High flux x-ray multi-spectral detection system and method

Abstract

This application relates to the field of X-ray detection technology, specifically to a high-throughput X-ray multi-energy spectral detection system and method. The detection method includes preparing n filters Z with different K absorption limits. i , i∈(1,n), n≥15; the incident X-rays, after collimation, pass through each filter Z i The electrical signal S was detected after attenuation. i S i =∫η×[φ(E)×C i (E)]dE,(E min E max ); for electrical signal S i The incident X-ray energy spectrum is obtained by discretizing the spectrum and then solving for the least squares solution. Based on the detection principle of energy integration, this application achieves flexible modulation and demodulation of high-throughput X-ray energy spectra through mathematical combinations of filters with different linear attenuation coefficients, balancing detection cost with obtaining high-resolution X-ray energy spectra.

Description

Technical Field

[0001] This application relates to the technical field of X-ray detection, and in particular to a high-throughput X-ray multi-energy spectral detection system and detection method. Background Technology

[0002] In modern medical diagnosis, X-ray computed tomography (CT) technology has been widely used. It employs a non-contact detection method, based on the absorption characteristics of X-rays to different materials. By detecting the attenuation characteristics of X-rays after passing through a substance, it obtains information about the internal structure and material composition of the object. A long-term development trend in the field of X-rays is the shift from single-energy black-and-white images to multi-energy color images. This can effectively distinguish materials of different densities and, combined with subtraction algorithms, extract features of the target object. Currently, there are two main detection principles in the field of X-ray imaging: traditional X-ray imaging based on energy integrating detectors and multi-energy spectral X-ray imaging based on photon counting detectors.

[0003] An energy-integrating detector acquires all photons (flux of approximately 10) within the circuit's integration time (ms to s). 6 ~10 9 cps / mm 2 The current mainstream technology for X-ray imaging is based on the intensity of X-rays. Energy integrating detectors receive X-ray photons of different energies as a whole after they pass through an object, reflecting the average attenuation characteristics of X-rays. They cannot distinguish between X-ray photons of different energies, making it difficult to differentiate materials with similar density distributions. This limits qualitative and quantitative analysis of matter, and they are easily affected by radiation hardening and noise. Therefore, traditional X-ray imaging technology has poor image quality and can only produce grayscale images, unable to obtain multi-energy color images. Experienced doctors need to interpret image contours and grayscale levels to diagnose illnesses. Attempts have been made to use multiple exposures of X-rays with different energy spectra and side-incident detection with multi-layer detectors to achieve limited energy resolution with integrating detectors, but this "pseudo-multi-energy scheme" has low energy resolution and low practical application value.

[0004] The industry pins its hopes for multi-energy spectral X-ray detection on photon counting technology. Photon counting detectors possess the energy resolution capability of individual X-ray photons, allowing simultaneous measurement of photon counts at multiple energy thresholds. Photons with differentiated energy levels can be used to obtain multi-energy color images based on their attenuation characteristics (e.g., low-energy X-ray photons are more sensitive to soft tissues like the lungs, while high-energy photons are more sensitive to hard tissues like bone). Photon counting detectors can obtain X-ray energy spectrum data, thus providing attenuation information of matter at multiple energy thresholds. Using photon count data from multiple energy bands of the object under test, multiple images can be created, and a high-resolution, high signal-to-noise ratio, low-radiation-dose fused image can be obtained through image fusion algorithms. Multi-energy spectral X-ray imaging technology has advantages such as accurate matter resolution, high imaging signal-to-noise ratio, strong practicality, and low radiation dose, and has broad application prospects in the field of medical imaging. However, current photon counting detectors have many limitations—low count rate (<10). 8 cps / mm 2 The limitations of this technology, such as poor counting stability and count rate being limited by dead time, restrict the effectiveness of multi-energy X-ray detection and limit the development speed and application prospects of energy spectrum detection based on photon counting technology.

[0005] The aforementioned technologies suffer from a trade-off between detection cost and energy resolution. Summary of the Invention

[0006] In order to achieve both detection cost and resolution in X-ray energy spectroscopy detection, the purpose of this application is to provide a high-throughput X-ray multi-energy spectroscopy detection system and detection method.

