A method for gain compensation of a silicon photomultiplier by adjusting bias voltage

Abstract

The application relates to a silicon photomultiplier bias voltage adjustment gain compensation method, which comprises the following steps: for each unit detector in a PET system, an FPGA determines whether the bias voltage and gain of the unit detector need to be corrected based on the working state of the unit detector; if the unit detector is in an idle state, the FPGA acquires a bias voltage parameter for adjusting the unit detector, and obtains gain compensation information corresponding to the bias voltage and the working temperature based on the bias voltage parameter and a curve of the change of the working temperature of the unit detector over time; and the FPGA performs gain compensation on process data in the use state of the unit detector based on the gain compensation information, so as to obtain corrected detection data as original data for reconstructing a PET image. The above method does not increase the system waiting dead time of system temperature acquisition and judgment, does not affect data acquisition, and maintains the stability of the gain of the silicon photomultiplier of the PET system detector.

Description

Technical Field

[0001] This invention relates to the field of nuclear radiation detector technology, and in particular to a method for gain compensation by adjusting the bias voltage of a silicon photomultiplier tube. Background Technology

[0002] Typical temperature compensation for silicon photomultiplier tubes (SMTs) involves using a temperature sensor to detect changes in the ambient temperature. The signal is then processed through an analog-to-digital converter (ADC), microcontroller, digital-to-analog converter (DAC), and switching boost circuit to adjust the SMT's bias voltage in real-time, thereby stabilizing the SMT's gain. While this method is generally sufficient for temperature gain compensation in most applications, in the PET (Polymer Electron Device) field, where high-activity data acquisition and high-speed transmission require real-time temperature monitoring, temperature judgment, and voltage adjustment to change the gain, significant data transmission and processing time is consumed. This results in a dead time for the PET system, reducing its sensitivity.

[0003] One method is to perform dynamic gain compensation on the integrated signal after it passes the trigger threshold during the acquisition process. However, this compensation can only reduce the impact of exceeding the energy window. Temperature changes can cause significant fluctuations in the count rate above the trigger high threshold, and the timing low threshold can also be affected by changes in signal gain, thus impacting the time resolution of the PET. From the perspective of PET structure principles, to reduce system dead time at high activity, the trigger high threshold should be as close as possible to the lower limit of the energy window, but not higher. This minimizes the resources occupied by invalid signals exceeding the threshold for sampling, integration, and subsequent analysis. Signal fluctuations caused by temperature variations may cause some valid events to be intercepted by the high threshold, while also allowing more invalid events to affect the gain.

[0004] To address the above issues, in order to solve the problem of real-time temperature acquisition and compensation consuming system resources, reduce system dead time, and maintain stable gain, count rate, and time resolution of the silicon photomultiplier tube in the PET system detector under some relatively extreme conditions, a method is needed for non-real-time temperature acquisition that compensates for the gain of the silicon photomultiplier tube by predicting bias changes. Summary of the Invention

[0005] (a) Technical problems to be solved

[0006] In view of the above-mentioned shortcomings and deficiencies of the prior art, the present invention provides a silicon photomultiplier tube bias voltage adjustment gain compensation method.

[0007] (II) Technical Solution

[0008] To achieve the above objectives, the main technical solutions adopted by the present invention include:

[0009] In a first aspect, embodiments of the present invention provide a silicon photomultiplier tube bias voltage adjustment gain compensation method, comprising:

[0010] S10. For each unit detector in the PET system, the FPGA determines whether the bias value of the unit detector needs to be corrected based on the working status of the unit detector.

[0011] S20. If the unit detector is in an idle state, the FPGA obtains the bias voltage parameter used to adjust the unit detector, and the gain compensation information corresponding to the bias voltage and the operating temperature of the unit detector over time based on the bias voltage parameter and the curve of the operating temperature of the unit detector.

[0012] S30. Based on the gain compensation information, the FPGA performs gain compensation on the process data in the use state of the unit detector to obtain the corrected detection data as the original data for reconstructing the PET image.

[0013] Optionally, S20 includes:

[0014] S21. The FPGA acquires a first curve of the operating temperature and gain change of the unit detector based on a first preset time period.

[0015] S22, The FPGA obtains a second curve showing the change of unit detector gain with bias voltage based on a second preset time period;

[0016] S23. The FPGA obtains a third curve of the working temperature of the unit detector changing with time based on a third preset time period, and processes it in an approximately linear fitting manner to obtain the result.

[0017] S24. Based on the results of the first curve, the second curve, and the approximate linear fitting process, obtain information on the time-varying bias voltage used to keep the gain stable, and obtain the gain compensation information.

[0018] The first preset time period is longer than the second preset time period, and longer than the third preset time period, and the second preset time period is different from the first preset time period.

[0019] Optionally, S21 includes:

[0020] S211. The operating temperature of each unit detector is read using the temperature sensor of each unit detector;

[0021] S212. With the radiation barrel placed in the middle of all unit detectors, record the energy peak at 511 keV in the single crystal energy spectrum within one cycle to obtain the operating temperature and peak position variation point of each single crystal strip.

