Processing method and device of flicker pulse, equipment and storage medium

Abstract

The application discloses a method and device for processing a flickering pulse, an equipment and a storage medium. The method comprises the following steps: obtaining a target function model corresponding to the flickering pulse, wherein the target function model comprises one or more to-be-determined parameters; converting the target function model to obtain a first corresponding relationship between variables of the target function model and one or more intermediate parameters, and a second corresponding relationship between the intermediate parameters and the to-be-determined parameters; digitally sampling the flickering pulse to obtain sampling data; determining the intermediate parameters based on the first corresponding relationship by taking the sampling data as variables; and transmitting the intermediate parameters and the second corresponding relationship to an external device, so that the external device determines the to-be-determined parameters based on the intermediate parameters and by taking the second corresponding relationship. The application can process original sampling data to realize data compression and then transmission, can reduce the load of a data transmission network, and can reduce the consumption of the computing resources of a server.

Description

Technical Field

[0001] This application relates to the field of data processing, and in particular to a method, apparatus, device, and storage medium for processing flicker pulses. Background Technology

[0002] In positron emission tomography (PET) applications, gamma rays are converted into visible light signals by a scintillation crystal. These visible light signals are further converted into scintillation pulse signals by a photoelectric conversion device. By sampling and processing these scintillation pulse signals, a series of application images or energy spectrum information can be obtained. Among these processes, scintillation pulse sampling and processing of the sampled data are two crucial steps. High-quality sampling provides accurate raw data for subsequent processing, while fast, efficient, and stable processing ensures excellent final results.

[0003] Currently, after sampling the scintillation pulses, the sampled data is packaged and sent from the detection device to a processing device, such as a server, via a network. The server then processes the received sampled data to obtain relevant energy information. However, the amount of sampled data is generally very large. For example, during a PET scan, the detection device continuously detects a large number of scintillation pulses and outputs sampled data. Although compression methods are used during data transmission, a significant amount of bandwidth is still required for data transmission. The server also needs to consume substantial computing resources for output processing after receiving the sampled data. This inevitably increases the network transmission load and impacts the server's processor's computing power. Summary of the Invention

[0004] The technical problem to be solved by the embodiments of this application is how to reduce the network transmission load of data transmission during pulse sampling and reduce the consumption of server computing resources.

[0005] To address the aforementioned problems, this application discloses a method, apparatus, device, and storage medium for processing flicker pulses.

[0006] According to a first aspect of this application, a method for processing flicker pulses is provided. The method includes: acquiring a target function model corresponding to the flicker pulse, the target function model including one or more parameters to be determined; transforming the target function model to obtain a first correspondence between variables of the target function model and one or more intermediate parameters, and a second correspondence between the intermediate parameters and the parameters to be determined; digitally sampling the flicker pulse to acquire sampled data; using the sampled data as the variables and determining the intermediate parameters based on the first correspondence; and transmitting the intermediate parameters and the second correspondence to an external device, so that the external device can determine the parameters to be determined based on the intermediate parameters and the second correspondence.

[0007] According to some embodiments of this application, obtaining the target function model corresponding to the flashing pulse includes: obtaining the original function model, wherein the original function model conforms to a Gaussian function; and performing normalization processing on the original function model to determine the target function model.

[0008] According to some embodiments of this application, determining the first correspondence and the second correspondence includes: performing mathematical processing operations on the objective function model to determine the correspondence; wherein the mathematical processing operations include at least taking the logarithm, parameter transformation, differentiation, and matrix transformation.

[0009] According to some embodiments of this application, the digital sampling of the flicker pulse includes performing ADC sampling or multi-threshold sampling on the flicker pulse.

[0010] According to some embodiments of this application, when performing multi-threshold sampling, the acquisition of sampling data includes: presetting multiple thresholds; for each threshold, comparing the flashing pulse with the threshold to determine the state change signal when the flashing pulse crosses the threshold; performing digital time sampling on the state change signal to obtain the corresponding threshold-time pair; and specifying multiple threshold-time pairs to constitute the sampling data.

[0011] According to some embodiments of this application, the intervals between the plurality of thresholds are equal.

[0012] According to some embodiments of this application, determining the intermediate parameters includes: performing a baseline transformation on the sampled data to obtain transformed data; designating the transformed data as the variable; and solving for the intermediate parameters using the first correspondence relationship.

[0013] According to a second aspect of this application, a method for processing a flickering pulse is provided. The method includes: obtaining a target function model corresponding to the flickering pulse, the target function model including one or more parameters to be determined; obtaining a first correspondence between variables of the target function model and one or more intermediate parameters; digitally sampling the flickering pulse to obtain sampled data; using the sampled data as the variables and determining the intermediate parameters based on the first correspondence; and transmitting the intermediate parameters to an external device so that the external device can determine the parameters to be determined based on the intermediate parameters and using a second correspondence between the intermediate parameters and the parameters to be determined.

[0014] According to some embodiments of this application, obtaining the target function model corresponding to the flashing pulse includes: obtaining the original function model, wherein the original function model conforms to a Gaussian function; and performing normalization processing on the original function model to determine the target function model.

[0015] According to some embodiments of this application, the first correspondence and the second correspondence are determined based on the following operations, including: performing mathematical processing operations on the objective function model to determine the correspondence; wherein the mathematical processing operations include at least taking the logarithm, parameter transformation, differentiation, and matrix transformation.

[0016] According to some embodiments of this application, the digital sampling of the flicker pulse includes: performing ADC sampling or multi-threshold sampling on the flicker pulse.

[0017] According to some embodiments of this application, when performing multi-threshold sampling, the acquisition of sampling data includes: presetting multiple thresholds; for each threshold, comparing the flashing pulse with the threshold to determine the state change signal when the flashing pulse crosses the threshold; performing digital time sampling on the state change signal to obtain the corresponding threshold-time pair; and specifying multiple threshold-time pairs to constitute the sampling data.

[0018] According to some embodiments of this application, the intervals between the plurality of thresholds are equal.

[0019] According to some embodiments of this application, determining the intermediate parameters includes: performing a baseline transformation on the sampled data to obtain transformed data; designating the transformed data as the variable; and solving for the intermediate parameters using the first correspondence relationship.

[0020] According to a third aspect of this application, a processing apparatus for flicker pulses is provided. The apparatus includes: a first acquisition module configured to acquire a target function model corresponding to the flicker pulse, the target function model including one or more parameters to be determined; a conversion module configured to convert the target function model to acquire a first correspondence between variables of the target function model and one or more intermediate parameters, and a second correspondence between the intermediate parameters and the parameters to be determined; a first sampling module configured to digitally sample the flicker pulse to acquire sampled data; a first determination module configured to use the sampled data as the variables and determine the intermediate parameters based on the first correspondence; and a first transmission module configured to transmit the intermediate parameters and the second correspondence to an external device, so that the external device can determine the parameters to be determined based on the intermediate parameters and the second correspondence.

