Energy threshold acquisition method, base material decomposition method, system, device, medium

Abstract

This disclosure provides a method for obtaining an energy threshold, a method for decomposing a matrix material, a system, an apparatus, and a medium. The method for obtaining the energy threshold includes: acquiring imaging images of at least two preset calibration phantoms corresponding to preset energy ranges based on preset imaging parameters; wherein the preset calibration phantoms include a target matrix material, and the preset energy ranges are determined according to a preset energy threshold in the preset imaging parameters; acquiring the mass decay coefficient of the preset calibration phantoms based on the imaging images; determining the decay difference between the target matrix materials based on the mass decay coefficient; and determining the target energy threshold for imaging based on the decay difference and the preset energy threshold. This disclosure calculates the decay difference based on the actually measured mass decay coefficient of the preset calibration phantom corresponding to the target matrix material, and determines the target energy threshold based on the decay difference and the preset energy threshold used during measurement, which can assist in determining the selection of the target energy threshold for any target matrix material to be decomposed.

Description

Technical Field

[0001] This disclosure relates to the field of photon counting technology, and in particular to a method for obtaining an energy threshold, a method for decomposing a base material, a system, an apparatus, and a medium. Background Technology

[0002] Photo-counting CT (PCCT) is another CT revolution following spiral CT and multi-slice spiral CT. Compared with traditional CT, PCCT adds the concept of energy bin.

[0003] PCCT, by pre-setting energy thresholds, can create multiple energy ranges corresponding to the number of detectors in a photon-counting CT device. A single scan typically yields several data points, which are then distributed into different energy ranges based on photon energy. Photon-counting CT can perform imaging based on photons in different energy ranges, providing richer X-ray attenuation information and improving the accuracy of material identification and imaging effects.

[0004] The principle behind photon-counting CT for matter decomposition is that different elements have different attenuation coefficients under different energy X-rays. For example, certain elements with k-edge properties (such as iodine, gadolinium, and gold contained in contrast agents) exhibit a sudden increase in their attenuation coefficient under specific energy X-rays. This sudden increase in the attenuation coefficient leads to a significant decrease in the photon count value in the corresponding energy range. Utilizing this property, photon-counting CT can achieve the decomposition of multiple substances (if the number of decomposable substances is M, then 2 ≤ M ≤ N).

[0005] However, except for a few high atomic number contrast agents, such as iodine, gold, and gadolinium, for most elements or compounds with lower atomic numbers, the k-edge energy is too low and falls outside the energy range commonly used in photon-counting CT. Therefore, the k-edge properties cannot be used for substance decomposition. For example, the k-edge energy of calcium is approximately 4 keV, while in photon-counting CT, to eliminate the influence of detector electronic noise, the minimum energy is usually higher than 10 keV. Therefore, the k-edge energy of calcium is not a meaningful reference for determining the threshold of the energy range. Summary of the Invention

[0006] To address the aforementioned technical problems, this disclosure provides a method for obtaining energy thresholds, a method for decomposing base materials, a system, equipment, and a medium.

[0007] In a first aspect, this disclosure provides a method for obtaining an energy threshold, the method comprising:

[0008] Based on preset imaging parameters, at least two preset calibration phantoms are acquired, each corresponding to a preset energy range; wherein, the preset calibration phantoms include target matrix materials, and the preset energy ranges are determined according to preset energy thresholds in the preset imaging parameters;

[0009] The mass attenuation coefficient of the preset calibration phantom is obtained based on the imaging image;

[0010] The decay difference between the target base materials is determined based on the mass decay coefficient.

[0011] The target energy threshold for imaging is determined based on the attenuation difference and the preset energy threshold.

[0012] Optionally, the preset imaging parameters include multiple preset energy thresholds;

[0013] The step of acquiring imaging images of at least two preset calibration phantoms corresponding to preset energy ranges based on preset imaging parameters includes:

[0014] Acquire imaging images of each of the preset calibration phantoms corresponding to different preset energy ranges; wherein the preset calibration phantoms are arranged side by side, and the different preset energy ranges are determined according to the multiple preset energy thresholds.

[0015] Optionally, when the morphological parameters of the preset calibration phantoms are the same, the imaging image is a projection image;

[0016] The step of obtaining the mass attenuation coefficient of the preset calibration phantom based on the imaging image includes:

[0017] Segment the projection area corresponding to each preset calibration model from the projection diagram;

[0018] Calculate the average projection value of each of the preset calibration phantoms based on the projection area;

[0019] The mass decay coefficient of each preset calibration phantom corresponding to the energy range is obtained based on the density of the preset calibration phantom and the average projection value.

[0020] Optionally, the imaging image is a three-dimensional reconstructed image;

[0021] The step of obtaining the mass attenuation coefficient of the preset calibration phantom based on the imaging image includes:

[0022] Based on the three-dimensional reconstruction image, the CT values ​​corresponding to the preset calibration phantoms are obtained respectively;

[0023] The mass decay coefficient of the preset calibration phantom corresponding to the energy range is obtained based on the density of the preset calibration phantom and the CT value.

