Pet data correction method, device, system, electronic device and storage medium

Abstract

The application relates to a PET data correction method, device, system, electronic device and storage medium. The method comprises the following steps: controlling a phantom to move in the detection range of a detection module under the condition that the radioactive source in the phantom is at different activities, and obtaining a detection data set; wherein the distance between the edge of the phantom and the radioactive source is anisotropic distribution; determining a detection data subset matched with the PET data to be corrected in the detection data set, and obtaining a dead time correction factor according to the matched detection data subset; and correcting the PET data according to the dead time correction factor. The method can balance the cost and accuracy of the dead time correction.

Description

Technical Field

[0001] This application relates to the field of medical imaging technology, and in particular to PET data correction methods, apparatus, systems, electronic devices, and storage media. Background Technology

[0002] The quantitative accuracy of PET images is crucial for clinical diagnosis. During image reconstruction, the dead-time effect leads to an underestimation of quantification in the reconstructed images, affecting the accuracy of diagnosis and other applications relying on image quantification. Therefore, proper dead-time correction must be performed for any missing valid events.

[0003] In the PET calibration method, the same fixed dead time factor calibration table obtained by uniform water phantom calibration is used for scanning all objects. This results in better quantitative accuracy of the image reconstructed from the data after correction based on the dead time factor calibration table when scanning objects with similar shapes to those used in calibration; however, when the shapes of the water phantoms used in scanning and calibration differ significantly, the quantitative accuracy of the image reconstructed from the data after correction based on the dead time factor calibration table deteriorates.

[0004] To address this issue, related techniques utilize multiple phantoms of varying shapes to obtain dead-time correction tables that vary with the scanned object. Traditional high-activity decay experiments are then performed on these phantoms of different shapes, generating multiple different lookup tables. The relationships between the values ​​in these lookup tables and the single-event count rate ratios or peak-to-valley ratios of the energy spectrum during each phantom experiment are fitted to obtain a table of correction coefficient transformation factors relevant to the scanned object. This solution requires conducting multiple high-activity decay experiments on water phantoms of different shapes, resulting in long experimental cycles, high costs, and significant radiation doses to operators.

[0005] There is currently no effective solution to the problem that related technologies cannot balance the cost and accuracy of dead-time correction. Summary of the Invention

[0006] Therefore, it is necessary to provide a PET data correction method, apparatus, system, electronic device, and storage medium that can balance the cost and accuracy of dead time correction to address the aforementioned technical problems.

[0007] Firstly, this embodiment provides a PET data correction method, the method comprising:

[0008] With the radioactive source inside the phantom at different activity levels, the phantom is controlled to move within the detection range of the detection module to obtain a detection dataset; wherein the distance between the edge of the phantom and the radioactive source is anisotropically distributed.

[0009] A subset of probe data that matches the PET data to be corrected is determined in the probe dataset, and a dead time correction factor is obtained based on the matched subset of probe data.

[0010] The PET data are corrected according to the dead time correction factor.

[0011] In some embodiments, the phantom is controlled to move within the detection range of the detection module to obtain a detection dataset, including:

[0012] The detection module obtains multiple subsets of detection data when it detects the phantom at different positions.

[0013] The set of multiple subsets of the probe data is referred to as the probe dataset.

[0014] In some embodiments, controlling the movement of the phantom within the detection range of the detection module when the radioactive source within the phantom is at different activity levels includes:

[0015] Determine whether the radioactive source has decayed to a preset activity level;

[0016] If it is determined that the radioactive source has decayed to the preset activity, the control phantom moves within the detection range.

[0017] In some embodiments, determining a subset of probe data in the probe dataset that matches the PET data to be calibrated includes:

[0018] A first energy spectrum of the PET data and a second energy spectrum of multiple subsets of detection data are obtained; wherein the detection dataset contains the multiple subsets of detection data.

[0019] In the second energy spectrum, a target second energy spectrum that matches the first energy spectrum is determined, and the subset of detection data corresponding to the target second energy spectrum is taken as the subset of detection data that matches the PET data.

[0020] In some embodiments, the detection module includes multiple detection units, obtains a dead-time correction factor based on the matched subset of detection data, and corrects the PET data based on the dead-time correction factor, including:

[0021] Determine the first detection unit for collecting the PET data;

[0022] In the matched subset of detection data, the first data obtained by the first detection unit when detecting the phantom is acquired;

[0023] The PET data acquired by the first detection unit is corrected based on the dead time correction factor obtained from the first data.