[0021] According to some embodiments of this application, in order to obtain the target function model corresponding to the flashing pulse, the first acquisition module is configured to: acquire the original function model, wherein the original function model conforms to a Gaussian function; perform normalization processing on the original function model to determine the target function model.

[0022] According to some embodiments of this application, in order to obtain the first correspondence and the second correspondence, the conversion module is configured to perform mathematical processing operations on the objective function model to determine the correspondence; wherein, the mathematical processing operations include at least taking the logarithm, parameter transformation, differentiation, and matrix transformation.

[0023] According to some embodiments of this application, in order to digitally sample the flicker pulse, the first sampling module is positioned as follows: performing ADC sampling or multi-threshold sampling on the flicker pulse.

[0024] According to some embodiments of this application, when performing multi-threshold sampling, in order to obtain sampling data, the first sampling module is configured to: preset multiple thresholds; for each threshold, compare the flashing pulse with the threshold to determine the state change signal when the flashing pulse crosses the threshold; perform digital time sampling on the state change signal to obtain the corresponding threshold-time pair; and specify multiple threshold-time pairs to constitute the sampling data.

[0025] According to some embodiments of this application, the intervals between the plurality of thresholds are equal.

[0026] According to some embodiments of this application, in order to determine the intermediate parameters, the first determining module is configured to: perform a baseline transformation on the sampled data to obtain transformed data; designate the transformed data as the variable; and solve for the first intermediate parameters using the first correspondence relationship.

[0027] According to a fourth aspect of this application, a processing apparatus for flicker pulses is provided. The apparatus includes: a second acquisition module configured to acquire an objective function model corresponding to the flicker pulse, the objective function model including one or more parameters to be determined; a receiving module configured to acquire a first correspondence between variables of the objective function model and one or more intermediate parameters; a second sampling module configured to digitally sample the flicker pulse to acquire sampled data; a second determining module configured to use the sampled data as the variables and determine the intermediate parameters based on the first correspondence; and a second transmission module configured to transmit the intermediate parameters to an external device, so that the external device can determine the parameters to be determined based on the intermediate parameters and using the second correspondence between the intermediate parameters and the parameters to be determined.

[0028] According to some embodiments of this application, in order to obtain the target function model corresponding to the flashing pulse, the second acquisition module is configured to: acquire the original function model, wherein the original function model conforms to a Gaussian function; perform normalization processing on the original function model to determine the target function model.

[0029] According to some embodiments of this application, the first correspondence and the second correspondence are determined based on the following operations, including: performing mathematical processing operations on the objective function model to determine the correspondence; wherein the mathematical processing operations include at least taking the logarithm, parameter transformation, differentiation, and matrix transformation.

[0030] According to some embodiments of this application, in order to digitally sample the flicker pulse, the second sampling module is configured to perform ADC sampling or multi-threshold sampling on the flicker pulse.

[0031] According to some embodiments of this application, when performing multi-threshold sampling, in order to obtain sampling data, the second sampling module is configured to: preset multiple thresholds; for each threshold, compare the flashing pulse with the threshold to determine the state change signal when the flashing pulse crosses the threshold; perform digital time sampling on the state change signal to obtain the corresponding threshold-time pair; and specify multiple threshold-time pairs to constitute the sampling data.

[0032] According to some embodiments of this application, the intervals between the plurality of thresholds are equal.

[0033] According to some embodiments of this application, in order to determine one or more intermediate parameters, the second determining module is configured to: perform a baseline transformation on the sampled data to obtain transformed data; designate the transformed data as the variable; and solve for the intermediate parameters using the first correspondence.

[0034] According to a fifth aspect of this application, a processing apparatus is provided. The processing apparatus includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, performs the steps of the method described above.

[0035] According to a sixth aspect of this application, a computer-readable storage medium is provided. The storage medium stores a computer program that, when executed by a processor, implements the steps of the method described above.

[0036] The flicker pulse processing method disclosed in this application can process the original sampled data to compress the data before transmission, which can reduce the load on the data transmission network and reduce the consumption of server computing resources. Attached Figure Description

[0037] This application will be further described by way of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting; in these embodiments, the same reference numerals denote the same structures, wherein:

[0038] Figure 1 This is an exemplary flowchart of a method for processing flashing pulses according to some embodiments of this application;

[0039] Figure 2 This is an exemplary flowchart of another method for processing flashing pulses according to some embodiments of this application;

[0040] Figure 3 This is an exemplary schematic diagram of a flashing pulse waveform shown according to some embodiments of this application;

[0041] Figure 4 This is an exemplary schematic diagram of sampling a flash pulse according to some embodiments of this application;

[0042] Figure 5 This is an exemplary schematic diagram of another sampling of a flashing pulse according to some embodiments of this application;

[0043] Figure 6 This is an exemplary block diagram of a data processing system for scintillation pulse processing according to some embodiments of this application;

[0044] Figure 7 This is an exemplary block diagram of another data processing system for scintillation pulse sampling, according to some embodiments of this application;

[0045] Figure 8 This is an exemplary functional block diagram of a data processing system for flash pulse processing according to some embodiments of this application. Detailed Implementation

[0046] To make the above-mentioned objectives, features, and advantages of this application more apparent and understandable, 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.

[0047] It should be noted that when a component is said to be "fixed to" another component, it can be directly fixed to the other component or there may be an intervening component. When a component is said to be "connected to" another component, it can be directly connected to the other component or there may be an intervening component. The terms "vertical," "horizontal," "left," "right," and similar expressions used in this document are for illustrative purposes only.

[0048] 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 the 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.

[0049] 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.

[0050] Figure 1 This is an exemplary flowchart of a flicker pulse processing method according to some embodiments of this application. In some embodiments, the flicker pulse processing method 100 can be executed by a first data processing system 600. For example, the flicker pulse processing method 100 can be stored in a storage device (such as the built-in storage unit of the first data processing system 600 or an external storage device) in the form of a program or instructions, which, when executed, can implement the flicker pulse processing method 100. Figure 1 As shown, the flashing pulse processing method 100 may include the following steps.

[0051] Step 110: Obtain the objective function model corresponding to the flashing pulse.

