Correction method, device, computer storage medium and digital pet system

Abstract

The application discloses a correction method, device, computer storage medium and digital PET system. The correction method comprises the following steps: automatically collecting single event data formed by background radiation of a scintillation crystal in a detector; counting energy spectra of a plurality of scintillation crystal channels based on the single event data, performing main peak extraction on the energy spectra, and obtaining main peak positions of the scintillation crystal channels; processing the main peak positions of the scintillation crystal channels in a same group to obtain a measured main peak in the corresponding group, and obtaining an energy correction factor of the group based on the measured main peak; and restricting the single event data through a time window and a single energy window to screen out a single energy window event data set, performing coincidence processing on the single energy window event data set to obtain coincidence events, constructing a time difference feature set based on time difference of each coincidence event, and generating a time correction parameter by using the time difference feature set. The application can realize passive, automatic and continuous correction.

Description

Technical Field

[0001] This invention relates to the field of data processing, and in particular to a calibration method, apparatus, computer storage medium, and digital PET system. Background Technology

[0002] Positron emission tomography (PET) equipment includes detectors and other necessary hardware and software. During long-term operation, the detector's performance can change due to factors such as temperature drift, device aging, and gain drift. These performance changes can affect the accuracy and repeatability of images. Therefore, regular energy and time corrections of the detector are necessary.

[0003] Most existing correction methods rely on manual intervention, such as using external radiation sources (e.g. 68 Ge 22 Na) performs point source scanning, line source scanning, and other methods to achieve correction. These traditional correction methods have several problems: 1. They rely on external radiation sources, requiring additional radioactive isotopes, which increases both cost and radiation safety risks; 2. They are cumbersome and time-consuming, requiring multiple steps such as system shutdown, manual source placement, data acquisition, and manual correction; 3. They are highly dependent on operators, demanding high levels of operational standardization and professional technical skills, making standardization difficult; 4. They have low real-time performance and automation, mostly only able to execute within the planned cycle or after an abnormal alarm, unable to achieve continuous monitoring and automatic correction. Summary of the Invention

[0004] Therefore, it is necessary to provide a calibration method, apparatus, computer storage medium, and digital PET system to address at least one technical problem existing in traditional solutions.

[0005] According to a first aspect of this application, a correction method is provided, comprising: automatically acquiring single-event data formed by background radiation from a scintillation crystal in a detector; statistically analyzing the energy spectra of several scintillation crystal channels based on the single-event data, extracting the main peak from the energy spectra and obtaining the main peak position of each scintillation crystal channel, processing the main peak positions of scintillation crystal channels within the same group to obtain the measured main peak within the corresponding group, and obtaining the energy correction factor of the group based on the measured main peak; constraining the single-event data through a time window and a single energy window to filter out a single-energy-window event dataset, performing conformance processing on the single-energy-window event dataset to obtain conformance events, constructing a time difference feature set based on the time difference of each conformance event, and generating time correction parameters using the time difference feature set.

[0006] According to one embodiment of this application, the scintillation crystal includes a lutetium-based scintillation crystal or a lanthanum-based scintillation crystal.

[0007] According to one embodiment of this application, the step of processing the main peak positions of scintillation crystal channels within the same group to obtain the measured main peak within the corresponding group includes: performing statistical processing on the main peak positions of multiple scintillation crystals within the same group, and using the statistical average or weighted value of all main peak positions within the same group as the measured main peak of that group.

[0008] According to one embodiment of this application, obtaining the energy correction factor of the group based on the measured main peak includes: comparing the measured main peak of the group with the historical reference main peak, and calculating the corresponding energy correction factor of the group.

[0009] According to one embodiment of this application, the energy correction factor corresponding to this group is calculated, including:

[0010] Energy correction factor is or ,in This indicates the energy value corresponding to the historical reference peak. This indicates the measurement of the energy of the main peak. This represents the average energy of the measured main peak.

[0011] According to one embodiment of this application, after obtaining the energy correction factor of the group, the correction method further includes: multiplying the original single-event energy value collected by each scintillation crystal channel in the group with the energy correction factor as the corrected single-event energy value.

[0012] According to one embodiment of this application, the step of performing conformity processing on the single-energy window event dataset to obtain conforming events includes: constructing a candidate set of event pairs based on the single-energy window event dataset, and extracting the temporal features, energy features, and spatial encoding of the detection unit for each event pair to form an input feature vector; inputting the input feature vector into the event pair discrimination model to obtain the discrimination result of valid conforming events, and outputting the corresponding response line information for event pairs that are determined to be valid conforming events.

[0013] According to one embodiment of this application, the discrimination model is: ,in, This indicates the result of the judgment that the event constitutes a valid matching event. This represents the input feature vector.

[0014] According to one embodiment of this application, the step of constructing a time difference feature set based on the time difference of flight of each matching event includes: for event pairs that are determined to be valid matching events, calculating the time difference of flight of two single events based on the response line information, and summarizing them to form a time difference feature set for time correction.

[0015] According to one embodiment of this application, generating time correction parameters using the time difference feature set includes: constructing a time deviation inversion model based on the time difference feature set, forming a correspondence between the observation vector composed of the time difference feature set and the time offset parameters corresponding to the scintillation crystal channels in each group; and inverting and solving the time offset parameters by minimizing the error between the predicted time difference and the observed time difference to generate the time correction parameters for the scintillation crystal channels in each group.

[0016] According to one embodiment of this application, the inversion model is represented as follows: ,in, This represents an observation vector composed of a set of time difference features. This represents the time offset parameter for each group.

[0017] According to one embodiment of this application, generating a time correction parameter using the time difference feature set includes: comparing the time difference feature set with theoretical values ​​derived from a database model, and assigning a time correction parameter to the scintillation crystal channel in each group based on the comparison result.

[0018] According to one embodiment of this application, after generating the time correction parameter, the correction method further includes: subtracting the collected original single-event timestamp from the time correction parameter to obtain the corrected single-event timestamp.

[0019] According to one embodiment of this application, the automatic acquisition of single-event data formed by the background radiation of the scintillation crystal in the detector includes: counting and recording the single-event count rate in each scintillation crystal channel; if, after acquisition, the single-event count rate of a certain scintillation crystal channel is less than a preset value, then the scintillation crystal channel is marked as an abnormal channel.

[0020] According to one embodiment of this application, the correction method further includes: for the abnormal channel, using the mean of other channels in the same group as its own energy correction factor, and using interpolation of adjacent channels to obtain its own time offset.

[0021] According to a second aspect of this application, a correction device is provided, comprising: an acquisition module configured to automatically acquire single-event data formed by background radiation from a scintillation crystal in a detector; an energy correction factor generation module configured to statistically analyze the energy spectra of several scintillation crystal channels based on the single-event data, extract the main peak from the energy spectra and obtain the main peak position of each scintillation crystal channel, process the main peak positions of scintillation crystal channels within the same group to obtain the measured main peak within the corresponding group, and obtain the energy correction factor for the group based on the measured main peak; and a time correction parameter generation module configured to constrain the single-event data through a time window and a single energy window to filter out a single-energy-window event dataset, perform conformance processing on the single-energy-window event dataset to obtain conformance events, construct a time difference feature set based on the time difference of each conformance event, and generate time correction parameters using the time difference feature set.

