Three-dimensional imaging method and system based on negative muon

Abstract

The invention discloses a negative muon-based three-dimensional imaging method and system. The method comprises the following steps: S1, emitting a negative muon beam; s2, determining the position of an interaction point of the negative muon in the to-be-imaged sample according to the position of the emergence point, the emission direction unit momentum vector of the negative muon and the movement distance of the negative muon in the emergence direction; and S3, performing three-dimensional imaging on the to-be-imaged sample according to the position of the interaction point in the to-be-imaged sample. Due to the adoption of the technical scheme, compared with the prior art, the method has the advantages that the calculation precision of the three-dimensional reconstruction point is remarkably improved by combining the emergent position and the movement track information of the negative muon, and the problem of insufficient imaging depth in the prior art is effectively solved. And secondly, through a regionalization imaging technology, three-dimensional reconstruction points are divided according to regions, and point density threshold optimization is combined, so that noise interference is effectively reduced, and imaging precision and image definition are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of negative muon imaging, and particularly relates to a three-dimensional imaging method and system based on negative muons. Background Art

[0002] The muon-induced X-ray emission spectroscopy (MIXE) technique is a non-destructive detection method that uses the interaction between a muon beam and a sample material to induce X-ray emission for elemental analysis. According to the literature Smith, J., et al. (2020). Advanced Techniques in Muon Induced X-ray Emission (MIXE) for Material Analysis. Journal of Applied Physics, 128(4), 1045 - 1060, the existing negative muon imaging methods mainly use a single-energy muon beam to perform two-dimensional or shallow three-dimensional imaging of a sample, including the following steps: First, generation and guidance of the muon beam: A single-energy muon beam (generally fixed in a momentum range of about 3 GeV) is generated by a particle accelerator and guided towards the sample. Second, interaction between the sample and muons: The muons interact with the atomic nuclei in the sample, thereby exciting characteristic X-rays in the sample. Third, collection of X-ray data by a photon detector: A highly sensitive photon detector is used to record the X-ray information emitted by the sample, including the two-dimensional arrival positions and energy data of the photons. Fourth, application of an imaging algorithm: The two-dimensional distribution of the sample is reconstructed using a known physical model based on the photon position and energy information; in some technical solutions, a stacking algorithm with different depths is attempted for three-dimensional reconstruction (Wang, H., et al. (2018). Photon Detection and Energy Analysis in MIXE-based Imaging. International Journal of Spectroscopy, 34(2), 567 - 579.). Fifth, noise processing and image optimization: Statistical analysis is performed on the collected photon data to exclude outliers or noise data to improve the accuracy of the imaging results (Lee, Y., et al. (2019). Noise Filtering and Imaging Optimization in Muon Induced Emission Techniques. Physics Reports, 452(6), 1223 - 1240.).

[0003] However, the inventors of the present invention have found that the above technologies have at least the following technical problems: In the existing negative muon imaging technology, the emission position and direction information of muons are not incorporated into the three-dimensional reconstruction algorithm, and the movement distance of muons inside the sample cannot be effectively calculated, resulting in low accuracy of the depth information in three-dimensional imaging and poor imaging quality. Summary of the Invention

[0004] The present invention provides a three-dimensional imaging method and system based on negative muons to solve the technical problems of low accuracy of the depth information in three-dimensional imaging and poor imaging quality in the existing negative muon imaging technology.

[0005] To achieve the above object, the present invention adopts the following technical solutions.