[0052] In some embodiments, the scintillation pulses can be acquired by a radiation detection device. The radiation detection device may include a semiconductor detector, such as a PN junction semiconductor detector, a lithium-drift semiconductor detector, a high-purity germanium semiconductor detector, a germanium-lithium semiconductor detector, a silicon-lithium semiconductor detector, a silicon microstrip semiconductor detector, a metal surface barrier semiconductor detector, etc. The radiation detection device may also include a scintillation detector. This scintillation detector may include a scintillation crystal and a photoelectric conversion device coupled together. The scintillation crystal (e.g., BGO, PWO, LYSO:Ce, GAGG:Ce, NaI:TI, CsI:TI, LaBr3:Ce, BaF2, etc.) is used to convert detected high-energy rays (such as gamma rays, neutron rays, etc.) into visible light signals, and the photoelectric conversion device (e.g., a photomultiplier tube PMT, a silicon photomultiplier tube SiPM, etc.) is used to convert the visible light signals into electrical signals, which are output as scintillation pulses through electronic devices connected to the photoelectric conversion device.

[0053] In some embodiments, the output flicker pulse can be shaped by a shaping circuit. This shaping circuit transforms the waveform of the flicker pulse to make it highly approximate the function model of a Gaussian function. For example, the shaping circuit may include a pre-filter amplifier circuit incorporating multiple stages of Gaussian shaping circuitry, such as more than four stages. After multiple Gaussian shaping processes, the waveform of the flicker pulse can approximate the shape described by the Gaussian function. Figure 3 As shown, Figure 3 This is an exemplary schematic diagram of a flicker pulse waveform according to some embodiments of this application. The shape of the flicker pulse 300 conforms to a symmetrical bell shape described by a Gaussian function. It includes a rising edge where the pulse amplitude increases over time, and a falling edge where the pulse amplitude decreases over time after reaching its peak. The functional model describing the shape of the flicker pulse 300 can be a Gaussian function model as shown in Equation 1 below:

[0054]

[0055] Where y represents the amplitude of the flicker pulse, x represents the time corresponding to the amplitude of the flicker pulse, a represents the maximum amplitude of the flicker pulse (i.e., the peak value of the flicker pulse), b represents the axis of symmetry of the flicker pulse (expressed in time), and c represents the standard deviation (i.e., the width of the Gaussian RMS value). In some embodiments, Equation 1 above may also be referred to as the original function model of the flashing pulse.

[0056] It is understandable that the amplitude of a flicker pulse can be determined based on its form. The pulse signal can be an electrical pulse, an acoustic pulse, a thermal pulse, or a pressure wave, etc. For example, when the pulse signal is an electrical pulse, its corresponding characteristics can be voltage, current, and energy. Therefore, the amplitude of the flicker pulse can be voltage, current, or energy. When the pulse signal is an acoustic pulse, its corresponding characteristic can be sound intensity. Therefore, the amplitude of the flicker pulse can be sound intensity. When the pulse signal is a pressure wave, its corresponding characteristic can be pressure. Therefore, the amplitude of the flicker pulse can be pressure. And so on, without further elaboration. Furthermore, the flicker pulse signal in this application can be extended to a continuous signal; generally, it is sufficient to consider a continuous signal as a pulse signal arranged according to a certain period, and this application does not impose specific limitations.

[0057] In some embodiments, the original function model of the scintillation pulse can be normalized to determine the target function model. For example, since horizontally shifting the scintillation pulse does not cause a change in energy information, for Equation 1, let X = xb, Y = y, and shift the axis of symmetry of the scintillation pulse to the Y-axis. Then Equation 1 can be transformed into Equation 2 as shown below:

[0058]

[0059] Where Y represents the normalized amplitude of the flicker pulse, and X represents the normalized time corresponding to the normalized amplitude of the flicker pulse. In some embodiments, Equation 2 can be determined as the objective function model corresponding to the flicker pulse, and a and c can be one or more parameters to be determined included in the objective function model.

[0060] Step 120: Transform the objective function model to obtain the correspondence between the variables of the objective function model and one or more intermediate parameters.

[0061] In some embodiments, the variables of the objective function model can be X and Y as shown in Equation 2 above. X is the independent variable of the objective function model, and Y is the dependent variable of the objective function model. The objective function model can be subjected to data processing operations to determine the correspondence. The mathematical processing operations may include at least taking the logarithm, parameter transformation, differentiation, and matrix transformation.

[0062] For example, Equation 2, which describes the objective function model, can be taken as its logarithm to obtain Equation 3 as shown below:

[0063]

[0064] By changing the parameters in Equation 3, let Z = lnY, k0 = lna, Equation 3 can then be transformed into Equation 4 as shown below:

[0065] Z = k0 + k2 * X 2 (4)

[0066] To minimize the error between the indicated curve and the waveform of the flashing pulse after one or more parameters of the objective function model are determined, that is, to minimize the error between Z-(k0+k2*X) and the waveform of the flashing pulse. 2 The value of ) is minimized. Let R = Z - (k0 + k2 * X) 2 ), then R 2 =[Z-(k0+k2*X)] 2 )] 2 The variables in the objective function model can be derived from sampled data obtained by sampling the flicker pulses. For example, the amplitude of the flicker pulse at a certain moment (or sampling moment) can be obtained. Exemplary sampled data can be obtained using (x... i ,y i Let ) represent i = 1, 2, 3, ..., n. Where x i Indicates the sampling time, y i Indicates at sampling time x i The amplitude corresponding to the flash pulse. n represents the number of sampled data sets, or the number of sampling times. Similarly, for (x... i ,y i ) Execution time normalization, let X i =x i -b, Y i =y i Substituting these values ​​into the error calculation formula above, we can obtain Equation 5 as shown below:

[0067]

[0068] It can be known that when R 2 The closer F is to 0, the smaller the error. Let F = R 2 =0, and by differentiating with respect to k0 and k2 respectively, we can obtain equations 6 and 7 as shown below:

[0069]

[0070]

[0071] By rearranging equations 6 and 7 above, we can obtain equations 8 and 9 as shown below:

[0072]

[0073]

[0074] Performing matrix transformations on equations 8 and 9 above, we obtain equation 10 as shown below:

[0075]

[0076] make If KK, RR, QQ, and YY are specified as one or more intermediate parameters, then the above relationship can be determined as the first correspondence between the one or more intermediate parameters and the variables of the objective function model.

[0077] Based on the data specified above, Equation 10 can be transformed into Equation 11 as shown below:

[0078]

[0079] Performing matrix operations on Equation 11 yields Equations 12 and 13 as shown below:

[0080] n*k0+KK*k2=YY(12)

[0081] KK*k0+RR*k2=QQ(13)

[0082] Solving the system of equations formed by equations 12 and 13 yields equations 14 and 15 as shown below:

[0083]

[0084]

[0085] And k0 = lna, The second correspondence between the one or more intermediate parameters and the one or more parameters to be determined can be shown in Equations 16 and 17 below:

[0086]

[0087]

[0088] Step 130: Digitally sample the flickering pulse to obtain sampled data.