[0007] Firstly, the high-throughput X-ray multi-energy spectral detection method provided in this application adopts the following technical solution:

[0008] A high-throughput X-ray multi-energy spectroscopy detection method includes the following steps:

[0009] Prepare n types of filters Z with different K absorption limits i , i∈(1,n), n≥15;

[0010] After the incident X-rays are collimated, they pass through each filter Z. i attenuation;

[0011] The electrical signal S was detected after attenuation. i , In the formula, η is the proportionality coefficient. The energy spectrum of the incident X-rays, (E min E max ) represents the energy range of the incident X-rays, C i (E)=E×e -μi(E)diWhere E is the energy of the incident X-ray, μ i (E) represents filter Z. i The attenuation coefficient, d i For filter Z i The thickness;

[0012] In (E) min E max Within the energy range, n types of filters divide this energy range into m energy windows based on the K absorption limit. j , j∈(1,m);

[0013] Filter Z i In each energy window W j C inside i (E) is denoted as C ij φ(E) is denoted as φ within each energy window. j For electrical signal S i Discretization

[0014] Based on Solving for the least squares solution yields the partial energy spectrum of the incident X-rays. Based on the partial energy spectrum of incident X-rays The incident X-ray energy spectrum was obtained.

[0015] By adopting the above technical solution, based on the detection principle of energy integration, and through the mathematical combination of filters with different attenuation coefficients, flexible modulation and demodulation of high-throughput X-ray energy spectra are achieved, resulting in the detection of X-ray energy spectra with fine resolution. On the one hand, although photon counting energy spectroscopy theoretically has higher resolution, it is constrained by many practical factors, such as complex circuit design and stringent single-crystal requirements, preventing current photon counting energy spectroscopy from reaching its theoretical resolution. The energy resolution of this application is approximately 15-20%, comparable to the performance of photon counting detectors and far exceeding all previous "pseudo-multi-energy schemes" of energy integration detectors, thus possessing real application value. On the other hand, the detection cost is lower and the practicality is stronger. Current photon counting energy spectroscopy involves extremely high costs due to high-purity raw material purification, stringent single-crystal selection, and complex electronic design. This application eliminates the need for expensive circuit design and stringent single-crystal selection; it only requires filter materials of various elements in a simple integrating detector, significantly reducing costs. Furthermore, based on the principle of energy integration, this application avoids the bottlenecks of low count rate and dead time associated with photon counting detectors.

[0016] Optional, n = 30-40.

[0017] By adopting the above technical solution, the number of filter types can be increased, thereby improving the resolution of the detected X-ray energy spectrum. Theoretically, the larger the value of n, the better. Considering practical factors, the preferred value of n is 30-40, which improves the resolution while simplifying the operation steps.

[0018] Optional, filter Z i The materials used in its production are selected from elements with atomic numbers from 40 to 83.

[0019] By adopting the above technical solution, with the exception of a few radioactive and rare elements, most elements with atomic numbers from 40 to 83 are metallic elements, which facilitates the fabrication of filters, and in (E min E max Within the energy range, it can screen materials with a relatively uniform distribution of the K absorption limit, thereby improving the detection resolution.

[0020] Optionally, elements from 40 to 83 can be used to fabricate filter Z in its elemental metallic form. i Alternatively, it can be mixed with PVB in compound form and pressed into a filter. i .

[0021] By adopting the above technical solution, in the preparation process, the metal element that can be formed into a sheet can be directly used as a filter, while other element filters are made by mixing and pressing PVB (polyvinyl butyral) in the form of a compound, which promotes the pressing effect and has a small absorption of X-rays, so the impact on the test results can be basically ignored.

[0022] Optionally, the compound may be selected as an oxide, chloride, or sulfate in order of stability.

[0023] By adopting the above technical solutions, the stability of the tableted product is ensured while promoting tablet formation.

[0024] Optionally, the mass ratio of the compound to PVB is 1:0.45-0.55.

[0025] By adopting the above technical solution, the tableting effect is improved while reducing the impact on test results.