[0022] According to one embodiment of this application, the scintillation crystal includes a lutetium-based scintillation crystal or a lanthanum-based scintillation crystal.

[0023] According to one embodiment of this application, the energy correction factor generation module is configured to perform statistical processing on the main peak positions of multiple scintillation crystals in the same group, and use the statistical average or weighted value of all main peak positions in the same group as the measured main peak of the group.

[0024] According to one embodiment of this application, the energy correction factor generation module is configured to compare the measured main peak of the group with the historical reference main peak and calculate the corresponding energy correction factor of the group.

[0025] According to one embodiment of this application, the energy correction factor generation module is configured to set the energy correction factor to... or ,in This indicates the energy value corresponding to the historical reference peak. This indicates the measurement of the energy of the main peak. This represents the average energy of the measured main peak.

[0026] According to one embodiment of this application, the correction device further includes an energy correction module configured to use the product of the original single-event energy value collected by each scintillation crystal channel in the group and the energy correction factor as the corrected single-event energy value.

[0027] According to one embodiment of this application, the time correction parameter generation module is configured to: construct a candidate set of event pairs based on a single-energy window event dataset, and extract the time features, energy features, and spatial encoding of the detection unit for each event pair to form an input feature vector; input the input feature vector into the event pair discrimination model to obtain the discrimination result of valid matching events, and output the corresponding response line information for event pairs that are determined to be valid matching events.

[0028] According to one embodiment of this application, the discrimination model is: ,in, This indicates the result of the judgment that the event constitutes a valid matching event. This represents the input feature vector.

[0029] According to one embodiment of this application, the time correction parameter generation module is configured to: for event pairs determined to be valid coincident events, calculate the flight time difference between two single events based on the response line information, and summarize them to form a time difference feature set for time correction.

[0030] According to one embodiment of this application, the time correction parameter generation module is configured to: construct a time deviation inversion model based on the time difference feature set, form a correspondence between the observation vector composed of the time difference feature set and the time offset parameter corresponding to the scintillation crystal channel in each group; and solve the time offset parameter by minimizing the error between the predicted time difference and the observed time difference to generate the time correction parameter of the scintillation crystal channel in each group.

[0031] According to one embodiment of this application, the inversion model is represented as follows: ,in, This represents an observation vector composed of a set of time difference features. This represents the time offset parameter for each group.

[0032] According to one embodiment of this application, the time correction parameter generation module is configured to: compare the time difference feature set with the theoretical value obtained from the database model, and assign a time correction parameter to the scintillation crystal channel in each group according to the comparison result.

[0033] According to one embodiment of this application, the correction device further includes: a time correction module configured to subtract the acquired original single-event timestamp from the time correction parameter to obtain the corrected single-event timestamp.

[0034] According to one embodiment of this application, the acquisition module is configured to count and record the single event count rate in each scintillation crystal channel. If, after acquisition, the single event count rate of a certain scintillation crystal channel is less than a preset value, then the scintillation crystal channel is marked as an abnormal channel.

[0035] According to one embodiment of this application, for the abnormal channel, the energy correction module is configured to use the average value of other channels in the same group as its own energy correction factor, and the time correction module is configured to use the interpolation of adjacent channels to obtain its own time offset.

[0036] According to a third aspect of this application, a computer storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the steps of the correction method as described in any of the above claims.

[0037] According to a fourth aspect of this application, a computer program product is provided, comprising a computer program or instructions that, when executed by a processor, implement the steps of the correction method as described in any of the above claims.

[0038] According to a fifth aspect of this application, a digital PET system is provided, including the calibration device as described in any of the preceding claims.

[0039] The calibration method, apparatus, computer storage medium, and digital PET system provided in this application firstly overcome the limitation of traditional PET system calibration relying on external sources by utilizing the natural decay of scintillation crystals for calibration, achieving passive calibration of the system's operating status. Secondly, by automatically acquiring and processing data without manual intervention, the system's autonomous management capabilities and operating efficiency are improved, achieving automated calibration of the system's operating status. Compared to traditional external source calibration that relies on manual initiation, this system requires no user operation during operation, effectively reducing the risk of system performance degradation due to misoperation or calibration omissions. Thirdly, by dynamically updating data from periodically acquired natural radiation events, the system can reflect changes in the detector's operating status in real time, improving the timeliness of calibration parameters and helping to ensure the long-term consistency of image reconstruction quality, thus achieving continuous calibration of the system's operating status. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of this specification or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0041] Figure 1 This is a flowchart illustrating the correction method in one embodiment of this application;

[0042] Figure 2 This is a flowchart illustrating an energy correction method in one embodiment of this application;

[0043] Figure 3 This is a flowchart illustrating the time correction method in one embodiment of this application;

[0044] Figure 4 This is the energy spectrum before energy correction in an application.

[0045] Figure 5 To and Figure 4 Energy-corrected spectrum in the same application;

[0046] Figure 6 A width plot of the time distribution before time correction in an application;

[0047] Figure 7 To and Figure 6 A time distribution width plot after time correction in the same application;

[0048] Figure 8 This is a schematic diagram of the structure of the correction device in one embodiment of this application;

[0049] Figure 9 This is a schematic diagram of the correction device in another embodiment of this application;

[0050] Figure 10 This is a schematic diagram of the structure of a computer system in one embodiment of this application;

[0051] Figure 11 This is an internal structural diagram of a computer device in one embodiment of this application. Detailed Implementation

[0052] To make the above-mentioned objectives, features, and advantages of this application more readily understood, the specific embodiments of this application are described in detail below with reference to the accompanying drawings. Many specific details are set forth in the following description to provide a thorough understanding of this application. However, this application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of this application. Therefore, this application is not limited to the specific embodiments disclosed below.

[0053] It should be noted that when an element is said to be "fixed to" another element, it can be directly fixed to the other element or there may be an intervening element. When an element is said to be "connected to" another element, it can be directly connected to the other element or there may be an intervening element. The terms "substantially equal" or "substantially equal to" as used herein mean that the difference between the two lies within a range of errors considered equivalent in the art. The terms "vertical," "horizontal," "left," "right," and similar expressions used herein are for illustrative purposes only.

[0054] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. The terms “and / or” or “and / or” as used herein include any and all combinations of one or more of the associated listed items.

[0055] In some embodiments, the calibration method can be executed by a calibration device. For example, the calibration method can be partially or wholly stored in a storage device (such as the built-in storage module of the detection device or an external storage device) in the form of a program or instructions, which can implement the calibration method when executed. The calibration device disclosed in this application for implementing the above-described calibration method can be either a device with abundant computing resources (e.g., a computer, server, cloud computing, etc.) or a device with limited computing resources (e.g., a hardware circuit such as an FPGA (Field Programmable Gate Array) chip board or an ASIC (Application-Specific Integrated Circuit) chip board).

[0056] The following description, with reference to the accompanying drawings, illustrates some preferred embodiments of the present application. It should be noted that the following description is for illustrative purposes only and is not intended to limit the scope of protection of this application.

[0057] Figure 1 This is a flowchart illustrating the correction method in one embodiment of the present application. In one embodiment, the correction method may include the following steps 100 to 300.