[0006] On the one hand, a three-dimensional imaging method based on negative muons is provided, including the following steps:

[0007] S1. Emit a negative muon beam;

[0008] S2. Determine the position of the interaction point of the negative muon in the sample to be imaged according to the position of the exit point, the unit momentum vector of the emission direction of the negative muon, and the movement distance of the negative muon in the emission direction;

[0009] S3. Perform three-dimensional imaging on the sample to be imaged according to the position of the interaction point in the sample to be imaged;

[0010] Wherein, a negative muon source, a first detector, a second detector, the sample to be imaged, and a third detector are arranged in sequence along the emission direction of the negative muon; the position of the exit point is the position where the negative muon hits the second detector; the unit momentum vector of the emission direction of the negative muon is determined by the positions where the negative muon hits the first detector and the second detector;

[0011] The movement distance of the negative muon in the emission direction is determined by the following method:

[0012] Determine the distance between the two according to the positions of the exit point and the hit point; the hit point is the point where the photon hits the third detector;

[0013] Subtract the exit time from the hit time to obtain the relative arrival time; wherein, the exit time is the time when the negative muon hits the second detector, and the hit time is the time when the photon hits the third detector;

[0014] According to the speed of the negative muon, the distance, and the relative arrival time, use the time-distance inversion algorithm to determine the movement distance of the negative muon in the emission direction.

[0015] In some embodiments, the negative muon beam includes negative muons with various different energies, and the energy range is from zero to the critical energy.

[0016] In some embodiments, the method for determining the critical energy includes:

[0017] Penetrating the sample to be imaged with negative muons of the initial energy;

[0018] If the negative muons completely penetrate the sample, reduce the energy; if they do not stay at the edge of the thickest end of the sample, increase the energy;

[0019] Determine the energy value at which the negative muons exactly stay at the edge of the thickest end of the sample as the critical energy.

[0020] In some embodiments, between step S1 and S2, the following steps are further included: Through energy screening, only retain the photon information and negative muon information corresponding to the characteristic energy of the elements of the main components of the sample to be imaged.

[0021] In some embodiments, between step S2 and S3, the following steps are further included:

[0022] Divide the interaction points into multiple regions according to different height ranges;

[0023] Determine the density of the interaction points in each region;

[0024] Adopt an adaptive threshold method to eliminate the interaction points with a density lower than the set threshold.

[0025] On the other hand, a three-dimensional imaging system based on negative muons is provided, including a memory, a processor, and a computer program stored on the memory, and the processor executes the computer program to implement the steps of the above method.

[0026] On the other hand, a computer-readable storage medium is provided, on which a computer program / instructions are stored, and when the computer program / instructions are executed by a processor, the steps of the above method are implemented.

[0027] On the other hand, a computer program product is provided, including a computer program / instructions, and when the computer program / instructions are executed by a processor, the steps of the above method are implemented.

[0028] The present invention has at least the following technical effects or advantages:

[0029] 1. By combining the emission position and movement trajectory information of negative muons, the calculation accuracy of three-dimensional reconstruction points is significantly improved, and the problem of insufficient imaging depth in the prior art is effectively solved.

[0030] 2. Through the regional imaging technology, the three-dimensional reconstruction points are divided and processed by region, and combined with the optimization of the point density threshold, the noise interference is effectively reduced, and the imaging accuracy and image clarity are significantly improved.

[0031] 3. The present invention can perform hierarchical processing on samples with complex structures, achieve focused analysis of specific regions, and meet the high-precision imaging requirements of multi-layer samples.

[0032] 4. By screening specific muon-induced X-ray energies, the distribution of target elements in the sample can be accurately identified, especially with significant advantages in the detection of low atomic number elements.

[0033] 5. The present invention can be widely applied to multiple fields such as material analysis, industrial non-destructive testing, and biological sample analysis, providing an efficient tool for the study of the internal structure and element distribution of complex samples. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a schematic structural diagram of an imaging device in an embodiment of the present invention;

[0035] Figure 2 It is a schematic diagram of the negative muon movement trajectory and the three-dimensional position inversion process based on photon information in an embodiment of the present invention;

[0036] Figure 3 It is a schematic diagram of the density of interaction points in different regions in an embodiment of the present invention;

[0037] Figure 4a It is a schematic diagram (front view) of the modeling of the sample to be imaged in an embodiment of the present invention;

[0038] Figure 4b It is a schematic diagram (stereogram) of the modeling of the sample to be imaged in an embodiment of the present invention;

[0039] Figure 5a It is a schematic diagram (front view) of the unoptimized imaging in an embodiment of the present invention;

[0040] Figure 5b It is a schematic diagram (stereogram) of the unoptimized imaging in an embodiment of the present invention;

[0041] Figure 6a It is a schematic diagram (front view) of the imaging after region optimization in an embodiment of the present invention;

[0042] Figure 6b It is a schematic diagram (stereogram) of the imaging after region optimization in an embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0043] In order to better understand the above technical solutions, the above technical solutions will be described in detail below in conjunction with the accompanying drawings of the specification and specific embodiments.