[0089] In some embodiments, the digital sampling may include ADC sampling (or oscilloscope sampling). An exemplary ADC sampling method samples the flicker pulses at regular time intervals according to a sampling rate. A higher sampling rate results in a shorter time interval and more sampled data. For example, a sampling rate of 1 GS / s represents a time interval of 1 ns, and a sampling rate of 2.5 GS / s represents a time interval of 0.4 ns. Figure 4An exemplary schematic diagram of sampling a flash pulse according to some embodiments of this application is shown. This sampling is an ADC sampling. For ease of illustration, two sampling moments are used in the example description. Figure 4 As shown, the flicker pulse is sampled at sampling time t1 to obtain the amplitude A1 of the flicker pulse at t1. Similarly, the flicker pulse is sampled at sampling time t2 to obtain the amplitude A2 of the flicker pulse at t2. Therefore, assuming there are m sampling times, the sampled data obtained after ADC sampling can be expressed as (t... m A m ) represents. Where, t m Indicates the sampling time, A m Indicates at t m The amplitude of the flickering pulse is given, where m represents the number of samples, determined based on the sampling rate.

[0090] In some embodiments, the digital sampling may include multi-threshold sampling. When using multi-threshold sampling, multiple thresholds can be preset, and the flash pulse is compared with the preset multiple thresholds to obtain the time when the flash pulse crosses the threshold, and a threshold-time pair is formed with the corresponding threshold to form the sampling data. Figure 5 An exemplary schematic diagram of another sampling of a flicker pulse according to some embodiments of this application is shown. This sampling is multi-threshold sampling. For ease of illustration, two thresholds are used in the example description. The device for performing multi-threshold sampling may include a comparator and a time-to-time converter. The comparator may be used to compare the flicker pulse with a threshold, outputting a state change signal when the flicker pulse crosses the threshold. The time-to-time converter may be used to digitize the state change signal output by the comparator to obtain the time when the flicker pulse crosses the threshold. The resulting threshold-time pair constitutes the sampled data. Figure 5As shown, the amplitude of the flicker pulse gradually increases over time. At this time, the comparator compares the flicker pulse with threshold A3. When the flicker pulse crosses threshold A3 from bottom to top, the comparator generates a state change signal. The time-to-digital converter digitizes this state change information to obtain the corresponding transition time t3. Subsequently, the amplitude of the flicker pulse continues to increase. The comparator compares the flicker pulse with threshold A4. When the flicker pulse crosses threshold A4 from bottom to top, the comparator generates another state change signal. The time-to-digital converter digitizes this state change information to obtain the corresponding transition time t4. After reaching its peak, the flicker pulse gradually decreases over time. At this time, the comparator continues to compare the flicker pulse with threshold A4. When the flicker pulse crosses threshold A4 from top to bottom, the comparator generates a state change signal. The time-to-digital converter digitizes this state change information to obtain the corresponding transition time t5. If the amplitude of the flash pulse continues to decrease, the comparator will generate a state change signal when the flash pulse crosses the threshold A3 from top to bottom. The time-to-digital converter can digitize and sample this state change signal to obtain the corresponding transition time t6. This completes the entire sampling process. In multi-threshold sampling, one threshold can correspond to two threshold-time pairs. When the number of thresholds set is n, sampling data containing 2n threshold-time pairs will be obtained.

[0091] In some embodiments, the device implementing the scintillation pulse sampling process may also include a scintillation pulse acquisition circuit board. The comparator and time-to-digital converter mentioned above can be integrated into the scintillation pulse acquisition circuit board. The scintillation pulse acquisition circuit board may also include other components, such as a digital-to-analog converter (DAC) for setting a threshold, and a chip (e.g., an FPGA chip, where the time-to-digital converter can be implemented using the carry chain within the FPGA) for providing logic resources for the time-to-digital converter. Therefore, the scintillation pulse acquisition circuit board can also be referred to as a chip board. These components can be electrically connected on the scintillation pulse acquisition circuit board to achieve data transmission.

[0092] It should be understood that in actual sampling, the pulse waveform is not as... Figure 4 or Figure 5 Instead of the smoothness shown, there will be more fluctuations, which will actually manifest as... Figure 4 or Figure 5 The waveform shown fluctuates upwards or downwards within its upper and lower range. Figure 4 or Figure 5The smoothed waveform shown is for illustrative purposes. Therefore, in actual sampling, the waveform may cross the same threshold multiple times within a very short period of time at the rising or falling edge. In actual sampling, the average time of crossing the threshold multiple times within a certain time window or time period can be used as the time of crossing the threshold. This is something that can be easily implemented by those skilled in the art based on the teachings of this application, and will not be elaborated here.

[0093] In some embodiments, the types of preset thresholds for implementing multi-threshold sampling can be determined based on the manifestation of the flicker pulse. For example, the flicker pulse can be an electrical pulse signal, an acoustic pulse signal, a thermal pulse signal, or a pressure wave signal, etc. Energy indicators used to represent the flicker pulse include voltage, current, sound intensity, heat, pressure, etc. Therefore, the thresholds can be voltage thresholds, current thresholds, sound intensity thresholds, heat thresholds, pressure thresholds, etc.

[0094] In some embodiments, the intervals between the plurality of thresholds may be equal. That is, the plurality of thresholds may form an arithmetic sequence. Taking voltage thresholds as an example, the intervals between the plurality of thresholds may be 10mV, 20mV, 30mV, etc. The intervals between the plurality of thresholds may also be unequal. For example, the plurality of thresholds may form a geometric sequence with a common ratio of 2.

[0095] In some embodiments, the plurality of thresholds can be determined based on empirical data and / or prior information about the flicker pulse. For example, taking an electrical pulse as an example, summary data from a large number of electrical pulses shows that the peak value of its associated noise is generally below 60mV. Therefore, the lowest threshold among the plurality of thresholds can be set to 60mV. As another example, the prior information about the flicker pulse can yield the magnitude of the pulse peak value. In this case, multiple thresholds within the peak value of the flicker pulse can be set so that relevant data can be collected for each threshold. Of course, the plurality of thresholds may not all be within the peak value of the flicker pulse. For example, a certain number of thresholds can be set, with the calculation based on the threshold data actually crossed by the flicker pulse during the comparison process. Taking voltage thresholds as an example, suppose eight thresholds are set as 60mV, 80mV, 100mV, 120mV, 140mV, 160mV, 180mV, and 200mV. If the peak value of the flicker pulse is high (e.g., 220mV), then the flicker pulse may cross more thresholds, such as all eight thresholds. If the peak value of the flicker pulse is low (e.g., 150mV), then the flicker pulse may cross fewer thresholds, such as the first 5 thresholds.