[0026] Optionally, the mass ratio of the compound to PVB is 1:0.5.

[0027] By adopting the above technical solution, the tableting effect is improved while reducing the impact on test results.

[0028] Optional, n types of filters Z i The absorption limit of K is (E) min E max Within the energy range, they tend to be evenly spaced.

[0029] By adopting the above technical solutions, the resolution of the detection spectrum is improved.

[0030] Secondly, the high-throughput X-ray multi-energy spectral detection system provided in this application adopts the following technical solution:

[0031] A high-throughput X-ray multi-energy spectral detection system includes:

[0032] X-ray emitter, used to emit incident X-rays;

[0033] A collimation mold, located behind the X-ray emitter, is used to receive incident X-rays and collimate them;

[0034] A filter bank consisting of n different filter types Z with varying absorption limits (K). i , i∈(1,n), n≥15, each filter Z i It is selectively placed behind the collimating mold to attenuate the collimated incident X-rays and produce outgoing X-rays;

[0035] The detector is placed on filter Z. i Behind, used to detect emitted X-rays and obtain electrical signals S i ;

[0036] The host computer is used to receive the signal from each filter Z. i Corresponding electrical signal S i The incident X-ray energy spectrum was obtained by inverse solving, specifically:

[0037] In the formula, η is the proportionality coefficient. The energy spectrum of the incident X-rays, (E min E max ) represents the energy range of the incident X-rays, C i (E)=E×e -μi(E)di Where E is the energy of the incident X-ray, μ i (E) represents filter Z. i The attenuation coefficient, d i For filter Z i The thickness;

[0038] In (E) min E max Within the energy range, n types of filters divide this energy range into m energy windows based on the K absorption limit. j , j∈(1,m);

[0039] Filter Z i In each energy window W j C inside i (E) is denoted as C ij φ(E) is denoted as φ within each energy window.j For electrical signal S i Discretization

[0040] Based on Solving for the least squares solution yields the partial energy spectrum of the incident X-rays.

[0041] Based on the partial energy spectrum of incident X-rays The incident X-ray energy spectrum was obtained.

[0042] By adopting the above technical solution, a high-throughput X-ray multi-energy spectrum detection system is constructed based on the detection principle of energy integration. Through the mathematical combination of filters with different linear attenuation coefficients, flexible modulation and demodulation of high-throughput X-ray energy spectrum is achieved, and X-ray energy spectrum with fine resolution is obtained. It has lower detection cost and stronger practical operability.

[0043] In summary, this application includes at least one of the following beneficial technical effects:

[0044] Based on the detection principle of energy integration, and through the mathematical combination of filters with different linear attenuation coefficients, flexible modulation and demodulation of high-throughput X-ray energy spectra are achieved, and fine-resolution X-ray energy spectra are obtained.

[0045] On the one hand, although theoretically photon counting energy spectrum detection has a higher resolution, it is constrained by many practical factors, such as complex circuit design and stringent single crystal requirements, which prevents current photon counting energy spectrum detection from reaching its theoretical resolution. The energy resolution of this application can rival the performance of photon counting detectors and far exceeds all previous energy integration detector "pseudo-multi-energy schemes", thus having real application value.

[0046] On the other hand, the detection cost is lower and the practicality is stronger. Current photon counting energy spectrum detection involves extremely high costs due to the purification of high-purity raw materials, rigorous selection of good single crystals, and complex electronic design. This application does not require expensive circuit design and rigorous single crystal selection. It can be completed with filter materials of various elements under a simple integrating detector, which greatly reduces the cost.

[0047] Furthermore, based on the principle of energy integration, this application avoids the bottlenecks of low count rate and dead time associated with photon counting detectors. Attached Figure Description

[0048] Figure 1 These are the 35 types of filters with different K absorption limits in Embodiment 1 of this application;

[0049] Figure 2 These are the energy spectrum and ideal energy spectrum detected in Embodiment 1 of this application;

[0050] Figure 3 This is the limit resolution-energy map detected in Embodiment 1 of this application. Detailed Implementation

[0051] To improve the resolution of high-throughput X-ray multi-energy spectral detection, related technologies employ photon counting energy spectral detection. However, due to many practical factors, current photon counting energy spectral detection falls far short of its theoretical resolution and has a high detection cost; this application is based on this.

