A 3D coded gamma imaging detector based on a magic cube structure and an imaging method thereof

Abstract

The present application belongs to the technical field of nuclear radiation detection and imaging, and particularly relates to a 3D coded gamma imaging detector based on a magic cube structure and an imaging method thereof. The gamma imaging detector adopts a spatial geometric array layout; in a plurality of spatial cells of the array, shielding units and detection modules are randomly filled heterogeneously. The shielding units adopt high-atomic-number materials, and are used for spatial modulation of omnidirectional incident gamma rays, to form anisotropic response characteristics. The detection modules are used for recording energy deposition and counting information of the gamma rays. The present application expands the traditional 2D planar coded gamma imaging into a 3D magic cube structure gamma imaging with three-dimensional spatial topology coding, and constructs a three-dimensional omnidirectional system response array by using the random distribution of the shielding units and the detection blocks in space. Without a complex coincidence electronics data acquisition system, the spatial correlation of the counts of each unit is solved, to realize accurate reconstruction of the spatial position and intensity distribution of a high-energy gamma ray source.

Description

Technical Field

[0001] This invention belongs to the field of nuclear radiation detection and imaging technology, specifically relating to a 3D coded gamma imaging detector based on a Rubik's Cube structure and its imaging method. Background Technology

[0002] Current radiometric mapping and visualization technologies mainly rely on the following types of equipment, but all of them have limitations: 1. Coded Aperture Camera: Relies on a front-end coded mask. Although it has high spatial resolution, its field of view (FOV) is usually small (generally less than 60°). In addition, the mask is usually very heavy to achieve shielding, resulting in poor portability. To obtain a wide field of view, a mechanical scanning detector is used: It relies on mechanically rotating the shield to obtain directionality. It is bulky and has moving parts, resulting in low reliability.

[0003] 2. Compton Camera: Relies on the coincidence measurement of scattering and absorption events. Its disadvantages are: Hardware complexity: Requires high-performance electronic systems, resulting in high costs.

[0004] Inefficient: Only a very small percentage of cases are valid, resulting in long imaging times.

[0005] Algorithm limitations: Image reconstruction iterations involve huge computational loads, and the number of valid events in image reconstruction is small, making it difficult to achieve high-performance real-time monitoring.

[0006] Insufficient reliability: It relies on coincidence measurement of multiple detection modules, but when the detection module or coincidence measurement electronics fail, the entire system fails, resulting in low reliability. Summary of the Invention

[0007] To address the shortcomings of existing imaging devices, such as narrow field of view, heavy weight, complex electronics, and insufficient reliability, this invention provides a 3D coded gamma imaging detector and its imaging method based on a Rubik's Cube structure. The aim is to provide a 3D coded gamma imaging detector with a 4π full field of view, highly compact structure, no need for composite circuits, simple algorithm, and high imaging efficiency and reliability.

[0008] To achieve the above objectives, the present invention provides the following solution: A 3D coded gamma imaging detector based on a Rubik's Cube structure, wherein the gamma imaging detector adopts a spatial geometric array layout, and shielding units and detection modules are randomly filled in several spatial cells of the array. The spatial geometric array includes any one of a cube array, a polyhedral array, or an irregular spatial lattice. The shielding unit is used to block gamma rays incident at any angle to varying degrees. The detection module is used to record and count the energy deposition of gamma rays.

[0009] Preferably, the gamma imaging detector further includes a signal processing module; The signal processing module is used to acquire the pulse amplitude spectrum of each detection module using a multi-channel digital analysis method, and combine it with a direction calculation algorithm based on the angular response mode to realize high-energy gamma-ray imaging.

[0010] Preferred directional solving algorithms based on angular response modes include: Through Monte Carlo simulation and experimental calibration, the response of the gamma imaging detector at various discrete angles in 4π space was obtained, and a response matrix was constructed. Based on the response matrix, and combining the counting vectors of each detection unit with the spatial source distribution vector, an imaging mathematical model is constructed. Solve the imaging mathematical model to reconstruct the image of the radiation source.

