Multichannel data processing methods, devices, computer storage media, computer program products, and radiation detection systems

Abstract

This application discloses a multi-channel data processing method, apparatus, computer storage medium, computer program product, and radiation detection system. The multi-channel data processing method includes: acquiring time and energy information of several photoelectric conversion channels triggered by each target event; determining the maximum energy based on all the energy information, and determining several target channels based on the maximum energy; and determining the arrival time of the event by performing an energy-weighted average based on the energy and time information of all target channels. This application fully utilizes the correlation between photon statistics and time measurement accuracy from a physical perspective, introducing energy as a weighting factor, which enables the reconstructed arrival time to align with the photoelectric conversion channel with stronger optical signal and less time jitter, thereby improving time resolution.

Description

Technical Field

[0001] This invention relates to the field of data processing, and in particular to a multi-channel data processing method, apparatus, computer storage medium, computer program product, and radiation detection system. Background Technology

[0002] Studies have found that due to the influence of the light emission process and optical propagation characteristics in scintillation crystals, a single gamma-photon event often leads to multiple photoelectric conversion channels simultaneously receiving visible light signals, especially in structures where there is no one-to-one mapping between the crystal and the photoelectric conversion device. This triggers multiple time channels in most cases, degrading time resolution performance. Generally, the main causes of this phenomenon can be attributed to two categories: intercrystalline scattering and light diffusion. Intercrystalline scattering can be eliminated through event filtering, while the multi-time channel triggering caused by light diffusion cannot be eliminated by filtering. This is because in structures where there is no one-to-one mapping between the crystal and the photoelectric conversion device, light diffusion is fundamental to reconstructing the accurate position of the crystal. The reconstruction of the position spectrum relies on information provided by multiple photoelectric conversion channels that receive visible light. This means that, theoretically, the more photoelectric conversion channels that receive visible light and output waveforms, the better the position resolution.

[0003] Unlike location reconstruction, which requires multiple energy information points, time information typically extracts only the arrival time at a threshold point. Multiple time information points can introduce leading or lagging time errors. Common time extraction methods are based on signal filtering, selecting a single time signal to obtain accurate time. In scintillation detectors, due to the diffusion and reflection effects of light within the crystal, a single gamma photon interaction often generates responses in multiple adjacent readout channels, resulting in significant signal energy dispersion. In this case, using only the time information corresponding to a single channel for event timing easily introduces statistical fluctuations and systematic biases, thereby degrading time resolution performance.

[0004] Therefore, how to extract time information that is closer to the actual incident time from multiple time signals has become a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0005] Therefore, it is necessary to provide a multi-channel data processing method, apparatus, computer storage medium, computer program product, and radiation detection system to address at least one technical problem existing in traditional solutions.

[0006] According to a first aspect of this application, a multi-channel data processing method is provided, comprising: acquiring time information and energy information of several photoelectric conversion channels triggered by each target event; determining a maximum energy based on all the energy information, and determining several target channels based on the maximum energy; and determining the arrival time of the event by performing an energy-weighted average based on the energy information and time information of all target channels.

[0007] According to one embodiment of this application, determining a maximum energy based on all the energy information and determining a plurality of target channels based on the maximum energy includes: determining a maximum energy based on all the energy information, determining candidate channels based on the maximum energy, and determining the target channels among the candidate channels.

[0008] According to one embodiment of this application, the energy of each candidate channel is greater than or equal to 30% of the maximum energy.

[0009] According to one embodiment of this application, after determining the maximum energy based on all the energy information and determining several target channels using the maximum energy, the multi-channel data processing method further includes: obtaining the corresponding time information for all the target channels through a channel index.

[0010] According to one embodiment of this application, after determining the maximum energy based on all the energy information and determining several target channels with the maximum energy, the multi-channel data processing method further includes: removing target channels with invalid time information and performing an energy-weighted average process on the remaining target channels.

[0011] According to one embodiment of this application, after determining the maximum energy based on all the energy information and determining several target channels with the maximum energy, the multi-channel data processing method further includes: determining whether the number of target channels with valid time information is greater than a preset threshold; if it is greater, removing target channels with invalid time information and performing an energy-weighted average process with the remaining target channels; otherwise, selecting the remaining channels from all channels or candidate channels as substitutes for the removed channels and performing an energy-weighted average process with all the substitute target channels.

[0012] According to one embodiment of this application, the arrival time of the event is determined by energy-weighted averaging based on the energy information and time information of all target channels, including: calculating the energy-weighted average using the following formula (1): Formula (1) in, Indicates the target channel number. Indicates the first The energy value of each target channel Indicates the first Time values ​​for each target channel Indicates the arrival time of the event.

[0013] According to one embodiment of this application, the arrival time of the event is determined by energy-weighted averaging based on the energy information and time information of all target channels, including: calculating the energy-weighted average using the following formula (2): Formula (2) in, Indicates the target channel number. Indicates the first The energy value of each target channel Indicates the first Time values ​​for each target channel Indicates the first The weights of the energy and time values ​​corresponding to each target channel Indicates the arrival time of the event.

[0014] According to one embodiment of this application, before acquiring the time information and energy information of several photoelectric conversion channels triggered by each target event, the multi-channel data processing method further includes: acquiring the event generated by gamma photon incident; and eliminating inter-crystal scattering events by using the pre-determined event regions corresponding to each scintillation crystal and the coordinates of each event.

[0015] According to one embodiment of this application, the process of determining the event regions on each predetermined scintillation crystal includes: determining the aggregation position of non-scattering events and the location information of scattering events corresponding to each scintillation crystal based on the positioning information of several events in the scintillation crystal or crystal array; and dividing the event regions of the corresponding scintillation crystal based on the aggregation position of non-scattering events and the location information of scattering events.

[0016] According to one embodiment of this application, inter-crystal scattering events are eliminated by using the pre-determined event regions corresponding to each scintillation crystal and the coordinates of each event. This includes: for each event, obtaining its position coordinates on the crystal; if the position coordinates are located within any event region, the event is identified as a target event; otherwise, it is identified as an inter-crystal scattering event and eliminated.

[0017] According to a second aspect of this application, a multi-channel data processing apparatus is provided, comprising: a second acquisition module configured to acquire time information and energy information of a plurality of photoelectric conversion channels triggered by each target event; a target channel determination module configured to determine a maximum energy based on all the energy information, and determine a plurality of target channels based on the maximum energy; and an energy weighted averaging module configured to perform an energy weighted averaging based on the energy information and time information of all target channels to determine the arrival time of the event.

[0018] According to one embodiment of this application, the target channel determination module is configured to determine the maximum energy based on all the energy information, determine candidate channels through the maximum energy, and determine the target channel among the candidate channels.