[0096] Step 140: Use the sampled data as the variable, and determine one or more intermediate parameters based on the first correspondence.

[0097] It is known that sampled data typically requires a standard reference, such as time zero, to indicate the start time of sampling. However, the sampling process is always subject to various factors, leading to inconsistencies between the sampling reference and the standard reference. Therefore, the sampled data can be transformed to obtain sampled data under a standard reference, facilitating calculations and improving computational efficiency. (x...) n ,y n ) describes the sampled data, where x n Indicates the sampling time, y n Indicates in x n The amplitude of the flash pulse. When the digitization sampling is ADC sampling, n represents the number of samples, or the number of data samples. When the digitization sampling is multi-threshold sampling, n represents the number of threshold-time pairs obtained. For example, when the flash pulse crosses 8 thresholds, 16 threshold-time pairs can be obtained, so n = 16. Meanwhile, horizontal shift does not affect the energy information of the flash pulse; therefore, the reference transformation can be a time reference transformation of the sampled data. The sampled data after the reference transformation can be called transformed data, and the time reference value used can be x1, which is the sampling time obtained at the first sampling point. Let pp... i =x i -x1, 1≤i≤n, then the transformed data obtained after the reference transformation can be represented as (pp n ,y n The transformed data can be designated as variables of the objective function model. By combining the first correspondence between the one or more intermediate parameters and the variables, the one or more intermediate parameters can be determined. According to the first correspondence mentioned above:

[0098]

[0099]

[0100]

[0101]

[0102] and X i =x i -b, Y i =y i First, the transformed data (pp) can be... n ,y n ) and (X n ,Y n Then X will be matched accordingly. i =pp i -b, Y i =y iHere, 'b' represents the axis of symmetry of the flash pulse (expressed in time). During sampling, if it is ADC sampling, the sampling rate limits the interval between any two adjacent sampling times to be the same. Therefore, the mean of these sampling times can be considered to approach or equal to 'b'. If it is multi-threshold sampling, since the flash pulse is a symmetrical bell shape, the time it takes for the flash pulse to cross the same threshold twice is symmetrical about the axis of symmetry of the flash pulse. That is, the mean of the time it takes for the flash pulse to cross all thresholds is equal to 'b'. Therefore, 'b' can be determined based on the following formula 18:

[0103]

[0104] Therefore, combining Z = lnY, the one or more intermediate parameters can be determined as follows:

[0105]

[0106]

[0107]

[0108]

[0109] By substituting the transformed data into the above formula, one or more intermediate parameters can be determined.

[0110] Step 150: Transmit the one or more intermediate parameters and the second correspondence to an external device, so that the external device can determine one or more parameters to be determined for the objective function model based on the one or more intermediate parameters and the correspondence.

[0111] It is understandable that processing a closed-loop scintillation pulse can include pulse acquisition, sampling, and data processing. Front-end components, including radiation detection devices, acquire the pulse, while scintillation pulse acquisition boards sample the pulse. Back-end components, including processing devices such as computers and servers, process the data. The front-end components transmit sampled data to the back-end components; however, the large amount of data transmitted during this process can lead to significant network load. Furthermore, processing large amounts of data received by the computer or server requires substantial computing resources. In step 150, the sampled data for the scintillation pulse is processed before transmission. That is, one or more intermediate parameters can be transmitted. This significantly reduces the amount of data transmitted, greatly reducing network load. External devices, such as computers and servers, can directly utilize the second correspondence—that is, the second correspondence between the received intermediate parameters and one or more parameters to be determined in the objective function model of the scintillation pulse—based on one or more received intermediate parameters, and consume minimal computing resources to determine the specific expression of the objective function model of the scintillation pulse. Integration can then be performed to obtain the energy value of the scintillation pulse. This energy value can be used for image reconstruction (e.g., PET image reconstruction) or material identification (e.g., identifying the elemental composition of geological layers in geological exploration).

[0112] In some embodiments, the processing method 100 can be executed by a chip board. For example, the aforementioned scintillation pulse acquisition board. The chips on the chip board may include PLD, CPLD, FPGA, or ASIC chips. The chip board can sample the scintillation pulses and utilize its limited computing resources to partially process the sampled data, reducing the size of the sampled data. This process can be considered another form of "data compression."

[0113] The following example illustrates the transmission of data.

[0114] Taking multi-threshold sampling of scintillation pulses as an example, assuming 8 thresholds are set, 16 threshold-time pairs (i.e., sampled data) can be collected to determine the energy value of the scintillation pulse. That is, determining the energy value of a scintillation pulse requires 16 time data sets. One time data set is 6 bytes in size (5 bytes for coarse time and 1 byte for fine time). Therefore, the total size of the 16 time data sets is 96 bytes. Furthermore, along with other information that needs to be transmitted with the time data, such as the event type (i.e., the time event) and channel information identifier (i.e., which detection channel of the scintillation pulse detector received a high-energy particle that generated the scintillation pulse), the total data size will exceed 96 bytes. (T0-T...) 15This means that after processing through the aforementioned steps of processing method 100, the size of these 16 time data points can be reduced to 20 bytes. For example, the event type, channel information identifier, and T0 will not be processed. T0 still occupies 6 bytes. The subsequent 15 time points can be replaced using one or more of the aforementioned intermediate parameters. The encapsulation format for all data to be transmitted can be as follows:

[0115]

[0116] Among them, EF is used to distinguish the event type, CC represents the number of channels, and they occupy a total of 2 bytes. T0 occupies 6 bytes, encoded as T0[47:40], T0[39:32], T0[31:24], T0[23:16], T0[15:8], and T0[7:0] respectively. The one or more intermediate parameters, together with other information, occupy the remaining 12 bytes. This includes KK-23bits (KK is less than 23 bits, according to prior information it occupies a maximum of 23 bits, occupying 3 bytes), QQ-24bits (QQ is less than 24 bits, according to prior information it occupies a maximum of 24 bits, occupying 3 bytes), dynamic_len-5bits (threshold-related storage occupies a maximum of 5 bits, less than 1 byte, sharing 1 byte with RR), and RR-42bits (RR is less than 42 bits, according to prior information it occupies a maximum of 42 bits, occupying 6 bytes). In the above example, dynamic_len-5bits is 5 bits. The example summarizes the set thresholds as 8, corresponding to 16 sampling time points. Therefore, there are 16 sampling time points corresponding to the amplitude of the flicker pulses. 16 < 25 = 32, therefore, 5 bits are sufficient to store the relevant data of the sampling amplitudes. A 5-bit storage unit is used to store the sampling point data corresponding to the number of thresholds actually crossed by the flicker pulse. Simultaneously, the number of samples, n, can also be used for subsequent calculations.