[0011] Preferably, the method for obtaining the response of the gamma imaging detector at various discrete angles in 4π space through Monte Carlo simulation and experimental calibration, and constructing the response matrix, includes: The calibration scheme was designed by selecting a standard gamma source and using Monte Carlo simulation to simulate and calculate the response data of the detector array composed of the detection modules at different angles. The response matrix was constructed for the design of the gamma imaging algorithm, and the theoretical design of the gamma imaging algorithm was carried out. The response data of the real detector array were obtained through experiments, and a response matrix for actual imaging reconstruction was constructed. Combined with the theoretical design of the gamma imaging algorithm, a calibration platform was built to calibrate the gamma imaging detector. According to the discrete angular spatial position, the standard gamma source scanned the gamma imaging detector in the polar angle and azimuth angle direction, recorded the counting spectrum at each position and monitored the dead time in real time, and obtained the detector array measurement data under multiple angles. The data preprocessed by background subtraction, dead time calibration, energy calibration, and peak integration were used to analyze the detector array measurement data at multiple angles. The data was then normalized by combining the activity of the radioactive source, the distance between the source and the detector, and the measurement time to obtain the relative response. Based on the relative response obtained through experimental calibration and normalization, a response function is constructed and the uncertainty is analyzed to generate a normalized response matrix.

[0012] This invention also provides an imaging method for a 3D coded gamma imaging detector based on a Rubik's Cube structure. The method utilizes the aforementioned gamma imaging detector and includes: Gamma rays are incident into a scintillator to deposit energy and generate an optical signal, which is then recorded by a photomultiplier tube to obtain a current pulse. The current pulses are processed using front-end analog circuitry to obtain digital waveforms; Digital signal processing and physical quantity extraction are performed on the digitized waveform to obtain energy, count, and time information; Based on the energy, count, and time information, and combined with the directional calculation algorithm based on the angular response mode, the energy spectrum, dose rate, imaging image, and data file are obtained.

[0013] Preferred, the orientation calculation algorithm based on angular response mode includes: Through Monte Carlo simulation and experimental calibration, the response of the gamma imaging detector at various discrete angles in 4π space was obtained, and a response matrix was constructed. Based on the response matrix, and combining the counting vectors of each detection unit with the spatial source distribution vector, an imaging mathematical model is constructed. Solve the imaging mathematical model to reconstruct the image of the radiation source.

[0014] Preferably, the method for obtaining the response of the gamma imaging detector at various discrete angles in 4π space through Monte Carlo simulation and experimental calibration, and constructing the response matrix, includes: The calibration scheme was designed by selecting a standard gamma source and using Monte Carlo simulation to simulate and calculate the response data of the detector array composed of the detection modules at different angles. The response matrix was constructed for the design of the gamma imaging algorithm, and the theoretical design of the gamma imaging algorithm was carried out. The response data of the real detector array were obtained through experiments, and a response matrix for actual imaging reconstruction was constructed. Combined with the theoretical design of the gamma imaging algorithm, a calibration platform was built to calibrate the gamma imaging detector. According to the discrete angular spatial position, the standard gamma source scanned the gamma imaging detector in the polar angle and azimuth angle direction, recorded the counting spectrum at each position and monitored the dead time in real time, and obtained the detector array measurement data under multiple angles. The data preprocessed by background subtraction, dead time calibration, energy calibration, and peak integration were used to analyze the detector array measurement data at multiple angles. The data was then normalized by combining the activity of the radioactive source, the distance between the source and the detector, and the measurement time to obtain the relative response. Based on the relative response obtained through experimental calibration and normalization, a response function is constructed and the uncertainty is analyzed to generate a normalized response matrix.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: Omnidirectional imaging (4π FOV): Breaking through the limitation of traditional imagers that can only see "front", it can simultaneously sense the radiation distribution in all directions around.

[0016] High sensitivity and high efficiency: It utilizes all gamma-ray events entering the detector, eliminating the need to eliminate non-matching events like the Compton camera, thus increasing imaging speed by 1-2 orders of magnitude.