[0019] According to one embodiment of this application, the energy of each candidate channel is greater than or equal to 30% of the maximum energy.

[0020] According to one embodiment of this application, the multi-channel data processing apparatus further includes an index module configured to obtain corresponding time information for all the target channels through a channel index.

[0021] According to one embodiment of this application, the target channel determination module is configured to eliminate target channels with invalid time information and perform an energy-weighted average process on the remaining target channels.

[0022] According to one embodiment of this application, the target channel determination module is configured to determine whether the number of target channels with valid time information is greater than a preset threshold. If it is greater, the target channels with invalid time information are removed and the remaining target channels are used to perform an energy-weighted average process. Otherwise, the remaining channels are selected from all channels or candidate channels as substitutes for the removed channels and the remaining target channels are used to perform an energy-weighted average process.

[0023] According to one embodiment of this application, the energy weighted averaging module is configured to perform energy weighted averaging calculation using the following formula (1): Formula (1) in, Indicates the target channel number. Indicates the first The energy value of each target channel Indicates the first Time values ​​for each target channel Indicates the arrival time of the event.

[0024] According to one embodiment of this application, the energy weighted averaging module is configured to perform energy weighted averaging calculation using the following formula (2): Formula (2) in, Indicates the target channel number. Indicates the first The energy value of each target channel Indicates the first Time values ​​for each target channel Indicates the first The weights of the energy and time values ​​corresponding to each target channel Indicates the arrival time of the event.

[0025] According to one embodiment of this application, the multi-channel data processing apparatus further includes: a first acquisition module configured to acquire events generated by gamma photon incident; and a scattering event filtering module configured to filter out inter-crystal scattering events by using predetermined event regions on each scintillation crystal and the coordinates of each event.

[0026] According to one embodiment of this application, the scattering event filtering module is configured to: determine the aggregation position of non-scattering events and the position information of scattering events on each scintillation crystal based on the positioning information of several events in the scintillation crystal or crystal array; and divide the event region of the corresponding scintillation crystal based on the aggregation position of the non-scattering events and the position information of the scattering events.

[0027] According to one embodiment of this application, the scattering event filtering module is configured to obtain the position coordinates of each event on the crystal. If the position coordinates are located within any event region, the event is identified as a target event; otherwise, it is identified as an inter-crystal scattering event and rejected.

[0028] According to one embodiment of this application, the first acquisition module includes a detector, which includes a scintillation crystal, a photoelectric conversion device, and a readout electronics section. The scintillation crystal and the photoelectric conversion device are not coupled one-to-one, and the photoelectric conversion device and the readout electronics section correspond one-to-one.

[0029] According to a third aspect of this application, a computer storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the steps of the multi-channel data processing method as described in any of the above claims.

[0030] According to a fourth aspect of this application, a computer program product is provided, comprising a computer program or instructions that, when executed by a processor, implement the steps of the multichannel data processing method as described in any of the above claims.

[0031] According to a fifth aspect of this application, a radiation detection system is provided, including a multi-channel data processing device as described in any of the preceding claims.

[0032] The multi-channel data processing method, apparatus, computer storage medium, computer program product, and radiation detection system provided in this application fully utilize the correlation between photon statistics and time measurement accuracy in a physical sense. Generally, channels with higher energy correspond to stronger optical signals, and their time measurements are less affected by photon statistical fluctuations and electronic noise; therefore, they should have a higher weight in data processing. By introducing energy as a weighting factor, the data processing method provided in this application naturally aligns the obtained arrival times with channels that have stronger optical signals and lower time jitter. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in the embodiments of this specification or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0034] Figure 1 This is a schematic diagram of a non-one-to-one mapping coupling between a scintillation crystal and a photoelectric conversion device. Figure 2 A diagram illustrating the multichannel triggering phenomenon caused by light diffusion; Figure 3 To and Figure 2 The corresponding electrical signal diagrams of the four triggered SiPM outputs; Figure 4 This is a flowchart illustrating a multi-channel data processing method in one embodiment of this application; Figure 5 This is a flowchart illustrating a multi-channel data processing method in another embodiment of this application; Figure 6 This is a map of the event regions on each predetermined scintillation crystal in one example of this application; Figure 7 This is a flowchart illustrating a multi-channel data processing method in yet another embodiment of this application. Figure 8 This is a flowchart illustrating a multi-channel data processing method in yet another embodiment of this application. Figure 9(a) shows the distribution of CTR in the fastest time extraction method; Figure 9(b) shows the overall conformity time difference distribution in the fastest time extraction method; Figure 10(a) shows the distribution of CTR in the maximum energy extraction method; Figure 10(b) shows the overall coincidence time difference distribution in the maximum energy extraction method; Figure 11(a) shows the distribution of CTR when the position spectrum inversion extraction method is rounded up; Figure 11(b) shows the overall coincidence time difference distribution when the position spectrum inversion extraction method is rounded up; Figure 12(a) shows the distribution of CTR when the position spectrum inversion extraction method is rounded down; Figure 12(b) shows the overall coincidence time difference distribution when the position spectrum inversion extraction method is rounded down; Figure 13(a) shows the distribution of CTR in the reconstruction method provided in this application; Figure 13(b) shows the overall coincidence time difference distribution in the reconstruction method provided in this application; Figure 14(a) shows the average coincidence time resolution distribution of the fastest time extraction method in the row direction; Figure 14(b) shows the average conformance temporal resolution distribution of the reconstruction method provided in this application in the row direction; Figure 14(c) shows the average coincidence time resolution distribution of the fastest time extraction method in the column direction; Figure 14(d) shows the average conformance temporal resolution distribution of the reconstruction method provided in this application in the row direction; Figure 15 This is a schematic diagram of the structure of a multi-channel data processing device in one embodiment of this application; Figure 16 This is a schematic diagram of the structure of a multi-channel data processing device in another embodiment of this application; Figure 17 This is a schematic diagram of the structure of a multi-channel data processing device in yet another embodiment of this application; Figure 18 This is a schematic diagram of the structure of a computer system in one embodiment of this application; Figure 19 This is an internal structural diagram of a computer device in one embodiment of this application. Detailed Implementation

[0035] To make the above-mentioned objectives, features, and advantages of this application more readily understood, the specific embodiments of this application are described in detail below with reference to the accompanying drawings. Many specific details are set forth in the following description to provide a thorough understanding of this application. However, this application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of this application. Therefore, this application is not limited to the specific embodiments disclosed below.