[0024] In some embodiments, controlling the movement of the phantom within the detection range of the detection unit includes:

[0025] Control the phantom to perform a preset number of reciprocating movements within the detection range; and / or,

[0026] The phantom is controlled to move at a constant speed within the detection range.

[0027] Secondly, this embodiment provides a PET data correction device, the device comprising:

[0028] The acquisition module is used to control the movement of the phantom within the detection range of the detection module under different activity levels of the radioactive source inside the phantom to obtain a detection dataset; wherein the distance between the edge of the phantom and the radioactive source is anisotropically distributed;

[0029] A matching module is used to determine a subset of probe data in the probe dataset that matches the PET data to be corrected, and to obtain a dead time correction factor based on the matched subset of probe data.

[0030] A correction module is used to correct the PET data according to the dead time correction factor.

[0031] Thirdly, this embodiment provides a PET data correction system, the system comprising: a PET detector, a phantom, and a PET data correction device; wherein, the phantom contains a radiation source, and the distance between the edge of the phantom and the radiation source is anisotropically distributed;

[0032] The PET detector is used to detect the phantom.

[0033] The PET data correction device is used to implement the PET data correction method described in the first aspect.

[0034] Fourthly, this embodiment provides a computer device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the PET data correction method described in the first aspect above.

[0035] Fifthly, this embodiment provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the PET data correction method described in the first aspect above.

[0036] The aforementioned PET data correction method, apparatus, system, electronic device, and storage medium utilize a phantom with an anisotropic distribution of distance between its edge and the radiation source. This phantom moves within the detection range of the detection module under different activity levels, acquiring the resulting detection dataset. This is equivalent to obtaining the detection results calibrated when multiple phantoms of different shapes are used to conduct high-activity decay experiments, thus solving the high cost problem associated with conducting high-activity decay experiments with separate phantoms. Furthermore, by using a dead-time correction factor of a subset of detection data matched to the PET data to be corrected, the PET data is corrected. This addresses the inaccuracy problem when using a fixed dead-time factor obtained from the same phantom calibration, achieving a balance between the accuracy and efficiency of dead-time correction. Attached Figure Description

[0037] Figure 1 This is a diagram illustrating the application environment of a PET data correction method in one embodiment;

[0038] Figure 2 This is a flowchart illustrating a PET data correction method in one embodiment;

[0039] Figure 3 This is a schematic diagram of a cross-section of the mold body through the central axis in one embodiment;

[0040] Figure 4 This is a schematic diagram of the movement of the phantom within the detection module in one embodiment;

[0041] Figure 5 This is a schematic diagram of the data collection by the detection module in one embodiment;

[0042] Figure 6 This is a schematic diagram of the PET-CT system and phantom in one embodiment;

[0043] Figure 7 This is a structural block diagram of a PET data correction device in one embodiment;

[0044] Figure 8 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0045] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0046] In traditional PET data calibration methods, the same uniform phantom is used to calibrate all object scans to obtain a model of the detector module's single-event count rate as a function of the radioactive source activity within a specific energy window. The dead-time correction factor is then obtained through a single radioactive phantom decay experiment. The specific method is as follows:

[0047] Assuming the system belongs to the non-paralyzable model, then:

[0048] m = n + n b -m(n+n b )τ

[0049] Where n is the event rate incident on the detector, m is the event rate measured by the detector, and τ is the dead time factor. b It is the background count rate.

[0050] In a decay experiment, multiple sets of data were collected at different time points, and the event rate measured by the detector for each set of data was denoted as m. i , where i is a positive integer. Since the dead-time effect of the system is relatively weak at low activity, the background count rate n can be obtained by linear fitting using the 10 measurements with the lowest activity. b Since the event rate measured by the detector is proportional to the activity of the radioactive source, it should conform to an exponential decay change, i.e.: Substituting this into the above equation, the equation can be transformed into:

[0051]

[0052] For m i greater than 10 times n b For the sampling points, the influence of the background count rate can be ignored, and the above formula becomes:

[0053]

[0054] After transforming the data obtained from the sampling points according to the independent and dependent variable forms in the above formula, a standard linear equation can be obtained. Linear fitting yields the slope and intercept, from which the dead time factor τ can be calculated. The derivation process of the paralysis model is similar, except that the relationship between the actual event rate of the incident detector and the event rate received by the detector becomes:

[0055] m = ne -λτ

[0056] Ignoring the background count rate, the equations are transformed into a system of linear equations:

[0057] λτ+ln(m)=-n0τe -λτ +ln(n0)