[0058] Step 100: Automatically collect single-event data formed by the background radiation of the scintillation crystal in the detector.

[0059] The automatic data acquisition is preferably performed periodically or conditionally during idle periods. Idle periods can be when the PET equipment has no inspection tasks, such as between 2:00 AM and 4:00 AM. Periodicity can be every 3 days, 5 days, 1 month, or any other arbitrary interval. Conditional acquisition can be based on predetermined conditions that indicate a detector malfunction requiring calibration, or conditions that require calibration after a certain period of use. For example, when the system temperature sensor detects a temperature change in the detector module exceeding ±1.5℃, automatic calibration is triggered to address performance fluctuations caused by thermal drift. It is understood that when periodic acquisition is used, calibration is performed during the idle period of the day when the interval expires; when conditional acquisition is used, calibration is performed during the idle period of the day when the condition is triggered; when both periodic and conditional acquisition are used in combination, calibration will be performed during the idle period of the day when either time or condition is triggered.

[0060] As described above, the automatic data acquisition can be achieved by configuring the system to automatically power on during idle periods and under specific conditions, performing idle data acquisition—that is, automatically acquiring data using the background radiation of the scintillation crystal without an external radiation source. Scintillation crystals capable of spontaneously emitting gamma photons based on their own background radiation (i.e., without relying on an external radiation source) are typically those whose lattice elements contain naturally occurring radioactive isotopes (such as...). 138 La、 176 Lu、 227 Ac, etc.), for example, when the scintillation crystal is a lutetium-based scintillation crystal, such as lutetium yttrium silicate, it exists naturally. 176 Lu's background radiation can undergo spontaneous decay, producing gamma photons; similarly, when the scintillation crystal is a lanthanum-based scintillation crystal, such as lanthanum bromide, it exists naturally. 138 La background radiation can undergo spontaneous decay, producing gamma photons.

[0061] For example, in this embodiment of the application, step 100 can be set to: the time for performing the data collection is greater than or equal to 10 minutes, so as to ensure that the number of single events is sufficient.

[0062] A single event refers to an event in which a single high-energy photon is deposited on a scintillation crystal and converted into visible light by the scintillation crystal, and then the electronic data recorded by the corresponding electronic channel of the scintillation crystal is recorded. The single event data may include timestamp, energy, scintillation crystal channel number, crystal strip index, etc.

[0063] Preferably, step 100 may include counting and recording the single-event count rate in each scintillation crystal channel. If, after acquisition, the single-event count rate of a certain scintillation crystal channel is less than a preset value, then that scintillation crystal channel is marked as an abnormal channel. The preset value is, for example, less than 10 cps. For abnormal channels, the data from that channel can be removed, excluded from the acquisition of correction data, and the information of all abnormal channels can be recorded before prompting the user.

[0064] Step 200: Based on the single-event data, statistically analyze the energy spectra of several scintillation crystal channels, extract the main peak from the energy spectra and obtain the main peak position of each scintillation crystal channel, process the main peak positions of scintillation crystal channels in the same group to obtain the measured main peak in the corresponding group, and obtain the energy correction factor of the group based on the measured main peak.

[0065] In some examples, scintillation crystals are grouped according to their arrangement. Multiple scintillation crystals (e.g., 4×4 or 9×9) are arranged in an array, with each crystal forming a channel. An array of scintillation crystals is grouped into a single group. In some cases, a group is also called a block, and scintillation crystals within the same block can share the same energy correction factor. Each block is coupled to a photoelectric conversion device. After coupling with the photoelectric conversion device, a block, combined with other necessary components such as circuitry, forms a detection unit. Several detection units are combined to form a detector.

[0066] In other examples, groups can be formed according to the temperature sensor area, grouping channels within the same temperature control area together.

[0067] Specifically, see Figure 2 Step 200 may include:

[0068] Step 210: Automatically statistically determine the energy spectrum distribution corresponding to each scintillation crystal channel based on single-event data. Let the energy spectrum of the i-th scintillation crystal channel be denoted as... in, It represents an energy channel or equivalent energy value.

[0069] Step 220: Extract the main peak from the energy spectrum using peak fitting or statistical analysis methods to obtain the main peak position of each scintillation crystal channel. Let the energy of the main peak position of the i-th scintillation crystal channel be denoted as . .

[0070] Optionally, in step 220, a local maximum point is found within a set energy range. Taking yttrium lutetium silicate as an example, the energy range can be 280keV-340keV, and taking lanthanum bromide as an example, the energy range can be 120keV-170keV. The amplitude of the maximum point is required to be several times higher than the average of several scintillation crystal channels on both sides to ensure the statistical significance of the peak value.

[0071] Optionally, step 220 can also use a multi-peak decomposition method to extract the main peak. There may be other weak peaks near the main peak. A Gaussian mixture model is used to decompose the candidate interval, and then the parameters of each Gaussian component are solved iteratively by the expectation-maximization algorithm to extract the mean value corresponding to the main peak.

[0072] Step 230: Perform statistical processing on the main peak positions of multiple scintillation crystals within the same group (e.g., Block), and use the statistical average or weighted value of all main peak positions within the same group (e.g., Block) as the measured main peak of that group.

[0073] Taking the statistical average as the measurement peak of this block as an example, the average energy of the measurement peak is measured. , where N is the number of scintillation crystal channels within the Block.

[0074] Taking the weighted value as the measurement peak of this block as an example, the energy of the measurement peak is measured. ,in, The weighting factor represents the energy of the main peak position in each scintillation crystal channel.

[0075] Step 240: Compare the measured main peak of the group (e.g., Block) with the historical reference main peak, and calculate the energy correction factor corresponding to the group (e.g., Block).

[0076] For example, or ,in This indicates the energy value corresponding to the historical reference peak. This represents the energy correction factor.

[0077] Furthermore, at the application level, after step 240, the following steps are also included:

[0078] Step 250: Multiply the original single-event energy value acquired by each scintillation crystal channel within the group by the energy correction factor to obtain the corrected single-event energy value. Subsequent single-event energy values ​​acquired by each scintillation crystal channel within the group (e.g., Block) are then uniformly corrected according to the following relationship: ,in, The original energy measurement value before correction. This is the corrected energy value. The group can be located based on the channel address included in the single-event data, and then the energy correction factor of that group can be used for energy correction.

[0079] Step 300: Constrain the single event data by time window and single energy window to filter out single energy window event datasets, perform conformity processing on the single energy window event datasets to obtain conforming events, construct a time difference feature set based on the flight time difference of each conforming event, and use the time difference feature set to generate time correction parameters.

[0080] Taking lutetium yttrium silicate scintillation crystal as an example, its energy distribution has relatively fixed and known characteristics. Based on this, this application does not need to distinguish multiple energy ranges, but instead sets a single energy window (e.g., [250keV, 350keV], filtering out single events with an energy of 307keV) to select only events within the main energy range for subsequent processing, thereby: 1. reducing data processing complexity and improving computational efficiency; 2. reducing statistical fluctuations caused by multi-energy window division and improving the statistical stability of time difference; 3. improving the utilization rate of effective events under low count rate background radiation conditions.