[0036] It should be noted that when an element is said to be "fixed to" another element, it can be directly fixed to the other element or there may be an intervening element. When an element is said to be "connected to" another element, it can be directly connected to the other element or there may be an intervening element. The terms "substantially equal" or "substantially equal to" as used herein mean that the difference between the two lies within a range of errors considered equivalent in the art. The terms "vertical," "horizontal," "left," "right," and similar expressions used herein are for illustrative purposes only.

[0037] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. The terms “and / or” or “and / or” as used herein include any and all combinations of one or more of the associated listed items.

[0038] To provide those skilled in the art with a deeper understanding of light diffusion, it is further described here. Figure 1 The diagram shows a structure in which crystal 10 and photoelectric conversion device 20 (e.g., SiPM) are not coupled in a one-to-one correspondence, where blue dashed arrows represent light diffusion and yellow dashed arrows represent inter-crystal scattering. Figure 2 The phenomenon of multichannel triggering caused by light diffusion is shown. Figure 3 It shows the relationship with Figure 2 The corresponding electrical signals F1~F4 output by the four triggered SiPMs are transmitted through... Figure 3 It can be observed that all four triggered SiPMs output electrical signals. These electrical signals represent the relationship between the triggering time and voltage amplitude of the corresponding SiPM. The time-amplitude relationships of the four electrical signals are different. Therefore, it is necessary to determine the time information that is closer to the actual incident time from the four time-amplitude relationships.

[0039] To address this issue, existing technologies commonly employ methods such as the fastest time extraction method, the time selection method based on the energy maximum channel, and the time selection method based on position spectrum inversion.

[0040] The fastest time extraction method is based on the prior physical properties of time information. Specifically, in the same gamma-photon interaction event, the signal that first crosses the discrimination threshold usually corresponds to the channel where the photon arrives earliest or where the light propagation path is shortest. This method is simple to implement, requires relatively low hardware and computational resources, and can effectively avoid the time averaging effect caused by multi-channel superposition, achieving superior time resolution performance in most cases. However, this method is sensitive to noise and dark counting, and may introduce the risk of false triggering when the optical signal is weak or the response between channels is uneven.

[0041] The timing selection method based on the channel with the highest energy utilizes the correlation between energy and time information. It posits that, under light-sharing conditions, the channel with the highest energy deposition often corresponds to the SiPM pixel closest to the photon interaction position, making its timing signal more statistically representative. Compared to the fastest timing extraction method, this method can suppress timing jitter caused by edge channels, optical crosstalk, or weak light signals to some extent, and is more advantageous in obtaining stable timing information under conditions of significant multi-channel light sharing. However, its performance depends on the accuracy of energy measurement and the consistency of energy-time correlation.

[0042] The time selection method based on position spectrum inversion utilizes the spatial distribution information of the crystal in the position spectrum to inversely deduce the SiPM channel corresponding to the γ-photon interaction position, and uses the fast output signal of this channel as the source of event time information. In practical applications, this method may encounter situations where the crystal position is located at the boundary of adjacent SiPM channels, leading to uncertainty in event attribution. To address this issue, two different partitioning strategies can be employed: a floor-down strategy, where the crystal position at the boundary of two adjacent SiPM channels is assigned to the SiPM channel with the smaller number; and a floor-up strategy, assigning the position to the SiPM channel with the larger number. These partitioning principles apply the same processing method in both row and column directions. By introducing a position spectrum-based time selection strategy, spatial information can be used to constrain time channel selection to a certain extent, effectively avoiding interference from non-dominant optical path channels in time extraction, and providing a foundation for subsequent performance comparison and optimization of different time selection strategies.

[0043] However, the methods described above are fundamentally based on signal filtering, selecting a single time signal to obtain accurate time. In scintillation detectors, due to the diffusion and reflection effects of light within the crystal, a single gamma interaction often generates responses in multiple adjacent readout channels, resulting in significant dispersion of signal energy. In this case, using only the time information corresponding to a single channel for event timing easily introduces statistical fluctuations and systematic biases, thereby degrading time resolution performance.

[0044] In view of the technical problems existing in the prior art, this application proposes a multi-channel data processing method, apparatus and supporting applications that can at least optimize time resolution performance.

[0045] In some embodiments, the multi-channel data processing method can be executed by a multi-channel data processing device. For example, the multi-channel data processing method can be partially or wholly stored in a storage device (such as the built-in storage module of the detection device or an external storage device) in the form of a program or instructions, which, when executed, can implement the multi-channel data processing method. The multi-channel data processing device disclosed in this application for implementing the above-mentioned multi-channel data processing method can be either a device with a large amount of computing resources (e.g., a computer, server, cloud computing, etc.) or a device with limited computing resources (e.g., FPGA (Field Programmable Gate Array) chip board, ASIC (Application-Specific Integrated Circuit) chip board, and other hardware circuits).

[0046] 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.

[0047] Figure 4 This is a flowchart illustrating a multi-channel data processing method in one embodiment of this application; Figure 5 This is a flowchart illustrating a multi-channel data processing method in another embodiment of this application. In one embodiment, the multi-channel data processing method may include steps 100 to 500. It should be noted that steps 100 and 200 are optional steps. The multi-channel data processing method provided in this application can be based on events that have been pre-acquired and intercrystalline scattering events have been eliminated. That is, the method steps provided in this application can be executed starting from step 300.

[0048] Step 100: Obtain the event generated by the gamma photon incident.

[0049] This data can be acquired through a detector and a data processing system. The detector includes a scintillation crystal, a photoelectric conversion device, and readout electronics. The scintillation crystal and the photoelectric conversion device are not coupled one-to-one; multiple scintillation crystals can be coupled to a single photoelectric conversion device, or... Figure 1 One or more scintillation crystals in the illustrated scintillation crystal array correspond to multiple adjacent photoelectric conversion devices. In one example, a scintillation crystal array containing 20×20 crystals is coupled to a photoelectric conversion array containing 8×8 SiPMs.

[0050] The scintillation crystal can be any one of NaI, CsI, LYSO, YSO, LaBr3:Ce, or BGO, and the photoelectric conversion device can be any one of a photomultiplier tube (PMT), photodiode, or silicon photomultiplier (SiPM), preferably SiPM. The crystal's function is to convert the gamma photon-generated rays into visible light signals, and the photoelectric conversion device's function is to convert the visible light signals into scintillation pulses. Further, the scintillation pulses are digitally sampled by the readout electronics at the back end of the photoelectric conversion device. Taking multi-voltage threshold sampling as an example, multiple voltage thresholds need to be preset using a digital-to-analog converter (DAC) before sampling. By recording the time information of the scintillation pulse crossing these voltage thresholds, a series of "time-voltage" pairs are obtained. Then, the data processing system combines the prior information of the scintillation pulses and uses a fitting method to reconstruct the original information of the pulses, including the position, energy, and time information of the original signal. The original signal is then processed to obtain several events. This process can be implemented using methods already described in existing technologies, and will not be elaborated upon in this application.