[0044] A three-dimensional imaging method based on negative muons includes the following steps:

[0045] S1. Emit a negative muon beam, which includes negative muons with various different energies, and the energy range is from zero to the critical energy.

[0046] In this embodiment, a vase sample is used as the research object, and its main component is iron, and its shape is shown in FIGS. 4(a, b). The energy of the emitted negative muons is (0 - 25 MeV) and the number is 10 million. The experimental objective is to realize the three-dimensional reconstruction and imaging of the iron element inside the vase sample by screening the muon-induced X-rays of iron and combining the negative muon trajectory information. After using the third detector (photon detector) to collect the characteristic muon-induced X-rays released inside the vase sample, preferably, through photon energy screening, only the photon signals and negative muon signals corresponding to the characteristic energy of iron (Fe) element (such as Fe-Kα ray 1235 keV) are retained, and the energy resolution of the detector is 2%, and the rest of the signals are eliminated.

[0047] Preferably, the following method is adopted in this embodiment to determine the critical energy of the vase sample:

[0048] Use negative muons with an initial energy (such as 30 MeV) to penetrate the sample to be imaged;

[0049] If the negative muons completely penetrate the sample, reduce the energy; if they do not stay at the edge of the thickest end of the sample, increase the energy;

[0050] Determine the energy value when the negative muons just stay at the edge of the thickest end of the sample as the critical energy. The measured critical energy value is 25 MeV.

[0051] S2. According to the position (x2, y2, z2) of the exit point, the unit momentum vector (p x , p y , p z ) of the emission direction of the negative muons, and the moving distance d of the negative muons in the emission direction, determine the position (x′, y′, z′) of the interaction point of the negative muons in the sample to be imaged. In the coordinate system of this embodiment, the center point of the negative muon emission source is taken as the origin, the negative muon emission direction is the positive direction of the y-axis, the horizontal inward direction is the positive direction of the x-axis, and the vertically upward direction is the positive direction of the z-axis, as Figure 1 shown.

[0052] The calculation formula for the position (x′, y′, z′) of the interaction point of the negative muons in the sample to be imaged is as follows:

[0053] (x′, y′, z′) = (x2 + p x ×d, y2 + p y ×d, z2 + p x ×d);

[0054] The imaging device of the present invention is as Figure 1As shown, a negative muon emission source 1, a first detector 2, a second detector 3, a sample to be imaged 4, and a third detector 5 are arranged in sequence along the emission direction of the negative muons.

[0055] Among them, the position of the exit point is the position where the negative muons hit the second detector 3;

[0056] The unit momentum vector (p x , p y , p z ) of the emission direction of the negative muons is determined by the positions where the negative muons hit the first detector and the second detector, specifically:

[0057]

[0058] In the formula, (x1, y1, z1) are the coordinate values where the negative muons hit the first detector, and (x2, y2, z2) are the coordinate values where the negative muons hit the second detector.

[0059] The movement distance d of the negative muons in the emission direction is determined by the following method:

[0060] According to the positions of the exit point and the hit point, the distance r between the two is determined; the hit point is the point where the photon hits the third detector;

[0061]

[0062] In the formula, (x γ , y γ , z γ ) are the coordinate values where the negative muons hit the third detector.