[0024] Optionally, the step of determining the attenuation difference between the target base materials based on the mass attenuation coefficient includes:

[0025] The decay difference between the target base materials is determined using a similarity algorithm based on the mass decay coefficient.

[0026] Secondly, this disclosure provides a method for decomposing a basic substance, the method comprising:

[0027] According to the energy threshold acquisition method described in the first aspect, the target energy threshold corresponding to the target base material in the decomposed material is obtained;

[0028] Based on the target energy threshold, the decomposition images corresponding to the target base material are obtained respectively.

[0029] Thirdly, this disclosure provides an energy threshold acquisition system, the system comprising:

[0030] The acquisition module is used to acquire imaging images of at least two preset calibration phantoms corresponding to preset energy ranges based on preset imaging parameters; wherein, the preset calibration phantoms include target matrix materials, and the preset energy ranges are determined according to preset energy thresholds in the preset imaging parameters;

[0031] The attenuation coefficient acquisition module is used to acquire the mass attenuation coefficient of the preset calibration phantom based on the imaging image.

[0032] The attenuation difference calculation module is used to determine the attenuation difference between the target base materials based on the mass attenuation coefficient.

[0033] The target determination module is used to determine the target energy threshold based on the attenuation difference and the preset energy threshold.

[0034] Optionally, the preset imaging parameters include multiple preset energy thresholds;

[0035] The acquisition module is used to acquire imaging images of each of the preset calibration phantoms corresponding to different preset energy ranges; wherein the preset calibration phantoms are arranged side by side, and the different preset energy ranges are determined according to the plurality of preset energy thresholds.

[0036] Optionally, when the morphological parameters of the preset calibration phantoms are the same, the imaging image is a projection image;

[0037] The attenuation coefficient acquisition module is used to segment the projection area corresponding to each preset calibration phantom from the projection map; calculate the average projection value of each preset calibration phantom based on the projection area; and obtain the mass attenuation coefficient of each preset calibration phantom corresponding to the energy range according to the density of the preset calibration phantom and the average projection value.

[0038] Optionally, the imaging image is a three-dimensional reconstructed image;

[0039] The attenuation coefficient acquisition module is used to obtain the CT value corresponding to the preset calibration phantom based on the three-dimensional reconstruction image; and to obtain the mass attenuation coefficient of the preset calibration phantom corresponding to the energy range according to the density of the preset calibration phantom and the CT value.

[0040] Optionally, the attenuation difference calculation module is used to determine the attenuation difference between the target base materials based on the mass attenuation coefficient using a similarity algorithm.

[0041] Fourthly, this disclosure provides a basic material decomposition system, the system comprising:

[0042] The threshold determination module is used to obtain the target energy threshold corresponding to the target base material in the decomposed material according to the energy threshold acquisition system described in the third aspect.

[0043] The material decomposition module is used to obtain decomposition images corresponding to the target base material based on the target energy threshold.

[0044] Fifthly, this disclosure provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the energy threshold acquisition method described in the first aspect or the base material decomposition method described in the second aspect.

[0045] In a sixth aspect, this disclosure provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, it implements the energy threshold acquisition method of the first aspect or the base material decomposition method of the second aspect.

[0046] The positive advancements of this disclosure are as follows: This disclosure provides an energy threshold acquisition method, a base material decomposition method, a system, equipment, and a medium. The energy threshold acquisition method calculates the attenuation difference based on the actual measured mass attenuation coefficient of a preset calibration phantom corresponding to the target base material. It then analyzes and determines the target energy threshold based on the attenuation difference and the preset energy threshold used during measurement, facilitating the acquisition of a decomposition image of the target base material in practical applications. It is not limited to the energy value corresponding to the theoretical k-edge of the material and is applicable to the decomposition of any target base material, assisting in determining the selection of the target energy threshold for any target base material to be decomposed. Furthermore, when the morphological parameters of the preset calibration phantoms are consistent, analysis can be performed in the projection domain by scanning the preset calibration phantoms from a single angle, eliminating the need for 360° scanning and image reconstruction before analysis in the image domain. This allows for simple and rapid analysis and determination of the target energy threshold when decomposing the target base material. Attached Figure Description

[0047] Figure 1 A flowchart illustrating the energy threshold acquisition method provided in this embodiment of the disclosure;

[0048] Figure 2 This is a schematic diagram showing the placement of the preset calibration phantoms provided in the embodiments of this disclosure;

[0049] Figure 3 A schematic flowchart of the basic material decomposition method provided in the embodiments of this disclosure;

[0050] Figure 4 This is a schematic diagram of the energy threshold acquisition system provided in an embodiment of the present disclosure;

[0051] Figure 5 This is a schematic diagram of the basic material decomposition system in an embodiment of this disclosure;

[0052] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0053] The present invention will be further illustrated by way of embodiments below, but the present invention is not limited to the scope of the embodiments described herein.

