Compton camera XFCT imaging system and image reconstruction method thereof

Abstract

The present invention discloses a Compton camera XFCT imaging system and an image reconstruction method thereof, comprising: a ray source and two sets of double-layer Compton camera detectors, wherein the two sets of double-layer Compton camera detectors are arranged at intervals in a straight line, the ray source is located beside the straight line, and the two sets of double-layer Compton camera detectors are symmetrical about the ray source, and the ray source is a gamma ray source; the two sets of double-layer Compton camera detectors each include a scattering detector and an absorption detector, the scattering detector is used to record the position where Compton scattering occurs and the deposited energy of recoil electrons; the absorption detector is used to receive scattered photons and record the absorption position and deposited energy.

Description

Technical Field

[0001] The present invention relates to the field of medical imaging technology, and in particular to a Compton camera XFCT imaging system and an image reconstruction method thereof. Background Art

[0002] Existing X-ray computed tomography (XCT) technologies include traditional spiral CT, static CT, and micro-CT. These technologies are based on the differences in X-ray absorption and attenuation among different biological tissues. As X-ray beams pass through the human body, they are absorbed and scattered by various tissues, causing variations in X-ray intensity after exiting the body. Detectors receive these attenuated X-ray signals and convert them into electrical or digital signals. A computer then processes and reconstructs these signals, ultimately generating cross-sectional images of the human body.

[0003] X-ray fluorescence computed tomography (XFCT) is an imaging technique that combines X-ray fluorescence analysis and X-CT. X-rays are irradiated into a sample to excite high-Z tracer atoms within it, generating X-ray fluorescence photons. These are then received by an X-ray fluorescence detector, providing information on the spatial distribution of tracer concentration within the sample. This overcomes the shortcomings of traditional CT in detecting certain subtle lesions or when high tissue differentiation is required. However, this technology still has many problems. It requires mechanical collimation of the photon direction, which reduces photon absorption, and requires long scanning times, which increases radiation risks. It also has low spatial resolution and is limited in resolving high-atomic-number elements. Existing image reconstruction algorithms require a significant amount of time to acquire data, are computationally complex, and are difficult to remove noise, resulting in low imaging accuracy.

[0004] The Compton Camera (CC) uses the physical effect of Compton scattering to track the direction of incident photons and perform "electronic collimation." This eliminates the need for mechanical collimators and enables 3D imaging through one or more scanning views. Its compact size, light weight, and low power consumption make it suitable for portable and space-constrained applications. However, this method also has several drawbacks, including low fluorescence photon utilization, low detection efficiency, and limited energy resolution. The reconstruction algorithm is computationally complex and time-consuming when processing large amounts of data or high-resolution imaging, and is severely susceptible to noise interference. Summary of the Invention

[0005] The object of the present invention is to provide a Compton camera XFCT imaging system and an image reconstruction method thereof, so as to solve the problems of low imaging efficiency and poor imaging quality of existing imaging systems.

[0006] A first aspect of the present invention provides a Compton camera XFCT imaging system, comprising:

[0007] X-ray source and two sets of double-layer Compton camera detectors,

[0008] The two sets of double-layer Compton camera detectors are arranged in a straight line at intervals, and the radiation source is located beside the straight line. The two sets of double-layer Compton camera detectors are symmetrical about the radiation source, and the radiation source is a gamma ray source.

[0009] Both sets of double-layer Compton camera detectors include scattering detectors and absorption detectors. The scattering detectors are used to record the location where Compton scattering occurs and the deposited energy of the recoil electrons; the absorption detectors are used to receive scattered photons and record the absorption location and deposited energy.

[0010] Furthermore, the distance between the scattering detector and the sample to be measured is 60 mm, and the distance between the scattering detector and the absorption detector is 20 mm.

[0011] Furthermore, the scattering detector is made of silicon and has a size of 20 mm×20 mm×5 mm.

[0012] Furthermore, the absorption detector is made of cadmium zinc telluride and has a size of 50 mm×50 mm×5 mm.