[0117] In the example above, the sampled data for a single flash pulse is reduced from over 96 bytes to 20 bytes, a significant decrease in data volume. This reduction in data transmission decreases network load and improves transmission efficiency. Furthermore, it also reduces server computing resource consumption and increases data processing speed.

[0118] It should be noted that the above-mentioned Figure 1 The descriptions of the various steps in this specification are for illustrative purposes only and do not limit the scope of this specification. Those skilled in the art can, under the guidance of this specification, [perform certain tasks / activities]. Figure 1 Various modifications and changes have been made to the steps described herein. However, these modifications and changes remain within the scope of this specification.

[0119] The flicker pulse processing method disclosed in this application can process the original sampled data to compress the data before transmission, which can reduce the load on the data transmission network and reduce the consumption of server computing resources.

[0120] Figure 2 This is an exemplary flowchart illustrating another method for processing flicker pulses according to some embodiments of this application. In some embodiments, the flicker pulse processing method 200 can be executed by a second data processing system 700. For example, the flicker pulse processing method 200 can be stored in a storage device (such as the built-in storage unit of the second data processing system 700 or an external storage device) in the form of a program or instructions, which, when executed, can implement the flicker pulse processing method 200. Figure 2 As shown, the flashing pulse processing method 200 may include the following steps.

[0121] Step 210: Obtain the objective function model corresponding to the flashing pulse.

[0122] Step 220: Obtain the first correspondence between the variables of the objective function model and one or more intermediate parameters.

[0123] Step 230: Digitally sample the flickering pulse to obtain sampled data.

[0124] Step 240: Use the sampled data as the variable, and determine one or more intermediate parameters based on the first correspondence.

[0125] Step 250: Transmit one or more intermediate parameters to an external device so that the external device can determine one or more parameters to be determined in the objective function model based on the one or more intermediate parameters using a second correspondence relationship; the second correspondence relationship reflects the transformation between the one or more intermediate parameters and the one or more parameters to be determined.

[0126] In some embodiments, processing method 200 may have some steps that are the same as or similar to those of processing method 100. For example, processing method 200 may also be executed by the chip board, which processes the sampled data of the flicker pulse to determine one or more intermediate parameters and transmits one or more intermediate parameters to an external device to determine the specific expression of the objective function model corresponding to the flicker pulse. The difference between processing method 200 and processing method 100 is that the first correspondence between the variables of the objective function model corresponding to the flicker pulse and one or more intermediate parameters may be transmitted by an external device, rather than being obtained by the chip board using its own computing resources for function transformation. The process by which the external device determines the first correspondence may be the same as described in the relevant part of processing method 100. By using an external device for parameter transformation, the computing resources of the chip board can be saved, further reducing the computational load of the chip board and thus making the parameter transformation faster.

[0127] It should be noted that the above-mentioned Figure 2 The descriptions of the various steps in this specification are for illustrative purposes only and do not limit the scope of this specification. Those skilled in the art can, under the guidance of this specification, [perform certain tasks / activities]. Figure 2 Various modifications and changes have been made to the steps described herein. However, these modifications and changes remain within the scope of this specification.

[0128] Figure 6 This is an exemplary block diagram of a data processing system according to some embodiments of this specification. This data processing system can perform sampled data processing of flicker pulses. For example... Figure 6 As shown, the first data processing system 600 may include a first acquisition module 610, a conversion module 620, a first sampling module 630, a first determination module 640, and a first transmission module 650.

[0129] The first acquisition module 610 can be used to acquire the target function model corresponding to the scintillation pulse according to step 110 as shown above. The scintillation pulse can be acquired by a radiation detection device, such as a scintillation detector. The photoelectric conversion device of the scintillation detector can convert visible light signals into electrical signals, and the electrical signals are output in the form of scintillation pulses through electronic devices connected to the photoelectric conversion device. The output scintillation pulses can be shaped by a shaping circuit to obtain a waveform that conforms to a Gaussian function model. The function model used to represent this waveform can be designated as the original function model of the scintillation pulse. The first acquisition module 610 can normalize the original function model to determine the target function model.

[0130] The transformation module 620 can be used to transform the objective function model according to step 120 as shown above, to obtain the correspondence between the variables of the objective function model and one or more intermediate parameters. The transformation module 620 can perform data processing operations on the objective function model to determine the correspondence. The mathematical processing operations may include at least taking the logarithm, parameter transformation, differentiation, and matrix conversion.

[0131] The first sampling module 630 can be used to digitally sample the flicker pulse according to step 130 as shown above to obtain sampled data. The digital sampling may include ADC sampling (or oscilloscope sampling). The digital sampling may include multi-threshold sampling. When using multi-threshold sampling, multiple thresholds can be preset, and the flicker pulse is compared with these preset thresholds to obtain the time when the flicker pulse crosses the threshold. A threshold-time pair is then formed with the corresponding threshold to generate the sampled data. The intervals between the multiple thresholds can be equal and can be determined based on empirical data and / or prior information about the flicker pulse.

[0132] The first determining module 640 can be used to determine the intermediate parameters based on the first correspondence relationship, using the sampled data as the variables according to step 140 as shown above. The first determining module 640 can transform the sampled data to obtain sampled data under a standard benchmark, facilitating calculation and improving computational efficiency. The sampled data after benchmark transformation can be called transformed data. The transformed data can be designated as variables of the objective function model. Combining the first correspondence relationship between the intermediate parameters and the variables, the first determining module 640 can determine the intermediate parameters. The first determining module 640 can substitute the transformed data into the formula used to express the first correspondence relationship to determine the intermediate parameters.

[0133] The first transmission module 650 can be used to transmit one or more intermediate parameters and the second correspondence to an external device according to step 150 as shown above, so that the external device can determine the parameter to be determined based on the intermediate parameters and the correspondence. The intermediate parameters transmitted by the first transmission module 650 can greatly reduce the amount of data transmitted and significantly reduce network load. External devices, such as computers and servers, can directly use the second correspondence—that is, the second correspondence between the intermediate parameters and the parameter to be determined in the objective function model of the flicker pulse—based on the received intermediate parameters, and consume only a small amount of computing resources to determine the specific expression of the objective function model of the flicker pulse.

[0134] For further descriptions of the above modules, please refer to the flowchart section of this application, such as... Figure 1 .

[0135] Figure 7 This is an exemplary block diagram of another data processing system according to some embodiments of this specification. This data processing system can perform sampled data processing of flicker pulses. For example... Figure 7 As shown, the second data processing system 700 may include a second acquisition module 710, a receiving module 720, a second sampling module 730, a second determination module 740, and a second transmission module 750.