[0081] Specifically, see Figure 3 Step 300 may include:

[0082] Step 310: Apply time window and single energy window constraints to the collected single-event data to obtain a single-energy-window event dataset. The time window is, for example,... Energy window, for example The dataset can be denoted as ,in, This represents the k-th single event. This represents the energy of the k-th single event. This represents the timestamp of the k-th single event. A time window can limit the time range of events to avoid random coincidences; a single energy window can select events near a specific characteristic energy in the background energy spectrum (e.g., 307 keV ± 15%) to reduce interference from scattering events.

[0083] Step 320: Construct a candidate set of event pairs based on the single-energy window event dataset, and extract the temporal features, energy features, and spatial encoding of the probe unit for each event pair to form the input feature vector. The single-energy window event dataset is, for example, S, and the candidate set of event pairs is, for example, [example of S]. , ,in, This represents a feature vector composed of information contained in event pairs. and This represents the spatial code of the corresponding detection unit, which corresponds to the spatial location information.

[0084] The detection unit includes blocks and photoelectric conversion devices, for example, a block and a SiPM array coupled together to form the main part of a detection unit.

[0085] Step 330: Input the input feature vector into the event pair discrimination model to obtain the discrimination result. When the discrimination result is greater than a set value, it can be identified as a valid matching event, and the corresponding response line information is output for the valid matching event. The output of the event pair discrimination model is usually designed as the confidence / probability score of the event pair constituting a valid matching event—the larger the value, the more likely it is to be a valid matching event. Therefore, using the discrimination result to determine (if it is greater than the set value, it is identified as a valid matching event) conforms to the conventional usage of binary classification models. In practice, the set value may not be fixed, but rather an ROC curve can be plotted based on historical labeled data (e.g., known true matching / random matching samples), for example, taking a value between 0.1 and 1 to reduce the false positive rate of random matching.

[0086] The response line information, for example, consists of the position coordinates of the scintillation crystals deposited for two single events. The event pair discrimination model is as follows: ,in, This indicates the result of judging whether an event pair constitutes a valid match. The event pair discrimination model can be obtained by training a classifier using logistic regression or a lightweight neural network on a dataset formed from previous data.

[0087] In one embodiment, the event pair discrimination model is a logistic regression classification model. The logistic regression classification model uses the temporal difference information, energy information, and spatial encoding information of the probe units of the event pairs as input features. In another embodiment, the event pair discrimination model is a lightweight neural network classification model. The lightweight neural network classification model includes: an input layer, at least one fully connected hidden layer, and an output layer. The input layer receives the temporal features, energy features, and spatial encoding features of the event pairs. The hidden layer extracts the nonlinear correlation between the input features. The output layer uses a sigmoid activation function and outputs a discrimination result between 0 and 1.

[0088] Step 340: For event pairs determined to be valid matching events, calculate the time difference between the two individual events based on the response line information, and summarize them to form a time difference feature set for time correction. Event pairs include, for example... The time difference feature set can be represented as , This represents the time difference between two single events. , and These are the raw timestamps for two single events.

[0089] Step 350: Based on the aforementioned time difference feature set, construct a time deviation inversion model. The inversion model can be expressed as follows: ,in, This represents an observation vector composed of a set of time difference features. This represents the time offset parameter for each group.

[0090] Step 360: By minimizing the error between the predicted time difference and the observed time difference, the time offset parameters are inverted and solved to generate the time correction parameters for the scintillation crystal channels in each group. The time offset parameters can be expressed as... The time correction parameter can be expressed as time Offset.

[0091] Among them, the time offset parameter The optimal estimate is obtained by solving the model. This optimal estimate can be used as the time offset parameter. The two are numerically equivalent and correspond one-to-one with each group. All scintillation crystal channels located in the same group share the same time offset parameter.

[0092] It should be noted that the above and They have slightly different meanings. This represents the variable to be optimized in the inversion model, that is, the parameter values ​​that are traversed and tried during the solution process—it is the independent variable in the optimization problem, and it is not a certain fixed value itself, but rather a formula. And placeholders in the argmin expression. This represents the optimal solution obtained by minimizing the error, i.e., the specific parameter values ​​output after the inversion calculation—that is, the set of parameters actually calculated in the formula and ultimately used to generate the time offset. In other words: It is a variable. This is the final value (solution) of the variable after optimization.

[0093] As an alternative to step 360 above, this application may further include step 360': comparing the time difference feature set with the theoretical values ​​derived from the database model, and assigning a time correction parameter to the scintillation crystal channel in each group based on the comparison result. Specifically, the database model can be trained based on a large amount of previous datasets, which records theoretical values. The time difference feature set is compared with the set of theoretical values ​​in the database model to obtain a comparison result, and the time correction parameter is determined based on the comparison result.

[0094] In addition, at the application level, after step 360, the following are also included:

[0095] Step 370: Subtract the acquired original single-event timestamp from the time correction parameter to obtain the corrected single-event timestamp. Subsequent single-event timestamps are corrected according to the following relationship: ,in, This is the single-event timestamp before correction. This is the corrected single-event timestamp.

[0096] In addition, for the channels that are identified as abnormal, the average value of other channels in the same group can be used as its own energy correction factor, and the time offset can be obtained by interpolation of adjacent channels.

[0097] To demonstrate the corrective effect of this application, a specific example is provided below.

[0098] Using an existing PET / CT as the experimental subject, which includes a ring detector, a program is built into it that can implement the correction method provided in this application, and the energy spectrum distribution and time distribution width are obtained before and after correction, respectively. Figure 4 This is the energy spectrum before energy correction in an application. Figure 5 To and Figure 4 Energy-corrected spectrum in the same application; Figure 6 A width plot of the time distribution before time correction in an application; Figure 7 To and Figure 6 A time distribution width plot after time correction in the same application. The plot uses one block as an example; the blue curve represents the actual measured data (…). Figure 5 and Figure 7 (The green curve represents the actual measurement data after correction, while the green curve represents the result obtained based on Gaussian model fitting.) By comparison, it can be found that after correction using the method provided in this application, on the one hand, the main peak of the energy spectrum of the block is uniformly corrected to around 511 keV, indicating that the energy response consistency has been effectively improved; on the other hand, the temporal distribution width of the coincidence events is significantly reduced, and the temporal resolution is optimized from approximately 356 ps before correction to 319 ps, indicating that the correction method provided in this application effectively reduces time deviation and improves time consistency.

[0099] The correction method provided in this application, firstly, overcomes the limitation of traditional PET system correction relying on external sources by utilizing the natural decay of scintillation crystals for correction, achieving passive correction of the system's operating status; secondly, by automatically acquiring and processing data without manual intervention, it improves the equipment's autonomous management capabilities and operating efficiency, realizing automated correction of the system's operating status. Compared to traditional external source correction that relies on manual initiation, this system requires no user operation during operation, effectively reducing the risk of system performance degradation due to misoperation or correction omissions; thirdly, by dynamically updating data from periodically acquired natural radiation events, it can reflect changes in the detector's operating status in real time, improving the timeliness of correction parameters and helping to ensure the long-term consistency of image reconstruction quality, thus achieving continuous correction of the system's operating status.

