910 is running.

[0087] By way of example, the electronic device may be, for example, a positron emission tomography device.

[0088] According to another aspect of the present invention, a storage medium is provided, on which program instructions are stored. When the program instructions are executed by a computer or processor, the computer or processor executes the corresponding steps of the method for generating the crystal position lookup table according to the embodiment of the present invention, and is used to implement the corresponding modules in the device for generating the crystal position lookup table according to the embodiment of the present invention or the corresponding modules in the device for generating the crystal position lookup table. The storage medium may include, for example, a memory card of a smart phone, a storage component of a tablet computer, a hard disk of a personal computer, a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a portable compact disc read-only memory (CD-ROM), a USB memory, or any combination of the above storage media. The computer-readable storage medium may be any combination of one or more computer-readable storage media.

[0089] According to yet another aspect of the present invention, a computer program product is provided, comprising computer program instructions, which are used to execute the above-mentioned method for generating a crystal position lookup table when running.

[0090] A person skilled in the art can understand the specific implementation and beneficial effects of the above-mentioned crystal position lookup table generation device, electronic device, storage medium and computer program product by reading the above-mentioned detailed description of the crystal position lookup table generation method. For the sake of brevity, it will not be repeated here.

[0091] Although example embodiments have been described herein with reference to the accompanying drawings, it should be understood that the above example embodiments are merely illustrative and are not intended to limit the scope of the present invention. Various changes and modifications may be made therein by those skilled in the art without departing from the scope and spirit of the present invention. All such changes and modifications are intended to be included within the scope of the present invention as claimed in the appended claims.

[0092] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0093] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is merely a logical function division. In actual implementation, other division methods may be used. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not performed.

[0094] In the description provided herein, numerous specific details are described. However, it is understood that embodiments of the present invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques are not shown in detail so as not to obscure the understanding of this description.

[0095] Similarly, it should be understood that in order to streamline the present invention and aid in understanding one or more of the various inventive aspects, in the description of exemplary embodiments of the present invention, the various features of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof. However, this approach to the present invention should not be interpreted as reflecting the intention that the claimed invention requires more features than those explicitly recited in each claim. More precisely, as reflected in the corresponding claims, the inventive point is that the corresponding technical problem can be solved with fewer features than all the features of a single disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into the detailed description, with each claim itself serving as a separate embodiment of the present invention.

[0096] It will be understood by those skilled in the art that, except where mutually exclusive, all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or apparatus disclosed herein may be combined in any combination. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature providing the same, equivalent, or similar purpose.

[0097] Furthermore, those skilled in the art will appreciate that although some embodiments herein include certain features included in other embodiments but not other features, combinations of features from different embodiments are intended to be within the scope of the present invention and to form different embodiments. For example, in the claims, any of the claimed embodiments may be used in any combination.

[0098] The various component embodiments of the present invention can be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It should be understood by those skilled in the art that a microprocessor or a digital signal processor (DSP) can be used in practice to implement some or all of the functions of some modules in the device for generating the crystal position lookup table according to an embodiment of the present invention. The present invention can also be implemented as a device program (e.g., a computer program and a computer program product) for performing part or all of the methods described herein. Such a program for implementing the present invention can be stored on a computer-readable medium, or can have the form of one or more signals. Such a signal can be downloaded from an Internet website, or provided on a carrier signal, or provided in any other form.

[0099] It should be noted that the above embodiments illustrate rather than limit the invention, and that those skilled in the art may devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between brackets should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present invention may be implemented by means of hardware comprising several different elements and by means of appropriately programmed computers. In a unit claim enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third etc. does not indicate any order. These words may be interpreted as names.

[0100] The above is merely a description of specific embodiments of the present invention, and the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention are intended to be covered by the scope of protection of the present invention. The scope of protection of the present invention shall be based on the scope of protection of the claims.

Claims

1. A method for generating a crystal position lookup table, characterized in that: The method comprises: Acquire a two-dimensional position map indicating a position of an incident photon event, wherein the two-dimensional position map includes a plurality of light spots, and the plurality of light spots correspond one-to-one to a plurality of crystals of a positron emission tomography device; Dividing the two-dimensional position map according to an arrangement of sensor units of the positron emission tomography device coupled to the plurality of crystals to obtain at least two image blocks; An image position of a light spot included in each of the at least two image blocks is determined, and a crystal position lookup table is generated according to the image position of the light spot included in each of the at least two image blocks, wherein the crystal position lookup table is used to indicate positions of crystal boundaries between the plurality of crystals.

2. The method according to claim 1, characterized in that Before dividing the two-dimensional position map according to the arrangement of the sensor units coupled to the plurality of crystals to obtain at least two image blocks, the method further includes: In response to a user's arrangement customization operation, defining the arrangement of the sensor units; or, Acquiring device type information and / or device identification information of the positron emission tomography device, and determining an arrangement of the sensor units based on the device type information and / or the device identification information; or, The arrangement of the sensor units is determined based on the distribution of the multiple light spots in the two-dimensional position map.

3. The method according to claim 2, characterized in that Before dividing the two-dimensional position map according to the arrangement of the sensor units connected to the plurality of crystals to obtain at least two image blocks, the method further includes: In response to an arrangement updating operation by a user, the arrangement of the sensor units is updated.