[0136] The second acquisition module 710 can be used to acquire the objective function model corresponding to the flashing pulse according to step 210 above.

[0137] The receiving module 720 can be used to obtain a first correspondence between the variables of the objective function model and one or more intermediate parameters according to step 220 above.

[0138] The second sampling module 730 can be used to digitally sample the flashing pulse according to step 230 above to obtain sampling data.

[0139] The second determining module 740 can be used to determine one or more intermediate parameters based on the first correspondence relationship, using the sampled data as the variable according to step 240 above.

[0140] The second transmission module 750 can be used to transmit one or more intermediate parameters to an external device according to step 250 above, so that the external device can determine one or more parameters to be determined of the objective function model based on the intermediate parameters using a second correspondence relationship; the second correspondence relationship reflects the transformation between the intermediate parameters and the parameters to be determined.

[0141] The second acquisition module 710, the second sampling module 730, the second determination module 740, and the second transmission module 750 can perform the same or similar operations as the first acquisition module 610, the first sampling module 630, the first determination module 640, and the first transmission module 650. The receiving module 720 can accept the first correspondence between the variables of the objective function model corresponding to the flashing pulse and one or more intermediate parameters transmitted by an external device.

[0142] For further descriptions of the above modules, please refer to the flowchart section of this application, for example... Figures 1-2 .

[0143] It should be understood that Figure 6 and Figure 7The systems and modules shown can be implemented in various ways. For example, in some embodiments, the systems and modules can be implemented by 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 an appropriate instruction execution system, such as a microprocessor or dedicated-design hardware. Those skilled in the art will understand that the methods and systems described above can be implemented using computer-executable instructions and / or included in processor control code, for example, 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 systems and modules of this specification can be implemented not only by 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 by software, for example, executed by various types of processors, or by a combination of the aforementioned hardware circuits and software (e.g., firmware).

[0144] 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 principles of the system, may arbitrarily combine the modules or construct subsystems connected to other modules without departing from these principles. For example, 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.

[0145] Figure 8 This is an exemplary block diagram of a processing device according to some embodiments of this application. The processing device 800 may include any components used to implement the systems described in the embodiments of this application. For example, the processing device 800 may be implemented using hardware, software programs, firmware, or a combination thereof. For example, the processing device 800 may implement a first data processing system 600 and a second data processing system 700. For convenience, only one processing device is shown in the figure; however, the computing functions described in the embodiments of this application can be implemented in a distributed manner by a set of similar platforms to distribute the system's processing load.

[0146] In some embodiments, the processing device 800 may include a processor 810, a memory 820, an input / output component 830, and a communication port 840. In some embodiments, the processor (e.g., CPU) 810 may execute program instructions as one or more processors. In some embodiments, the memory 820 includes different forms of program memory and data memory, such as a hard disk, read-only memory (ROM), random access memory (RAM), etc., for storing a wide variety of data files processed and / or transmitted by a computer. In some embodiments, the input / output component 830 may be used to support input / output between the processing device 800 and other components. In some embodiments, the communication port 840 may be connected to a network for data communication. Exemplary processing devices may include program instructions executed by the processor 810 stored in read-only memory (ROM), random access memory (RAM), and / or other types of non-transitory storage media. The methods and / or processes of the embodiments of this specification may be implemented as program instructions. The processing device 800 may also receive programs and data disclosed in this application via network communication.

[0147] For ease of understanding, Figure 8 Only one processor is illustrated in this specification. However, it should be noted that the processing device 800 in the embodiments of this specification may include multiple processors, and therefore the operations and / or methods described in the embodiments of this specification that are implemented by one processor may also be implemented jointly or independently by multiple processors. For example, in this specification, the processor of the processing device 800 executes steps 110 and 120. It should be understood that steps 110 and 120 may also be executed jointly or independently by two different processors of the processing device 800 (e.g., the first processor executes step 110, the second processor executes step 120, or the first and second processors jointly execute steps 110 and 120).

[0148] The scintillation pulse processing method provided in this application can be specifically used in photon detection and is applicable to various fields, such as medical imaging technology, high-energy physics, lidar, autonomous driving, precision analysis, and optical communication. In a specific example, the scintillation pulse processing method, apparatus, detector, electronic device, and storage medium provided in this application can be applied to positron emission tomography (PET). In a PET system, photon data can be acquired using the scheme described in the embodiments of this application, followed by image reconstruction. In other specific examples of this application, the scintillation pulse processing method, apparatus, detector, electronic device, and storage medium provided in this application can be applied to various digital devices, such as CT equipment, MRI equipment, radiation detection equipment, oil exploration equipment, low-light detection equipment, SPECT equipment, security inspection equipment, gamma cameras, X-ray equipment, DR equipment, and other devices utilizing the principle of high-energy ray conversion, as well as other photoelectric conversion application devices, or a combination of the above-mentioned devices.

[0149] 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.

[0150] Furthermore, this specification uses specific terms to describe embodiments thereof. For example, "an embodiment," "one embodiment," and / or "some embodiments" refer to a particular feature, structure, or characteristic associated with at least one embodiment of this specification. Therefore, it should be emphasized and noted that references to "an embodiment," "one embodiment," or "an alternative embodiment" in different locations throughout this specification do not necessarily refer to the same embodiment. Moreover, certain features, structures, or characteristics in one or more embodiments of this specification can be appropriately combined.

[0151] 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,” “unit,” “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.

[0152] 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.

[0153] 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).

[0154] 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.

[0155] 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.

[0156] 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.

[0157] 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.

[0158] 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 method for processing flicker pulses, characterized in that, The processing method includes: Obtain the objective function model corresponding to the flashing pulse, wherein the objective function model includes one or more parameters to be determined; Transform the objective function model to obtain a first correspondence between the variables of the objective function model and one or more intermediate parameters, and a second correspondence between the intermediate parameters and the parameter to be determined; Perform ADC sampling or multi-threshold sampling on the flicker pulse. When performing multi-threshold sampling, the method includes: presetting multiple thresholds; for each threshold, comparing the flicker pulse with the threshold to determine the state change signal when the flicker pulse crosses the threshold; performing digital time sampling on the state change signal to obtain the corresponding threshold-time pair; and specifying multiple threshold-time pairs to constitute the sampling data. The sampled data is used as the variable, and the intermediate parameter is determined based on the first correspondence. The intermediate parameters and the second correspondence are transmitted to an external device so that the external device can determine the parameter to be determined based on the intermediate parameters and the second correspondence.

2. The method for processing flicker pulses according to claim 1, characterized in that, The objective function model for obtaining the flicker pulse includes: Obtain the original function model, which conforms to a Gaussian function; The original function model is normalized to determine the target function model.