[0017] Extremely lightweight: Compared with traditional lead / tungsten shielded coded aperture cameras, the 3D cube structure of this invention reduces the thickness of the shell while achieving modulation. The structure is compact, and when the control volume is within 5cm×5cm×5cm, the weight of the whole machine can be reduced to less than 1kg, making it suitable for drones or robots.

[0018] Low cost: Using general-purpose MCA and SiPM, no expensive ASIC chips are required, making it easy to deploy at large scale. Attached Figure Description

[0019] To more clearly illustrate the technical solution of the present invention, the drawings used in the embodiments are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a schematic diagram of the geometric layout of the Rubik's Cube detector according to an embodiment of the present invention, wherein (a) is a cube, (b) is a tetrahedron, and (c) is a dodecahedron; Figure 2 The following diagrams illustrate the imaging principles of embodiments of the present invention, where (a) is coded aperture imaging, (b) is Compton imaging, (c) is hybrid imaging, and (d) is response mode imaging. Figure 3 This is a flowchart illustrating the detector response matrix calibration process according to an embodiment of the present invention. Figure 4 This is a flowchart illustrating the signal and data processing of an embodiment of the present invention; Figure 5 The reconstruction effect diagram of the embodiment of the present invention is as follows: the distribution map of radiation source points, where (a) is a spherical map and (b) is a latitude and longitude map. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0023] Example 1 The present invention provides a 3D coded gamma imaging detector based on a Rubik's Cube structure. The gamma imaging detector adopts a spatial geometric array layout, in which shielding units and detection modules are randomly filled in several spatial cells of the array. The spatial geometric array includes any one of a cube array, a polyhedral array, or an irregular spatial lattice. The shielding unit is used to block gamma rays incident at any angle to varying degrees. The detection module is used to record the energy deposition of gamma rays.

[0024] The specific implementation process of this invention is as follows: The physical structure design of the gamma imaging detector is as follows: Cube array construction: The gamma imaging detector adopts a spatial geometric array layout, including a cube array (such as... Figure 1 (a)), tetrahedral arrays (such as) Figure 1 (b) or a dodecahedral array (such as...) Figure 1 Any one of (c)).

[0025] Hybrid arrangement mode: Taking the simplest 3×3×3 cubic array as an example, shielding units (shielding blocks) and detection modules are randomly filled in the 27 cells. The shielding units (such as tungsten blocks) are used to block gamma rays incident from any angle to different degrees, acting as a 3D mask; the detection modules (such as GAGG scintillators connected to SiPM) are responsible for recording the energy deposition and counting of gamma rays.

[0026] Anisotropic Design: Under the condition of random arrangement between the detector array and the shielding block through Monte Carlo simulation, the accuracy of X-ray source azimuth reconstruction, angular resolution, detection efficiency, directional discrimination, and omnidirectional response uniformity of the detector array are analyzed. Combining the principles of multi-objective optimization algorithms, weights are assigned to calculate the comprehensive score of the detector array structure, obtaining a better 3D cube structure layout. To seek a balance among multiple indicators, weights are assigned to each indicator for comprehensive score calculation. First, the five indicators are standardized, converting them into positive indicators with values ​​in the range [0,1], where larger values ​​are better. Then, a weight vector W = [0.35, 0.25, 0.20, 0.10, 0.10] is set to correspond to reconstruction accuracy, angular resolution, directional discrimination, omnidirectional response uniformity, and detection efficiency, respectively, and a weighted scoring method is used to calculate the comprehensive score of each layout. This random 3D spatial distribution ensures that when gamma rays are incident from any angle in 4π space, the detector modules at different positions are shielded to varying degrees by the shielding unit. The resulting detector array response forms a response matrix containing information about the gamma ray incident orientation. Due to the introduction of the shielding block, the gamma imaging detector maintains high orientation reconstruction accuracy even for high-energy gamma rays. Furthermore, the detector modules, employing a combination of scintillators and SiPMs, have independent acquisition circuits for each module, eliminating the need for dual-end readout and coincidence circuits. This simplifies the system's data acquisition electronics and increases reliability. This invention utilizes shielding blocks and avoids dual-end readout, eliminating the need for coincidence acquisition methods. It achieves higher resolution for orientation reconstruction in high-energy gamma-ray imaging, simplifies the electronics system, and increases reliability.