[0052] This application provides a high-throughput X-ray multi-energy spectral detection method, including the following steps: Step 1, preparing n types of filters Z with different K absorption limits. i , i∈(1,n), n≥15, in some embodiments, n=30-40, n types of filters are made of different filter materials, that is, the K absorption limit of each filter is different, and the Z of n types of filters. i The absorption limits K are denoted in ascending order as {Z1, Z2, ..., Z...} i ... Z n-1 Z n}, i∈(1,n), n≥15, where the n K absorption limits are denoted as {K1, K2, ..., K} in ascending order. i K n-1 K n}, i∈(1,n);

[0053] Step 2: After collimation, the incident X-rays pass through each filter Z. i Attenuation, during the detection process, the filter Z is replaced. i Complete all filters Z i The electrical signal under attenuation was detected after the collimated incident X-rays were attenuated, and the electrical signal was denoted as S. i , i∈(1,n);

[0054] Electrical signal S i It can be represented as:

[0055] The detector converts the input light signal into an electrical signal output. The magnitude of the output electrical signal (the number of charges generated by the detector) is related to the energy of the incident X-rays. The greater the energy of the X-rays, the more charges are generated, and the larger the detected electrical signal. That is, the detector's electrical signal Signal(E) = α × E, where α is the proportionality coefficient and E is the energy of the incident X-rays.

[0056] Furthermore, it can be seen that the electrical signal of the integrating detector is:

[0057]

[0058] In the above formula, ∫ represents the integral sign, α is the proportionality coefficient, β is the proportionality coefficient (the two proportionality coefficients can be combined into a single proportionality coefficient η), and E is the energy of the incident X-ray. For the X-ray energy spectrum (the term to be solved), E min E max This is achieved by setting the X-ray tube. In one embodiment, it can be set to 20-80 keV, 0-100 keV, etc., depending on the actual situation.

[0059] A filter Z is placed in front of the integrating detector. i Given filter Z i The attenuation coefficient is μ i (E), thickness d i If i∈(1,n), then the filter Z i The attenuation of incident X-rays can be denoted as: e -μi(E)di ;

[0060] Considering the photoelectric effect and various scattering methods, based on equation (1), the electrical signal generated on the detector by the attenuated spectrum is:

[0061]

[0062] Let C i (E)=E×e -μi(E)di Equation (2) can be simplified as follows:

[0063]

[0064] In (E) min E max Within the energy range, n types of filters divide this energy range into m energy windows based on the K absorption limit. j , j∈(1,m);

[0065] It is approximated that the filter Z i In each energy window W j C inside i (E) is a constant, denoted as C. ij ;

[0066] φ(E) is a constant within each energy window, denoted as

[0067] For the electrical signal S corresponding to equation (3) i Discretization yields:

[0068]

[0069] For all filters Z i have:

[0070]

[0071] Step 3: Based on equation (5) above, solve for the least squares solution to obtain the partial energy spectrum of the incident X-rays. During the solution process:

[0072] The error in the coefficient matrix is ​​a kind of random noise. Random noise affects the low-rank approximation of the matrix. It is necessary to increase the "tolerance of the calculated rank" to make the minimum norm least squares solution close to the actual value, while ensuring that random noise does not destroy the solution.

[0073] Step 4: Analytical Energy Spectrum Based on Incident X-rays The incident X-ray energy spectrum was obtained.

[0074] In some embodiments, filter Z i The materials used in its fabrication are elements with atomic numbers from 40 to 83. During the fabrication process, these elements are used in their metallic form to create the filter Z. i Alternatively, it can be mixed with PVB in compound form and pressed into a filter. i In one embodiment, the compound is selected in order of stability as an oxide, chloride, or sulfate, depending on the properties of the element itself.

[0075] In some embodiments, the mass ratio of the compound to PVB is 1:0.45-0.55, and in one specific embodiment, the mass ratio of the compound to PVB is 1:0.5.