3. The method for processing flicker pulses according to claim 1, characterized in that, Obtaining the first correspondence and the second correspondence includes: Mathematical processing operations are performed on the objective function model to determine the correspondence; wherein the mathematical processing operations include at least taking the logarithm, parameter transformation, differentiation, and matrix transformation.

4. The method for processing flicker pulses according to claim 1, characterized in that, The intervals between the multiple thresholds are equal.

5. The method for processing flicker pulses according to claim 1, characterized in that, Determining the intermediate parameters includes: Perform a reference transformation on the sampled data to obtain transformed data; The transformed data is designated as the variable, and the intermediate parameters are solved using the first correspondence.

6. A method for processing flicker pulses, characterized in that, The processing method includes: Obtain the objective function model corresponding to the flashing pulse, wherein the objective function model includes one or more parameters to be determined; Obtain the first correspondence between the variables of the objective function model and one or more intermediate parameters; Perform ADC sampling or multi-threshold sampling on the flicker pulse. When performing multi-threshold sampling, the method includes: presetting multiple thresholds; for each threshold, comparing the flicker pulse with the threshold to determine the state change signal when the flicker pulse crosses the threshold; performing digital time sampling on the state change signal to obtain the corresponding threshold-time pair; and specifying multiple threshold-time pairs to constitute the sampling data. The sampled data is used as the variable, and the intermediate parameter is determined based on the first correspondence. The intermediate parameters are transmitted to an external device so that the external device can determine the parameter to be determined based on the intermediate parameters and using a second correspondence between the intermediate parameters and the parameter to be determined.

7. The method for processing flicker pulses according to claim 6, characterized in that, The objective function model for obtaining the flicker pulse includes: Obtain the original function model, which conforms to a Gaussian function; The original function model is normalized to determine the target function model.

8. The method for processing flicker pulses according to claim 6, characterized in that, The first and second correspondences are determined based on the following operations: Mathematical processing operations are performed on the objective function model to determine the correspondence; wherein the mathematical processing operations include at least taking the logarithm, parameter transformation, differentiation, and matrix transformation.

9. The method for processing flicker pulses according to claim 6, characterized in that, The intervals between the multiple thresholds are equal.

10. The method for processing flicker pulses according to claim 6, characterized in that, Determining the intermediate parameters includes: Perform a reference transformation on the sampled data to obtain transformed data; The transformed data is designated as the variable, and the intermediate parameters are solved using the first correspondence.

11. A processing device for scintillation pulses, characterized in that, The processing device includes: The first acquisition module is configured to acquire the objective function model corresponding to the flashing pulse, wherein the objective function model includes one or more parameters to be determined. The conversion module is configured to convert the objective function model to obtain a first correspondence between the variables of the objective function model and one or more intermediate parameters, and a second correspondence between the intermediate parameters and the parameters to be determined. The first sampling module is configured to perform ADC sampling or multi-threshold sampling on the flicker pulse. When performing multi-threshold sampling, in order to obtain sampling data, the first sampling module is configured to: preset multiple thresholds; for each threshold, compare the flicker pulse with the threshold to determine the state change signal when the flicker pulse crosses the threshold; perform digital time sampling on the state change signal to obtain the corresponding threshold-time pair; and specify multiple threshold-time pairs to constitute the sampling data. The first determining module is configured to use the sampled data as the variable and determine the intermediate parameter based on the first correspondence relationship; The first transmission module is configured to transmit the intermediate parameters and the second correspondence to an external device, so that the external device can determine the parameter to be determined based on the intermediate parameters and the second correspondence.

12. The flash pulse processing apparatus according to claim 11, characterized in that, To obtain the objective function model corresponding to the flickering pulse, the first acquisition module is configured as follows: Obtain the original function model, which conforms to a Gaussian function; The original function model is normalized to determine the target function model.

13. The flash pulse processing apparatus according to claim 11, characterized in that, To obtain the first correspondence and the second correspondence, the conversion module is configured as follows: Mathematical processing operations are performed on the objective function model to determine the correspondence; wherein the mathematical processing operations include at least taking the logarithm, parameter transformation, differentiation, and matrix transformation.

14. The flash pulse processing apparatus according to claim 11, characterized in that, The intervals between the multiple thresholds are equal.

15. The flash pulse processing apparatus according to claim 11, characterized in that, To determine the intermediate parameters, the first determining module is configured as follows: Perform a reference transformation on the sampled data to obtain transformed data; The transformed data is designated as the variable, and the intermediate parameters are solved using the first correspondence.

16. A processing device for scintillation pulses, characterized in that, The device includes: The second acquisition module is configured to acquire the objective function model corresponding to the flashing pulse, wherein the objective function model includes one or more parameters to be determined. The receiving module is configured to obtain a first correspondence between the variables of the objective function model and one or more intermediate parameters; The second sampling module is configured to perform ADC sampling or multi-threshold sampling on the flicker pulse. When performing multi-threshold sampling, in order to obtain sampling data, the second sampling module is configured to: preset multiple thresholds; for each threshold, compare the flicker pulse with the threshold to determine the state change signal when the flicker pulse crosses the threshold; perform digital time sampling on the state change signal to obtain the corresponding threshold-time pair; and specify multiple threshold-time pairs to constitute the sampling data. The second determining module is configured to use the sampled data as the variable and determine the intermediate parameter based on the first correspondence relationship; The second transmission module is configured to transmit the intermediate parameters to an external device so that the external device can determine the parameter to be determined based on the intermediate parameters and using a second correspondence between the intermediate parameters and the parameter to be determined.

17. The flash pulse processing apparatus according to claim 16, characterized in that, To obtain the objective function model corresponding to the flickering pulse, the second acquisition module is configured as follows: Obtain the original function model, which conforms to a Gaussian function; The original function model is normalized to determine the target function model.

18. The flash pulse processing apparatus according to claim 16, characterized in that, The first and second correspondences are determined based on the following operations: Mathematical processing operations are performed on the objective function model to determine the correspondence; wherein the mathematical processing operations include at least taking the logarithm, parameter transformation, differentiation, and matrix transformation.

19. The flash pulse processing apparatus according to claim 16, characterized in that, The intervals between the multiple thresholds are equal.

20. The flash pulse processing apparatus according to claim 16, characterized in that, To determine the intermediate parameters, the second determining module is configured as follows: Perform a reference transformation on the sampled data to obtain transformed data; The transformed data is designated as the variable, and the intermediate parameters are solved using the first correspondence.

21. A processing apparatus, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the processing method as described in any one of claims 1-10.

22. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the steps of the method as described in any one of claims 1-10.

Images