[0027] like Figure 1 As shown, the geometric layout of the 3D coded gamma imaging detector (Rubik's cube detector) based on the Rubik's cube structure of the present invention is diverse. Figure 1 Three case studies are presented: cube, tetrahedron, and dodecahedron. The type, material, and size of the gamma imaging detector are adjusted according to the on-site radiation environment to improve its portability, sensitivity, imaging efficiency, and resolution. Taking a 3×3×3 cube detector as an example, the detection module uses GAGG (Ce), which is the most durable due to its high density, non-hygroscopic and non-deliquescent properties, low packaging requirements, and high count rate. GAGG blocks are used in conjunction with SiPM, and the output signal of SiPM is sent to an external analog-to-digital converter (ADC) of the cube detector. The signal output by the ADC is connected to the FPGA for energy spectrum acquisition. Each detection module operates independently without the need for ASIC electronics. Even if a detection module fails, it does not affect the detector imaging; only the response matrix needs to be calibrated in advance. By combining different detector arrangement schemes using corner pieces, edge pieces, and code pieces, a cube detector array can be constructed, thus expanding the array's layout.

[0028] Furthermore, the detection module consists of: The detection module consists of a scintillator (such as GAGG(Ce), LaBr3, CeBr3, etc.), an optical coupling layer, and a silicon photomultiplier tube (SiPM).

[0029] A scintillator (e.g., 6mm × 6mm × 6mm) is used to capture gamma rays, a SiPM is responsible for converting optical signals into electrical signals, and an optical coupling layer is used to connect the scintillator and the SiPM.

[0030] Furthermore, the gamma imaging detector also includes a signal processing module: The signal processing module is used for multi-channel digital analysis (MCA) to directly acquire the pulse amplitude spectrum of each detector module. Using a standard gamma source energy scale, the pulse amplitude spectrum can be corrected to an energy spectrum. The full-energy peak regions in the energy spectrum are then counted, representing the detector module's response to that type of gamma isotope. Given the differences in response between different detector modules to gamma source illumination, a response vector for the detector array can be constructed by combining the detector's serial number. The gamma detector array vectors at different polar and azimuth angles constitute the detector response matrix. Combined with a direction calculation algorithm based on angular response modes, high-energy gamma-ray imaging and azimuth reconstruction are achieved.

[0031] Non-coincidence acquisition method: Unlike the Compton camera, the gamma imaging algorithm relies on the detection information from the scattering and absorbing layers. Therefore, it requires time-based coincidence measurements to sense the response event caused by the same gamma ray incident from the information detected by the two detector modules. In this invention, each detector module of the gamma imaging detector independently acquires gamma irradiation response counts, eliminating the need for coincidence measurements and greatly simplifying hardware requirements.

[0032] Furthermore, the orientation calculation algorithm based on the angular response mode includes: Response matrix establishment: Through Monte Carlo simulations (Geant4 / MCNP / Fluka / EGS, etc.) and experimental calibration, the response of the gamma imaging detector at various discrete angles in 4π space is obtained, and the response matrix is ​​constructed. R ; Mathematical model: based on response matrix R Combined with the response count vectors of each detection module in the detector array S and spatial source distribution vector W Construct an imaging mathematical model, the expression of which is: S = RW ; Image reconstruction: The optimal imaging mathematical model is solved using either Gradient Descent (GDM) or Maximum Likelihood Expectation-Maximization (ML-EM). WThis allows for the reproduction of the position and intensity of the radiation source in a three-dimensional or spherical coordinate system, thus enabling image reconstruction of the radiation source.