[0013] A second aspect of the present invention provides an image reconstruction method for a Compton camera XFCT imaging system, which is used in the above-mentioned Compton camera XFCT imaging system. The method comprises placing a sample to be measured on a straight line between two sets of double-layer Compton camera detectors arranged at intervals, and making the two sets of double-layer Compton camera detectors symmetrical about the straight line connecting the radiation source and the sample to be measured, comprising:

[0014] S01: irradiating the sample to be tested with gamma rays emitted by the ray source, so that the gamma rays interact with the elements in the sample to produce fluorescent photons; wherein the fluorescent photons are incident on the scattering detector to generate Compton scattering events, and the fluorescent photons after Compton scattering are absorbed by the absorption detector to generate Compton absorption events;

[0015] S02: Receive and record the fluorescence photons when the Compton scattering event occurs through the corresponding scattering detector to obtain Compton scattering event data, wherein the Compton scattering event data includes the scattering point position (x) when the fluorescence photons undergo Compton scattering. s ,y s ,z s ) and deposition energy E s ;

[0016] S03: Receive and record the fluorescence photons when the Compton absorption event occurs through the corresponding absorption detector to obtain Compton absorption event data, wherein the Compton absorption event data includes the absorption point position (x a ,y a ,z a ) and deposition energy E a ;

[0017] S04: filtering the Compton scattering event data and the Compton absorption event data;

[0018] S05: performing angle calculation on the filtered Compton scattering event data and the Compton absorption event data to obtain a scattering angle θ i ;

[0019] S06: dividing the space where the sample to be tested and the two sets of double-layer Compton camera detectors are located into a plurality of cubic units to obtain a voxel space, wherein each cubic unit serves as a voxel;

[0020] S07: According to the scattering angle θ i Back-projecting the filtered Compton scattering event data and the Compton absorption event data into the voxel space;

[0021] S08: Calculating the propagation direction of the fluorescent photon according to the projection The intersection coordinates of the fluorescent photon and the voxel, the path length d of the fluorescent photon in the voxel ij and the energy deposition ratio e ij , and update the system matrix to obtain the system matrix element a ij ;

[0022] S09: According to the system matrix element a ij The intensity value f of the voxel is calculated using the MLEM algorithm. j Perform iterative updates to obtain a reconstruction result matrix, perform three-dimensional volume reconstruction on the reconstruction result matrix using a visualization software tool to obtain a reconstruction result image, and adjust the iteration parameters in real time according to the reconstruction result image until the reconstruction result image meets the preset requirements.

[0023] Furthermore, S04: filtering the Compton scattering event data and the Compton absorption event data, including:

[0024] Calculate the scattering point position (x s ,y s ,z s) and the absorption point position (x a ,y a ,z a ) between s-a , the distance d s-a The distance threshold d th For comparison, if d s-a <d th , then the corresponding scattering point position (x s ,y s ,z s ) and the corresponding absorption point position (x a ,y a ,z a ) are deleted from the Compton scattering event data and the Compton absorption event data, respectively.

[0025] Further, S05: performing angle calculation on the filtered Compton scattering event data and the Compton absorption event data to obtain a scattering angle θ i ,include:

[0026] From the filtered Compton scattering event data and Compton absorption event data, the scattering angle θ is calculated using the Compton scattering angle calculation formula according to the deposition energy Es at the scattering point and the deposition energy Ea at the absorption point. i , the formula is:

[0027] Among them, m e c 2 represents the electron rest energy.

[0028] Further, S08: Calculate the propagation direction of the fluorescent photon according to the projection The intersection coordinates of the fluorescent photon and the voxel, the path length d of the fluorescent photon in the voxel ij and the energy deposition ratio e ij , and update the system matrix to obtain the system matrix element a ij ,include:

[0029] Calculate the fluorescence photon from the scattering point position (x s ,y s ,z s ) to the absorption point position (x a ,y a ,z a ) direction vector The formula is: For the direction vector Normalization is performed to obtain the propagation direction of the fluorescence photon The formula is:

[0030]