[0054] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this embodiment, unless otherwise stated, "a plurality of" means two or more.

[0055] See Figure 1 , Figure 1 An energy threshold acquisition method is illustrated in an embodiment of this disclosure. This method is used to acquire a target energy threshold corresponding to a target base material in the material to be decomposed, so that subsequent decomposition images corresponding to the target base material can be acquired based on the target energy threshold.

[0056] like Figure 1 As shown, the method for obtaining the energy threshold includes:

[0057] Step S101: Based on preset imaging parameters, acquire imaging images of at least two preset calibration phantoms corresponding to preset energy ranges; wherein, the preset calibration phantoms include target matrix materials, and the preset energy ranges are determined according to preset energy thresholds;

[0058] Step S102: Obtain the mass attenuation coefficient of the preset calibration phantom based on the imaging image;

[0059] Step S103: Determine the attenuation difference between target base materials based on the mass attenuation coefficient;

[0060] Step S104: Determine the target energy threshold for imaging based on the attenuation difference and the preset energy threshold.

[0061] In step S101, the imaging image of each preset calibration phantom under the same preset imaging parameters is obtained.

[0062] The preset imaging parameters include image exposure parameters such as tube voltage, tube current, exposure time, and preset energy threshold. The preset energy range is determined based on the preset energy threshold.

[0063] In practical applications, some imaging devices have a default maximum energy threshold, meaning that a preset energy range can be formed by including only the minimum energy threshold in the preset imaging parameters. This preset energy range extends from the minimum energy threshold to the maximum energy threshold. In this case, an imaging image corresponding to a single preset energy range can be obtained for the preset calibration phantom. For other imaging devices, such as photon counting CT devices, which can simultaneously acquire imaging images of multiple preset energy ranges, the preset imaging parameters can include multiple preset energy thresholds.

[0064] In some embodiments, to acquire images of preset calibration phantoms more efficiently, multiple preset calibration phantoms can be arranged side-by-side in the imaging device. This not only allows for the simultaneous acquisition of images of multiple preset calibration phantoms but also reduces the differences in imaging conditions between the images of the preset calibration phantoms, such as the influence of airborne impurities on the images.

[0065] Specifically, step S101 includes:

[0066] Acquire imaging images of each preset calibration phantom corresponding to a different preset energy range; wherein, the preset calibration phantoms are arranged side by side, and the different preset energy ranges are determined according to multiple preset energy thresholds.

[0067] In step S102, the corresponding step is selected based on the imaging image to obtain the mass attenuation coefficient of the preset calibration phantom.

[0068] In some embodiments, since the morphological parameters of the preset calibration phantoms are the same, it is only necessary to scan the preset calibration phantoms from a single angle to perform attenuation difference analysis based on the projection map of the preset calibration phantoms. That is, the imaging image obtained in step S101 can be a projection map.

[0069] Specifically, step S102 includes:

[0070] Segment the projection area corresponding to each preset calibration model from the projection diagram;

[0071] Calculate the average projection value of each preset calibration phantom based on the projection area;

[0072] The mass decay coefficient of each preset calibration phantom in the corresponding energy range is obtained based on the density and average projection value of the preset calibration phantom.

[0073] For example, refer to Figure 2 Preset calibration phantoms A and B are arranged side-by-side in the ray path of the photon counting CT device, such that... Figure 2 The X-rays emitted from the single X-ray source shown pass only through a single pre-defined calibration phantom, and are received by a detector after passing through the phantom. This ensures that the projection images of pre-defined calibration phantom A and pre-defined calibration phantom B do not overlap. If the pre-defined calibration phantom needs to be fixed to a carrier, the projection image of the carrier can be obtained first, followed by the projection image of the pre-defined calibration phantom fixed to the carrier. Subtracting the two projection images yields the projection image of the X-rays passing only through the pre-defined calibration phantom.

[0074] After acquiring the photon count map from the photon counting CT device, the projection map for each energy range is calculated according to the Lambert-Beer law. The photon count map includes a set of photon counts for each energy range, which consists of photon counts (I) corresponding to different energies within the energy range. The photon counts are used to characterize the number of photons with the same energy.

[0075] For example, a region where the ray passes through only air is selected from the photon counting map, and the photon count I0 after the ray passes through only air is counted. Based on the photon count after the ray passes through only air and the photon count for each energy in the photon count set, the projection map P for each energy range is calculated.

[0076] The projection P is calculated as follows:

[0077]

[0078] The projection map is used to represent the attenuation integral along the ray path. Then, in the projection map P, the projection regions of the preset calibration phantom A and the preset calibration phantom B are obtained using threshold segmentation and connected component judgment.