[0022] S213. Adjust the operating temperature of the unit detector, obtain multiple peak position change information and normalize it, and use the average peak position of all single crystal strips of the unit detector to characterize the peak position of the unit detector, and obtain the first curve of the operating temperature and gain change of the unit detector.

[0023] The first curve is represented as: G 增益 (Temp) = a 增益 ×Temp+b 增益 ; Formula (k1);

[0024] The coefficient 'a' was obtained through linear fitting. 增益 and b 增益 Temp is the operating temperature, G 增益 (Temp) Gain as a function of operating temperature.

[0025] Optionally, S22 includes:

[0026] A radiation source is placed in the middle region of the detector in the PET system, and the operating temperature of the unit detector is fixed. The FPGA adjusts the bias value of the unit detector, and for each bias value, the single-event data is statistically analyzed based on integer multiple periods.

[0027] Based on the information of gain and corresponding voltage under standard conditions, the information of the relationship between the change value of single-stage event data and the bias voltage difference is obtained as the second curve of the gain factor difference changing with the bias voltage.

[0028] The second curve is represented as: ΔG=a 偏压 ×ΔV+b 偏压 , formula (k2)

[0029] The coefficient 'a' was obtained through linear fitting. 偏压 and b 偏压 ΔV is the bias voltage difference, and ΔG is the gain factor difference.

[0030] Optionally, S23 includes:

[0031] The third curve showing the change of the operating temperature of the detector in the measurement unit over time;

[0032] The third curve is represented as: Temp 降 =a 降 t+b 降 Temp 升 =a 升 t+b 升 ;Formula (k3)

[0033] The real-time calibration retains 5 sets of recorded values, each set including: the start time of the period t star descent time T 下降 and rise time T上升 Maximum temperature within the cycle: Temp max and minimum value Temp min ;

[0034] Approximate linear fitting methods include: t star =t max(上组) The starting time is the maximum temperature (Temp) of the last complete cycle at the corresponding scale time. max The corresponding time t max ;

[0035] T 下降 =t min -t star ;T 上升 =t max -t min ;

[0036] Each time a new value is obtained, it is updated by adding 1 / 16 of the original value to 15 / 16. The remaining 4 sets of values ​​T 下降 T 上升 Temp max and Temp min All are averaged using this method on a rolling basis;

[0037] That is: Current value = New value * 1 / 16 + Old value * 15 / 16;

[0038] Let: t = t 当前 -t star The formula coefficient 'a' is obtained based on 5 sets of values. 降 b 降 a 升 b 升 ;

[0039] a 降 =(Temp min -Temp max ) / T 下降 b 降 =Temp max ;

[0040] a 升 =(Temp max -Temp min ) / T 上升 b 升 =Temp min .

[0041] Optionally, the real-time scale retains 5 sets of recorded values, including:

[0042] Determine the initial period rise time T using either offline analysis with average period and average temperature extremes, or by using records from the previous calibration.0上升 and descent time T 0下降 Maximum initial temperature (Temp) 0max and minimum starting temperature Temp 0min ;

[0043] FPGA in the first cycle range (T) 0上升 +T 0下降 Get the maximum temperature (Temp) within the first cycle. 1max and the time t for the maximum temperature 1max And the minimum temperature of the first cycle, Temp. 1min and t 1min ; ΔT=t 1min -t 1max If the time difference is greater than 0, then ΔT is used as the new descending cycle, represented by T. 1下降 This means that if the difference ΔT is less than 0, then ΔT is used as the new downward cycle. 1上升 express;

[0044] Perform cycle start point correction, t 1max The time is taken as the starting point of a new cycle, and a new minimum value Temp is sought within the extended interval of the new cycle. 2min and corresponding time t 2min and the maximum value Temp 2max and time t 2max T 2下降 =t 2min -t 1max T 2上升 =t 2max -t 2min , t 2max The time is taken as the starting point of a new cycle, and the new value is obtained by rolling in sequence.

[0045] Optionally, S24 includes:

[0046] If the gain is stable at G 标准 Then, adjusting the bias voltage ΔV will change the gain value by ΔG = G. 增益 -G 标准 ;

[0047] Based on known test results: G 标准 =a 增益 ×Temp 标准 +b 增益 ;

[0048] Temp 标准 It is a definite value, representing the detector's expected average operating temperature;

[0049] G 增益 =a 增益 ×Temp+b 增益; ΔG=a 偏压 ×ΔV+b 偏压 =G 增益 -G 标准 ;

[0050] The bias voltage versus temperature relationship function is as follows:

[0051] a 偏压 ×ΔV+b 偏压 =a 增益 ×(Temp-Temp 标准 );

[0052] ΔV=(a 增益 ×(Temp-Temp 标准 )-b 偏压 ) / a 偏压 ;Formula (k4)

[0053] a 偏压 b 偏压 a 增益 and b 增益 To obtain known parameters for measurement.