[0031] Calculate the intersection coordinates of the fluorescent photon and the voxel, where the position of the voxel can be expressed as (x j ,y j ,z j );

[0032] The range of the voxel in the X-axis, Y-axis, and Z-axis directions is calculated using the range formula. j1 =X j +0.5×ΔX,X j2 =X j +1×ΔX,Y j1 =Y j +0.5×ΔY,Y j2 =Y j +1×ΔY,Z j1 =Z j +0.5×ΔZ,Z j2 =Z j +1×ΔZ, where X j1 and X j2 Indicates the range of the voxel in the X-axis direction, Y j1 and Y j2 Indicates the range of the voxel in the Y-axis direction, Z j1 and Z j2 represents the range of the voxel in the Z-axis direction, ΔX, ΔY, and ΔZ represent the variable range of the voxel in the X-axis, Y-axis, and Z-axis respectively, and j represents the index of the voxel;

[0033] Through the photon propagation formula The value range of the parameter t on the X-axis, Y-axis, and Z-axis is calculated by the voxel boundary inequality formula:

[0034] X0+td x ∈[X j1 ,X j2 ],Y0+td y ∈[Y j1 ,Y j2 ],Z0+td z ∈[Z j1 ,Z j2 ],in, Represents the position vector of the fluorescent photon at the initial position, X0, Y0, X0 respectively represent The components on the X-axis, Y-axis, and Z-axis, d x d y d z Respectively Components on the X-axis, Y-axis, and Z-axis;

[0035] Substitute the value range of parameter t on the X-axis, Y-axis and Z-axis into the photon propagation formula respectively Performing calculations to obtain the coordinates of the intersection of the fluorescent photon and the voxel;

[0036] Calculate the path length d of the fluorescent photon in the voxel according to the intersection coordinates ij , the formula is:

[0037] in, and represents the boundary intersection point when the fluorescence photon intersects the voxel;

[0038] According to the Beer-Lambert law, the intensity attenuation of the fluorescent photons after passing through the voxel and the energy deposition ratio e of the fluorescent photons in the voxel are calculated. ij , the formula is:

[0039] Where I0 and I represent the energy of the fluorescence photon before and after attenuation in the voxel, μ j represents the attenuation coefficient of fluorescence photons in the voxel;

[0040] According to the propagation direction Intersection coordinates, path length d ij and the energy deposition ratio e ij Update the system matrix to obtain the system matrix element a ij , the formula is:

[0041] Furthermore, according to the system matrix element a i j uses the MLEM algorithm to calculate the intensity value f of the voxel j Perform iterative updates to obtain the reconstruction result matrix, including:

[0042] Initialize the algorithm parameters, including the number of iterations n, the initial voxel intensity estimate f j (0) , assign an initial value to the weight of each voxel in the voxel space, and iteratively update the voxel intensity value f of the voxel in combination with the MLEM algorithm j , the formula is:

[0043] Wherein, i represents the index of the observation data detected by the double-layer Compton camera detector, j represents the index of the voxel, and f j represents the intensity value of voxel j, f j(n) represents the intensity value of voxel j at n iterations, f j (n+1) represents the intensity value of voxel j at the next iteration, and m represents the upper limit of the observed data.

[0044] Furthermore, adjusting iteration parameters in real time according to the reconstructed image until the reconstructed image meets preset requirements includes:

[0045] Adjust the preset distance threshold d th : If artifacts occur, increase the preset distance threshold d th If the noise events increase, the preset distance threshold d is reduced. th , where the scattering point position (x s ,y s ,z s ) and the absorption point position (x a ,y a ,z a ) between s-a , is less than the preset distance threshold d th The event is judged as a noise event;

[0046] Adjust the attenuation coefficient μ of fluorescent photons in voxels j Value: Set different attenuation coefficients μ according to different elements j Numeric value;

[0047] Adjust the initial voxel intensity estimate f according to the element concentration in the reconstructed image j (0) .