[0079] Based on the average projection value of the projection area of ​​the preset calibration model The density ρ of the preset calibration phantom, the average length D of the ray passing through the preset calibration phantom, and the method for calculating the mass attenuation coefficient μ of the preset calibration phantom are as follows:

[0080]

[0081] The projection map is actually a set of projection values, and the average projection value of the projection area of ​​the preset calibration model is the average value of the projection values ​​in the projection area of ​​the preset calibration model.

[0082] In other embodiments, if it is unclear whether the morphological parameters of the preset calibration phantoms are the same, or if preset calibration phantoms with the same morphological parameters cannot be found, a 360-degree scan of the preset calibration phantoms can be performed to obtain a three-dimensional reconstruction image of the preset calibration phantoms. Then, regions corresponding to each preset calibration phantom are selected in the three-dimensional reconstruction image to calculate their respective CT values, and then attenuation difference analysis is performed. That is to say, the imaging image obtained in step S101 can be a three-dimensional reconstruction image.

[0083] Specifically, step S102 includes:

[0084] Based on the 3D reconstruction image, obtain the CT values ​​corresponding to the preset calibration phantoms respectively;

[0085] The mass decay coefficient of the preset calibration phantom in the corresponding energy range is obtained based on the density and CT value of the preset calibration phantom.

[0086] Among them, the attenuation information of any point in space can be directly obtained based on the three-dimensional reconstruction map, so there are no special requirements for the shape parameters and placement of the preset calibration model.

[0087] Based on the conversion relationship between CT value and linear attenuation coefficient, the density ρ of the calibration phantom and the mass attenuation coefficient μ of water in the corresponding energy range are preset. w The method for calculating the mass attenuation coefficient of the preset calibration phantom is as follows:

[0088]

[0089] In step S103, a similarity algorithm is mainly used to determine the attenuation difference between target base materials based on the mass attenuation coefficient.

[0090] The similarity algorithms include dimensionless similarity measurement algorithms such as cosine similarity, standardized Euclidean distance, Mahalanobis distance, and Pearson correlation coefficient.

[0091] Taking the cosine similarity algorithm as an example, the attenuation difference between preset calibration phantom A and preset calibration phantom B is the cosine similarity of their mass attenuation coefficients. The larger the cosine similarity, the smaller the attenuation difference between preset calibration phantom A and preset calibration phantom B in that energy range, which is less conducive to decomposition; conversely, the smaller the cosine similarity, the larger the attenuation difference between preset calibration phantom A and preset calibration phantom B in that energy range, which is more conducive to the decomposition of target matrix a in preset calibration phantom A and target matrix b in preset calibration phantom B.

[0092] Therefore, the specific calculation method for the attenuation difference cosθ between target base material a and target base material b is as follows:

[0093]

[0094] Where, μ A To preset the mass decay coefficient of calibration phantom A, μ B The mass decay coefficient of the preset calibration model B is used.

[0095] Furthermore, in the case where the image is a projection image, since the morphological parameters of the preset calibration phantom A and preset calibration phantom B are the same, and they are arranged side by side during imaging, it can be approximately assumed that the average length of preset calibration phantom A that the ray needs to pass through in the projection region of preset calibration phantom A and preset calibration phantom B is the same as the average length of preset calibration phantom B that the ray needs to pass through.

[0096] Therefore, if the cosine similarity algorithm has been determined to be used to calculate the attenuation difference between target base materials, the density ρ of the preset calibration model and the average length D of the ray passing through the preset calibration model can be eliminated when calculating the attenuation difference between target base material a and target base material b.

[0097] For example, if the mass decay coefficient μ of the preset calibration phantom A in the first preset energy range is obtained respectively A1 and the mass decay coefficient μ in the second preset energy range A2 And the mass decay coefficient μ of the preset calibration model B in the first preset energy range. B1 and the mass decay coefficient μ in the second preset energy range B2 Therefore, the specific calculation method for the attenuation difference cosθ between target substrate a and target substrate b is as follows:

[0098]

[0099] in, The average projection value of the projection area of ​​the preset calibration phantom A in the first preset energy range. The average projection value of the projection area of ​​the preset calibration phantom A in the second preset energy range. The average projection value of the projection area of ​​the preset calibration phantom B in the first preset energy range. The average projection value of the projection area of ​​the preset calibration model B in the second preset energy range.

[0100] When the imaging image is a 3D reconstructed image, the cosine similarity algorithm can be used to calculate the attenuation difference between target substrate a and target substrate b, thereby eliminating the density ρ of the preset calibration phantom and the mass attenuation coefficient μ of water in the corresponding energy range. w .

[0101] For example, if the mass decay coefficient μ of the preset calibration phantom A in the first preset energy range is obtained respectively A1 and the mass decay coefficient μ in the second preset energy range A2 And the mass decay coefficient μ of the preset calibration model B in the first preset energy range. B1 and the mass decay coefficient μ in the second preset energy range B2 Therefore, the specific calculation method for the attenuation difference cosθ between target substrate a and target substrate b is as follows:

[0102]

[0103] Among them, CT A1 To preset the CT value of the calibration phantom A in the first preset energy range, CT A2 To preset the CT value of the calibration phantom A in the second preset energy range, CT B1 To preset the CT value of the calibration phantom B in the first preset energy range, CT B2 The CT value in the second preset energy range corresponding to the preset calibration phantom B is set.