[0063] Subtract the emission time t0 from the hit time t γ to obtain the relative arrival time t, that is, t = t γ - t0. Among them, the emission time t0 is the time when the negative muons hit the second detector, and the hit time t γ is the time when the photon hits the third detector;

[0064] According to the velocity v, distance r, and relative arrival time t of the negative muons, use the time - distance inversion algorithm to determine the movement distance d of the negative muons in the emission direction, using the following formula:

[0065]

[0066] In the formula, β = v / c, and θ is the angle between the emission direction of the negative muons and the line connecting the position where the negative muons hit the second detector and the position where the photon hits the third detector. As Figure 2 shown, the emission direction of the negative muons is from S to U, the position where the negative muons hit the second detector is S, and the position where the photon hits the third detector is P. Therefore, θ is the angle between SU and SP.

[0067] Figure 2 This is a schematic diagram of the trajectory of negative muons in the present invention and the three-dimensional position inversion process based on photon information. Figure 2 In the figure, S is the position where the negative muon hits the second detector 3, P is the position where the photon hits the third detector 5, and U is the position of the interaction point in the sample to be imaged, that is, the position where the negative muon is captured in the sample to be imaged.

[0068] The velocity v of the negative muon needs to consider its rest energy m μ c 2 and kinetic energy K μ , and can be calculated by the following formula:

[0069]

[0070] In the formula, c is the speed of light (3.0×10 8 m / s), m μ is the rest mass of the negative muon (105.7 MeV / c 2 ), E μ is the total energy of the negative muon, E μ = K μ + m μ c 2 , where the kinetic energy K μ can be measured by the second detector.

[0071] S3. Perform three-dimensional imaging on the sample to be imaged according to the position (x′, y′, z′) of the interaction point in the sample to be imaged; for example, the root software can be used to directly reconstruct the imaging diagram, as shown in Figures 5(a, b).

[0072] Preferably, in order to further improve the imaging accuracy, the following steps are further included between steps S2 and S3:

[0073] Divide the interaction points into multiple regions according to different height ranges;

[0074] Determine the density of the interaction points in each region;

[0075] Adopt an adaptive threshold method to remove the interaction points with a density lower than the set threshold.

[0076] The specific steps are as follows:

[0077] Data extraction and region division: First, extract the data points of each z-axis region and divide them according to the set z-axis interval (for example, the z-axis range is from -10 mm to 10 mm, and the step size is 0.2 mm). For each region, extract the corresponding x and y coordinates to form a two-dimensional coordinate set within the region.

[0078] Generate a 2D heatmap: For the data points in each z-axis region, use a 2D histogram (e.g., the histcounts2 function) to generate a heatmap in the xoy plane. This heatmap shows the distribution of each point within the region, facilitating the visualization and analysis of the imaging data. As Figure 3 shown.

[0079] Adaptive threshold calculation: For the heatmap data of each region, calculate its mean and standard deviation. Based on the weighted coefficients of the mean and standard deviation (e.g., mean weight coefficient k1 = 0.5 and standard deviation weight coefficient k2 = 0.2), calculate the adaptive threshold. The threshold is used to screen the valid signals in the heatmap and remove the low-density noise points. This process ensures the filtering of noise and enhances the signal quality of the imaging.

[0080] Noise filtering and normalization: Set all data points less than the threshold to zero to remove the low-density noise. Then normalize the remaining valid data to ensure that the maximum value of all data in the heatmap is 1 for subsequent image generation.

[0081] Heatmap saving: Save the heatmap generated for each z-axis region and output it as an image file in a specified format (e.g., PNG format). All generated heatmaps are saved in a predetermined folder for subsequent 3D imaging use.

[0082] After that, based on the heatmap generated in the previous step, perform z-axis reconstruction using 3D Slicer. Complete the full 3D imaging reconstruction by importing the 2D heatmap sequence into 3D Slicer and setting the z-axis height. The specific steps are as follows:

[0083] Image import and cropping: Import the 2D heatmaps generated in the fourth step into Photoshop for cropping. Each heatmap is cropped to 500x500 pixels and arranged in the z-axis order. This process ensures the consistency of the images in terms of size and order to meet the requirements of 3D Slicer.