[0051] Step 200: Eliminate inter-crystal scattering events by using the pre-determined event regions corresponding to each scintillation crystal and the coordinates of each event.

[0052] Figure 6 The illustration shows predetermined event regions corresponding to each scintillation crystal in one example, where the rectangular area enclosed by the red line surrounding the white light spot is the event region of the corresponding scintillation crystal. It is understood that in other examples, the event regions may be other shapes, such as irregular shapes, circles, or ellipses. It is also understood that the shapes of the event regions on different scintillation crystals in the same scintillation crystal array may be the same, not exactly the same, or completely different. Furthermore, one event region is provided corresponding to each scintillation crystal.

[0053] For methods of determining event regions, existing technologies can be referenced. In a preferred example, a method is provided that is particularly suitable for determining the non-one-to-one coupling structure of the scintillation crystal and photoelectric conversion device of this application. This method generally follows the following steps: based on the positioning information of several events in the scintillation crystal or crystal array, the aggregation position of non-scattering events and the position information of scattering events on each scintillation crystal are determined; the event region of the corresponding scintillation crystal is divided based on the position information of the non-scattering events and scattering events at the aggregation position. For each event in subsequent acquisition, its position coordinates on the scintillation crystal are obtained. If the position coordinates are located within any event region, the event is identified as a target event; otherwise, it is identified as an inter-crystal scattering event and discarded. Among the target events that are not discarded, in addition to normal events, there are actually light scattering events. These light scattering events will cause temporal resolution degradation. Based on the analysis of the background technology, light scattering events are not suitable for rejection. Therefore, this application takes a different approach and uses a multi-channel data processing method to determine the temporal information of all target events to solve the problem of temporal resolution degradation caused by light scattering events.

[0054] Step 300: Obtain the time and energy information of several photoelectric conversion channels triggered by each target event.

[0055] The aforementioned photoelectric conversion channels can be all photoelectric conversion channels triggered by the target event, or a selection of them. For example, photoelectric conversion channels that are far from the photoelectric conversion channels with the highest, second highest, or higher energy can be eliminated to reduce interference.

[0056] Generally, different gamma photons are incident into the detector in a specific time sequence. Therefore, the target event can be roughly distinguished by the timing information of the photoelectric conversion channel being triggered. For example, if multiple timing information points are within the same time period (e.g., 20 ns), then these timing information points are considered to belong to the same target event. Furthermore, the energy information belonging to the same target event can be filtered. For example, an energy range can be set according to the incident photon energy, such as 200 keV to 600 keV. The initially obtained energy information can be finely filtered to remove energy information outside the energy range. The remaining energy information and its corresponding timing information serve as the data basis for step 400.

[0057] Step 400: Determine the maximum energy based on all the energy information, and determine several target channels based on the maximum energy.

[0058] For example, step 400 may sort all energy information, form all energy information into an energy vector, or form all energy information into a histogram to determine the maximum energy.

[0059] Optionally, step 400 may include: determining a maximum energy based on all the energy information, determining candidate channels based on the maximum energy, and determining the target channel from the candidate channels. The energy of the candidate channels may have a specific relationship with the maximum energy; for example, the energy of all candidate channels may be greater than or equal to 30% of the maximum energy, which can effectively suppress invalid channels introduced by noise or weak light diffusion while preserving the main optical signal contribution.

[0060] Furthermore, the process of determining the target channel from the candidate channels may include sorting the candidate channels by energy level and selecting the top few channels with the highest energy (e.g., 4) as the target channel to avoid introducing too many low-weight channels and causing noise accumulation.

[0061] Alternatively, in the method provided in this application, see [link to relevant documentation]. Figure 7 Between steps 400 and 500, step 410 may further include: obtaining the corresponding time information for all the target channels using the channel index. Since in some cases some channels may not generate valid time information, steps 420 and / or steps 430-450 may also be included after step 410, see [link to relevant documentation]. Figure 8 .

[0062] Step 420: Remove target channels with invalid time information and proceed to step 500 with the remaining target channels.

[0063] Step 430: Determine whether the number of target channels with valid time information is greater than a preset threshold; if yes, proceed to step 440: remove target channels with invalid time information and proceed to step 500 with the remaining target channels; otherwise, proceed to step 450: select the remaining channels from all channels or candidate channels as replacements (new target channels) for the removed channels and proceed to step 500 with all the replacement target channels. The number of replacement channels can be equal to, slightly less than, or slightly greater than the number of removed channels, but generally, the total number of replacement target channels must be greater than the preset threshold. The preset threshold can be set empirically, and its value can vary depending on the application scenario of the detector; generally, the preset threshold must be greater than or equal to 2.

[0064] Step 500: Determine the arrival time of the event by performing an energy-weighted average based on the energy and time information of all target channels.

[0065] Specifically, in the example of this application, the energy-weighted average can be calculated using the following formula (1): Formula (1) in, Indicates the target channel number. Indicates the first The energy value of each target channel Indicates the first Time values ​​for each target channel Indicates the arrival time of the event.

[0066] In the above example, the multi-channel data processing method provided in this application fully utilizes the correlation between photon statistics and time measurement accuracy in a physical sense. Generally, channels with higher energy correspond to stronger optical signals, and their time measurements are less affected by photon statistical fluctuations and electronic noise; therefore, they should have a higher weight in data processing. By introducing energy as a weighting factor, the data processing method provided in this application naturally aligns the acquired arrival times with channels that have stronger optical signals and lower time jitter.

[0067] Furthermore, in this application, the following formula (2) can also be used for energy weighted average calculation: Formula (2) in, Indicates the target channel number. Indicates the first The energy value of each target channel Indicates the first Time values ​​for each target channel Indicates the first The weights of the energy and time values ​​corresponding to each target channel Indicates the arrival time of the event.

[0068] Unlike the example in Equation (1), the example in Equation (2) further introduces the weights of each target channel, which can refine the contribution of each target channel to the arrival time and further optimize the time resolution.

[0069] To demonstrate the advantages of the multi-channel data processing method provided in this application compared to existing methods, the applicant conducted experiments using detectors of the same specifications. These detectors consisted of a 20×20 crystal array coupled to an 8×8 SiPM array. There was no one-to-one mapping between the crystals and SiPMs, but the readout circuits corresponded one-to-one with the SiPMs. By employing different extraction strategies for the photon arrival time of a single event, the corresponding coincidence time resolution (CTR) was calculated, and the performance of each method in terms of overall performance and spatial distribution consistency was evaluated. Table 1 summarizes the corresponding time resolution performance indicators for each aspect.