[0100] Based on the description of the above-described calibration method embodiments, this application also provides a calibration apparatus. The apparatus may include devices (including distributed systems), software (applications), modules, components, servers, clients, etc., that use the methods described in the embodiments of this specification, combined with necessary hardware implementations. Based on the same inventive concept, the apparatuses in one or more embodiments provided in this application are as described in the following embodiments. Since the implementation schemes and methods for solving the problem by the apparatus are similar, the implementation of specific apparatuses in the embodiments of this specification can refer to the implementation of the foregoing methods, and repeated details will not be elaborated further. As used below, the terms "module" or "module group" can refer to a combination of software and / or hardware that implements a predetermined function. Although the apparatuses described in the following embodiments are preferably implemented in software, hardware implementations, or a combination of software and hardware, are also possible.

[0101] See Figure 8 The correction device 800 may include: a data acquisition module 810, an energy correction factor generation module 820, and a time correction parameter generation module 830. Optionally, see [link to relevant documentation]. Figure 9 The calibration device 800 may also include a quality control module 801, an energy calibration module 840, and a time calibration module 850.

[0102] Specifically, the quality control module 801 can be configured to trigger other modules to perform calibration work according to a set program. This can be done periodically, at intervals of 3 days, 5 days, one month, or any other time, or conditionally, based on predetermined conditions that indicate a detector malfunction requiring calibration, or when the detector has been used for a certain period and requires calibration. For example, when the system temperature sensor detects a temperature change in the detector module exceeding ±1.5℃, calibration is automatically triggered to address performance fluctuations caused by thermal drift.

[0103] Specifically, the acquisition module 810 is configured to automatically acquire single-event data formed by the background radiation of the scintillation crystal in the detector. Preferably, automatic acquisition can be performed periodically or conditionally during idle periods, where idle periods can be when the PET equipment has no inspection tasks, such as between 2:00 AM and 4:00 AM. It is understood that when periodic acquisition is used, calibration is performed during the idle period of the day when the interval expires; when conditional acquisition is used, calibration is performed during the idle period of the day when the condition is triggered; when both periodic and conditional acquisition are used in combination, calibration will be performed during the idle period of the day when either periodic or conditional acquisition is triggered.

[0104] As described above, the automatic data acquisition can be achieved by configuring the system to automatically power on during idle periods for idle data acquisition, i.e., automatically acquiring data using the background radiation of the scintillation crystal without the need for an external radiation source. Scintillation crystals capable of spontaneously emitting gamma photons based on their own background radiation (i.e., without relying on an external radiation source) are typically those whose lattice elements contain naturally occurring radioactive isotopes (such as...). 138 La、 176 Lu、 227 Ac), for example, when the scintillation crystal is a lutetium-based scintillation crystal, such as lutetium yttrium silicate, it exists naturally. 176 Lu's background radiation can undergo spontaneous decay, producing gamma photons; similarly, when the scintillation crystal is a lanthanum-based scintillation crystal, such as lanthanum bromide, it exists naturally. 138 La background radiation can undergo spontaneous decay, producing gamma photons.

[0105] For example, in this application embodiment, the acquisition module can be set to perform acquisition for a time greater than or equal to 10 minutes to ensure that the number of single events is sufficient.

[0106] A single event refers to an event in which a single high-energy photon is deposited on a scintillation crystal and converted into visible light by the scintillation crystal, and then the electronic data recorded by the corresponding electronic channel of the scintillation crystal is recorded. The single event data may include timestamp, energy, scintillation crystal channel number, crystal strip index, etc.

[0107] Preferably, the acquisition module 810 can also be configured to count and record the single-event count rate in each scintillation crystal channel. If, after acquisition, the single-event count rate of a certain scintillation crystal channel is less than a preset value, then that scintillation crystal channel is marked as an abnormal channel. The preset value is, for example, less than 10 cps. For abnormal channels, the data of that channel can be discarded, excluded from the acquisition of correction data, and the information of all abnormal channels can be recorded before prompting the user.

[0108] Specifically, the energy correction factor generation module 820 is configured to statistically analyze the energy spectra of several scintillation crystal channels based on the single-event data, extract the main peak from the energy spectra and obtain the main peak position of each scintillation crystal channel, process the main peak position of the scintillation crystal channels in the same group to obtain the measured main peak in the corresponding group, and obtain the energy correction factor of the group based on the measured main peak.

[0109] In some examples, scintillation crystals are grouped according to their arrangement. Multiple scintillation crystals (e.g., 4×4 or 9×9) are arranged in an array, with each crystal forming a channel. An array of scintillation crystals is grouped into a single group. In some cases, a group is also called a block, and scintillation crystals within the same block can share the same energy correction factor. Each block is coupled to a photoelectric conversion device. After coupling with the photoelectric conversion device, a block, combined with other necessary components such as circuitry, forms a detection unit. Several detection units are combined to form a detector.

[0110] In other examples, groups can be formed according to the temperature sensor area, grouping channels within the same temperature control area together.

[0111] Optionally, in one example of this application, the energy correction factor generation module 820 is configured to: automatically statistically determine the energy spectrum distribution corresponding to each scintillation crystal channel based on single-event data, and denot the energy spectrum of the i-th scintillation crystal channel as... in, This represents the energy channel or equivalent energy value; the main peak of the energy spectrum is extracted using peak fitting or statistical analysis methods to obtain the energy of the main peak position of the i-th scintillation crystal channel. ; Statistical processing is performed on the main peak positions of multiple scintillation crystals within the same group (e.g., Block), and the statistical average or weighted value of all main peak positions within the same group (e.g., Block) is used as the measured main peak of that group; The measured main peak of this group (e.g., Block) is... (or ) and historical reference peak By comparing the results, the energy correction factor corresponding to this group (e.g., Block) is calculated. For example, or ,in This indicates the energy value corresponding to the historical reference peak. This represents the energy correction factor. For example, taking the statistical average as the measured peak of this block, the energy average of the measured peak... Where N is the number of scintillation crystal channels within the Block; taking the weighted value as the measurement peak of the Block as an example, the energy of the measurement peak is measured. ,in, The weighting factor represents the energy of the main peak position in each scintillation crystal channel.

[0112] Optionally, the energy correction factor generation module 820 can also be configured to find local maxima within a set energy range. For example, the energy range set for yttrium lutetium silicate scintillation crystal can be 280keV-340keV, and the energy range set for lanthanum bromide scintillation crystal can be 120keV-170keV. Within the set energy range, the local maxima point is required to be several times higher than the average value of several scintillation crystal channels on both sides, so as to ensure the statistical significance of the peak value.

[0113] Optionally, the energy correction factor generation module 820 can also be configured to extract the main peak using a multi-peak decomposition method. Other weak peaks may exist near the main peak. The candidate interval is decomposed using a Gaussian mixture model, and then the parameters of each Gaussian component are solved iteratively using the expectation-maximization algorithm to extract the mean value corresponding to the main peak.