[0054] Optionally, S25 includes:

[0055] The variable in ΔV is temperature (Temp), based on the third curve to which Temp belongs, according to formula (k3):

[0056] get:

[0057]

[0058] Based on coefficient a 降 b 降 a 升 b 升 and t=t 当前 -t star ;

[0059] get:

[0060]

[0061]

[0062] t 当前 The time it takes to acquire data in real time is a variable.

[0063] ΔV 降 and ΔV 升 Judgment conditions:

[0064] Remainder = (t) 当前 -t star) / (T 下降 +T 上升 The remainder of ).

[0065] Remainder ≤ T 下降 For the descent period, use the formula ΔV 降 ;

[0066] Remainder > T 下降 For the rising cycle, use the formula ΔV 升 .

[0067] Optionally, S30 includes:

[0068] Based on the gain compensation information, the FPGA adjusts the bias voltage of the unit detector according to the bias voltage value to which the gain compensation information belongs during the use state of the unit detector, so as to correct before passing the energy window, and then sequentially passes through the energy window screening and time coincidence screening to obtain the corrected detection data as the original data for reconstructing the PET image.

[0069] In a second aspect, embodiments of the present invention provide a detection device, comprising: a unit detector based on a silicon photomultiplier tube and an FPGA, wherein all unit detectors are electrically connected to the FPGA, and the FPGA executes a silicon photomultiplier tube bias adjustment gain compensation method as described in any of the first aspects above.

[0070] Thirdly, embodiments of the present invention provide a PET system that includes the detection device described in the second aspect above.

[0071] (III) Beneficial Effects

[0072] The method of this invention minimizes the system's reading, transmission, and judgment time when acquiring data in real time in the PET system. It can synchronously compensate the gain of the silicon photomultiplier tube according to temperature changes, thereby ensuring the sensitivity and stability of the PET system and improving the system's time resolution.

[0073] The method of this invention does not increase the system waiting dead time for temperature acquisition and judgment, and does not affect data acquisition; it continuously acquires the periodic function parameters of the scale temperature change during idle time, ensuring that the bias voltage adjustment function model can be accurately predicted over time when acquiring patient data without temperature acquisition; it also ensures that the gain of the PET detector remains stable during patient data acquisition.

[0074] In addition, gain stabilization is compensated from the analog circuit output, which ensures that the low threshold used for timing is relatively stable and improves the time resolution of the PET system.

[0075] In use, the high threshold can be increased as much as possible, and invalid high threshold data can be reduced, ensuring that the high threshold used for trigger judgment is relatively stable. Under high activity conditions, the system dead time is reduced, and the sensitivity of the PET system is improved. Attached Figure Description

[0076] Figure 1 This is a flowchart of the real-time temperature compensation process.

[0077] Figure 2 This is a schematic diagram showing how the gain of a detector at a certain location changes with temperature.

[0078] Figure 3 This is a schematic diagram showing how the gain difference of a detector at a certain location changes with the pressure difference;

[0079] Figure 4 This is a schematic diagram showing the temperature change of a detector at a certain location over time.

[0080] Figure 5 This is a schematic diagram showing the change in single-lift count rate of a detector at a certain location before and after correction, as a function of temperature.

[0081] Figure 6 This is a flowchart illustrating a silicon photomultiplier tube bias voltage adjustment gain compensation method according to an embodiment of the present invention. Detailed Implementation

[0082] To better explain and facilitate understanding of the present invention, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0083] This invention relates to the field of nuclear radiation detectors and is used in conjunction with radiation detectors in nuclear medicine imagers employing radiation transmission or radiopharmaceuticals, such as positron emission tomography (PET) and single-photon emission computed tomography (SPECT) imagers. The detectors utilize silicon photomultiplier tubes as the photoelectric conversion element. This invention can also be applied to other radiation imaging modalities and to systems and methods employing radiation detectors, such as those used in astronomy and airport baggage screening.

[0084] The method in this embodiment can be illustrated using a PET system as an example. However, it is not limited to using only a PET system.

[0085] Example 1

[0086] like Figure 1 and Figure 6 As shown, this embodiment of the invention provides a silicon photomultiplier tube bias voltage adjustment gain compensation method, the method comprising:

[0087] S10. For each unit detector in the PET system, the FPGA determines whether the bias value of the unit detector needs to be corrected based on the working status of the unit detector.

[0088] The FPGA is brought to an idle state to acquire the bias value, and then corrected before performing the integration operation of the probe data acquisition based on the latest acquired bias value in the usage state.

[0089] S20. If the unit detector is in an idle state, the FPGA obtains the bias voltage parameter used to adjust the unit detector, and the gain compensation information corresponding to the bias voltage and the operating temperature of the unit detector over time based on the bias voltage parameter and the curve of the operating temperature of the unit detector.

[0090] S30, based on the gain compensation information, the FPGA performs gain compensation on the process data in the usage state of the unit detector to obtain the corrected detection data as the original data for reconstructing the PET image.