[0033] Specifically, such as Figure 2 As shown, gamma-ray imaging detectors can be classified into four types according to their principles: coded aperture imaging, Compton imaging, coded aperture-Compton hybrid imaging, and detector response mode gamma-ray imaging. Cocoded aperture imaging uses a lead / tungsten coded plate to modulate and project gamma rays onto a gamma detector array for imaging. It can detect low-energy rays, but has a small imaging field of view. Compton imaging technology uses scattering and absorbing layer detectors to measure the scattering and deposition energy of Compton scattered photons and performs imaging based on the Compton scattering angle relationship. This solves the field of view problem of coded aperture imaging, but has a high lower limit for the detected ray energy. Furthermore, due to the Compton event filtering, the number of effective events for the imaging algorithm is small. To ensure a high number of imaging events, a large number of imaging units and complex ASIC electronics systems with appropriate capabilities are necessary. Compton hybrid active coded imaging increases the number of effective events required for imaging by replacing the coded plate with a detector, but still suffers from a large number of imaging detector units, complex electronics systems, poor system reliability, and insufficient portability. Detector response mode gamma imaging is a relatively new imaging method that uses the difference in response of a detector array to gamma rays incident from different directions to image a radiation source. Each detector module works independently without the need for matching, and it has advantages such as simple electronics, high imaging efficiency, compact structure, and high reliability.

[0034] γ-ray imaging using detector response mode reconstructs the direction of the γ-ray source based on the measured detector response encoding. The matrix... S Defined as the measured detector response count vector, matrix R Defined as a pre-measured response matrix, the matrix W Defined as the spatial source distribution vector, i.e., the direction of the gamma-ray source. Ideally, these three matrices should satisfy the following relationship: S = RW (1) (2) in this case, n This indicates the number of detection modules in the gamma-ray detection array. m This indicates the number of gamma ray incident points. s 1. s 2… s n This indicates that the detector modules 1, 2... in the detector array n The count of the detected full-energy peaks (i.e., the count of the response of each module to the characteristic nuclide). r 1,1 , r1,2 … r 1,m This represents the response of detection module 1 to γ-ray sources at discrete positions with different azimuth and polar angles; w 1. w 2… w m This represents the probability distribution of gamma-ray azimuth discretely according to azimuth and polar angles. Due to insufficient system detection capability and... S and R Due to the uncertainty, equation (2) does not have a unique solution. The goal is to find a solution that minimizes the squared error. W Value, thus serving as a feasible solution: (3) The parameter σ is a multidimensional surface. By repeatedly calculating and updating the position vector using gradient descent, the minimum value of the target value σ can be gradually approached. To solve the adaptive step size problem, the maximum likelihood expectation maximization (ML-EM) algorithm can be used. To solve the adaptive step size problem and improve the iteration convergence speed, the ordered subset expectation maximization (OS-EM) algorithm can be used.

[0035] Furthermore, through Monte Carlo simulations and experimental calibration, the response of the gamma imaging detector at various discrete angles within the 4π space is obtained, and the methods for constructing the response matrix include: The calibration scheme selects a standard gamma source and uses Monte Carlo simulation to calculate the response data of the detector array composed of detection modules at different angles. A response matrix is ​​constructed for the design of the gamma imaging algorithm, thus enabling the theoretical design of the gamma imaging algorithm. (The response matrix constructed by Monte Carlo simulation is only used for the theoretical design of the imaging algorithm (including setting the angle step polar angle Δθ, azimuth angle Δφ, and source-detector distance, etc.). In practical applications, imaging requires obtaining the corresponding response matrix through experimental measurements.) Due to individual differences in actual detection modules, it is necessary to obtain the response data of the actual detector array through experiments, construct a response matrix for actual imaging reconstruction rather than for the algorithm theoretical design stage, combine the theoretical design of the gamma imaging algorithm, build a calibration platform to calibrate the gamma imaging detector; according to the discrete angular spatial position, make the standard gamma source scan the gamma imaging detector in the polar angle and azimuth direction, record the counting spectrum at each position and monitor the dead time in real time to obtain the detector array measurement data at multiple angles. The data preprocessed by background subtraction, dead time calibration, energy calibration, and peak integration were used to analyze the detector array measurement data at multiple angles. The data was then normalized by combining the activity of the radioactive source, the distance between the source and the detector, and the measurement time to obtain the relative response. Based on the relative response obtained through experimental calibration and normalization, a response function is constructed and the uncertainty is analyzed to generate a normalized response matrix. The normalized response matrix is ​​obtained by normalizing the response values ​​in the response matrix to their maximum values.