[0058] However, this method yields a fixed dead-time factor correction table. Specifically, the electronic processing circuit performs energy integration on each Type I signal whose energy integral value is greater than the first threshold (i.e., the noise threshold) to obtain energy information of the incident event deposition. However, to improve the circuit's processing capability, not all Type I signals are typically processed. Only Type II events with an energy integral value greater than the second threshold (rawCut) are decoded to determine the event's incident position. Furthermore, to reduce the impact of scattering events and further enhance the circuit's processing capability, only Type III events with energy greater than the third threshold (LLD) but less than the upper energy limit (ULD) are considered for compliance judgment to generate valid events for final reconstruction. The system can typically only count the count rate (i.e., energy qualified block count rate) of Type II or even Type III events for dead-time correction. Therefore, the traditional dead-time correction method, which determines the dead-time based on a model of the detector module's single-event count rate changing with the radioactive source activity under a specific energy window, cannot fully cover all factors causing the system's electronic dead time. This leads to quantitative bias in the system dead time factor calibrated using high-activity decay experiments on standard phantoms when reconstructing images from other phantoms or human data.

[0059] To address the aforementioned issues, related technologies utilize multiple phantoms of different shapes to calibrate a dead-time correction table that varies with the scanned object. For ease of understanding, an example is provided using three uniform water phantoms of varying thicknesses to obtain a dead-time correction table that varies with the scanned object:

[0060] Three uniform water phantoms of different thicknesses were acquired, ensuring that the water phantoms covered the entire axial field of view (FOV) of the PET. For example, if the axial distance of the PET was 2m, a phantom with a length of 2m was required. The three uniform water phantoms of different thicknesses were placed within the detection range of the PET to perform a conventional high-activity decay experiment, resulting in three different lookup tables. Then, the ratio of single-event count rates within different energy windows, or the peak-to-valley ratio of the event energy spectrum, was calculated for each phantom experiment. Finally, the relationship between different lookup table values ​​and the ratio of single-event count rates or the peak-to-valley ratio of the energy spectrum was fitted to obtain a baseline dead-time correction table and a table of correction coefficient transformation factors related to the scanned object. In the actual dead-time correction stage, the transformation factor of the dead-time factor lookup table was first calculated based on the ratio of single-event count rates within two different energy windows in the acquired data, or the peak-to-valley ratio of the acquired data energy spectrum. This factor was then applied to the baseline lookup table to obtain the final dead-time correction factor.

[0061] However, conducting activity decay experiments on multiple models of different shapes requires a long time, is costly, and exposes operators to a large radiation dose; furthermore, when used for calibration of long-axis systems, the phantoms that need to be infused are large, which further increases the cost.

[0062] The PET data correction method provided in this application embodiment can be applied to... Figure 1 In the environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104, or it can be located in the cloud or on other network servers. The data storage system stores data such as PET phantom detection results and calculated dead time factors. Server 104 can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0063] In one embodiment, such as Figure 2 As shown, a PET data correction method is provided, which can be applied to... Figure 1 Taking the terminal in the example, the explanation includes the following steps:

[0064] In step S201, the phantom is moved within the detection range of the detection module under different activity levels of the radioactive source inside the phantom to obtain a detection dataset; wherein the distance between the edge of the phantom and the radioactive source is anisotropically distributed.

[0065] The phantom contains a radioactive source, and the space between the phantom and the radioactive source is filled with a medium, which can be water or other solutions. The anisotropic distribution of the distance between the phantom's edge and the radioactive source allows the same detection module to obtain different count rates of Type I and Type II events when collecting data from phantoms at different locations. In other words, for the same detection module, data obtained from detecting phantoms at different locations is equivalent to data obtained from detecting phantoms of different shapes in traditional techniques. To achieve this anisotropic distribution, the shape of the phantom can be set so that the distance between the phantom's edge and the radioactive source varies with the azimuth angle. Alternatively, to achieve this anisotropic distribution, sleeves can be continuously added or removed from the outside of the phantom as it moves within the detection module's range. The speed of the phantom within the detection module's range does not affect the acquisition of the detection data set; that is, the phantom can move at a uniform speed or a non-uniform speed, without restriction.

[0066] Optionally, when the radioactive source inside the phantom is at a certain activity level, the phantom is controlled to move within the detection range of the detection module; when the radioactive source inside the phantom is at a different activity level, the phantom is again controlled to move within the detection range of the detection module. The above steps are repeated, and a detection dataset is obtained based on the data detected by the detection module during the multiple movements of the phantom.