[0104] Typically, the calculation focuses on the attenuation difference between two target base materials, i.e., the attenuation difference between a pair of target base materials.

[0105] Furthermore, for cases where more than two energy ranges are formed based on multiple preset energy thresholds in the preset imaging parameters, the specific calculation method for the attenuation difference cosθ between target substrate a and target substrate b is as follows:

[0106]

[0107] In step S104, the target energy threshold for actual decomposition can be determined based on the preset energy threshold in the current preset imaging parameters combined with the attenuation difference. Alternatively, the preset energy threshold in the preset imaging parameters can be continuously adjusted to calculate the attenuation difference between the target matrix materials under each preset energy threshold setting, and the preset energy threshold with the largest attenuation difference is usually selected as the optimal energy threshold for the decomposition of the target matrix materials.

[0108] In practical applications, a compromise can be made by comprehensively considering the image quality under the above-mentioned optimal energy threshold and different preset energy threshold settings, so that the attenuation difference is large and the image signal-to-noise ratio corresponding to different energy ranges is small.

[0109] See Figure 3 , Figure 3 An embodiment of the present disclosure provides a method for decomposing a base substance.

[0110] like Figure 3 As shown, the method for decomposing the base material includes:

[0111] Step S301: Based on the above energy threshold acquisition method, obtain the target energy threshold corresponding to the target base material in the decomposed material;

[0112] Step S302: Obtain the decomposition images corresponding to the target base material based on the target energy threshold.

[0113] See Figure 4 , Figure 4 An energy threshold acquisition system according to an embodiment of this disclosure is illustrated. This system is used to acquire the target energy threshold corresponding to the target base material in the material to be decomposed, so that subsequent decomposition images corresponding to the target base material can be acquired based on the target energy threshold.

[0114] like Figure 4 As shown, the energy threshold acquisition system includes:

[0115] The acquisition module 401 is used to acquire imaging images of at least two preset calibration phantoms corresponding to preset energy ranges based on preset imaging parameters; wherein the preset calibration phantoms include target matrix materials, and the preset energy ranges are determined according to preset energy thresholds in the preset imaging parameters.

[0116] The attenuation coefficient acquisition module 402 is used to acquire the mass attenuation coefficient of a preset calibration phantom based on the imaging image.

[0117] Attenuation difference calculation module 403 is used to determine the attenuation difference between target base materials based on the mass attenuation coefficient;

[0118] The target determination module 404 is used to determine the target energy threshold based on the attenuation difference and the preset energy threshold.

[0119] The acquisition module 401 is specifically used to acquire the imaging image of each preset calibration phantom under the same preset imaging parameters.

[0120] The preset imaging parameters include image exposure parameters such as tube voltage, tube current, exposure time, and preset energy threshold. The preset energy range is determined based on the preset energy threshold.

[0121] In practical applications, some imaging devices have a default maximum energy threshold, meaning that a preset energy range can be formed by including only the minimum energy threshold in the preset imaging parameters. This preset energy range extends from the minimum energy threshold to the maximum energy threshold. In this case, an imaging image corresponding to a single preset energy range can be obtained for the preset calibration phantom. For other imaging devices, such as photon counting CT devices, which can simultaneously acquire imaging images of multiple preset energy ranges, the preset imaging parameters can include multiple preset energy thresholds.

[0122] In some embodiments, to acquire images of preset calibration phantoms more efficiently, multiple preset calibration phantoms can be arranged side-by-side in the imaging device. This not only allows for the simultaneous acquisition of images of multiple preset calibration phantoms but also reduces the differences in imaging conditions between the images of the preset calibration phantoms, such as the influence of airborne impurities on the images.

[0123] Specifically, the acquisition module 401 is used to acquire imaging images of each preset calibration phantom corresponding to different preset energy ranges; wherein, the preset calibration phantoms are arranged side by side, and the different preset energy ranges are determined according to multiple preset energy thresholds.

[0124] The attenuation coefficient acquisition module 402 is specifically used to select the appropriate steps based on the imaging image to obtain the mass attenuation coefficient of the preset calibration phantom.

[0125] In some embodiments, since the morphological parameters of the preset calibration phantoms are the same, it is only necessary to scan the preset calibration phantoms from a single angle to perform attenuation difference analysis based on the projection map of the preset calibration phantoms. That is to say, the imaging image acquired by the acquisition module 401 can be a projection map.

[0126] Specifically, the attenuation coefficient acquisition module 402 is used to segment the projection area corresponding to each preset calibration phantom from the projection map; calculate the average projection value of each preset calibration phantom based on the projection area; and obtain the mass attenuation coefficient of each preset calibration phantom corresponding to the energy range according to the density and average projection value of the preset calibration phantom.