[0070] Table 1. Relationship between different time extraction methods and time resolution performance.

[0071] Time extraction method Overall CTR CTR mean CTR standard deviation CTR minimum / maximum Fastest extraction method 365.9 372.3 41.0 301.6 / 574.6 Maximum energy extraction method 369.5 380.2 66.2 301.2 / 1056.0 Position inversion method (rounding up) 374.1 390.7 82.2 300.0 / 985.4 Position inversion method (rounding down) 374.4 391.7 82.0 300.0 / 933.6 Energy weighting method 355.7 360.4 25.3 301.4 / 495.6

[0072] As shown in Table 1, among the traditional methods based on single-channel time signal selection, the fastest time extraction method exhibits the best overall time resolution performance, with an overall CTR of 365.9 ps and a mean and standard deviation of 372.3 ± 41.0 ps, ​​and the distribution is relatively concentrated. This indicates that, in the case of simultaneous triggering of multiple channels, prioritizing the selection of the earliest time signal to cross the threshold can reduce the accumulation of time jitter to a certain extent, demonstrating good feasibility and stability. The time selection method based on the channel with the highest energy achieves an overall time resolution of 369.5 ps, which is numerically close to that of the fastest time extraction method. However, its mean and standard deviation are 380.2 ± 66.2 ps, significantly higher than that of the fastest time extraction method, and the time resolution distribution is also more dispersed. This suggests that in some events, especially when multiple SiPM channels receive similar energies, selecting the time channel solely based on energy magnitude can easily introduce instability, leading to a decrease in time extraction consistency. The time selection method based on position spectrum inversion (regardless of whether it employs rounding up or rounding down strategies) exhibits relatively poor time resolution performance. Taking the round-up method as an example, the overall CTR is 374.1 ps, with a mean and standard deviation of 390.7 ± 82.2 ps. The results show that when the crystal position is close to the boundary region of adjacent SiPMs, this method has a certain degree of randomness in the selection of time channels, which significantly amplifies the time jitter and limits the overall time resolution.

[0073] Combining Table 1 and Figures 9(a) to 12(b), where the horizontal axis represents time and the vertical axis represents event counts, blue dots represent time spectra, and red curves represent Gaussian fitting curves, it can be observed that when the crystal is located in the SiPM interface region and the optical signal is received by multiple SiPM channels, the aforementioned traditional time extraction methods all produce obvious high-temporal-resolution degradation regions at the corresponding locations, manifested as high-value fringes distributed along the row or column directions in the image. This indicates that when the light-sharing effect is significant, the single-time-channel extraction strategy is insufficient to fully utilize multi-channel information and is unable to effectively suppress the degradation of temporal resolution performance.

[0074] In contrast, referring to Figures 13(a) and 13(b), the horizontal axis represents time, the vertical axis represents event count, the blue dots represent the time spectrum, and the red curves represent Gaussian fitting curves. The multi-channel data processing method provided in this application shows significant advantages in both overall performance and spatial consistency. Numerical results show that the multi-channel data processing method provided in this application achieves an overall time resolution of 355.7 ps, with a mean and standard deviation of 360.4 ± 25.3 ps. Not only is the overall CTR superior to the aforementioned traditional methods, but the dispersion of its time distribution is also significantly reduced. Spatially, the method of this application significantly alleviates the high time resolution degradation stripes caused by light sharing in the position spectrum. To further evaluate the improvement effect of this method on time resolution performance when the crystal is located in the SiPM interface region, the average coincidence time resolution distribution in the row and column directions is statistically analyzed, as shown in Figures 14(a) to 14(d), and compared with the fastest time extraction method. The results show that, in both directions, the regions with significantly higher local temporal resolution were effectively suppressed, and the temporal resolution distribution became more uniform.

[0075] From a physical perspective, when visible light generated by the interaction of gamma photons in a crystal is distributed across multiple SiPM channels, its energy and time information are shared across these channels. Therefore, simply selecting the time signal from one channel as the event time inevitably ignores the effective time information contained in other channels. The multi-channel data processing method provided in this application introduces a multi-channel energy distribution and weightedly fuses the time information from each channel. Without significantly increasing hardware complexity, it fully utilizes the complete time and energy information preserved by the one-to-one readout structure of the photoelectric conversion channel and the readout electronics, thereby effectively mitigating the negative impact of light diffusion on time resolution performance.

[0076] In summary, the multi-channel data processing method provided in this application can significantly improve the time resolution performance degradation problem caused by light sharing (light diffusion) in small crystal, high spatial resolution detectors, and provides a simple and effective solution for further improving time resolution performance while maintaining a simple hardware structure.

[0077] Based on the description of the above embodiments of the multi-channel data processing method, this application also provides a multi-channel data processing apparatus. The apparatus may include devices (including distributed systems), software (applications), modules, components, servers, clients, etc., using the methods described in the embodiments of this specification, combined with necessary hardware implementations. Based on the same innovative concept, the apparatuses in one or more embodiments provided in this application are as described in the following embodiments. Since the implementation schemes and methods for solving the problem by the apparatus are similar, the implementation of specific apparatuses in the embodiments of this specification can refer to the implementation of the foregoing methods, and repeated details will not be repeated. As used below, the terms "module" or "module group" can refer to a combination of software and / or hardware that implements a predetermined function. Although the apparatuses described in the following embodiments are preferably implemented in software, hardware implementations, or a combination of software and hardware, are also possible.

[0078] Figure 15 This is a schematic diagram of the structure of a multi-channel data processing device in one embodiment of this application; Figure 16 This is a schematic diagram of the structure of a multi-channel data processing device in another embodiment of this application. In one embodiment, the multi-channel data processing device 1500 may include a first acquisition module 1510, a scattering event filtering module 1520, a second acquisition module 1540, a target channel determination module 1550, and an energy-weighted averaging module 1560. It should be noted that in the multi-channel data processing device 1500 provided in this application, the first acquisition module 1510 and the scattering event filtering module 1520 are optional modules and can operate directly based on events that have been pre-acquired and in which intercrystalline scattering events have been eliminated.

[0079] Specifically, the first acquisition module 1510 is configured to acquire events generated by gamma photon incident light. The first acquisition module 1510 may include a detector and a data processing system. The detector includes a scintillation crystal, a photoelectric conversion device, and readout electronics. The scintillation crystal and the photoelectric conversion device are not coupled one-to-one; multiple scintillation crystals can be coupled to a single photoelectric conversion device, or... Figure 1 One or more scintillation crystals in the illustrated scintillation crystal array correspond to multiple adjacent photoelectric conversion devices. In one example, a scintillation crystal array containing 20×20 crystals is coupled to a photoelectric conversion array containing 8×8 SiPMs.