[0084] Import into 3D Slicer: Import the cropped and organized heatmap files into 3D Slicer. In 3D Slicer, these images will be used as slices at different z-axis levels and arranged and displayed in order.

[0085] Set the z-axis height: In 3D Slicer, by setting the z-axis height of the object model, associate the position of each image with its corresponding z-axis coordinate. In this way, all heatmaps are arranged in the order of z-axis height, forming a 3D data set.

[0086] Global Threshold Screening: The imported images are further screened using the global threshold function in 3D Slicer. By setting appropriate thresholds, noise points in the images are removed, and valid imaging data is retained. This step helps to further improve the imaging quality and ensure the accuracy and integrity of the reconstructed images.

[0087] Three-Dimensional Reconstruction: The image data after threshold screening is used for three-dimensional reconstruction. In 3D Slicer, all the two-dimensional heatmaps are inversed in sequence to generate the final three-dimensional imaging map. By stacking the heatmap data layer by layer, a three-dimensional reconstructed image with high precision and quality is formed. The optimized imaging schematic diagrams are shown in Figures 6(a,b).

[0088] In the specification provided herein, numerous specific details are set forth. However, it is understood that embodiments of the present invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0089] Similarly, it should be understood that, in order to streamline this disclosure and assist in understanding one or more of the various inventive aspects, in the foregoing description of the exemplary embodiments of the present invention, the various features of the present invention are sometimes grouped together in a single embodiment, figure, or description thereof. However, the disclosed method should not be construed as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as the claims reflect, the inventive aspects lie in less than all the features of the single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of the present invention.

[0090] Those skilled in the art should understand that the modules or units or groups of the devices in the examples disclosed herein may be arranged in the devices as described in this embodiment, or alternatively may be located in one or more devices different from the devices in this example. The modules in the foregoing examples may be combined into one module or further divided into multiple sub-modules.

[0091] Those skilled in the art can understand that the modules in the devices in the embodiments can be adaptively changed and arranged in one or more devices different from those of the embodiments. The modules or units or groups in the embodiments can be combined into one module or unit or group, and in addition, they can be divided into multiple sub-modules or sub-units or sub-groups. Except that at least some of such features and / or processes or units are mutually exclusive, any combination can be adopted to combine all the features disclosed in this specification (including the accompanying claims, abstract and drawings) and all the processes or units of any method or device thus disclosed. Unless otherwise explicitly stated, each feature disclosed in this specification (including the accompanying claims, abstract and drawings) can be replaced by an alternative feature that provides the same, equivalent or similar purpose.

[0092] In addition, those skilled in the art can understand that although some of the embodiments described herein include certain features included in other embodiments rather than other features, the combination of the features of different embodiments means that it is within the scope of the present invention and forms different embodiments.

[0093] In addition, some of the embodiments herein are described as a combination of methods or method elements that can be implemented by a processor of a computer system or by other devices performing the functions. Therefore, a processor having the necessary instructions for implementing the method or method elements forms a device for implementing the method or method elements. In addition, the elements described herein in the device embodiments are examples of the following devices: the device is used to implement the functions performed by the elements for the purpose of implementing the present invention.

[0094] The various technologies described here can be implemented in combination with hardware or software, or a combination of them. Thus, the method and device of the present invention, or certain aspects or parts of the method and device of the present invention, can take the form of program code (i.e., instructions) embedded in a tangible medium, such as a floppy disk, CD-ROM, hard disk drive or any other machine-readable storage medium, where when the program is loaded into a machine such as a computer and executed by the machine, the machine becomes a device for practicing the present invention.

[0095] In the case where the program code is executed on a programmable computer, the computing device generally includes a processor, a processor-readable storage medium (including volatile and non-volatile memories and / or storage elements), at least one input device, and at least one output device. Among them, the memory is configured to store the program code; the processor is configured to execute the method of the present invention according to the instructions in the program code stored in the memory.

[0096] By way of example and not limitation, computer-readable media includes computer storage media and communication media. Computer-readable media includes computer storage media and communication media. Computer storage media stores information such as computer-readable instructions, data structures, program modules or other data. Communication media typically embodies computer-readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism, and includes any information delivery media. A combination of any of the above is also included within the scope of computer-readable media.