[0036] Specifically, Figure 3 A flowchart for the calibration of the response matrix of a 3D cube gamma imaging detector is presented. First, a calibration scheme is designed, selecting a standard gamma source (energy point), such as Cs-137, Co-60, Ba-133, Eu-52, etc. Centered on the gamma imaging detector, the 4π space is discretized according to the polar angle θ and azimuth angle φ with step lengths Δθ and Δφ. The distance between the radiation source and the gamma imaging detector is set. A 2-DOF mechanical platform is used to control the rotation of the gamma imaging detector, and calibration ensures the accuracy of the rotation angle, thus calibrating the gamma imaging detector. Specific steps: Before calibration, in the absence of any radiation source, the detector is used to collect data, thereby measuring the environmental background and checking the stability of the statistical count. Then, a standard gamma radiation source is introduced, and scanning is performed according to the discrete angular spatial position in the θ and φ directions, recording the count spectrum at each position and monitoring the dead time in real time. Data preprocessing was performed using background subtraction, dead time calibration, energy scale correction, and peak integration. The relative response was obtained by normalizing the data based on the activity of the radioactive source, the distance between the source and the detector, and the measurement time. The response function R(θ,φ) was constructed and uncertainty was evaluated (error statistics, angle positioning error, activity uncertainty, combined standard uncertainty, etc.). Finally, the response matrix and discrete angle response table were generated for imaging and γ source orientation inversion.

[0037] Furthermore, Figure 4 A signal processing flowchart is presented. Gamma rays incident on a scintillator deposit energy to produce light. The light propagates within the scintillator, reaches the boundary, passes through a coupler, and is recorded by a photomultiplier tube, converting the light signal into a current pulse. The front-end analog circuit processes this current pulse, including biasing and protection, charge-sensitive preamplifier, filtering, and shaping amplification. Finally, it is sampled by an ADC and converted into a digital waveform. The digital waveform then undergoes digital filtering, baseline recovery, pulse integration, peak detection, dead-time correction, and temperature drift correction to achieve digital signal processing. Then, physical quantities are extracted: high-precision time information is obtained using digital constant-ratio timing, and energy information is obtained using charge integration. Subsequently, an energy spectrum function is constructed. S ( E )=Σ δ ( E - E i A histogram of energy distribution is formed, in which, S ( E Let be the energy spectrum distribution function, representing the energy as... EAt that time, the radiation intensity or event distribution density δ It is a unit impulse function. E i For the first i The energy measurements of the detected gamma rays are used. In dose calculation, the G(E) function energy weighting algorithm is employed, and the compensation factors calculated by Monte Carlo and verified experimentally are used to perform weighted summation on each channel address of the energy spectrum, thereby obtaining accurate dose rate data with energy compensation characteristics. Finally, combined with the imaging algorithm, the energy spectrum, dose rate, imaging image, and data file are output.

[0038] Figure 5 The reconstructed image shown is from a Monte Carlo simulation, employing a 3×3×3 array of cube-shaped gamma detectors. Eight detector modules are located at the eight corner pieces of the cube. The radiation source is 1 meter from the detector, with a polar angle of 90° and an azimuth angle of 90° in the detector coordinate system. The radiation source location distribution map, calculated using the Maximum Likelihood Expectation-Maximization (ML-EM) algorithm, is shown below. Figure 5 As shown, (a) is a spherical map and (b) is a latitude and longitude map.

[0039] In summary, this invention provides an omnidirectional gamma-ray imaging device and processing method based on angular response mode, constructed using spatially randomly distributed shielding bodies and detection units. It realizes the extension of 2D planar coding to 3D Rubik's Cube random coding, and can achieve reliable gamma-ray imaging without the need for a complex conformal electronics data acquisition system.