4. The method according to claim 2, characterized in that The determining the arrangement of the sensor units based on the distribution of the plurality of light spots in the two-dimensional position map includes: Grouping the plurality of light spots in the two-dimensional position map according to the preset information on the number of light spots in the group and the preset information on the distance between the light spots in the group to determine at least two light spot groups; The arrangement of the sensor units is determined based on the image positions of each of the at least two light spot groups in the two-dimensional position map, wherein each sensor unit in the determined arrangement corresponds to a unique light spot group, and the image positions of each of the at least two light spot groups in the two-dimensional position map are used to indicate the distribution.

5. The method according to any one of claims 1 to 4, characterized in that Dividing the two-dimensional position map according to the arrangement of the sensor units of the positron emission tomography device coupled to the plurality of crystals to obtain at least two image blocks, including: Based on the row and column information of the sensor units, the two-dimensional position map is evenly divided into the at least two image blocks according to the number of rows and columns corresponding to the row and column information, wherein the row and column information is used to indicate the arrangement of the sensor units.

6. The method according to any one of claims 1 to 4, characterized in that The determining the image position of the light spot contained in each of the at least two image blocks includes: A peak value detection of pixel values is performed on each of the at least two image blocks to determine an image position of a light spot included in the image block.

7. The method according to claim 6, characterized in that The performing peak value detection of pixel values on each of the at least two image blocks to determine the image position of the light spot contained in the image block includes: For each of the at least two image blocks, summing pixel values of each pixel point in the image block along a first direction to obtain first projection data and summing pixel values along a second direction to obtain second projection data, wherein the first projection data includes different summation result data distributed along the second direction, and the second projection data includes different summation result data distributed along the first direction; Peak detection is performed on the first projection data and the second projection data respectively. When the peak number of the first projection data and the peak number of the second projection data both meet a preset first quantity requirement, the image position of the light spot contained in the image block is determined according to the peak position of the first projection data and the peak position of the second projection data.

8. The method according to claim 7, characterized in that The performing peak value detection of pixel values on each of the at least two image blocks to determine the image position of the light spot contained in the image block further includes: When the number of peaks of the first projection data and the number of peaks of the second projection data do not meet the first number requirement, detecting the image block using a preset Hough circle detection algorithm; if the number of circle centers indicated by the detection result obtained by the current detection does not meet the preset second number requirement, adjusting the preset algorithm parameters of the Hough circle detection algorithm, and returning to executing the operation of detecting the image block using the preset Hough circle detection algorithm until the number of circle centers indicated by the detection result obtained by the current detection meets the second number requirement, or the number of detections is greater than or equal to a preset number threshold; When the number of circle centers indicated by the detection result obtained in the current detection meets the second number requirement, the image position of the light spot included in the image block is determined according to the position of the circle center indicated by the detection result.

9. The method according to claim 8, characterized in that The preset algorithm parameters include a minimum distance between detected circle centers and an accumulator threshold.

10. The method according to claim 8, characterized in that The first quantity requirement includes: the number of peaks of the first projection data is equal to the preset number of light spots in the second direction, and the number of peaks of the second projection data is equal to the preset number of light spots in the first direction; The second quantity requirement includes: the number of detected circle centers is equal to the number of preset light spots in the image block.

11. The method according to any one of claims 1 to 4, characterized in that: Generating a crystal position lookup table according to the image position of the light spot contained in each of the at least one image blocks comprises: generating a Vero map according to the image position of the light spot contained in each of the at least one image block, wherein the Vero map includes a plurality of sub-regions, and the plurality of sub-regions correspond one-to-one to the plurality of crystals; The crystal position lookup table is generated based on the Vero diagram, and the crystal position lookup table includes a crystal number and crystal boundary information corresponding to each of the multiple sub-regions.

12. The method according to any one of claims 1 to 4, characterized in that The step of generating a crystal position lookup table according to the image position of the light spot contained in each of the at least one image block further includes: Different colors are used to mark the sub-regions where any two crystal boundaries at least partially overlap.

13. A device for generating a crystal position lookup table, characterized in that: The device comprises: an acquisition module, configured to acquire a two-dimensional position map indicating a position of an incident photon event, wherein the two-dimensional position map includes a plurality of light spots, and the plurality of light spots correspond one-to-one to a plurality of crystals of a positron emission tomography device; a dividing module, configured to divide the two-dimensional position map according to an arrangement of sensor units of the positron emission tomography device coupled to the plurality of crystals, to obtain at least two image blocks; A generation module is configured to determine an image position of a light spot contained in each of the at least two image blocks, and generate a crystal position lookup table based on the image position of the light spot contained in each of the at least two image blocks, wherein the crystal position lookup table is configured to indicate positions of crystal boundaries between the plurality of crystals.

14. An electronic device comprising a processor and a memory, characterized in that: The memory stores computer program instructions, which are used by the processor to execute the method for generating a crystal position lookup table according to any one of claims 1 to 12 when the processor is running the computer program instructions.

15. A storage medium having program instructions stored thereon, characterized in that: The program instructions are used to execute the method for generating a crystal position lookup table according to any one of claims 1 to 12 when running.

16. A computer program product comprising computer program instructions, characterized in that The computer program instructions are used to execute the method for generating a crystal position lookup table according to any one of claims 1 to 12 when running.

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