[0097] As used herein, unless otherwise specified, the use of ordinal numbers "first", "second", "third", etc. to describe ordinary objects merely indicates different instances of similar objects and is not intended to imply that the objects so described must have a given order in time, space, ranking, or in any other manner.

[0098] Although the invention has been described in terms of a limited number of embodiments, those skilled in the art in this technical field will appreciate, based on the above description, that other embodiments may be contemplated within the scope of the invention thus described. In addition, it should be noted that the language used in this specification has been selected primarily for readability and teaching purposes rather than for the purpose of explaining or limiting the subject matter of the invention. Thus, many modifications and variations will be apparent to those of ordinary skill in the art in this technical field without departing from the scope and spirit of the appended claims. For the scope of the invention, the disclosure of the invention is illustrative, not restrictive, and the scope of the invention is defined by the appended claims.

[0099] Finally, the common knowledge recognized by those skilled in the art is not explained in detail in the present invention. The above is only a specific embodiment of the present invention and is not intended to limit the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A three-dimensional imaging method based on negative muons, characterized in that, The method includes the following steps: S1. Emitting a negative muon beam; S2. Determining the position of the interaction point of the negative muons in the sample to be imaged according to the position of the exit point, the unit momentum vector of the emission direction of the negative muons, and the moving distance of the negative muons in the exit direction; S3. Performing three-dimensional imaging on the sample to be imaged according to the position of the interaction point in the sample to be imaged; Wherein, a negative muon source, a first detector, a second detector, the sample to be imaged, and a third detector are arranged in sequence along the emission direction of the negative muons; the position of the exit point is the position where the negative muons hit the second detector; the unit momentum vector of the emission direction of the negative muons is determined by the positions where the negative muons hit the first detector and the second detector; The moving distance of the negative muons in the exit direction is determined by the following method: Determining the distance between the two according to the positions of the exit point and the hit point; the hit point is the point where the photon hits the third detector; subtracting the exit time from the hit time to obtain the relative arrival time; wherein, the exit time is the time when the negative muons hit the second detector, and the hit time is the time when the photon hits the third detector; According to the speed of the negative muons, the distance, and the relative arrival time, using the time-distance inversion algorithm to determine the moving distance of the negative muons in the exit direction.

2. The three-dimensional imaging method based on negative muons according to claim 1, characterized in that: The negative muon beam includes negative muons with a variety of different energies, and the energy range is from zero to the critical energy.

3. The three-dimensional imaging method based on negative muons according to claim 2, wherein The method for determining the critical energy includes: Penetrating the sample to be imaged with negative muons of the initial energy; If the negative muons completely penetrate the sample, reducing the energy; if they do not stay at the edge of the thickest end of the sample, increasing the energy; Determining the energy value at which the negative muons just stay at the edge of the thickest end of the sample as the critical energy.

4. The three-dimensional imaging method based on negative muons according to claim 2, wherein, Between step S1 and S2, the following step is further included: through energy screening, only retaining the photon information and negative muon information corresponding to the elemental characteristic energy of the main components of the sample to be imaged.

5. The three-dimensional imaging method based on muons according to any one of claims 1-4, characterized in that, Between step S2 and S3, the following steps are further included: Dividing the interaction points into multiple regions according to different height ranges; Determining the density of the interaction points in each region; Using an adaptive threshold method to eliminate the interaction points with a density lower than the set threshold.

6. A three-dimensional imaging system based on muons, comprising a memory, a processor, and a computer program stored on the memory, characterized in that, The processor executes the computer program to implement the steps of the method according to any one of claims 1-5.

7. A computer-readable storage medium having computer programs / instructions stored thereon, characterized in that, When the computer program / instructions are executed by the processor, the steps of the method according to any one of claims 1-5 are implemented.

8. A computer program product, comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, the steps of the method according to any one of claims 1-5 are implemented.

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