[0080] The scintillation crystal can be any one of NaI, CsI, LYSO, YSO, LaBr3:Ce, or BGO, and the photoelectric conversion device can be any one of a photomultiplier tube (PMT), photodiode, or silicon photomultiplier (SiPM), preferably SiPM. The crystal's function is to convert the gamma photon-generated rays into visible light signals, and the photoelectric conversion device's function is to convert the visible light signals into scintillation pulses. Further, the scintillation pulses are digitally sampled by the readout electronics at the back end of the photoelectric conversion device. Taking multi-voltage threshold sampling as an example, multiple voltage thresholds need to be preset using a digital-to-analog converter (DAC) before sampling. By recording the time information of the scintillation pulse crossing these voltage thresholds, a series of "time-voltage" pairs are obtained. Then, the data processing system combines the prior information of the scintillation pulses and uses a fitting method to reconstruct the original information of the pulses, including the position, energy, and time information of the original signal. The original signal is then processed to obtain several events. This process can be implemented using methods already described in existing technologies, and will not be elaborated upon in this application.

[0081] Specifically, the scattering event filtering module 1520 is configured to eliminate inter-crystal scattering events by using pre-determined event regions on each scintillation crystal and the coordinates of each event.

[0082] Figure 6 The illustration shows predetermined event regions corresponding to each scintillation crystal in one example, where the rectangular area enclosed by the red line surrounding the white light spot is the event region of the corresponding scintillation crystal. It is understood that in other examples, the event regions may be other shapes, such as irregular shapes, circles, or ellipses. It is also understood that the shapes of the event regions on different scintillation crystals in the same scintillation crystal array may be the same, not exactly the same, or completely different. Furthermore, one event region is provided corresponding to each scintillation crystal.

[0083] For methods of determining event regions, existing technologies can be referenced. In a preferred example, a method is provided that is particularly suitable for determining the non-one-to-one coupling structure of the scintillation crystal and photoelectric conversion device of this application. This method generally follows the following steps: based on the positioning information of several events in the scintillation crystal or crystal array, the aggregation position of non-scattering events and the position information of scattering events on each scintillation crystal are determined; the event region of the corresponding scintillation crystal is divided based on the aggregation position of the non-scattering events and the position information of the scattering events. For each event in subsequent acquisition, its position coordinates on the scintillation crystal are obtained. If the position coordinates are located within any event region, the event is identified as a target event; otherwise, it is identified as an inter-crystal scattering event and discarded. Among the target events that are not discarded, in addition to normal events, there are actually light scattering events. These light scattering events will cause temporal resolution degradation. Based on the analysis of the background technology, light scattering events are not suitable for rejection. Therefore, this application takes a different approach and uses a multi-channel data processing method to determine the temporal information of all target events to solve the problem of temporal resolution degradation caused by light scattering events.

[0084] Specifically, the second acquisition module 1540 is configured to acquire the time information and energy information of several photoelectric conversion channels triggered by each target event.

[0085] The aforementioned photoelectric conversion channels can be all photoelectric conversion channels triggered by the target event, or a selection of them. For example, photoelectric conversion channels that are far from the photoelectric conversion channels with the highest, second highest, or higher energy can be eliminated to reduce interference.

[0086] Generally, different gamma photons are incident into the detector in a specific time sequence. Therefore, the target event can be roughly distinguished by the timing information of the photoelectric conversion channel being triggered. For example, if multiple timing information points are within the same time period (e.g., 20 ns), then these timing information points are considered to belong to the same target event. Furthermore, the energy information belonging to the same target event can be filtered. For example, an energy range can be set according to the incident photon energy, such as 200 keV to 600 keV. The initially obtained energy information can be finely filtered to remove energy information outside the energy range. The remaining energy information and its corresponding timing information serve as the data basis for the target channel determination module 1550.

[0087] Specifically, the target channel determination module 1550 is configured to determine the maximum energy based on all the energy information, and to determine several target channels based on the maximum energy. For example, the target channel determination module 1550 can sort all the energy information, form all the energy information into an energy vector, or form all the energy information into a histogram before determining the maximum energy.

[0088] Optionally, the target channel determination module 1550 is further configured to determine a maximum energy based on all the energy information, determine candidate channels through the maximum energy, and determine the target channel from among the candidate channels. The energy of the candidate channels may have a specific relationship with the maximum energy; for example, the energy of all candidate channels may be greater than or equal to 30% of the maximum energy. This can effectively suppress invalid channels introduced by noise or weak light diffusion while preserving the main optical signal contribution.

[0089] Furthermore, the process of determining the target channel from the candidate channels may include sorting the candidate channels by energy level and selecting the top few channels with the highest energy (e.g., 4) as the target channel to avoid introducing too many low-weight channels and causing noise accumulation.

[0090] Alternatively, see Figure 17 The apparatus provided in this application also includes an indexing module 1530, configured to obtain the corresponding time information for all target channels through channel indexing. Since some channels may not generate valid time information in some cases, the target channel determination module 1550 is further configured to remove target channels with invalid time information and use the remaining target channels as the data basis for subsequent modules. And / or the target channel determination module 1550 is further configured to determine whether the number of target channels with valid time information is greater than a preset threshold. If it is greater, the target channels with invalid time information are removed, and the remaining target channels are used as the data basis for subsequent modules. Otherwise, the remaining channels are selected from all channels or candidate channels as substitutes (new target channels) for the removed channels, and all the substitute target channels are used as the data basis for subsequent modules. The number of substitute channels can be equal to, slightly less than, or slightly greater than the number of removed channels, but generally, the number of all substitute target channels is required to be greater than the preset threshold. The preset threshold can be set empirically, and its value can vary depending on the application scenario of the detector.

[0091] Specifically, the energy weighted average determination module 1560 is configured to determine the arrival time of the event by performing an energy weighted average based on the energy information and time information of all target channels.

[0092] Specifically, in the example of this application, the energy-weighted average can be calculated using the following formula (1): Formula (1) in, Indicates the target channel number. Indicates the first The energy value of each target channel Indicates the first Time values ​​for each target channel Indicates the arrival time of the event.

[0093] In the above example, the multi-channel data processing apparatus 1500 provided in this application fully utilizes the correlation between photon statistics and time measurement accuracy in a physical sense. Typically, channels with higher energy correspond to stronger optical signals, and their time measurements are less affected by photon statistical fluctuations and electronic noise; therefore, they should have a higher weight in time reconstruction. By introducing energy as a weighting factor, the reconstruction method provided in this application can naturally align the reconstructed arrival time with the channel that has the stronger optical signal and less time jitter.