[0127] For example, refer to Figure 2 Preset calibration phantoms A and B are arranged side-by-side in the ray path of the photon counting CT device, such that... Figure 2 The X-rays emitted from the single X-ray source shown pass only through a single pre-defined calibration phantom, and are received by a detector after passing through the phantom. This ensures that the projection images of pre-defined calibration phantom A and pre-defined calibration phantom B do not overlap. If the pre-defined calibration phantom needs to be fixed to a carrier, the projection image of the carrier can be obtained first, followed by the projection image of the pre-defined calibration phantom fixed to the carrier. Subtracting the two projection images yields the projection image of the X-rays passing only through the pre-defined calibration phantom.

[0128] After acquiring the photon count map from the photon counting CT device, the projection map for each energy range is calculated according to the Lambert-Beer law. The photon count map includes a set of photon counts for each energy range, which consists of photon counts (I) corresponding to different energies within the energy range. The photon counts are used to characterize the number of photons with the same energy.

[0129] For example, a region where the ray passes through only air is selected from the photon counting map, and the photon count I0 after the ray passes through only air is counted. Based on the photon count after the ray passes through only air and the photon count for each energy in the photon count set, the projection map P for each energy range is calculated.

[0130] The projection P is calculated as follows:

[0131]

[0132] The projection map is used to represent the attenuation integral along the ray path. Then, in the projection map P, the projection regions of the preset calibration phantom A and the preset calibration phantom B are obtained using threshold segmentation and connected component judgment.

[0133] Based on the average projection value of the projection area of ​​the preset calibration model The density ρ of the preset calibration phantom, the average length D of the ray passing through the preset calibration phantom, and the method for calculating the mass attenuation coefficient μ of the preset calibration phantom are as follows:

[0134]

[0135] The projection map is actually a set of projection values, and the average projection value of the projection area of ​​the preset calibration model is the average value of the projection values ​​in the projection area of ​​the preset calibration model.

[0136] In other embodiments, if it is unclear whether the morphological parameters of the preset calibration phantoms are the same, or if preset calibration phantoms with the same morphological parameters cannot be found, a 360-degree scan of the preset calibration phantoms can be performed to obtain a three-dimensional reconstruction image of the preset calibration phantoms. Then, regions corresponding to each preset calibration phantom are selected in the three-dimensional reconstruction image to calculate their respective CT values, and then attenuation difference analysis is performed. That is to say, the imaging image obtained in step S101 can be a three-dimensional reconstruction image.

[0137] Specifically, the attenuation coefficient acquisition module 402 is used to acquire the CT value corresponding to the preset calibration phantom based on the three-dimensional reconstruction image; and to acquire the mass attenuation coefficient of the preset calibration phantom corresponding to the energy range based on the density and CT value of the preset calibration phantom.

[0138] Among them, the attenuation information of any point in space can be directly obtained based on the three-dimensional reconstruction map, so there are no special requirements for the shape parameters and placement of the preset calibration model.

[0139] Based on the conversion relationship between CT value and linear attenuation coefficient, the density ρ of the calibration phantom and the mass attenuation coefficient μ of water in the corresponding energy range are preset. w The method for calculating the mass attenuation coefficient of the preset calibration phantom is as follows:

[0140]

[0141] The attenuation difference calculation module 403 is mainly used to determine the attenuation difference between target base materials based on the mass attenuation coefficient using a similarity algorithm.

[0142] The similarity algorithms include dimensionless similarity measurement algorithms such as cosine similarity, standardized Euclidean distance, Mahalanobis distance, and Pearson correlation coefficient.

[0143] Taking the cosine similarity algorithm as an example, the attenuation difference between preset calibration phantom A and preset calibration phantom B is the cosine similarity of their mass attenuation coefficients. The larger the cosine similarity, the smaller the attenuation difference between preset calibration phantom A and preset calibration phantom B in that energy range, which is less conducive to decomposition; conversely, the smaller the cosine similarity, the larger the attenuation difference between preset calibration phantom A and preset calibration phantom B in that energy range, which is more conducive to the decomposition of target matrix a in preset calibration phantom A and target matrix b in preset calibration phantom B.

[0144] Therefore, the specific calculation method for the attenuation difference cosθ between target base material a and target base material b is as follows:

[0145]

[0146] Where, μ A To preset the mass decay coefficient of calibration phantom A, μB The mass decay coefficient of the preset calibration model B is used.

[0147] Furthermore, in the case where the image is a projection image, since the morphological parameters of the preset calibration phantom A and preset calibration phantom B are the same, and they are arranged side by side during imaging, it can be approximately assumed that the average length of preset calibration phantom A that the ray needs to pass through in the projection region of preset calibration phantom A and preset calibration phantom B is the same as the average length of preset calibration phantom B that the ray needs to pass through.