[0067] Step S202: Determine a subset of probe data in the probe dataset that matches the PET data to be corrected, and obtain the dead time correction factor based on the matched subset of probe data.

[0068] The length of the connection between the detection module and the radiation source varies within the phantom depending on its location. A longer connection results in data equivalent to data obtained from a thicker phantom; conversely, a shorter connection results in data equivalent to data obtained from a thinner phantom. Matching the subset of detection data with the PET data to be corrected means that the phantom shape corresponding to the subset of detection data matches the phantom shape corresponding to the PET data to be corrected.

[0069] Optionally, based on the ratio of the count rates of the first type of events and the second type of events in the detected data, or the energy spectrum distribution over time, the detected data that matches the phantom thickness corresponding to the PET data to be corrected is obtained from the detected dataset, and thus a subset of the detected data is obtained.

[0070] Step S203: Correct the PET data according to the dead time correction factor. Optionally, obtain the energy spectrum of the PET data and perform dead time correction processing on the energy spectrum of the PET data according to the dead time correction factor.

[0071] In the aforementioned PET data correction method, because the distance between the phantom edge and the radiation source is anisotropically distributed, the length of the line connecting the detection module and the radiation source within the phantom varies depending on the phantom's location. By moving a single phantom within its detection range, the detection module can obtain detection results from multiple phantoms of different shapes, i.e., a detection dataset. This avoids the high correction cost associated with separately calibrating dead-time correction factors using multiple phantoms of different shapes. Obtaining the dead-time correction factor from a subset of detection data matching the PET data to be corrected, and then correcting the PET data based on this dead-time correction factor, solves the problem of inaccurate dead-time factor correction when using a fixed dead-time factor obtained from calibrating the same uniform phantom to correct PET data.

[0072] Furthermore, in conventional techniques, when using a phantom for calibration to obtain the dead time correction factor, the phantom needs to cover the entire axial FOV of the PET. In the PET data calibration method of this embodiment, the phantom moves within the detection range, meaning the length of the phantom does not need to cover the entire axial FOV of the PET system. This reduces the size of the phantom, lowers the phantom infusion dose, and further reduces the cost of PET data calibration.

[0073] To facilitate the matching of probe data subsets, after acquiring the probe data of the phantom, it is merged to obtain multiple probe data subsets. In one embodiment, controlling the phantom to move within the detection range of the probe module to obtain a probe dataset includes: acquiring multiple probe data subsets obtained when the probe module probes the phantom at different positions; and using the collection of multiple probe data subsets as the probe dataset. The probe dataset includes multiple probe data subsets. For the same probe module, different probe data subsets correspond to probe data of phantoms of different shapes under the probe module, and each corresponds to a different dead time correction factor.

[0074] Optionally, multiple locations are selected within the detection range of the detection module. Whenever the phantom moves to a selected location, the detection data collected by the detection module is acquired. The detection data obtained by the detection module at the same selected location under different activities are considered as a subset of detection data. From these subsets, a subset of detection data whose shape matches the PET data to be corrected is determined.

[0075] Optionally, the movement of the phantom within the detection module is controlled when the radioactive source inside the phantom is at different activities. This includes: determining whether the radioactive source has decayed to a preset activity; and controlling the movement of the phantom within the detection range when the radioactive source has decayed to the preset activity. The radioactive source changes over time, decaying from high activity to low activity, and the preset activity is located within the decay range of the radioactive source activity. If the radioactive source has not decayed to the preset activity, the movement of the phantom is not controlled; if the radioactive source has decayed to the preset activity, the movement of the phantom is controlled.

[0076] To facilitate the processing of the probe data and obtain a subset of probe data, the movement of the phantom within the detection range of the detection module is controlled, including: controlling the phantom to move at a constant speed within the detection range. When the phantom moves at a constant speed, the amount of data collected by the detection module is the same when the phantom reaches the same position, simplifying the processing of the probe data. To improve correction accuracy, the movement of the phantom within the detection range of the detection module also includes: controlling the phantom to perform a preset number of back-and-forth movements within the detection range. The larger the preset number of movements, the larger the amount of data collected by the detection module, which can avoid errors and make the dead-time correction factor calculated based on the matched subset of probe data more accurate. Optionally, when controlling the phantom to move within the detection range of the detection module, the phantom is controlled to perform a preset number of back-and-forth movements at a constant speed within the detection range. This simplifies the processing of the probe data while improving correction accuracy.