[0094] Furthermore, in this application, the following formula (2) can also be used for energy weighted average calculation: Formula (2) in, Indicates the target channel number. Indicates the first The energy value of each target channel Indicates the first Time values ​​for each target channel Indicates the first The weights of the energy and time values ​​corresponding to each target channel Indicates the arrival time of the event.

[0095] Unlike the example in Equation (1), the example in Equation (2) further introduces the weights of each target channel, which can refine the contribution of each target channel to the arrival time and further optimize the time resolution.

[0096] For the beneficial effects of the multi-channel data processing apparatus provided in this application, and its comparison with the prior art, please refer to the description in the above-mentioned multi-channel data processing method, which will not be repeated here.

[0097] Corresponding to the aforementioned multi-channel data processing device, this application also provides a radiation detection system, which can be applied to multiple fields such as oil well logging, security inspection, and aerospace. The radiation detection system includes structures such as detectors and data processing systems. Each structure in the radiation detection system can perform multi-channel time reconstruction multiplexing while simultaneously realizing the detection function, thereby simplifying the system architecture.

[0098] It should be understood that Figures 15-17The apparatus and modules shown can be implemented in various ways. For example, in some embodiments, the apparatus and modules can be implemented in hardware, software, or a combination of both. The hardware portion can be implemented using dedicated logic; the software portion can be stored in memory and executed by a suitable instruction execution device, such as a microprocessor or dedicated-design hardware. Those skilled in the art will understand that the methods and apparatus described above can be implemented using computer-executable instructions and / or included in processor control code, for example, such code provided on a carrier medium such as a disk, CD, or DVD-ROM, a programmable memory such as read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The apparatus and modules described in this application can be implemented not only with hardware circuits such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field-programmable gate arrays, programmable logic devices, etc., but also with software, for example, executed by various types of processors, or with a combination of the aforementioned hardware circuits and software (e.g., firmware).

[0099] It should be noted that the above description of the modules is for convenience only and should not be construed as limiting this specification to the embodiments described. It is understood that those skilled in the art, after understanding the principle of the device, may arbitrarily combine the modules or construct subsystems connected to other modules without departing from this principle. For example, the modules may share a single storage module, or each module may have its own separate storage module. Such modifications are all within the scope of this specification.

[0100] Figure 18 This is a schematic diagram of a computer system for implementing a multi-channel data processing method in one embodiment of this application. (Refer to...) Figure 18 The computer system S00 may include a processing component S20, which further includes one or more processors, and memory resources represented by a memory S22 for storing instructions, such as application programs, that can be executed by the processors of the processing component S20. The application programs stored in the memory S22 may include one or more instructions, with each module corresponding to a set of instructions. Furthermore, the processing component S20 is configured to execute instructions to perform the aforementioned multichannel data processing method.

[0101] The operations and / or methods described in the embodiments of this specification, implemented by a single processor, may also be implemented jointly or independently by multiple processors. For example, if, in this application specification, the processor of the processing device executes steps 100 to 500, it should be understood that steps 100 to 500 may also be executed jointly or independently by two different processors of the processing device (e.g., the first processor executes steps 100 to 200, the second processor executes steps 300 to 500, or the first and second processors jointly execute steps 100 to 500).

[0102] The computer system S00 may further include: a power supply component S24 configured to perform power management of the computer system S00; a wired or wireless network interface S26 configured to connect the computer system S00 to a network; and an input / output (I / O) interface S28. The computer system S00 can operate on an operating system stored in memory S22, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, or similar.

[0103] In an exemplary embodiment, a computer-readable storage medium including instructions is also provided, such as a memory S22 including instructions, which can be executed by the processor of the computer system S00 to perform the above method. The storage medium can be a computer-readable storage medium, for example, a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0104] In an exemplary embodiment, a computer program product is also provided, the computer program product including instructions that can be executed by a processor of a computer system S00 to perform the above method.

[0105] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 19 As shown, Figure 19This is an internal structural diagram of a computer device according to one embodiment of this application. The computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores user- and task-related data used in the aforementioned multi-channel data processing method. The network interface communicates with external terminals via a network connection. When the computer program is executed by the processor, it implements a multi-channel data processing method.

[0106] Those skilled in the art will understand that Figure 19 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0107] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0108] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on its differences from other embodiments. In particular, hardware + program embodiments are basically similar to method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0109] It should be noted that the devices, electronic devices, servers, etc., described above according to the method embodiments may also include other implementation methods, and specific implementation methods can be referred to the description of the relevant method embodiments. Furthermore, new embodiments formed by the combination of features between various methods, devices, and server embodiments still fall within the scope of this application, and will not be elaborated upon here.

[0110] In the description of this specification, the references to "one embodiment," "an embodiment," and / or "some embodiments," "some embodiments," "other embodiments," "ideal embodiments," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative descriptions of the above terms do not necessarily refer to the same embodiment or example, and certain features, structures, or characteristics in one or more embodiments of this specification may be appropriately combined.

[0111] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0112] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

[0113] 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.

[0114] Furthermore, those skilled in the art will understand that various aspects of this specification can be described and illustrated in several patentable ways or situations, including any new and useful combination of processes, machines, products, or substances, or any new and useful improvements thereof. Accordingly, various aspects of this specification can be implemented entirely by hardware, entirely by software (including firmware, resident software, microcode, etc.), or by a combination of hardware and software. All of the above hardware or software may be referred to as a “data block,” “module,” “engine,” “module,” “component,” or “system.” Furthermore, various aspects of this specification may be represented as a computer product located on one or more computer-readable media, including computer-readable program code.

[0115] 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.

[0116] 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).

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] 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 multi-channel data processing method, characterized in that, include: Acquire the time and energy information of several photoelectric conversion channels triggered by each target event; The maximum energy is determined based on all the energy information, and several target channels are determined based on the maximum energy. The arrival time of the event is determined by an energy-weighted average based on the energy and time information of all target channels.

2. The multi-channel data processing method according to claim 1, characterized in that, Based on all the energy information, a maximum energy is determined, and several target channels are determined using the maximum energy, including: The maximum energy is determined based on all the energy information, candidate channels are determined based on the maximum energy, and the target channel is determined from the candidate channels.

3. The multi-channel data processing method according to claim 2, characterized in that, The energy of each candidate channel is greater than or equal to 30% of the maximum energy.