[0148] Therefore, if the cosine similarity algorithm has been determined to be used to calculate the attenuation difference between target base materials, the density ρ of the preset calibration model and the average length D of the ray passing through the preset calibration model can be eliminated when calculating the attenuation difference between target base material a and target base material b.

[0149] For example, if the mass decay coefficient μ of the preset calibration phantom A in the first preset energy range is obtained respectively A1 and the mass decay coefficient μ in the second preset energy range A2 And the mass decay coefficient μ of the preset calibration model B in the first preset energy range. B1 and the mass decay coefficient μ in the second preset energy range B2 Therefore, the specific calculation method for the attenuation difference cosθ between target substrate a and target substrate b is as follows:

[0150]

[0151] in, The average projection value of the projection area of ​​the preset calibration phantom A in the first preset energy range. The average projection value of the projection area of ​​the preset calibration phantom A in the second preset energy range. The average projection value of the projection area of ​​the preset calibration phantom B in the first preset energy range. The average projection value of the projection area of ​​the preset calibration model B in the second preset energy range.

[0152] When the imaging image is a 3D reconstructed image, the cosine similarity algorithm can be used to calculate the attenuation difference between target substrate a and target substrate b, thereby eliminating the density ρ of the preset calibration phantom and the mass attenuation coefficient μ of water in the corresponding energy range. w .

[0153] For example, if the mass decay coefficient μ of the preset calibration phantom A in the first preset energy range is obtained respectively A1 and the mass decay coefficient μ in the second preset energy range A2 And the mass decay coefficient μ of the preset calibration model B in the first preset energy range.B1 and the mass decay coefficient μ in the second preset energy range B2 Therefore, the specific calculation method for the attenuation difference cosθ between target substrate a and target substrate b is as follows:

[0154]

[0155] Among them, CT A1 To preset the CT value of the calibration phantom A in the first preset energy range, CT A2 To preset the CT value of the calibration phantom A in the second preset energy range, CT B1 To preset the CT value of the calibration phantom B in the first preset energy range, CT B2 The CT value in the second preset energy range corresponding to the preset calibration phantom B is set.

[0156] Typically, the calculation focuses on the attenuation difference between two target base materials, i.e., the attenuation difference between a pair of target base materials.

[0157] Furthermore, for cases where more than two energy ranges are formed based on multiple preset energy thresholds in the preset imaging parameters, the specific calculation method for the attenuation difference cosθ between target substrate a and target substrate b is as follows:

[0158]

[0159] The target determination module 404 can be used to determine the target energy threshold for actual decomposition based on the preset energy threshold in the current preset imaging parameters combined with the attenuation difference. Alternatively, it can continuously adjust the preset energy threshold in the preset imaging parameters, calculate the attenuation difference between the target matrix materials under each preset energy threshold setting, and typically select the preset energy threshold with the largest attenuation difference as the optimal energy threshold for the decomposition of the target matrix materials.

[0160] In practical applications, a compromise can be made by comprehensively considering the image quality under the above-mentioned optimal energy threshold and different preset energy threshold settings, so that the attenuation difference is large and the image signal-to-noise ratio corresponding to different energy ranges is small.

[0161] See Figure 5 , Figure 5 An embodiment of the present disclosure provides a base material decomposition system.

[0162] like Figure 5 As shown, the base material decomposition system includes:

[0163] The threshold determination module 501 is used to obtain the target energy threshold corresponding to the target base material in the decomposed material according to the above-mentioned energy threshold acquisition system.

[0164] The material decomposition module 502 is used to acquire the decomposition images corresponding to the target base material based on the target energy threshold.

[0165] See Figure 6 , Figure 6 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present disclosure. The electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the above-described energy threshold acquisition method. Figure 6 The electronic device 30 shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments disclosed herein.

[0166] like Figure 6 As shown, the electronic device 60 can be represented in the form of a general computing device, such as a server device. The components of the electronic device 60 may include, but are not limited to: at least one processor 61, at least one memory 62, and a bus 63 connecting different system components (including memory 62 and processor 61).

[0167] Bus 63 includes a data bus, an address bus, and a control bus.

[0168] The memory 62 may include volatile memory, such as random access memory (RAM) 621 and / or cache memory 622, and may further include read-only memory (ROM) 623.

[0169] The memory 62 may also include a program / utility 625 having a set (at least one) of program modules 624, including but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.

[0170] The processor 61 executes various functional applications and data processing by running computer programs stored in the memory 62, such as the energy threshold acquisition method described above in this disclosure.

[0171] Electronic device 60 can also communicate with one or more external devices 64 (e.g., keyboard, pointing device, etc.). This communication can be performed via input / output (I / O) interface 65. Furthermore, the model-generating device 60 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 66. Figure 6As shown, network adapter 66 communicates with other modules of the model-generated device 60 via bus 63. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the model-generated device 60, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems.