[0076] In some embodiments, n types of filters Z i The absorption limit of K is (E) min E max Within the energy range, they tend to be evenly spaced.

[0077] The present application will be further described in detail below with reference to the embodiments.

[0078] Obtaining the Ideal Energy Spectrum: The X-ray tube is used to emit high-throughput, continuous-spectrum, divergent incident X-rays. Because the parameters of the X-ray tube are known and fixed, a known spectrum is obtained by filtering and correcting the X-ray tube. This known spectrum is used as the ideal energy spectrum. Specifically, as follows... Figure 2 As shown;

[0079] Then, the known spectrum is treated as an unknown spectrum and detected and calculated using the multi-energy spectrum detection method in Example 1.

[0080] Example 1:

[0081] A high-throughput X-ray multi-energy spectroscopy detection method includes the following steps:

[0082] S1. Select and prepare n types of filters Z i , i∈(1,n), n≥15, each filter Z i Different filter materials used in manufacturing result in different absorption limits (K) for each type of filter. The number of filter types Z... i There are n K absorption limits. The detailed data of the K absorption limit of each material can be obtained by looking up the table. When the X-ray energy is equal to the ionization energy of an inner electron of the irradiated sample, resonance absorption will occur, causing the electron to be ionized into a photoelectron. The X-ray absorption coefficient will change abruptly. This abrupt change is called the absorption edge. It is named K absorption edge, L absorption edge, etc. according to the principal quantum number. In this application, the K absorption limit corresponds to the K absorption edge.

[0083] n types of filters Z i The absorption limits K are denoted in ascending order as {Z1, Z2, ..., Z...} i ... Z n-1 Z n}, i∈(1,n), n≥15, where the n K absorption limits are denoted as {K1, K2, ..., K} in ascending order. i K n-1 K n}, i∈(1,n);

[0084] Furthermore, the larger the value of n, the finer the modulation and demodulation of the high-throughput X-ray energy spectrum, and the better the resolution of multi-energy X-ray detection. Preferably, the filter material is constructed from the vast majority of elements with atomic numbers from a=40 (Zr) to a=83 (Bi) (excluding radioactive elements and a few rare elements). In this embodiment, n=35, and the filter materials corresponding to the 35 filter sheets Z are as follows: Figure 1As shown, it includes: ZrO2 (zirconium dioxide), Nb (niobium), Mo (molybdenum), RuO2 (ruthenium dioxide), PdCl2 (lead dichloride), Ag (silver), CdO (chromium oxide), In (indium), Sn (tin), Sb2O3 (antimony trioxide), Te (tellurium), CsCl (cesium chloride), BaSO4 (barium sulfate), La2O3 (lanthanum trioxide), CeO2 (cerium dioxide), Pr6O4 (praseodymium tetroxide), Nd2O3 (neodymium trioxide), and Sm2O3 (samarium trioxide). Eu2O3 (Eupolytriium oxide), Gd2O3 (Gadolinium oxide), Dy2O3 (Dysprosium oxide), Ho2O3 (Holmium oxide), Er2O3 (Erbium oxide), Tm2O3 (Thulium oxide), Yb2O3 (Ytterbium oxide), Lu2O3 (Lutium oxide), HfO2 (Hafnium oxide), Ta (Tantalum), W (Tungsten), IrO2 (Iridium oxide), Au (Gold), HgSO4 (Mercury sulfate), TiCl (Thallium chloride), Pb (Lead), Bi2O3 (Bismuth oxide);

[0085] In the preparation process of filter Z, metal elements that can be formed from sheet metal can be directly used as filter metals, such as Nb (niobium), Mo (molybdenum), Ag (silver), etc. Other elements can be selectively prepared by mixing their oxides (e.g., RuO2 (ruthenium dioxide)), chlorides (e.g., PdCl2 (lead dichloride)), sulfates (e.g., BaSO4 (barium sulfate)) with PVB (polyvinyl butyral) in the form of compressed sheets. The mass ratio of the oxides, chlorides or sulfates of other elements to PVB is 1:0.4-0.6. In this embodiment, the mass ratio is 1:0.5.