[0077] In one embodiment, determining a subset of probe data that matches the PET data to be calibrated in the probe dataset includes: acquiring a first energy spectrum of the PET data and a second energy spectrum of multiple probe data subsets; wherein the probe dataset contains multiple probe data subsets; determining a target second energy spectrum that matches the first energy spectrum in the second energy spectrum, and using the probe data subset corresponding to the target second energy spectrum as the probe data subset that matches the PET data.

[0078] Optionally, the peak-to-valley ratio of the first energy spectrum is obtained, and a target second energy spectrum with the peak-to-valley ratio closest to the first energy spectrum is determined. Data with different energy spectrum distributions correspond to data obtained during high-activity decay of phantoms of different shapes. Therefore, based on the energy spectrum distribution, the subset of probe data in the probe dataset that most closely resembles the shape of the PET data to be corrected can be determined. Furthermore, since the closer the shape of the scanned object corresponding to the PET data to be corrected is to the shape of the phantom corresponding to the dead-time factor applied when correcting the PET data, the higher the PET data correction accuracy, this embodiment uses energy spectrum distribution matching to obtain the dead-time factor from the subset of probe data, which can improve the accuracy of the corrected PET data.

[0079] In one embodiment, the detection module includes multiple detection units, obtains a dead time correction factor based on a matched subset of detection data, and corrects PET data based on the dead time correction factor, including: determining a first detection unit for collecting PET data; acquiring first data obtained by the first detection unit when it detects the phantom in the matched subset of detection data; and correcting the PET data collected by the first detection unit based on the dead time correction factor obtained from the first data.

[0080] In this detection module, multiple detection units are located at different positions, with the first detection unit being any one of the detection units in the module. When multiple detection units simultaneously detect the phantom, the connections between the detection units at different positions and the radiation source are different. Therefore, when detecting the same phantom at the same position, the detection units at different positions will obtain different data and energy spectra, and each will correspond to a phantom of a different shape.

[0081] In theory, different detection units can correct PET data based on the same dead-time correction factor. However, in practical applications, different detection units have individual differences. This embodiment improves the correction accuracy by obtaining the dead-time correction factor corresponding to the first detection unit and correcting the PET data collected by that detection unit.

[0082] Based on this embodiment, a similar correction method can be obtained for the PET data collected by other detection units in the detection module besides the first detection unit. That is, the dead time correction factor of each detection unit is obtained, and the PET data collected by each detection unit is corrected based on the corresponding dead time correction factor.

[0083] In one embodiment, Figure 3 A schematic diagram of a cross-section of a phantom through its central axis is provided, such as... Figure 3 As shown, the simulation includes a radioactive source FDG (Fludeoxyglucose) and is filled with water (H2O). The distance between the phantom edge and the radioactive source varies linearly with orientation. Based on Figure 3 The phantom shown was subjected to a high-activity decay experiment in a system containing a PET device. Specifically, during the decay process of the radioactive source inside the phantom from high activity to low activity, multiple preset activities were selected. When the radioactive source was at a preset activity, the phantom was controlled to move within the detection range of the PET system. Each movement lasted for a preset time, and it was ensured that the phantom moved at a uniform speed for at least one round trip within the PET detection range each time it moved.

[0084] The PET system's detection module includes multiple detection units, each corresponding to a crystal at a different location. Figure 4 A schematic diagram of the movement of a phantom within a detection module is provided. Figure 4 In the PET system's detection module, there are seven different crystals: crystal 1, crystal 2, ..., crystal 7, denoted as crystal1, crystal2, ..., crystal7. Control... Figure 3 The phantom shown moves within the detection range of each detection unit. Based on the phantom's position within the detection range, the collected detection data is divided. For example... Figure 4As shown, nine sampling locations were selected within the detection range. It should be understood that the number and location of crystals in the detection module, as well as the position of the phantom within the detection range, can be related to... Figure 4 The differences are not specified here.

[0085] Optionally, at a preset activity level, after the phantom moves at a constant speed for at least one round trip within the detection range of the PET system, the collected data is divided into 9 data groups, each corresponding to a specific point where the phantom has moved to. Figure 4 The data were collected at the nine acquisition locations shown. The data acquisition and segmentation steps were repeated until data sets were obtained from the PET system at multiple different preset activity levels of the radioactive source. Data sets corresponding to the same movement location were grouped together to obtain nine different subsets of detection data, including subset 1, subset 2, ..., subset 7, denoted as Frame1, Frame2, ..., Frame9, respectively. Figure 5 A schematic diagram of the data collected by the detection module is provided, such as... Figure 5 As shown, the horizontal axis represents time, the left vertical axis represents the bed location (Bedpos), and the right vertical axis represents the bed location number (bedpos index).