[0040] Example 2 Based on the same inventive concept, the present invention also provides an imaging method for a 3D coded gamma imaging detector based on a Rubik's Cube structure. The method is implemented using the gamma imaging detector described in the foregoing embodiments, and includes: Gamma rays are incident into a scintillator to deposit energy and generate an optical signal, which is then recorded by a photomultiplier tube to obtain a current pulse. The current pulses are processed using front-end analog circuitry to obtain digital waveforms; Digital signal processing and physical quantity extraction are performed on the digitized waveform to obtain energy, count, and time information; Based on the energy, count, and time information, and combined with the directional calculation algorithm based on the angular response mode, energy spectrum, dose rate, imaging image, and data file are obtained.

[0041] Specifically, gamma rays incident on a scintillator deposit energy to produce light. The light propagates within the scintillator, reaches the boundary, passes through a coupler, and is recorded by a photomultiplier tube, converting the light signal into a current pulse. The front-end analog circuit processes this current pulse, including biasing and protection, charge-sensitive pre-amplification, filtering, and shaping amplification. Finally, it is sampled by an ADC and converted into a digital waveform. The digital waveform then undergoes digital filtering, baseline recovery, pulse integration, peak detection, dead-time correction, and temperature drift correction to obtain energy, count, and time information from the digital signal. Finally, high-level processing constructs the energy spectrum, calculates the dose, calculates the response matrix, and performs imaging algorithm processing, ultimately outputting an energy spectrum, dose rate, imaging image, and data file.

[0042] Furthermore, the orientation calculation algorithm based on the angular response mode includes: Through Monte Carlo simulation and experimental calibration, the response of the gamma imaging detector at various discrete angles in 4π space was obtained, and a response matrix was constructed. Based on the response matrix, and combining the counting vectors of each detection unit with the spatial source distribution vector, an imaging mathematical model is constructed. Solve the imaging mathematical model to reconstruct the image of the radiation source.

[0043] Furthermore, through Monte Carlo simulations and experimental calibration, the response of the gamma imaging detector at various discrete angles within the 4π space is obtained, and the methods for constructing the response matrix include: The calibration scheme was designed by selecting a standard gamma source and using Monte Carlo simulation to simulate and calculate the response data of the detector array composed of the detection modules at different angles. The response matrix was constructed for the design of the gamma imaging algorithm, and the theoretical design of the gamma imaging algorithm was carried out. The response data of the real detector array were obtained through experiments, and a response matrix for actual imaging reconstruction was constructed. Combined with the theoretical design of the gamma imaging algorithm, a calibration platform was built to calibrate the gamma imaging detector. According to the discrete angular spatial position, the standard gamma source scanned the gamma imaging detector in the polar angle and azimuth angle direction, recorded the counting spectrum at each position and monitored the dead time in real time, and obtained the detector array measurement data under multiple angles. The data preprocessed by background subtraction, dead time calibration, energy calibration, and peak integration were used to analyze the detector array measurement data at multiple angles. The data was then normalized by combining the activity of the radioactive source, the distance between the source and the detector, and the measurement time to obtain the relative response. Based on the relative response obtained through experimental calibration and normalization, a response function is constructed and the uncertainty is analyzed to generate a normalized response matrix.

[0044] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made to the technical solutions of the present invention by those skilled in the art without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A 3D coded gamma imaging detector based on a Rubik's Cube structure, characterized in that, The gamma imaging detector adopts a spatial geometric array layout, in which shielding units and detection modules are randomly filled in several spatial cells of the array. The spatial geometric array includes any one of a cube array, a polyhedral array, or an irregular spatial lattice. The shielding unit is used to block gamma rays incident at any angle to varying degrees. The detection module is used to record and count the energy deposition of gamma rays.

2. The gamma imaging detector according to claim 1, characterized in that, The gamma imaging detector also includes a signal processing module; The signal processing module is used to obtain the pulse amplitude spectrum of each detection module using a multi-channel digital analysis method, and combine it with a direction calculation algorithm based on the angular response mode to achieve omnidirectional gamma-ray imaging.