[0086] S2. Establish a detection system, which includes:

[0087] X-ray tube, used to emit high-throughput, continuous-spectrum, divergent incident X-rays;

[0088] A collimation mold, located behind the X-ray tube, is used to receive incident X-rays and collimate them to obtain parallel X-rays.

[0089] Filter Z i It is located behind the collimation mold and is used to filter and modulate parallel X-rays to produce emitted X-rays.

[0090] The detector is located on filter Z. i The rear section is used to receive emitted X-rays and detect the electrical signal S. i Among them, the detector can be an integrating detector;

[0091] S3. Acquire the electrical signal of the emitted X-rays, including:

[0092] S3a, Determine the filter as filter Z. i , i = 1;

[0093] S3b, The incident X-rays generated by the X-ray tube are collimated by the collimating mold and then filtered by the filter Z. i After partial attenuation, the emitted X-rays are detected by the detector, and the electrical signal S of the emitted X-rays is obtained. i :

[0094] S i =∫η×[φ(E)×E×e -μi(E)di ]dE,(E min E max (101);

[0095] In equation (101), ∫ represents the integral symbol;

[0096] η is the proportionality coefficient;

[0097] φ(E) is the incident X-ray energy spectrum (a term to be solved);

[0098] E is the energy of the incident X-ray;

[0099] E min E max This is achieved by adjusting the X-ray tube settings. In this embodiment, it can be set to 0-100 keV, i.e., E. min =0keV,E max =100keV;

[0100] μ i (E) represents filter Z. i The attenuation coefficient, d i For filter Z i The thickness of the filter Z is then... i The attenuation of X-rays with energy E is e -μi(E)di The attenuation coefficient refers to the proportion of X-rays attenuated when passing through a material of unit thickness. It is related to the type of material, and the linear attenuation coefficient of a specific element can usually be found directly.

[0101] S3c, let C i (E)=E×e -μi(E)di Then equation (101) can be simplified as:

[0102] S i =ξ·∫φ(E)·C i (E)dE,(E min E max (102);

[0103] Incrementing S3d and i by 1 confirms that the filter is filter Z. i+1Repeat steps S3b-S3c to obtain: S i+1 =ξ·∫φ(E)·C i+1 (E)dE,(E min E max );

[0104] S3e, Repeat step S3d until i+1 = n, to obtain: S n =ξ·∫φ(E)·C n (E)dE,(E min E max );

[0105] In summary, the equations for the electrical signals of the n emitted X-rays corresponding to the n filters are as follows:

[0106] S1=ξ·∫φ(E)·C1(E)dE, S2=ξ·∫φ(E)·C2(E)dE,...,S i =ξ·∫φ(E)·C i (E)dE、......、

[0107] S n =ξ·∫φ(E)·C n (E)dE;

[0108] S4, in (E min E max Within the energy range, n types of filters divide this energy range into m energy windows based on the K absorption limit. j In one of the process embodiments, m energy windows W j Let them be denoted as {W1, W2, ..., W} in sequence. j ... W n W m In this embodiment, (E) min E max ) is 0-100 keV, and K m Taking <100 keV as an example, m energy windows W j The corresponding numbers are {0-K1, K1-K2, ..., K}, respectively. j-1 -K j K m-1 -K m K m -100 KeV};

[0109] It is approximated that the filter Z i (i∈(1,n), n≥15) in each energy window W j C within (j∈(1,m)) i (E)=(E×e -μi(E)di) is a constant, that is, C i (E)=C ij .

[0110] With filter Z i Taking i=1 as an example, C i (E)=C ij Including {C 11 C 12 C 1j C 1(n-1) C 1n C 1(m)}, a total of m terms, that is Specifically:

[0111]

[0112] at this time Within each energy window, a constant value is set. Equation (103) is discretized, and let... have to:

[0113]

[0114] Equation (104) includes:

[0115]

[0116] Combine the above n expressions into the following expression (105).