[0172] It should be noted that although several units / modules or sub-units / modules of the electronic device have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of this disclosure, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided and embodied by multiple units / modules.

[0173] This disclosure also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described energy threshold acquisition method.

[0174] The readable storage medium may be more specifically, including but not limited to: portable disks, magnetic disks, random access memory, read-only memory, erasable programmable read-only memory, optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0175] In a possible implementation, this disclosure can also be implemented as a program product comprising program code, which, when the program product is run on a terminal device, is used to cause the terminal device to execute the above-described energy threshold acquisition method.

[0176] The program code for executing this disclosure can be written using any combination of one or more programming languages. The program code can be executed entirely on a user device, partially on a user device, as a standalone software package, partially on a user device and partially on a remote device, or entirely on a remote device.

[0177] While specific embodiments of the present invention have been described above, those skilled in the art should understand that these are merely illustrative examples, and the scope of protection of the present invention is defined by the appended claims. Those skilled in the art can make various changes or modifications to these embodiments without departing from the principles and essence of the present invention, but all such changes and modifications fall within the scope of protection of the present invention.

Claims

1. An energy threshold acquisition method, characterized by, The energy threshold acquisition method includes: Based on preset imaging parameters, at least two preset calibration phantoms are acquired, each corresponding to a preset energy range; wherein, the preset calibration phantoms include target matrix materials, and the preset energy ranges are determined according to preset energy thresholds in the preset imaging parameters; The mass attenuation coefficient of the preset calibration phantom is obtained based on the imaging image; The decay difference between the target base materials is determined based on the mass decay coefficient. The target energy threshold for imaging is determined based on the attenuation difference and the preset energy threshold.

2. The energy threshold acquisition method of claim 1, wherein, The preset imaging parameters include multiple preset energy thresholds; The step of acquiring imaging images of at least two preset calibration phantoms corresponding to preset energy ranges based on preset imaging parameters includes: Acquire imaging images of each of the preset calibration phantoms corresponding to different preset energy ranges; wherein the preset calibration phantoms are arranged side by side, and the different preset energy ranges are determined according to the multiple preset energy thresholds.

3. The energy threshold acquisition method according to claim 1 or 2, characterized in that, When the morphological parameters of the preset calibration phantoms are the same, the imaging image is a projection image; The step of obtaining the mass attenuation coefficient of the preset calibration phantom based on the imaging image includes: Segment the projection area corresponding to each preset calibration model from the projection diagram; Calculate the average projection value of each of the preset calibration phantoms based on the projection area; The mass decay coefficient of each preset calibration phantom corresponding to the energy range is obtained based on the density of the preset calibration phantom and the average projection value.

4. The energy threshold acquisition method according to claim 1 or 2, characterized by, The imaging image is a three-dimensional reconstructed image; The step of obtaining the mass attenuation coefficient of the preset calibration phantom based on the imaging image includes: Based on the three-dimensional reconstruction image, the CT values ​​corresponding to the preset calibration phantoms are obtained respectively; The mass decay coefficient of the preset calibration phantom corresponding to the energy range is obtained based on the density of the preset calibration phantom and the CT value.

5. The energy threshold acquisition method of claim 1, wherein, The step of determining the attenuation difference between the target base materials based on the mass attenuation coefficient includes: The decay difference between the target base materials is determined using a similarity algorithm based on the mass decay coefficient.

6. A method of decomposing a base material, characterized by, The method for decomposing the base material includes: According to any one of claims 1-5, the energy threshold acquisition method obtains the target energy threshold corresponding to the target base material in the substance to be decomposed; Based on the target energy threshold, the decomposition images corresponding to the target base material are obtained respectively.

7. An energy threshold acquisition system, characterized by, The energy threshold acquisition system includes: The acquisition module is used to acquire imaging images of at least two preset calibration phantoms corresponding to preset energy ranges based on preset imaging parameters; wherein, the preset calibration phantoms include target matrix materials, and the preset energy ranges are determined according to preset energy thresholds in the preset imaging parameters; The attenuation coefficient acquisition module is used to acquire the mass attenuation coefficient of the preset calibration phantom based on the imaging image. The attenuation difference calculation module is used to determine the attenuation difference between the target base materials based on the mass attenuation coefficient. The target determination module is used to determine the target energy threshold based on the attenuation difference and the preset energy threshold.

8. A substrate decomposition system characterized by comprising: The base material decomposition system includes: A threshold determination module is used to obtain the target energy threshold corresponding to the target base material in the decomposed material according to the energy threshold acquisition system according to claim 7. The material decomposition module is used to acquire decomposition images corresponding to the target base material based on the target energy threshold.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the energy threshold acquisition method as described in any one of claims 1-5, or the base material decomposition method as described in claim 6.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, When the computer program is executed by the processor, it implements the energy threshold acquisition method as described in any one of claims 1-5, or the base material decomposition method as described in claim 6.

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