[0048] The present invention has at least the following beneficial effects:

[0049] The Compton camera XFCT imaging system provided in the present invention can track and detect photons from more angles, obtain more effective Compton events, improve angular resolution, and significantly reduce the half-maximum width (FWHM) of the distribution, thereby improving ARM performance by 19%. It also reduces the omission of fluorescent photons due to directional limitations, thereby reducing background interference. The system can more accurately determine the propagation direction of fluorescent photons and locate the position of the radiation source, and has better energy resolution, thereby improving the detection efficiency and imaging accuracy of the entire system for fluorescent photons and accelerating the imaging process.

[0050] In the present invention, the scattering angle θ is accurately calculated by filtering the Compton scattering event data and the Compton absorption event data. i and the propagation direction of the fluorescence photons The coordinates of the intersection of the fluorescent photon and the voxel, and the path length d of the fluorescent photon within the voxel ij and the energy deposition ratio eij It effectively suppresses noise and artifacts, accurately separates edge parts and positioning elements, and makes the position and concentration distribution of high-Z elements clearly discernible, thereby improving the image resolution and imaging accuracy, and helping to more accurately analyze the internal structure and element distribution of the measured sample. Calculate the propagation direction of fluorescent photons The coordinates of the intersection of the fluorescent photon and the voxel, and the path length d of the fluorescent photon within the voxel ij and the energy deposition ratio e ij Then update the system matrix to get the system matrix element a ij , system matrix element a ij Describes the projection probability of voxel j to the observed i-th data, the system matrix element a ij The element value can be adaptively adjusted according to the scattering angle and energy of different Compton scattering events, thereby accurately reflecting the scattering, absorption, and propagation and energy distribution of fluorescent photons between different voxels, thereby improving the accuracy of imaging. The voxel intensity value f is updated by combining the MLEM iterative formula j , which closely combines the voxel intensity update with the actual element distribution, thereby improving the spatial resolution and being able to more accurately identify the element types, especially for low-concentration elements, which can also be clearly displayed, improving the ability to resolve the details of the element distribution.

[0051] During the imaging process, visualization software is used to display the reconstructed image, which facilitates observation of the element distribution, noise level, resolution, etc. in the image, and enables timely detection of problems and corresponding adjustments, ensuring that the iterative process proceeds in the direction of improving image quality, further improving the imaging quality and making the entire imaging process more controllable and optimized.

[0052] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0053] Figure 1 A schematic diagram of the structure of a Compton camera XFCT imaging system provided by the present invention;

[0054] Figure 2 A flowchart of an image reconstruction method for a Compton camera XFCT imaging system provided by the present invention;

[0055] Figure 3 Schematic diagram of the photon propagation direction and its relationship with spatial voxels in the present invention;

[0056] Figure 4 A schematic diagram of three-dimensional volume reconstruction of a Compton camera XFCT imaging system provided by the present invention;

[0057] In the figure, 1. Radiation source; 2. Sample to be measured; 3. Scattering detector; 4. Water absorption detector. DETAILED DESCRIPTION

[0058] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0059] In the description of the present invention, it should be understood that the terms "upper", "lower", "front", "back", "left", "right", "top", "bottom", "inside", "outside", etc., indicating directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore should not be understood as limiting the present invention.

[0060] Example 1: Combination Figure 1-4 This embodiment is described.

[0061] This embodiment is a Compton camera XFCT imaging system, comprising:

[0062] Ray source 1 and two sets of double-layer Compton camera detectors,

[0063] The two sets of double-layer Compton camera detectors are arranged in a straight line at intervals, and the ray source 1 is located beside the straight line. The two sets of double-layer Compton camera detectors are symmetrical about the ray source 1, and the ray source 1 is a gamma ray source.

[0064] Both sets of double-layer Compton camera detectors include a scattering detector 3 and an absorption detector 4. The scattering detector 3 is used to record the location where Compton scattering occurs and the deposited energy of the recoil electrons; the absorption detector 4 is used to receive scattered photons and record the absorption location and deposited energy.