4. The multi-channel data processing method according to claim 1, characterized in that, After determining the maximum energy based on all the energy information, and determining several target channels using the maximum energy, the multi-channel data processing method further includes: For all the target channels, the corresponding time information is obtained through the channel index.

5. The multi-channel data processing method according to claim 1, characterized in that, After determining the maximum energy based on all the energy information, and determining several target channels using the maximum energy, the multi-channel data processing method further includes: The process involves removing target channels with invalid time information and performing an energy-weighted average on the remaining target channels.

6. The multi-channel data processing method according to claim 1, characterized in that, After determining the maximum energy based on all the energy information, and determining several target channels using the maximum energy, the multi-channel data processing method further includes: If the number of target channels with valid time information is greater than a preset threshold, then target channels with invalid time information are removed and energy-weighted averaging is performed on the remaining target channels. Otherwise, the remaining channels are selected from all channels or candidate channels as substitutes for the removed channels, and energy-weighted averaging is performed on all the substitute target channels.

7. The multi-channel data processing method according to claim 1, characterized in that, The arrival time of the event is determined by an energy-weighted average based on the energy and time information of all target channels, including: The energy-weighted average is calculated using the following formula (1): Official (1) in, Indicates the target channel number. Indicates the first The energy value of each target channel Indicates the first Time values ​​for each target channel Indicates the arrival time of the event.

8. The multi-channel data processing method according to claim 1, characterized in that, The arrival time of the event is determined by an energy-weighted average based on the energy and time information of all target channels, including: The energy-weighted average is calculated using the following formula (2): Official (2) in, Indicates the target channel number. Indicates the first The energy value of each target channel Indicates the first Time values ​​for each target channel Indicates the first The weights of the energy and time values ​​corresponding to each target channel Indicates the arrival time of the event.

9. The multi-channel data processing method according to claim 1, characterized in that, Before acquiring the time and energy information of several photoelectric conversion channels triggered by each target event, the multi-channel data processing method further includes: Acquire events generated by gamma photon incident; By identifying the event regions corresponding to each scintillation crystal and the coordinates of each event in advance, inter-crystal scattering events are eliminated.

10. The multi-channel data processing method according to claim 9, characterized in that, The process of determining the event regions corresponding to each pre-determined scintillation crystal includes: Based on the location information of several events in a scintillation crystal or crystal array, determine the aggregation location of non-scattering events and the location information of scattering events corresponding to each scintillation crystal; The event regions of the corresponding scintillation crystals are divided based on the aggregation locations of the non-scattering events and the location information of the scattering events.

11. The multi-channel data processing method according to claim 9, characterized in that, By defining the event regions corresponding to each scintillation crystal and the coordinates of each event in advance, inter-crystal scattering events are eliminated, including: For each event, obtain its position coordinates on the scintillation crystal. If the position coordinates are located within any event region, the event is identified as the target event; otherwise, it is identified as an inter-crystal scattering event and discarded.

12. A multi-channel data processing device, characterized in that, include: The second acquisition module is configured to acquire the time and energy information of several photoelectric conversion channels triggered by each target event; The target channel determination module is configured to determine the maximum energy based on all the energy information, and to determine several target channels based on the maximum energy. The energy-weighted averaging module is configured to determine the arrival time of the event by performing an energy-weighted averaging based on the energy and time information of all target channels.

13. The multi-channel data processing apparatus according to claim 12, characterized in that, The target channel determination module is configured to determine the maximum energy based on all the energy information, determine candidate channels through the maximum energy, and determine the target channel from the candidate channels.

14. The multi-channel data processing apparatus according to claim 13, characterized in that, The energy of each candidate channel is greater than or equal to 30% of the maximum energy.

15. The multi-channel data processing apparatus according to claim 12, characterized in that, Also includes: The index module is configured to retrieve the corresponding time information for all the target channels through the channel index.

16. The multi-channel data processing apparatus according to claim 12, characterized in that, The target channel determination module is configured to remove target channels with invalid time information and perform an energy-weighted average process on the remaining target channels.

17. The multi-channel data processing apparatus according to claim 12, characterized in that, The target channel determination module is configured to determine whether the number of target channels with valid time information is greater than a preset threshold. If it is greater, the target channels with invalid time information are removed and the remaining target channels are used to perform an energy-weighted average process. Otherwise, the remaining channels are selected from all channels or candidate channels as substitutes for the removed channels and the remaining target channels are used to perform an energy-weighted average process.

18. The multi-channel data processing apparatus according to claim 12, characterized in that, The energy weighted average module is configured to perform energy weighted average calculation using the following formula (1): Official (1) in, Indicates the target channel number. Indicates the first The energy value of each target channel Indicates the first Time values ​​for each target channel Indicates the arrival time of the event.

19. The multi-channel data processing apparatus according to claim 12, characterized in that, The energy weighted average module is configured to perform energy weighted average calculation using the following formula (2): Official (2) in, Indicates the target channel number. Indicates the first The energy value of each target channel Indicates the first Time values ​​for each target channel Indicates the first The weights of the energy and time values ​​corresponding to each target channel Indicates the arrival time of the event.

20. The multi-channel data processing apparatus according to claim 12, characterized in that, Also includes: The first acquisition module is configured to acquire events generated by gamma photon incident; The scattering event filtering module is configured to eliminate inter-crystal scattering events by using the pre-determined event regions corresponding to each scintillation crystal and the coordinates of each event.

21. The multi-channel data processing apparatus according to claim 20, characterized in that, The scattering event filtering module is configured to: Based on the location information of several events in a scintillation crystal or crystal array, determine the aggregation location of non-scattering events and the location information of scattering events corresponding to each scintillation crystal; The event regions of the corresponding scintillation crystals are divided based on the aggregation locations of the non-scattering events and the location information of the scattering events.

22. The multi-channel data processing apparatus according to claim 13, characterized in that, The scattering event filtering module is configured to obtain the position coordinates of each event on the crystal. If the position coordinates are located within any event region, the event is identified as the target event; otherwise, it is identified as an inter-crystal scattering event and eliminated.

23. The multi-channel data processing apparatus according to claim 13, characterized in that, The first acquisition module includes a detector, which includes a scintillation crystal, a photoelectric conversion device, and a readout electronics section. The scintillation crystal and the photoelectric conversion device are not coupled one-to-one, while the photoelectric conversion device and the readout electronics section correspond one-to-one.

24. A computer storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the multi-channel data processing method according to any one of claims 1 to 11.

25. A computer program product comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed by the processor, they implement the steps of the multi-channel data processing method according to any one of claims 1 to 11.

26. A radiation detection system, characterized in that, Includes the multi-channel data processing apparatus as described in any one of claims 12-23.

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