[0117]

[0118] S4. Based on equation (105), solve for the least squares solution to obtain the partial energy spectrum of the incident X-rays. Spectroscopy A one-to-one correspondence with m energy windows based on m energy windows W j {0-K1, K1-K2, ..., K j-1 -K j K m-1 -K m K m -100 KeV}, and the partial energy spectra φ1, φ2, ..., φ1 corresponding to each energy window. j , ......, φ m-1 φ m , get as Figure 2 The energy spectrum diagram shown in Example 1 is as follows: the horizontal axis represents the energy of the photon (kev), the vertical axis can be understood as the number of photons at a specific energy per unit area, and au represents the relative intensity, which can be understood as the proportion of photons at that energy.

[0119] according to Figure 2 It can be seen that the energy spectrum calculated in Example 1 has a high degree of matching with the ideal energy spectrum, with an overlap of more than 99%, indicating that the multi-energy spectrum detection method of the example is feasible and very accurate.

[0120] Resolution test:

[0121] For detectors designed to measure the energy of incident X-ray radiation, the most important metric is energy resolution. This metric measures how well the detector can distinguish between two close radiation energies. Generally, we can measure energy resolution by sending a single-energy radiation beam to the detector and observing the resulting energy spectrum. Ideally, we would like to see sharp functional energy peaks. In reality, this is not the case; the energy peak structure we usually observe has finite broadening and a Gaussian shape. This broadening is due to statistical fluctuations in the number of ionizations and excitations produced by the radiation within the detector. Energy resolution is usually given as the full width at half maximum (FWHM) at the peak of the spectrum. Energy closer to the FWHM is generally considered indistinguishable. If we express this width as ΔE, then the energy resolution at energy E is ΔE / E. Energy resolution is usually expressed as a percentage.

[0122] Figure 3 The limit resolution-energy diagram shows that the horizontal axis represents energy and the vertical axis represents energy resolution. The achievable energy resolution is 3.1%@59.5keV, which means that the minimum energy that a photon detector with an energy of 59.5keV can resolve is 59.5 × 3.1% = 1.8445keV.

[0123] The highest throughput is represented by photon-counting spectral CT, with photon throughput reaching hundreds of millions of X-ray photons per square millimeter of detector area per second, i.e., hundreds of millions of X-ray photons per square millimeter per second. Currently, in the clinical range of 80-140 keV peak, the energy resolution of this type of color CT application is about 15-20%.

[0124] Example 2

[0125] A high-throughput X-ray multi-energy spectral detection system includes:

[0126] X-ray emitter (ray source), used to emit incident X-rays;

[0127] A collimation mold, located behind the X-ray emitter, is used to receive incident X-rays and collimate them;

[0128] A filter bank consisting of n different filter types Z with varying absorption limits (K). i, i∈(1,n), n≥15, each filter Z i It is selectively placed behind the collimating mold to attenuate the collimated incident X-rays and produce outgoing X-rays;

[0129] The detector is placed on filter Z. i Behind, used to detect emitted X-rays and obtain electrical signals S i ;

[0130] The host computer is used to receive the signal from each filter Z. i Corresponding electrical signal S i The incident X-ray energy spectrum was obtained by inverse solving, specifically:

[0131] In the formula, η is the proportionality coefficient. The energy spectrum of the incident X-rays, (E min E max ) represents the energy range of the incident X-rays, C i (E)=E×e -μi(E)di Where E is the energy of the incident X-ray, μ i (E) represents filter Z. i The attenuation coefficient, d i For filter Z i The thickness;

[0132] In (E) min E max Within the energy range, n types of filters divide this energy range into m energy windows based on the K absorption limit. j , j∈(1,m);

[0133] Filter Z i In each energy window W j C inside i (E) is denoted as C ij , Recorded in each energy window as For electrical signal S i Discretization

[0134] Based on Solving for the least squares solution yields the partial energy spectrum of the incident X-rays.

[0135] Based on the partial energy spectrum of incident X-rays The incident X-ray energy spectrum was obtained.

[0136] The embodiments described in this specific implementation are preferred embodiments of this application and are not intended to limit the scope of protection of this application. Identical components are represented by the same reference numerals. Therefore, all equivalent changes made to the structure, shape, and principle of this application should be covered within the scope of protection of this application.