[0065] The ray source 1 is spaced apart from the sample 2 to be measured, and two sets of double-layer Compton camera detectors are symmetrically arranged on both sides of a straight line connecting the ray source 1 and the sample 2 to be measured, and the two sets of double-layer Compton camera detectors and the sample 2 to be measured are arranged in sequence in a straight line; the gamma rays emitted by the ray source 1 enter the sample 2 to be measured, and the gamma rays interact with the elements in the sample 2 to generate fluorescent photons, and the fluorescent photons incident on the Compton camera scattering detector 3 are Compton scattered in the Compton camera scattering detector 3, and the scattered fluorescent photons are received by the corresponding Compton camera absorption detector 4, and the position where the Compton scattering occurs and the deposited energy are recorded to obtain Compton scattering event data; the fluorescent photons passing through the scattering detector 3 are absorbed by the corresponding absorption detector 4, and the absorption position and deposited energy are recorded to obtain Compton absorption event data; and image reconstruction is performed using the Compton scattering event data and the Compton absorption event data.

[0066] Gamma ray source 1 is used, with coordinates set to (x, y, z) = (100 mm, 0 mm, 0 mm). The angle between source 1 and the double-layer Compton camera detector is 90°, and the momentum direction is randomly distributed on a circular disk centered at the origin. This layout and parameter settings ensure that the rays are stably and effectively irradiated onto sample 2.

[0067] In this scheme, the test sample 2 consists of a large cylinder with a radius of 25 mm and a height of 5 mm, and seven small cylinders filled with air, serving as the overall framework and background environment. The seven small cylinders, each with a radius of 2.5 mm and a height of 5 mm, are composed of a mixture of high-concentration Au and water, with concentrations of 2.0%, 4.0%, 6.0%, 8.0%, 10.0%, and 12.0%, respectively.

[0068] Both double-layer Compton camera detectors consist of two layers: a scattering detector 3 and an absorption detector 4. The scattering detector 3, made of silicon and measuring 20 mm x 20 mm x 5 mm, records the location of Compton scattering and the deposited energy of the recoil electrons. The absorption detector 4, made of cadmium zinc telluride (CdZnTe) and measuring 50 mm x 50 mm x 5 mm, receives scattered fluorescence photons and records their absorption location and deposited energy. Two sets of double-layer Compton camera detectors are symmetrically arranged on both sides of the straight line connecting the radiation source 1 and the sample under test 2. The distance between the scattering detector 3 and the sample under test 2 is 60 mm, and the distance between the scattering detector 3 and the absorption detector 4 is 20 mm. This layout enables the system to track and detect photons from more angles, obtain more effective Compton events, improve angular resolution, and significantly reduce the half-maximum width (FWHM) of the distribution, thereby improving ARM performance by 19% and reducing the omission of fluorescent photons due to directional limitations, thereby reducing background interference. The system can more accurately determine the propagation direction of fluorescent photons and locate the position of the radiation source, as well as have better energy resolution, thereby improving the detection efficiency and imaging accuracy of the entire system for fluorescent photons and accelerating the imaging process.

[0069] In material testing, accurate element distribution imaging is crucial for evaluating material uniformity, impurity distribution, and other performance indicators. The Compton camera XFCT imaging system in this solution can provide higher-resolution and more accurate element distribution images, helping researchers and engineers better understand the internal microstructure of materials and guide material research and development and production processes.

[0070] Example 2

[0071] The present invention also provides an image reconstruction method for a Compton camera XFCT imaging system, which is used in one of the Compton camera XFCT imaging systems described above, wherein a sample to be measured is placed on a straight line between two sets of double-layer Compton camera detectors arranged at intervals, and the two sets of double-layer Compton camera detectors are symmetrical about a straight line connecting the radiation source and the sample to be measured, comprising:

[0072] S01: irradiating the gamma rays emitted by the ray source 1 to the sample 2 to be tested. The gamma rays interact with the elements in the sample 2 to generate fluorescent photons. The fluorescent photons are incident on the scattering detector 3 to generate Compton scattering events. After Compton scattering, the fluorescent photons are absorbed by the absorption detector 4 to generate Compton absorption events.