[0114] Specifically, the time correction parameter generation module 830 is configured to constrain the single-event data through a time window and a single energy window to filter out a single-energy-window event dataset. The single-energy-window event dataset is then subjected to conformity processing to obtain conforming events. A time difference feature set is constructed based on the time-of-flight difference of each conforming event, and time correction parameters are generated using the time difference feature set. Taking lutetium yttrium silicate scintillation crystal as an example, its energy distribution has relatively fixed and known characteristics. Based on this, this application does not need to distinguish multiple energy ranges, but instead sets a single energy window (e.g., [250keV, 350keV], filtering out single events with an energy of 307keV), only filtering events within the main energy range for subsequent processing, thereby: 1. reducing data processing complexity and improving computational efficiency; 2. reducing statistical fluctuations caused by multi-energy-window division and improving the statistical stability of time differences; 3. improving the utilization rate of effective events under low count rate background radiation conditions.

[0115] Optionally, in one example of this application, the time correction parameter generation module 830 is configured to apply a time window to the acquired single-event data. and a single energy window Constraints are used to filter and obtain a single-window event dataset, denoted as... ,in, This represents the k-th single event. This represents the energy of the k-th single event. Represent the timestamp of the k-th single event; construct a candidate set of event pairs based on the single-window event dataset S. The temporal features, energy features, and spatial encoding of each event pair are extracted to form the input feature vector. ,in, This represents the spatial encoding of the corresponding detection unit, where the spatial encoding corresponds to spatial location information; the input feature vector is then input into the event pair discrimination model. ,in, This indicates the determination result of whether an event pair constitutes a valid match event, and outputs the corresponding response line information; for event pairs determined to be valid matches events... The time difference between two single events is calculated based on the response line information. And summarize them to form a time difference feature set for time correction. Based on the time difference feature set Construct a time deviation inversion model ,in, This represents an observation vector composed of a set of time difference features. This represents the time offset parameter corresponding to the scintillation crystal channel in each group; the time offset parameter is obtained by inversion by minimizing the error between the predicted time difference and the observed time difference. This is used to generate the time offset parameter for the scintillation crystal channels in each group. The detection unit includes blocks and photoelectric conversion devices, for example, a block and a SiPM array coupled together to form the main part of a detection unit. The time offset parameter... The optimal estimate is obtained by solving the model. This optimal estimate can be used as the time offset parameter. The two are numerically equivalent and correspond one-to-one with each scintillation crystal channel.

[0116] As an alternative example, the time correction parameter generation module 830 can also be configured to: compare the time difference feature set with the theoretical values ​​obtained from the database model, and assign a time correction parameter to the scintillation crystal channel in each group according to the comparison result. Specifically, the database model can be trained based on a large amount of previous datasets, which records theoretical values. The time difference feature set is compared with the set of theoretical values ​​in the database model to obtain a comparison result, and the time correction parameter is determined based on the comparison result.

[0117] Furthermore, at the application level, the correction device 800 also includes an energy correction module 840, configured to use the product of the original single-event energy value collected by each scintillation crystal channel in the group and the energy correction factor as the corrected energy value, which can be expressed by the formula: ,in, The original energy measurement value before correction. The corrected energy value. This is the energy correction factor. The group can be located based on the channel address included in a single event's data, and then the energy correction factor of that group can be used for energy correction.

[0118] In one example, to implement time correction, the correction device 800 further includes a time correction module 850, configured to subtract the acquired single-event timestamp from the time correction parameters to obtain the corrected single-event timestamp, which can be expressed by the formula: ,in, This is the single-event timestamp before correction. This is the corrected single-event timestamp. These are time correction parameters.

[0119] In addition, for the channels identified as abnormal, the average value of other channels in the same group can be used as its own energy correction factor, and the time offset can be obtained by interpolation of adjacent channels.

[0120] It is understood that any correction devices not fully described in this application can be referred to the correction methods described above, and due to space limitations, they will not be repeated here.

[0121] The calibration device provided in this application, firstly, overcomes the limitation of traditional PET system calibration relying on external sources by utilizing the natural decay of scintillation crystals for calibration, achieving passive calibration of the system's operating status; secondly, by automatically acquiring and processing data without manual intervention, it improves the device's autonomous management capability and operating efficiency, realizing automated calibration of the system's operating status. Compared to traditional external source calibration that relies on manual initiation, this system requires no user operation during operation, effectively reducing the risk of system performance degradation due to misoperation or calibration omissions; thirdly, by dynamically updating data from periodically acquired natural radiation events, it can reflect changes in the detector's operating status in real time, improving the timeliness of calibration parameters and helping to ensure the long-term consistency of image reconstruction quality, thus achieving continuous calibration of the system's operating status.

[0122] It should be understood that Figure 8 and Figure 9The apparatus and modules shown can be implemented in various ways. For example, in some embodiments, the apparatus and modules can be implemented in hardware, software, or a combination of both. The hardware portion can be implemented using dedicated logic; the software portion can be stored in memory and executed by a suitable instruction execution device, such as a microprocessor or dedicated-design hardware. Those skilled in the art will understand that the methods and apparatus described above can be implemented using computer-executable instructions and / or included in processor control code, for example, such code provided on a carrier medium such as a disk, CD, or DVD-ROM, a programmable memory such as read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The apparatus and modules described in this application can be implemented not only with hardware circuits such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field-programmable gate arrays, programmable logic devices, etc., but also with software, for example, executed by various types of processors, or with a combination of the aforementioned hardware circuits and software (e.g., firmware).

[0123] It should be noted that the above description of the modules is for convenience only and should not be construed as limiting this specification to the embodiments described. It is understood that those skilled in the art, after understanding the principle of the device, may arbitrarily combine the modules or construct subsystems connected to other modules without departing from this principle. For example, the modules may share a single storage module, or each module may have its own separate storage module. Such modifications are all within the scope of this specification.

[0124] Figure 10 This is a schematic diagram of a computer system used to implement the correction method in one embodiment of this application. (Refer to...) Figure 10 The computer system S00 may include a processing component S20, which further includes one or more processors, and memory resources represented by memory S22 for storing instructions, such as application programs, that can be executed by the processors of the processing component S20. The application programs stored in memory S22 may include one or more instructions, with each module corresponding to a set of instructions. Furthermore, the processing component S20 is configured to execute instructions to perform the aforementioned correction method.

[0125] The operations and / or methods described in the embodiments of this specification, implemented by a single processor, may also be implemented jointly or independently by multiple processors. For example, if, in this application specification, the processor of the processing device executes steps 100-300, it should be understood that steps 100-300 may also be executed jointly or independently by two different processors of the processing device (e.g., the first processor executes step 100, the second processor executes steps 200-300, or the first and second processors jointly execute steps 100-300).

[0126] The computer system S00 may further include: a power supply component S24 configured to perform power management of the computer system S00; a wired or wireless network interface S26 configured to connect the computer system S00 to a network; and an input / output (I / O) interface S28. The computer system S00 can operate on an operating system stored in memory S22, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, or similar.

[0127] In an exemplary embodiment, a computer-readable storage medium including instructions is also provided, such as a memory S22 including instructions, which can be executed by the processor of the computer system S00 to perform the above method. The storage medium can be a computer-readable storage medium, for example, a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0128] In an exemplary embodiment, a computer program product is also provided, the computer program product including instructions that can be executed by a processor of a computer system S00 to perform the above method.

[0129] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 11 As shown, Figure 11 This is an internal structural diagram of a computer device according to one embodiment of this application. The computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores user- and task-related data used in the aforementioned correction method. The network interface communicates with external terminals via a network connection. When the computer program is executed by the processor, it implements a correction method.