[0086] Data obtained from high-activity decay experiments on phantoms of different "shapes" for different crystals and frames. For example... Figure 4 As shown, when the model moves to the rightmost position, only CTystal7 can collect the model's data, and the data collected by CTystal7 is denoted as Frame1. When the model moves to the second position from the right shown in the diagram, both CTystal6 and CTystal7 can collect the model's data, and the data collected by CTystal6 and CTystal7 is denoted as Frame2. Similarly, the data contained in Frame3, Frame4, ..., Frame9 can be obtained.

[0087] The data collected by cttystal6 and cttystal7 correspond to two phantoms of different shapes. Specifically, when the phantom is at the second position from the right in the diagram, the line connecting cttystal6 and the radioactive source within the phantom is shorter within the phantom. The data collected by cttystal6 in Frame 2 is equivalent to the data collected when the phantom is thinner. When the phantom is at the second position from the right in the diagram, the line connecting cttystal7 and the radioactive source within the phantom is longer within the phantom. The data collected by cttystal7 in Frame 2 is equivalent to the data collected when the phantom is thicker. The energy spectrum distribution obtained when probing phantoms of different thicknesses is different. Therefore, cttystal6 and cttystal7 in Frame 2 are equivalent to data obtained from high-activity decay experiments on two phantoms of different "shapes," yielding two different energy spectra and dead-time correction factors.

[0088] When the phantom reaches its rightmost position, the length of the line connecting cttystal7 and the radiation source within the phantom is the same as the length of the line connecting cttystal6 and the radiation source within the phantom when the phantom reaches the second position from right to left. Therefore, the phantom "shape" corresponding to Frame 1 is the same as the phantom "shape" corresponding to the data collected by cttystal6 in Frame 2. Due to individual differences between different cttystals, there is a difference between the dead time correction factor corresponding to Frame 1 and the dead time correction factor corresponding to cttystal6 in Frame 2.

[0089] Multiple dead time factors are calculated based on the event count rates corresponding to different energy spectrum distributions in each subset. The results of these multiple dead time factors are then fitted with the energy spectrum distribution as the independent variable to obtain the dead time factors for different detection units in the PET system for different scanned objects. The energy spectrum distribution can be the peak-to-valley ratio of the energy spectrum (the highest value on the right side of the spectrum divided by the lowest value on the left side), or other energy spectrum distribution characteristics.

[0090] This embodiment can be applied to PET-CT systems. Figure 6 A schematic diagram of a PET-CT system and a phantom is provided, wherein, Figure 6 The box on the left shows the CT system, which contains a circular X-ray tube. Figure 6 The three consecutive boxes on the right represent a PET system comprising three detection modules. Each detection module contains multiple detectors, represented by gray boxes. The phantom can move back and forth within the PET system. It should be understood that this embodiment can also be applied to other systems that include PET scanning equipment, and is not limited thereto.

[0091] Based on the same inventive concept, this application also provides a PET data correction apparatus for implementing the PET data correction method described above. The solution provided by this apparatus is similar to the implementation described in the above method; therefore, the specific limitations in one or more PET data correction apparatus embodiments provided below can be found in the limitations of the PET data correction method described above, and will not be repeated here.

[0092] In one embodiment, such as Figure 7 As shown, a PET data correction device is provided, which includes an acquisition module, a matching module and a correction module.

[0093] The acquisition module is used to control the movement of the phantom within the detection range of the detection module under different activity levels of the radioactive source inside the phantom to obtain the detection dataset; wherein the distance between the edge of the phantom and the radioactive source is anisotropically distributed.

[0094] The matching module is used to determine the subset of probe data in the probe dataset that matches the PET data to be corrected, and to obtain the dead time correction factor based on the matched subset of probe data.

[0095] The calibration module is used to correct PET data based on the dead time correction factor.

[0096] In one embodiment, the acquisition module in the PET data correction device controls the phantom to move within the detection range of the detection module to obtain a detection dataset, including: acquiring multiple subsets of detection data obtained when the detection module detects the phantom at different positions; and using the collection of multiple subsets of detection data as the detection dataset.

[0097] Optionally, the acquisition module controls the movement of the phantom within the detection range of the detection module when the radioactive source within the phantom is at different activity levels, including: determining whether the radioactive source has decayed to a preset activity level; and controlling the movement of the phantom within the detection range when it is determined that the radioactive source has decayed to the preset activity level.