[0073] S02: Receive and record the fluorescence photons when the Compton scattering event occurs through the corresponding scattering detector 3 to obtain Compton scattering event data, wherein the Compton scattering event data includes the scattering point position (x s ,y s ,z s ) and deposition energy E s ;

[0074] S03: Receive and record the fluorescence photons when the Compton absorption event occurs through the corresponding absorption detector 4 to obtain Compton absorption event data, wherein the Compton absorption event data includes the absorption point position (x a ,y a ,z a ) and deposition energy E a ;

[0075] S04: filtering the Compton scattering event data and the Compton absorption event data;

[0076] S05: performing angle calculation on the filtered Compton scattering event data and the Compton absorption event data to obtain a scattering angle θ i ;

[0077] S06: dividing the space where the sample 2 to be tested and the two sets of double-layer Compton camera detectors are located into a plurality of cubic units to obtain a voxel space, wherein each cubic unit serves as a voxel;

[0078] S07: According to the scattering angle θ i Back-projecting the filtered Compton scattering event data and the Compton absorption event data into the voxel space;

[0079] S08: Calculating the propagation direction of the fluorescent photons according to the projection The intersection coordinates of the fluorescent photon and the voxel, the path length d of the fluorescent photon in the voxel ij and the energy deposition ratio e ij , and update the system matrix to obtain the system matrix element a ij ;

[0080] S09: According to the system matrix element a ij The intensity value f of the voxel is calculated using the MLEM algorithm. j Perform iterative updates to obtain a reconstruction result matrix, perform three-dimensional volume reconstruction on the reconstruction result matrix using a visualization software tool to obtain a reconstruction result image, and adjust the iteration parameters in real time according to the reconstruction result image until the reconstruction result image meets the preset requirements.

[0081] Turn on the ray source 1 to emit gamma rays. The gamma rays enter the sample 2 and interact with the high atomic number Au element in the sample 2, exciting the atoms to produce fluorescent photons. The fluorescent photons will be incident on the scattering detector 3 to cause a Compton scattering event. After the Compton scattering, the fluorescent photons will be absorbed by the absorption detector 4 to cause a Compton absorption event. The fluorescent photons are detected by the double-sided detectors of the Compton camera. When the fluorescent photons enter the scattering detector 3, the scattering detector 3 records the scattering point position (x s ,y s ,z s ) and deposition energy E s , and obtain Compton scattering event data. The fluorescence photons that have undergone Compton scattering enter the absorption detector 4 and are completely absorbed. The absorption detector 4 will record the absorption point position (x a ,y a ,z a ) and deposition energy E a , Compton absorption event data is obtained. The obtained Compton scattering event data and Compton absorption event data are filtered to obtain data with higher purity, thereby improving the imaging accuracy of the image.

[0082] Then, from the filtered Compton scattering event data and Compton absorption event data, the energy deposition E at the scattering point and absorption point is calculated. s and E a Calculate the scattering angle θ i The space where the sample 2 and the two sets of double-layer Compton camera detectors are located is divided into a plurality of cubic units to obtain a voxel space, wherein each of the cubic units is a voxel; according to the scattering angle θ i The filtered Compton scattering event data and Compton absorption event data are back-projected into voxel space.

[0083] Then calculate the propagation direction of the fluorescent photons based on the projection The coordinates of the intersection of the fluorescent photon and the voxel, and the path length d of the fluorescent photon within the voxel ij and the energy deposition ratio e ij , and update the system matrix to obtain the system matrix element a ij , system matrix element a ij Describes the projection probability of voxel j to the observed i-th data.

[0084] Finally, according to the system matrix element a ij The intensity value f of the voxel is calculated using the MLEM algorithm. j Perform iterative updates to obtain a reconstruction result matrix, perform three-dimensional volume reconstruction on the reconstruction result matrix using a visualization software tool to obtain a reconstruction result image, and after each iterative update, use a visualization software tool such as MATLAB to reconstruct the obtained reconstruction result matrix and display the reconstruction result image. Figure 4 As shown, the visualization software tool divides the 3D reconstruction space into a 3D array of voxels, extracts 2D slices from the array and adds colors. It then uses a loop to extract isosurfaces to create a 3D cube, and finally stores colors on the voxels to construct the 3D model. This method allows for intuitive observation of how the reconstructed image changes with each iteration, restoring the 3D structure of an object or scene from 2D projection data and enabling comprehensive analysis of the sample being tested.