[0091] The above method minimizes the system's reading, transmission, and judgment time when acquiring data in real time in the PET system. It can predict temperature changes and perform gain compensation for silicon photomultiplier tubes, thereby ensuring the sensitivity and stability of the PET system and improving the system's time resolution.

[0092] To better understand the process of obtaining the gain compensation parameters based on the gain acquisition mode in step S20 above, the following will provide a detailed explanation in conjunction with sub-steps S21 to S24.

[0093] S21. The FPGA acquires the first curve of the change in operating temperature and gain of the unit detector based on the first preset time period.

[0094] For example: S211, the operating temperature of each unit detector is read by means of the temperature sensor of each unit detector;

[0095] S212. With the radiation barrel (such as the Ge barrel) placed in the middle of all unit detectors, record the energy peak at 511 keV of the single crystal energy spectrum within one cycle to obtain the operating temperature and peak position variation point of each single crystal strip.

[0096] S213. Adjust the operating temperature of the unit detector, obtain multiple peak position change information and normalize it, and use the average value of all single crystal peaks of the unit detector to characterize the peak position of the unit detector, and obtain the first curve of the operating temperature and gain change of the unit detector.

[0097] The first curve is represented as: G 增益 (Temp) = a 增益 ×Temp+b 增益 ;Formula (k1);

[0098] The coefficient 'a' was obtained through linear fitting. 增益 and b 增益 Temp is the operating temperature, G 增益(Temp) Gain as a function of operating temperature.

[0099] S22. The FPGA obtains a second curve showing the change of unit detector gain with bias voltage based on a second preset time period.

[0100] S23. The FPGA obtains the third curve of the working temperature of the unit detector changing with time based on the third preset time period, and processes it in an approximately linear fitting manner to obtain the result.

[0101] S24. Information on the change of bias voltage value of the predictor unit detector over time;

[0102] S25. Based on the results of the first curve, the second curve, and the approximate linear fitting process, obtain information on the time-varying bias voltage used to keep the gain stable, and obtain gain compensation information.

[0103] The first preset time period is longer than the second preset time period, and longer than the third preset time period, and the second preset time period is different from the first preset time period.

[0104] In this embodiment, the FPGA can determine whether the temperature should be rising or falling based on the actual data acquisition time, calculate the bias value in real time, and adjust the bias of each detector to correct the effect of temperature on the gain of the photomultiplier tube in real time. It can perform normal energy path integration through a single-stage event that triggers a threshold, then filter by energy window, then by time conformity, and finally store the raw data as raw data on the computer (operating console) to await subsequent reconstruction into a PET image.

[0105] Example 2

[0106] To better understand the method of Embodiment 1 above, the following will be combined with... Figures 1 to 5 A detailed explanation of a gain compensation method for silicon photomultiplier tube bias adjustment is provided.

[0107] The PET system in practice uses a water-cooled and air-cooled cooling system. A water-cooled plate with circulating cooling water is placed close to the silicon photomultiplier tube on the detector for cooling, while the circuit board and FPGA that process the signal are cooled by air cooling.

[0108] Understandably, the PET system's computing processor is divided into two parts: a front-end FPGA and a back-end FPGA. The front-end FPGA is responsible for reading the detector sensor temperature and analog signal data. Through the written parameters, it can also control the analog-to-digital conversion and control the bias voltage applied to the detector. The back-end FPGA controls the data acquisition and parameter writing by the front-end FPGA, as well as the reprocessing and storage of the data transmitted from the front-end FPGA during data acquisition.

[0109] A PET system consists of dozens to hundreds of unit detectors, each with its own temperature sensor and readout circuit, as well as independent circuitry for controlling the applied bias voltage and reading the bias voltage.

[0110] like Figure 1 As shown, the first step is to calibrate each detector in the PET system before data acquisition. This calibration is performed in five steps:

[0111] The first step is to measure the change curve of the detector's operating temperature and gain.

[0112] The second step is to measure the curve of detector gain as a function of bias voltage.

[0113] The third step is to measure the change curve of the detector's operating temperature over time in the measurement system.

[0114] The fourth step is to obtain the curve of the real-time calibrator's operating temperature changing over time.

[0115] The fifth step is to predict the formula for how the bias voltage changes over time.

[0116] The sixth step is to implement real-time gain correction using an FPGA.

[0117] To better understand, each step will be explained in detail below.

[0118] Step 1: Measure the change curve of detector operating temperature and gain.

[0119] Used to test the operating temperature of a unit detector, the photosensitive element of a unit detector is generally composed of an array of dozens to hundreds of silicon photomultiplier tubes, each of which may correspond to one or more scintillator crystal strips. In practice, each detector has only one temperature sensor. If there are multiple temperature sensors, the average value of the multiple temperature sensors can be used to characterize the operating temperature of the detector, or different operating temperatures can be used to characterize the detector at different locations based on the location of the temperature sensors.