[0098] Optionally, the acquisition module controls the movement of the phantom within the detection range of the detection unit, including: controlling the phantom to perform a preset number of reciprocating movements within the detection range; and / or, controlling the phantom to move at a constant speed within the detection range.

[0099] In one embodiment, the matching module in the PET data correction device determines a subset of probe data that matches the PET data to be corrected from the probe dataset, including: acquiring a first energy spectrum of the PET data and a second energy spectrum of multiple probe data subsets; wherein the probe dataset contains multiple probe data subsets; determining a target second energy spectrum that matches the first energy spectrum in the second energy spectrum, and using the probe data subset corresponding to the target second energy spectrum as the probe data subset that matches the PET data.

[0100] In one embodiment, the detection module includes multiple detection units, the matching module obtains a dead time correction factor based on a subset of matched detection data, and the correction module corrects PET data based on the dead time correction factor, including: determining a first detection unit for collecting PET data; acquiring first data obtained by the first detection unit when it detects the phantom in the subset of matched detection data; and correcting the PET data collected by the first detection unit based on the dead time correction factor obtained from the first data.

[0101] Each module in the aforementioned PET data correction device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0102] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 8 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs in the non-volatile storage media to run. The database stores data such as PET phantom detection results and calculated dead time factors. The I / O interfaces are used for information exchange between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When executed by the processor, the computer program implements a PET data correction method.

[0103] Those skilled in the art will understand that Figure 8The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0104] In one embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to perform the following steps: controlling the movement of the phantom within the detection range of a detection module under different activity levels of a radioactive source within the phantom to obtain a detection dataset; wherein the distance between the edge of the phantom and the radioactive source is anisotropically distributed; determining a subset of detection data in the detection dataset that matches the PET data to be corrected, and obtaining a dead time correction factor based on the matched subset of detection data; and correcting the PET data based on the dead time correction factor.

[0105] In one embodiment, when the processor executes the computer program, it further implements the following steps: controlling the phantom to move within the detection range of the detection module to obtain a detection dataset, including: acquiring multiple subsets of detection data obtained by the detection module when it detects the phantom at different positions; and using the set of multiple subsets of detection data as the detection dataset.

[0106] Optionally, determining a subset of probe data that matches the PET data to be calibrated in the probe dataset includes: acquiring a first energy spectrum of the PET data and a second energy spectrum of multiple probe data subsets; wherein the probe dataset contains multiple probe data subsets; determining a target second energy spectrum that matches the first energy spectrum in the second energy spectrum, and using the probe data subset corresponding to the target second energy spectrum as the probe data subset that matches the PET data.

[0107] In one embodiment, when the processor executes the computer program, it further implements the following steps: controlling the phantom to move within the detection range of the detection module when the radioactive source in the phantom is at different activity levels, including: determining whether the radioactive source decays to a preset activity level; and controlling the phantom to move within the detection range when it is determined that the radioactive source has decayed to the preset activity level.

[0108] Optionally, controlling the phantom to move within the detection range of the detection unit includes: controlling the phantom to make a preset number of reciprocating movements within the detection range; and / or, controlling the phantom to move at a constant speed within the detection range.

[0109] In one embodiment, when the processor executes the computer program, it further implements the following steps: the detection module includes multiple detection units, obtains a dead time correction factor based on a matched subset of detection data, and corrects PET data based on the dead time correction factor, including: determining a first detection unit for collecting PET data; acquiring first data obtained by the first detection unit when detecting the phantom in the matched subset of detection data; and correcting the PET data collected by the first detection unit based on the dead time correction factor obtained from the first data.

[0110] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon. When executed by a processor, the computer program performs the following steps: controlling the movement of the phantom within the detection range of a detection module under different activity levels of the radioactive source within the phantom to obtain a detection dataset; wherein the distance between the edge of the phantom and the radioactive source is anisotropically distributed; determining a subset of detection data in the detection dataset that matches the PET data to be corrected, and obtaining a dead time correction factor based on the matched subset of detection data; and correcting the PET data based on the dead time correction factor.

[0111] In one embodiment, when the computer program is executed by the processor, it further implements the following steps: controlling the phantom to move within the detection range of the detection module to obtain a detection dataset, including: acquiring multiple subsets of detection data obtained by the detection module when it detects the phantom at different positions; and using the set of multiple subsets of detection data as the detection dataset.

[0112] Optionally, determining a subset of probe data that matches the PET data to be calibrated in the probe dataset includes: acquiring a first energy spectrum of the PET data and a second energy spectrum of multiple probe data subsets; wherein the probe dataset contains multiple probe data subsets; determining a target second energy spectrum that matches the first energy spectrum in the second energy spectrum, and using the probe data subset corresponding to the target second energy spectrum as the probe data subset that matches the PET data.