[0130] Those skilled in the art will understand that Figure 11 The 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.

[0131] Those skilled in the art will understand that all or part of the processes in 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 described above. 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.

[0132] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on its differences from other embodiments. In particular, hardware + program embodiments are basically similar to method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0133] It should be noted that the devices, electronic devices, servers, etc., described above according to the method embodiments may also include other implementation methods, and specific implementation methods can be referred to the description of the relevant method embodiments. Furthermore, new embodiments formed by the combination of features between various methods, devices, and server embodiments still fall within the scope of this application, and will not be elaborated upon here.

[0134] In the description of this specification, the references to "one embodiment," "an embodiment," and / or "some embodiments," "some embodiments," "other embodiments," "ideal embodiments," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative descriptions of the above terms do not necessarily refer to the same embodiment or example, and certain features, structures, or characteristics in one or more embodiments of this specification may be appropriately combined.

[0135] 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.

[0136] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

[0137] The basic concepts have been described herein. It is obvious that the detailed disclosure above is merely illustrative and does not constitute a limitation of this specification. Although not explicitly stated herein, various modifications, improvements, and corrections may be made to this specification by those skilled in the art. Such modifications, improvements, and corrections are suggested in this specification and therefore remain within the spirit and scope of the exemplary embodiments described herein.

[0138] Furthermore, those skilled in the art will understand that various aspects of this specification can be described and illustrated in several patentable ways or situations, including any new and useful combination of processes, machines, products, or substances, or any new and useful improvements thereof. Accordingly, various aspects of this specification can be implemented entirely by hardware, entirely by software (including firmware, resident software, microcode, etc.), or by a combination of hardware and software. All of the above hardware or software may be referred to as a “data block,” “module,” “engine,” “module,” “component,” or “system.” Furthermore, various aspects of this specification may be represented as a computer product located on one or more computer-readable media, including computer-readable program code.

[0139] Computer storage media may contain a propagated data signal containing computer program code, for example, on baseband or as part of a carrier wave. This propagated signal may take various forms, including electromagnetic, optical, and suitable combinations thereof. Computer storage media can be any computer-readable medium other than a computer-readable storage medium, which can be connected to an instruction execution system, apparatus, or device to enable communication, propagation, or transmission of a program for use. The program code located on the computer storage medium can be propagated through any suitable medium, including radio, cable, fiber optic cable, RF, or similar media, or any combination of the above media.

[0140] The computer program code required for the operation of each part of this manual can be written in any one or more programming languages, including object-oriented programming languages ​​such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB.NET, Python, etc.; conventional procedural programming languages ​​such as C, Visual Basic, Fortran 3003, Perl, COBOL 3002, PHP, ABAP; dynamic programming languages ​​such as Python, Ruby, and Groovy; or other programming languages. This program code can run entirely on the user's computer, or as a standalone software package on the user's computer, or partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter case, the remote computer can be connected to the user's computer through any network, such as a local area network (LAN) or wide area network (WAN), or connected to an external computer (e.g., via the Internet), or in a cloud computing environment, or used as a service such as Software as a Service (SaaS).

[0141] Furthermore, unless expressly stated in the claims, the order of processing elements and sequences, the use of numbers and letters, or other names described in this specification are not intended to limit the order of the processes and methods described herein. Although various examples have been discussed in the foregoing disclosure of some embodiments of the invention that are currently considered useful, it should be understood that such details are for illustrative purposes only, and the appended claims are not limited to the disclosed embodiments; rather, the claims are intended to cover all modifications and equivalent combinations that conform to the spirit and scope of the embodiments described herein. For example, while the system components described above can be implemented using hardware devices, they can also be implemented solely using software solutions, such as installing the described system on existing servers or mobile devices.

[0142] Similarly, it should be noted that, in order to simplify the description disclosed herein and thus aid in the understanding of one or more embodiments of the invention, the foregoing description of embodiments in this specification may sometimes combine multiple features into a single embodiment, drawing, or description thereof. However, this method of disclosure does not imply that the subject matter of this specification requires more features than those mentioned in the claims. In fact, the embodiments contain fewer features than all the features of a single embodiment disclosed above.

[0143] In some embodiments, numbers describing the quantity of components and attributes are used. It should be understood that such numbers used in the description of embodiments are modified in some examples with the terms "approximately," "approximately," or "generally." Unless otherwise stated, "approximately," "approximately," or "generally" indicates that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may be changed depending on the characteristics required by individual embodiments. In some embodiments, numerical parameters should take into account specified significant digits and employ a general method of digit reservation. Although the numerical ranges and parameters used to confirm their breadth of range in some embodiments of this specification are approximate values, in specific embodiments, such values ​​are set as precisely as feasible.

[0144] For each patent, patent application, patent application publication, and other material such as articles, books, specifications, publications, and documents referenced in this specification, the entire contents of which are incorporated herein by reference. This excludes historical application documents that are inconsistent with or conflict with the content of this specification, as well as documents that limit the broadest scope of the claims in this specification (currently or subsequently appended to this specification). It should be noted that in the event of any inconsistency or conflict between the descriptions, definitions, and / or terminology used in the supplementary materials to this specification and the content of this specification, the descriptions, definitions, and / or terminology used in this specification shall prevail.

[0145] Finally, it should be understood that the embodiments described in this specification are merely illustrative of the principles of the embodiments described herein. Other variations may also fall within the scope of this specification. Therefore, alternative configurations of the embodiments described herein are intended to be illustrative rather than limiting, and should be considered consistent with the teachings of this specification. Accordingly, the embodiments described herein are not limited to those explicitly introduced and described herein.

Claims

1. A calibration method, characterized in that, include: Automatically acquire single-event data formed by the background radiation of the scintillation crystal in the detector; Based on the single-event data, the energy spectra of several scintillation crystal channels are statistically analyzed. The main peaks of the energy spectra are extracted and the main peak positions of each scintillation crystal channel are obtained. The main peak positions of the scintillation crystal channels in the same group are processed to obtain the measured main peaks in the corresponding group. The energy correction factor of the group is obtained based on the measured main peaks. The single-event data is constrained by time windows and single energy windows to filter out single-energy window event datasets. The single-energy window event datasets are then subjected to conformity processing to obtain conforming events. A time difference feature set is constructed based on the flight time difference of each conforming event, and time correction parameters are generated using the time difference feature set.

2. The correction method according to claim 1, characterized in that, The scintillation crystal includes lutetium-based scintillation crystals or lanthanum-based scintillation crystals.

3. The correction method according to claim 1, characterized in that, The process of obtaining the measured main peak within the corresponding group by processing the main peak position of the scintillation crystal channel within the same group includes: The main peak positions of multiple scintillation crystals within the same group are statistically processed, and the statistical average or weighted value of all main peak positions within the same group is used as the measured main peak of that group.

4. The correction method according to claim 3, characterized in that, The energy correction factor for this group is obtained based on the measured main peak, including: By comparing the measured main peak of this group with the historical reference main peak, the corresponding energy correction factor of this group is calculated.

5. The correction method according to claim 4, characterized in that, The energy correction factors corresponding to this group are calculated, including: Energy correction factor is or ,in This indicates the energy value corresponding to the historical reference peak. This indicates the measurement of the energy of the main peak. This indicates the average energy value of the measured main peak.