[0120] The PET cooling system exhibits a relatively stable periodic temperature change. However, the detector's temperature, influenced by the cooling system, cannot remain constant and also varies periodically over time. Testing the gain requires a relatively long time to collect sufficient data for statistical analysis of the energy spectrum. Therefore, to minimize the impact of temperature on the statistics, it is necessary to know the length of the detector's operating temperature change period. When calculating the energy spectrum, the data collection length should be an integer multiple of the temperature change period or a sufficiently long time to negligiblely account for the temperature change's influence. The temperature corresponding to this set of gain data is the average temperature over one period.

[0121] When measuring the detector's operating temperature versus gain curve, the PET system does not correct or compensate for the silicon photomultiplier tube gain. During testing, a uniform Ge barrel source is placed centrally. The Ge source emits a pair of photons with an energy of 511 keV through electron-positron annihilation. The single-crystal energy spectrum will have an energy peak. The channel number corresponding to this peak position represents the gain at that temperature. Changing the cooling system alters the uniform operating temperature, causing a corresponding change in the channel number of the energy spectrum peak. This change in channel number corresponds to a change in gain. By manually controlling and changing the detector's operating temperature, the corresponding peak position is measured. Normalizing the changed channel number yields the detector's operating temperature and gain variation points. Figure 2 As shown, the gain G 增益 The relationship between temperature (Temp) and temperature change is linear. Using the function G... 增益 (Temp) = a 增益 ×Temp+b 增益 a is obtained through linear fitting 增益 and b 增益 value.

[0122] Step 2: Measure the change in detector gain with bias voltage.

[0123] The backend FPGA sends commands to the frontend FPGA to control and change the detector's bias voltage, measuring gain changes while maintaining a constant and uniform temperature. The Ge barrel source is placed in the center, and data is collected in integer multiples of the cycle for statistical analysis. As the bias voltage increases, the detector gain increases, and the relationship between gain and bias voltage is linear. Using the gain at a certain point and the corresponding voltage as a standard value, the curve showing the relationship between the gain difference and the bias voltage difference can be obtained, which is also linear. Figure 3 ΔG=a 偏压 ×ΔV+b 偏压 a is obtained through fitting 偏压 and b 偏压 value.

[0124] Step 3: Measure the temperature change curve over time.

[0125] By acquiring high-speed data on temperature changes in the PET system, and through offline analysis, the temperature change cycle range and temperature fluctuation range are determined. Since the system's heat generation and dissipation are essentially constant, the cycle and range of each detector are also essentially fixed, resulting in testing errors only within a very small range. The average temperature, however, will vary due to differences in water temperature settings and ambient temperature. The offline temperature change data over time, such as... Figure 2 It can analyze the average period of temperature changes and the average maximum and minimum values ​​of temperature fluctuations, providing initial calculated values ​​for online real-time calibration.

[0126] Step 4: Real-time temperature variation function over time.

[0127] Offline data analysis showed that polynomial fitting was optimal for both the rising and falling curves. However, due to the large number of fitting coefficients in the online real-time calibration process, an approximate linear fitting was chosen to reduce the difficulty of achieving online real-time calibration.

[0128] Temp 降 =a 降 t+b 降 ;

[0129] Temp 升 =a 升 t+b 升 ;

[0130] Through actual offline error calculation and comparison, the difference between the approximate linear fit and the polynomial fit of the rising curve is less than 0.15℃, and the difference between the approximate linear fit and the polynomial fit of the falling curve is less than 0.08℃. The gain difference under this temperature difference is negligible.

[0131] Online real-time calibration requires input of the initial period rise time T. 0上升 and descent time T 0下降 Maximum initial temperature (Temp) 0max and minimum starting temperature Temp 0min The initial value can be the average period and average temperature extreme value from offline analysis, or it can be the last result of the previous temperature value. The FPGA will automatically set the initial value within the first period range (T). 0上升 +T 0下降 Find the maximum temperature (Temp) within the first cycle. 1max and the time t at that point 1max And the minimum temperature of the first cycle, Temp. 1min and t 1min ΔT=t 1min -t 1max If the time difference is greater than 0, then ΔT is used as the new descending cycle, represented by T. 1下降 This means that if the difference ΔT is less than 0, then ΔT is used as the new downward cycle. 1上升 express.

[0132] It should be noted that the starting point for temperature measurement is random; it could be during an upward or downward trend. Only a pair of highest and lowest temperatures can be obtained for each temperature cycle, allowing the determination of the cycle's starting position. The cycle can begin with either the highest or lowest temperature. By determining the order of the highest and lowest temperatures, it's possible to identify whether the cycle is complete (upward or downward). If ΔT is greater than 0, t1max is used as the starting time, and this complete downward cycle is used for calibration calculations. If ΔT is less than 0, the data from this complete upward cycle can also be used for calibration calculations.

[0133] Perform cycle start point correction, t 1max The time interval is used as the starting point of a new cycle, and a new minimum value Temp is found within a range slightly larger than the first cycle. 2min and its corresponding time t 2min and the maximum value Temp 2max and the time t at that point 2max T 2下降 =t 2min -t 1max T 2上升 =t 2max -t 2min , t 2max The time is taken as the starting point of a new cycle, and the new value is obtained by rolling in sequence.