[0113] In one embodiment, when the computer program is executed by the processor, it further implements the following steps: controlling the phantom to move within the detection range of the detection module when the radioactive source in the phantom is at different activity levels, including: determining whether the radioactive source decays to a preset activity level; and controlling the phantom to move within the detection range when it is determined that the radioactive source has decayed to the preset activity level.

[0114] Optionally, controlling the phantom to move within the detection range of the detection unit includes: controlling the phantom to make a preset number of reciprocating movements within the detection range; and / or, controlling the phantom to move at a constant speed within the detection range.

[0115] In one embodiment, when the computer program is executed by the processor, it further implements the following steps: the detection module includes multiple detection units, obtains a dead time correction factor based on a matched subset of detection data, and corrects PET data based on the dead time correction factor, including: determining a first detection unit for collecting PET data; acquiring first data obtained by the first detection unit when detecting the phantom in the matched subset of detection data; and correcting the PET data collected by the first detection unit based on the dead time correction factor obtained from the first data.

[0116] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), 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. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0117] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0118] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method of PET data correction, characterized by, The method comprises: Controlling the phantom to move in the detection range of the detection module under the condition that the radioactive source in the phantom is at different activities respectively, to obtain a detection data set; wherein the distance between the edge of the phantom and the radioactive source is anisotropic distribution; Determining a detection data subset matching the PET data to be corrected in the detection data set, and obtaining a dead-time correction factor according to the matching detection data subset; Correcting the PET data according to the dead-time correction factor.

2. The method of claim 1, wherein, Controlling the phantom to move in the detection range of the detection module to obtain a detection data set comprises: Obtaining a plurality of detection data subsets obtained when the detection module detects the phantom moving to different positions; Taking the set of a plurality of detection data subsets as the detection data set.

3. The method of claim 1, wherein, Controlling the phantom to move in the detection range of the detection module under the condition that the radioactive source in the phantom is at different activities respectively comprises: Judging whether the radioactive source decays to a preset activity; Controlling the phantom to move in the detection range under the condition that it is judged that the radioactive source decays to the preset activity.

4. The method of claim 1, wherein, Determining a detection data subset matching the PET data to be corrected in the detection data set comprises: Obtaining a first energy spectrum of the PET data and a second energy spectrum of a plurality of detection data subsets; wherein the detection data set contains the plurality of detection data subsets; Determining a target second energy spectrum matching the first energy spectrum in the second energy spectrum, and taking the detection data subset corresponding to the target second energy spectrum as the detection data subset matching the PET data.

5. The method of claim 1, wherein, The detection module comprises a plurality of detection units, obtaining a dead-time correction factor according to the matching detection data subset, and correcting the PET data according to the dead-time correction factor comprises: Determining a first detection unit used for collecting the PET data; In the matching detection data subset, obtaining first data obtained when the first detection unit detects the phantom; Correcting the PET data collected by the first detection unit according to the dead-time correction factor obtained from the first data.

6. The method of claim 1, wherein, Controlling the phantom to move in the detection range of the detection unit comprises: Controlling the phantom to make a preset number of reciprocating movements in the detection range; and / or, Controlling the phantom to make uniform motion in the detection range.

7. A PET data correction apparatus characterized by comprising: The device comprises: An acquisition module, configured to control the phantom to move in the detection range of the detection module under the condition that the radioactive source in the phantom is at different activities respectively, to obtain a detection data set; wherein the distance between the edge of the phantom and the radioactive source is anisotropic distribution; A matching module, configured to determine a detection data subset matching the PET data to be corrected in the detection data set, and obtain a dead-time correction factor according to the matching detection data subset; A correction module, configured to correct the PET data according to the dead-time correction factor.

8. A PET data correction system characterized by, The system comprises a PET detector, a phantom and a PET data correction device; wherein the phantom contains a radioactive source, and the distance between the edge of the phantom and the radioactive source is anisotropic distribution; The PET detector is configured to detect the phantom; The PET data correction device is configured to implement the steps of the method of any one of claims 1 to 6. 9.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-8 when the computer program is executed by the processor. The processor implements the steps of the method of any one of claims 1 to 6 when executing the computer program.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program, which is executed by the processor, implements the steps of the method of any one of claims 1 to 6. The computer program, which is executed by the processor, implements the steps of the method of any one of claims 1 to 6.

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