Claims

1. A high-throughput X-ray multi-energy spectral detection method, characterized in that, Includes the following steps: Prepare n types of filters Z with different K absorption limits i , i∈(1,n), n≥15; After the incident X-rays are collimated, they pass through each filter Z. i attenuation; The electrical signal S was detected after attenuation. i S i =∫ η×[ (E)×C i (E)]dE,(E min E max In the formula, η is the proportionality coefficient. (E) represents the energy spectrum of the incident X-rays. min E max () represents the energy range of the incident X-rays. Where E is the energy of the incident X-ray, μ i (E) represents filter Z. i The attenuation coefficient, d i For filter Z i The thickness; In (E) min E max Within the energy range, n types of filters divide this energy range into m energy windows based on the K absorption limit. j , j∈(1,m); Filter Z i In each energy window W j C inside i (E) is denoted as C ij , (E) is denoted as within each energy window. j For electrical signal S i Discretization ; Based on Solving for the least squares solution yields the energy spectrum of the incident X-rays.

1. 2、......、 j ... n , m ; Based on the partial energy spectrum of incident X-rays 1. 2、......、 j ... n , m The incident X-ray energy spectrum was obtained; Among them, filter Z i The materials used in its fabrication are selected from elements with atomic numbers from 40 to 83, and there are n types of filter sheets Z. i The absorption limit of K is (E) min E max Within the energy range, they tend to be evenly spaced.

2. The high-throughput X-ray multi-energy spectral detection method according to claim 1, characterized in that, 30≤n≤40。 3. The high-throughput X-ray multi-energy spectral detection method according to claim 1, characterized in that, Filter Z is made from elements from 40 to 83 in their metallic form. i Alternatively, it can be mixed with PVB in compound form and pressed into a filter. i .

4. The high-throughput X-ray multi-energy spectral detection method according to claim 3, characterized in that, The compounds were selected in order of stability as oxides, chlorides, or sulfides.

5. The high-throughput X-ray multi-energy spectral detection method according to claim 3, characterized in that, The mass ratio of the compound to PVB is 1:0.45-0.

55.

6. The high-throughput X-ray multi-energy spectral detection method according to claim 5, characterized in that, The mass ratio of the compound to PVB is 1:0.

5.

7. A high-throughput X-ray multi-energy spectral detection system, characterized in that, include: X-ray emitter, used to emit incident X-rays; A collimation mold, located behind the X-ray emitter, is used to receive incident X-rays and collimate them; A filter bank consisting of n different filter types Z with varying absorption limits (K). i , i∈(1,n), n≥15, each filter Z i Selectively placed behind the collimating mold to attenuate the collimated incident X-rays and produce outgoing X-rays; The detector is placed on the filter Z. i Behind, used to detect emitted X-rays and obtain electrical signals S i ; host computer Used to receive each filter Z i Corresponding electrical signal S i The incident X-ray energy spectrum was obtained by inverse solving, specifically: S i =∫ η×[ (E)×C i (E)]dE,(E min E max In the formula, η is the proportionality coefficient. (E) represents the energy spectrum of the incident X-rays. min E max () represents the energy range of the incident X-rays. Where E is the energy of the incident X-ray, μ i (E) represents filter Z. i The attenuation coefficient, d i For filter Z i The thickness; In (E) min E max Within the energy range, n types of filters divide this energy range into m energy windows based on the K absorption limit. j , j∈(1,m); Filter Z i In each energy window W j C inside i (E) is denoted as C ij , (E) is denoted as within each energy window. j For electrical signal S i Discretization ; Based on Solving for the least squares solution yields the partial energy spectrum of the incident X-rays.

1. 2、......、 j ... n , m ; Based on the partial energy spectrum of incident X-rays 1. 2、......、 j ... n , m The incident X-ray energy spectrum was obtained; Among them, filter Z i The materials used in its fabrication are selected from elements with atomic numbers from 40 to 83, and there are n types of filter sheets Z. i The absorption limit of K is (E) min E max Within the energy range, they tend to be evenly spaced.

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