[0134] The real-time metric values ​​are recorded in a total of 5 sets, namely the period start time t. star descent time T 下降 and rise time T 上升 Maximum temperature within the cycle: Temp max and minimum value Temp min .

[0135] t star =t max(上组) The starting time is the maximum temperature (Temp) of the last complete cycle at the corresponding scale time. max The corresponding time t max .

[0136] T 下降 =t min -t star ;

[0137] T 上升 =t max -t min ;

[0138] The remaining 4 sets of values ​​T 下降 T 上升 Temp max and Temp min Each time a new value is obtained, it is updated by adding 1 / 16 of the original value to 15 / 16. All four sets of values ​​are averaged using this method.

[0139] That is: Current value = New value * 1 / 16 + Old value * 15 / 16.

[0140] The last five sets of recorded rolling values ​​were used as correction parameters.

[0141] Based on the approximate linear formula for the relationship between temperature and time:

[0142] Temp 降=a 降 t+b 降 Temp 升 =a 升 t+b 升 ;

[0143] Also: t = t 当前 -t star ;

[0144] The coefficient 'a' of the approximate linear formula above can be calculated using 5 sets of values. 降 b 降 a 升 b 升 :

[0145] a 降 =(Temp min -Temp max ) / T 下降 ;

[0146] b 降 =Temp max ;

[0147] a 升 =(Temp max -Temp min ) / T 上升 ;

[0148] b 升 =Temp min .

[0149] Step 5: Calculate the detector bias correction function and parameters over time.

[0150] The expected gain is to stabilize at G. 标准 However, the actual gain changes with temperature as G 实测 Therefore G 增益 This is a result of temperature effects; we want to compensate for the temperature effects and stabilize the gain at G. 标准 This requires adjusting the bias voltage ΔV, which changes the gain value by ΔG = G. 增益 -G 标准

[0151] Based on the known test results:

[0152] G 标准 =a 增益 ×Temp 标准 +b 增益 ;

[0153] Temp 标准 It is a definite value, representing the detector's expected average operating temperature;

[0154] G增益 =a 增益 ×Temp+b 增益 ;

[0155] ΔG=a 偏压 ×ΔV+b 偏压 ;

[0156] Given: ΔG = G 增益 -G 标准 ;

[0157] The bias voltage versus temperature relationship function can be derived:

[0158] a 偏压 ×ΔV+b 偏压 =a 增益 ×(Temp-Temp 标准 );

[0159]

[0160] a 偏压 b 偏压 a 增益 and b 增益 To obtain known parameters for measurement;

[0161] In ΔV, the variable is temperature (Temp), and Temp is a piecewise function divided into Temp... 降 and Temp 升

[0162] Temp 降 =a 降 t+b 降 Temp 升 =a 升 t+b 升 ;

[0163] It can be known that:

[0164]

[0165]

[0166] In the formula, all coefficients except t are known values. Five sets of data are substituted into the formula based on the real-time measurement records.

[0167] Substitute 5 sets of data into parameter a 降 b 降 a 升 b 升 Therefore, we can conclude that:

[0168]

[0169]

[0170] t 当前 The time it takes to acquire data in real time is a variable.

[0171] ΔV 降 and ΔV 升 Judgment conditions:

[0172] Remainder = (t) 当前 -t star ) / (T 下降 +T 上升 The remainder of ).

[0173] Remainder ≤ T 下降 For the descent period, use the formula ΔV 降 ;

[0174] Remainder > T 下降 For the rising cycle, use the formula ΔV 升 ;

[0175] The above formula is written into the front-end FPGA as a correction formula and used when collecting patient data.

[0176] Step 6: Implement real-time gain correction using FPGA.

[0177] When the PET system is idle, the back-end FPGA controls the front-end FPGA to continuously perform real-time online calibration. The back-end FPGA analyzes and calculates the real-time calibration. When the control software interface issues a data acquisition command to the system, the rolling calibration calculation stops. The last set of analyzed and calculated calibration values, totaling 5 sets, are retrieved from the back-end FPGA. star and descent time T 下降 and rise time T 上升 and Temp max and Temp min The data is uploaded as a parameter to the front-end FPGA and then the data acquisition begins.

[0178] The front-end FPGA determines whether the temperature should be rising or falling based on the actual data acquisition time, calculates the bias value in real time, and adjusts the bias voltage of each detector, thus correcting the gain of the photomultiplier tube in real time to mitigate the impact of temperature. It can perform normal energy path integration through a single-stage event that triggers a threshold, then filter by energy window, followed by time conformity filtering, and finally store the raw data on the computer, awaiting subsequent reconstruction into a PET image.