3. The gamma imaging detector according to claim 2, characterized in that, The orientation calculation algorithm based on angular response mode includes: Through Monte Carlo simulation and experimental calibration, the response of the gamma imaging detector at various discrete angles in 4π space was obtained, and a response matrix was constructed. Based on the response matrix, and combining the counting vectors of each detection unit with the spatial source distribution vector, an imaging mathematical model is constructed. Solve the imaging mathematical model to reconstruct the image of the radiation source.

4. The gamma imaging detector according to claim 3, characterized in that, The methods for obtaining the response of the gamma imaging detector at various discrete angles in 4π space through Monte Carlo simulation and experimental calibration, and constructing the response matrix, include: The calibration scheme was designed by selecting a standard gamma source and using Monte Carlo simulation to simulate and calculate the response data of the detector array composed of the detection modules at different angles. The response matrix was constructed for the design of the gamma imaging algorithm, and the theoretical design of the gamma imaging algorithm was carried out. The response data of the real detector array were obtained through experiments, and a response matrix for actual imaging reconstruction was constructed. Combined with the theoretical design of the gamma imaging algorithm, a calibration platform was built to calibrate the gamma imaging detector. According to the discrete angular spatial position, the standard gamma source scanned the gamma imaging detector in the polar angle and azimuth angle direction, recorded the counting spectrum at each position and monitored the dead time in real time, and obtained the detector array measurement data under multiple angles. The data preprocessed by background subtraction, dead time calibration, energy calibration, and peak integration were used to analyze the detector array measurement data at multiple angles. The data was then normalized by combining the activity of the radioactive source, the distance between the source and the detector, and the measurement time to obtain the relative response. Based on the relative response obtained through experimental calibration and normalization, a response function is constructed and the uncertainty is analyzed to generate a normalized response matrix.

5. An imaging method for a 3D coded gamma imaging detector based on a Rubik's Cube structure, wherein the method is implemented using the gamma imaging detector according to any one of claims 1-4, characterized in that, The method includes: Gamma rays are incident into a scintillator to deposit energy and generate an optical signal, which is then recorded by a photomultiplier tube to obtain a current pulse. The current pulses are processed using front-end analog circuitry to obtain digital waveforms; Digital signal processing and physical quantity extraction are performed on the digitized waveform to obtain energy, count, and time information; Based on the energy, count, and time information, and combined with the directional calculation algorithm based on the angular response mode, the energy spectrum, dose rate, imaging image, and data file are obtained.

6. The method according to claim 5, characterized in that, The orientation calculation algorithm based on the angular response mode includes: Through Monte Carlo simulation and experimental calibration, the response of the gamma imaging detector at various discrete angles in 4π space was obtained, and a response matrix was constructed. Based on the response matrix, and combining the counting vectors of each detection unit with the spatial source distribution vector, an imaging mathematical model is constructed. Solve the imaging mathematical model to reconstruct the image of the radiation source.

7. The method according to claim 6, characterized in that, The methods for obtaining the response of the gamma imaging detector at various discrete angles in 4π space through Monte Carlo simulation and experimental calibration, and constructing the response matrix, include: The calibration scheme was designed by selecting a standard gamma source and using Monte Carlo simulation to simulate and calculate the response data of the detector array composed of the detection modules at different angles. The response matrix was constructed for the design of the gamma imaging algorithm, and the theoretical design of the gamma imaging algorithm was carried out. The response data of the real detector array were obtained through experiments, and a response matrix for actual imaging reconstruction was constructed. Combined with the theoretical design of the gamma imaging algorithm, a calibration platform was built to calibrate the gamma imaging detector. According to the discrete angular spatial position, the standard gamma source scanned the gamma imaging detector in the polar angle and azimuth angle direction, recorded the counting spectrum at each position and monitored the dead time in real time, and obtained the detector array measurement data under multiple angles. The data preprocessed by background subtraction, dead time calibration, energy calibration, and peak integration were used to analyze the detector array measurement data at multiple angles. The data was then normalized by combining the activity of the radioactive source, the distance between the source and the detector, and the measurement time to obtain the relative response. Based on the relative response obtained through experimental calibration and normalization, a response function is constructed and the uncertainty is analyzed to generate a normalized response matrix.

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