6. The correction method according to claim 1, characterized in that, After obtaining the energy correction factors for this set, the correction method further includes: The product of the original single-event energy value collected by each scintillation crystal channel in the group and the energy correction factor is used as the corrected single-event energy value.

7. The correction method according to claim 1, characterized in that, The process of performing conformance processing on the single-window event dataset to obtain conformance events includes: A candidate set of event pairs is constructed based on a single-energy window event dataset, and the temporal features, energy features, and spatial encoding of the probe unit of each event pair are extracted to form an input feature vector. The input feature vector is fed into the event pair discrimination model to obtain the discrimination result of valid matching events. For event pairs that are determined to be valid matching events, the corresponding response line information is output.

8. The correction method according to claim 7, characterized in that, The discriminant model is: ,in, This indicates the result of the judgment that the event constitutes a valid matching event. This represents the input feature vector.

9. The correction method according to claim 7, characterized in that, The construction of the time difference feature set based on the time difference of flight for each matching event includes: For event pairs that are determined to be valid matching events, the flight time difference between the two individual events is calculated based on the response line information, and the results are summarized to form a time difference feature set for time correction.

10. The correction method according to claim 9, characterized in that, The process of generating time correction parameters using the time difference feature set includes: Based on the time difference feature set, a time deviation inversion model is constructed to form the correspondence between the observation vector composed of the time difference feature set and the time offset parameters of each group. By minimizing the error between the predicted time difference and the observed time difference, the time offset parameters are solved by inversion to generate time correction parameters for each group.

11. The correction method according to claim 10, characterized in that, The inversion model is expressed as follows: ,in, This represents an observation vector composed of a set of time difference features. This represents the time offset parameter for each group.

12. The correction method according to claim 9, characterized in that, The process of generating time correction parameters using the time difference feature set includes: Based on the time difference feature set, it is compared with the theoretical value obtained from the database model, and a time correction parameter is assigned to the scintillation crystal channel in each group according to the comparison result.

13. The correction method according to claim 1, characterized in that, After generating the time correction parameter, the correction method further includes: The original single-event timestamp collected is subtracted from the time correction parameter to obtain the corrected single-event timestamp.

14. The correction method according to claim 1, characterized in that, The automatic acquisition of single-event data formed by the background radiation of the scintillation crystal in the detector includes: The single event count rate in each scintillation crystal channel is counted and recorded. If, after the acquisition is completed, the single event count rate of a certain scintillation crystal channel is less than the preset value, then the scintillation crystal channel is marked as an abnormal channel.

15. The correction method according to claim 14, characterized in that, The correction method further includes: For the abnormal channel, the average value of other channels in the same group is used as its own energy correction factor, and the time offset is obtained by interpolation of adjacent channels.

16. A calibration device, characterized in that, include: The acquisition module is configured to automatically acquire single-event data formed by the background radiation of the scintillation crystal in the detector; The energy correction factor generation module is configured to statistically analyze the energy spectra of several scintillation crystal channels based on the single-event data, extract the main peak from the energy spectra and obtain the main peak position of each scintillation crystal channel, process the main peak positions of scintillation crystal channels in the same group to obtain the measured main peak in the corresponding group, and obtain the energy correction factor of the group based on the measured main peak. The time correction parameter generation module is configured to constrain the single event data through a time window and a single energy window to filter out a single energy window event dataset, perform conformity processing on the single energy window event dataset to obtain conforming events, construct a time difference feature set based on the flight time difference of each conforming event, and use the time difference feature set to generate time correction parameters.

17. The calibration device according to claim 16, characterized in that, The scintillation crystal includes lutetium-based scintillation crystals or lanthanum-based scintillation crystals.

18. The calibration device according to claim 16, characterized in that, The energy correction factor generation module is configured to perform statistical processing on the main peak positions of multiple scintillation crystals in the same group, and use the statistical average or weighted value of all main peak positions in the same group as the measured main peak of that group.

19. The calibration device according to claim 18, characterized in that, The energy correction factor generation module is configured to compare the measured main peak of the group with the historical reference main peak and calculate the corresponding energy correction factor for the group.

20. The calibration device according to claim 19, characterized in that, The energy correction factor generation module is configured to set the energy correction factor to... or ,in This indicates the energy value corresponding to the historical reference peak. This indicates the measurement of the energy of the main peak. This indicates the average energy value of the measured main peak.

21. The calibration device according to claim 16, characterized in that, It also includes an energy correction module, configured to use the product of the original single-event energy value collected by each scintillation crystal channel in the group and the energy correction factor as the corrected single-event energy value.

22. The calibration device according to claim 16, characterized in that, The time correction parameter generation module is configured to: construct a candidate set of event pairs based on a single-energy window event dataset, and extract the time features, energy features, and spatial encoding of the detection unit for each event pair to form an input feature vector; The input feature vector is input into the event pair discrimination model to obtain the discrimination result of valid matching events, and the corresponding response line information is output for the event pairs that are determined to be valid matching events.

23. The calibration device according to claim 22, characterized in that, The discriminant model is: ,in, This indicates the result of the judgment that the event constitutes a valid matching event. This represents the input feature vector.

24. The calibration device according to claim 22, characterized in that, The time correction parameter generation module is configured to: for event pairs that are determined to be valid matching events, calculate the flight time difference between two single events based on the response line information, and summarize them to form a time difference feature set for time correction.

25. The calibration device according to claim 24, characterized in that, The time correction parameter generation module is configured to: construct a time deviation inversion model based on the time difference feature set, form a correspondence between the observation vector composed of the time difference feature set and the time offset parameters of each group; and solve the time offset parameters by minimizing the error between the predicted time difference and the observed time difference to generate the time correction parameters of each group.

26. The calibration device according to claim 25, characterized in that, The inversion model is expressed as follows: ,in, This represents an observation vector composed of a set of time difference features. This represents the time offset parameter for each group.

27. The calibration device according to claim 24, characterized in that, The time correction parameter generation module is configured to: compare the time difference feature set with the theoretical value obtained from the database model, and assign a time correction parameter to the scintillation crystal channel in each group according to the comparison result.

28. The calibration device according to claim 16, characterized in that, Also includes: The time correction module is configured to subtract the original single-event timestamp collected from the time correction parameters to obtain the corrected single-event timestamp.

29. The calibration device according to claim 16, characterized in that, The acquisition module is configured to count and record the single event count rate in each scintillation crystal channel. If, after acquisition, the single event count rate of a certain scintillation crystal channel is less than a preset value, then the scintillation crystal channel is marked as an abnormal channel.

30. The calibration device according to claim 29, characterized in that, For the abnormal channel, the energy correction module is configured to use the average value of other channels in the same group as its own energy correction factor, and the time correction module is configured to use the interpolation of adjacent channels to obtain its own time offset.

31. A computer storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the correction method according to any one of claims 1 to 15.

32. A computer program product, characterized in that, It includes a computer program or instructions, characterized in that, when the computer program or instructions are executed by a processor, they implement the steps of the correction method according to any one of claims 1 to 15.

33. A digital PET system, characterized in that, Includes the calibration device as described in any one of claims 16-30.

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