[0179] In this embodiment, whether the real-time data acquisition can correctly correct the gain can be compared by the change in the count rate of the fixed bucket source. When no real-time correction is performed, it can be seen that the gain changes due to temperature changes in the single-lift energy window data, and the count rate of the energy window shows a certain regular change. When real-time correction is used, the difference in the count rate decreases significantly.

[0180] The method in this embodiment does not increase the system waiting dead time for temperature acquisition and judgment, and does not affect data acquisition; it continuously acquires the periodic function parameters of the scale temperature change during idle time, ensuring that the bias voltage adjustment function model can be accurately predicted over time when acquiring patient data without temperature acquisition; it also ensures that the gain of the PET detector remains stable during patient data acquisition.

[0181] Furthermore, the method of this embodiment can maximize the high threshold and reduce invalid high threshold data during use, ensuring that the high threshold used for triggering judgment is relatively stable, reducing system dead time under high activity conditions, and improving the sensitivity of the PET system.

[0182] In other words, the high threshold itself is usually stable. However, because the signal waveform size varies with temperature, although the high threshold remains constant, the actual over-threshold count rate changes with temperature, making the high threshold relatively unstable. The closer the high threshold is to the lower limit of the energy window, the better. However, since the waveform signal size varies, it's equivalent to the high threshold changing. To ensure the high threshold does not exceed the lower limit of the energy window, a margin needs to be left, allowing more invalid events to pass through the threshold to prevent the loss of valid events. The backend can filter out these invalid events through integration, but this consumes system transmission and computing resources and increases system dead time. Therefore, the method in this embodiment can maximize the high threshold and reduce invalid over-threshold data during use, ensuring the high threshold used for triggering judgment is relatively stable.

[0183] It should be noted that any reference numerals placed between parentheses in the claims should not be construed as limiting the claims. The word "comprising" does not exclude the presence of components or steps not listed in the claims. The word "a" or "an" preceding a component does not exclude the presence of a plurality of such components. The invention can be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In claims that enumerate several means, several of these means may be embodied by the same hardware. The use of the terms first, second, third, etc., is merely for convenience of expression and does not indicate any order. These terms can be understood as part of the component names.

[0184] Furthermore, it should be noted that in the description of this specification, the terms "one embodiment," "some embodiments," "embodiment," "example," "specific example," or "some examples," 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 expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Furthermore, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0185] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the claims should be interpreted to include both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0186] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, then this invention should also include these modifications and variations.

Claims

1. A method for gain compensation by bias adjustment of a silicon photomultiplier tube, characterized in that, include: S10. For each unit detector in the PET system, the FPGA determines whether the bias value of the unit detector needs to be corrected based on the working status of the unit detector. S20. If the unit detector is in an idle state, the FPGA obtains the bias voltage parameter used to adjust the unit detector, and the gain compensation information corresponding to the bias voltage and the operating temperature of the unit detector over time based on the bias voltage parameter and the curve of the operating temperature of the unit detector. S30. Based on the gain compensation information, the FPGA performs gain compensation on the process data in the usage state of the unit detector to obtain the corrected detection data as the original data for reconstructing the PET image. S20 includes: S21. The FPGA acquires a first curve of the operating temperature and gain change of the unit detector based on a first preset time period. S22, The FPGA obtains a second curve showing the change of unit detector gain with bias voltage based on a second preset time period; S23. The FPGA obtains a third curve of the working temperature of the unit detector changing with time based on a third preset time period, and processes it in an approximately linear fitting manner to obtain the result. S24. Based on the results of the first curve, the second curve, and the approximate linear fitting process, obtain information on the time-varying bias voltage used to keep the gain stable, and obtain the gain compensation information. The first preset time period is longer than the second preset time period, and longer than the third preset time period, and the second preset time period is different from the first preset time period.

2. The method according to claim 1, characterized in that, S21 includes: S211. The operating temperature of each unit detector is read using the temperature sensor of each unit detector; S212. With the radiation barrel placed in the middle of all unit detectors, record the energy peak at 511 keV in the single crystal energy spectrum within one cycle to obtain the operating temperature and peak position variation point of each single crystal strip. S213. Adjust the operating temperature of the unit detector, obtain multiple peak position change information and normalize it, and use the average peak position of all single crystal strips of the unit detector to characterize the peak position of the unit detector, and obtain the first curve of the operating temperature and gain change of the unit detector. The first curve is represented as: G 增益 (Temp) = a 增益 ×Temp +b 增益 ; Formula (k1); The coefficient 'a' was obtained through linear fitting. 增益 and b 增益 Temp is the operating temperature, G 增益 (Temp) Gain as a function of operating temperature.

3. The method according to claim 1, characterized in that, S22 includes: A radiation source is placed in the middle region of the detector in the PET system, and the operating temperature of the unit detector is fixed. The FPGA adjusts the bias value of the unit detector, and for each bias value, the single-event data is statistically analyzed based on integer multiple periods. Based on the information of gain and corresponding voltage under standard conditions, the information of the relationship between the change value of single-stage event data and the bias voltage difference is obtained as the second curve of the gain factor difference changing with the bias voltage. The second curve is represented as: ΔG = a 偏压 ×ΔV + b 偏压 , formula (k2); The coefficient 'a' was obtained through linear fitting. 偏压 and b 偏压 ΔV is the bias voltage difference, and ΔG is the gain factor difference.

4. The method according to claim 1, characterized in that, S23 includes: The third curve showing the change of the operating temperature of the detector in the measurement unit over time; The third curve is represented as: Temp 降 =a 降 t+b 降 Temp 升 =a 升 t+b 升 ;Formula (k3) The real-time calibration retains 5 sets of recorded values, each set including: the start time of the period t star descent time T 下降 and rise time T 上升 Maximum temperature within the cycle: Temp max and minimum value Temp min ; Approximate linear fitting methods include: t star =t max（上组） The starting time is the maximum temperature (Temp) of the last complete cycle at the corresponding scale time. max The corresponding time t max ; T 下降 =t min -t star ;T 上升 =t max -t min ; Each time a new value is obtained, it is updated by adding 1 / 16 of the original value to 15 / 16. The remaining 4 sets of values ​​T 下降 T 上升 Temp max and Temp min All are averaged using this method on a rolling basis; That is: Current value = New value * 1 / 16 + Old value * 15 / 16; Let: t=t 当前 -t star The formula coefficient 'a' is obtained based on 5 sets of values. 降 b 降 a 升 b 升 ; a 降 =(Temp min -Temp max ) / T 下降 ;b 降 =Temp max ; a 升 =(Temp max -Temp min ) / T 上升 ;b 升 =Temp min 。 5. The method according to claim 4, characterized in that, The real-time calibration retains 5 sets of recorded values, including: Determine the initial period rise time T using either offline analysis with average period and average temperature extremes, or by using records from the previous calibration. 0上升 and descent time T 0下降 Maximum initial temperature (Temp) 0max and minimum starting temperature Temp 0min ; FPGA in the first cycle range (T) 0上升 +T 0下降 Get the maximum temperature (Temp) within the first cycle. 1max and the time t for the maximum temperature 1max And the minimum temperature of the first cycle, Temp. 1min and t 1min ; ΔT=t 1min -t 1max If the time difference is greater than 0, then ΔT is used as the new descending cycle, represented by T. 1下降 This means that if the difference ΔT is less than 0, then ΔT is used as the new downward cycle. 1上升 express; Perform cycle start point correction, t 1max The time is taken as the starting point of a new cycle, and a new minimum value Temp is sought within the extended interval of the new cycle. 2min and corresponding time t 2min and the maximum value Temp 2max and time t 2max T 2下降 =t 2min -t 1max T 2上升 =t 2max -t 2min , t 2max The time is taken as the starting point of a new cycle, and the new value is obtained by rolling in sequence.

6. The method according to claim 4, characterized in that, S24 includes: If the gain is stable at G 标准 Then, adjusting the bias voltage ΔV will change the gain value by ΔG = G. 增益 -G 标准 ; Based on known test results: G 标准 =a 增益 × Temp 标准 + b 增益 ; Temp 标准 It is a definite value, representing the detector's expected average operating temperature; G 增益 =a 增益 × Temp + b 增益 ;ΔG=a 偏压 ×ΔV + b 偏压 =G 增益 -G 标准 ; The bias voltage versus temperature relationship function is as follows: a 偏压 ×ΔV + b 偏压 =a 增益 ×(Temp -Temp 标准 ); ΔV = (a 增益 × (Temp - Temp 标准 )) - b 偏压 )) / a 偏压 ; Equation (k4) a 偏压 b 偏压 a 增益 and b 增益 To obtain known parameters for measurement.

7. The method according to claim 6, characterized in that, S24 includes: The variable in ΔV is temperature (Temp), based on the third curve to which Temp belongs, according to formula (k3): get: ; ； Based on coefficient a 降 b 降 a 升 b 升 and t=t 当前 -t star ; get: ; ； t 当前 The time it takes to acquire the data in real time is a variable; ΔV 降 and ΔV 升 Judgment conditions: Remainder = (t) 当前 -t star ) / ( T 下降 +T 上升 The remainder of ). Remainder ≤ T 下降 For the descent period, use the formula ΔV 降 ; Remainder > T 下降 For the rising cycle, use the formula ΔV 升 .

8. The method according to any one of claims 1 to 7, characterized in that, S30 includes: Based on the gain compensation information, the FPGA adjusts the bias voltage of the unit detector according to the bias voltage value to which the gain compensation information belongs during the use state of the unit detector, so as to correct before passing the energy window, and then sequentially passes through the energy window screening and time coincidence screening to obtain the corrected detection data as the original data for reconstructing the PET image.

9. A detection device, characterized in that, include: Based on silicon photomultiplier tubes, unit detectors and FPGAs are used, with all unit detectors electrically connected to the FPGA, and the FPGA executes a silicon photomultiplier tube bias adjustment gain compensation method as described in any one of claims 1 to 7.

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