[0085] During the iterative process, pay close attention to the intermediate results. After each iteration, check the changes in the region of interest in the reconstructed image, including whether the shape, size, intensity, and other characteristics of the region are gradually becoming stable and accurate, and whether the noise in the background area is gradually decreasing. If anomalies are found, such as increased artifacts in certain areas or unreasonable element concentration distribution, promptly adjust the algorithm parameters or check whether there are any problems in the data acquisition process. If the element concentration distribution is unreasonable, check the accuracy of the system matrix calculation or adjust the initial voxel intensity estimate. Through continuous monitoring and adjustment, ensure that the iterative process can steadily improve image quality.

[0086] When the reconstructed image reaches the preset stop condition, the iterative update stops and the final iterative result is output. The final two-dimensional and three-dimensional reconstruction results are displayed in the form of images through visual reconstruction, which can facilitate further data processing, analysis, and comparison with other systems or research results. In practical applications, such as in the field of early cancer diagnosis, the reconstruction results can be compared and analyzed with the element distribution characteristics of normal tissues to determine whether there is abnormal element enrichment, etc., providing an important basis for disease diagnosis; in material testing, the material uniformity, impurity distribution and other performance indicators can be evaluated based on the element distribution, guiding the material research and development and production process.

[0087] In the present invention, the scattering angle θ is accurately calculated by filtering the Compton scattering event data and the Compton absorption event data. i and the propagation direction d of the fluorescent photon, the coordinates of the intersection of the fluorescent photon and the voxel, and the path length d of the fluorescent photon in the voxel ij and the energy deposition ratio e ij It effectively suppresses noise and artifacts, accurately separates edge parts and positioning elements, and makes the position and concentration distribution of high-Z elements clearly discernible, thereby improving the image resolution and imaging accuracy, and helping to more accurately analyze the internal structure and element distribution of the measured sample. Calculate the propagation direction of fluorescent photons The coordinates of the intersection of the fluorescent photon and the voxel, and the path length d of the fluorescent photon within the voxel ij and the energy deposition ratio e ij Then update the system matrix to get the system matrix element a ij , system matrix element a ij Describes the projection probability of voxel j to the observed i-th data, the system matrix element a ij The element value can be adaptively adjusted according to the scattering angle and energy of different Compton scattering events, thereby accurately reflecting the scattering, absorption, and propagation and energy distribution of fluorescent photons between different voxels, thereby improving the accuracy of imaging. The voxel intensity value f is updated by combining the MLEM iterative formula j , which closely combines the voxel intensity update with the actual element distribution, thereby improving the spatial resolution and being able to more accurately identify the element types, especially for low-concentration elements, which can also be clearly displayed, improving the ability to resolve the details of the element distribution.

[0088] During the imaging process, visualization software is used to display the reconstructed image, which facilitates observation of the element distribution, noise level, resolution, etc. in the image, and enables timely detection of problems and corresponding adjustments, ensuring that the iterative process proceeds in the direction of improving image quality, further improving the imaging quality and making the entire imaging process more controllable and optimized.

[0089] Medical applications such as early cancer diagnosis require more precise and efficient imaging technologies to detect changes in elemental distribution within tissues. This solution improves the imaging efficiency and quality of CC-XFCT systems, enabling more accurate visualization of the distribution of high-atomic-number elements in the body. This provides a more reliable basis for early cancer diagnosis, enhances the accuracy and timeliness of disease diagnosis, and ultimately improves patient treatment outcomes and prognosis.

[0090] Furthermore, filtering the Compton scattering event data and the Compton absorption event data includes:

[0091] Calculate the scattering point position (x s ,y s ,z s ) and the absorption point position (x a ,y a ,z a ) between s-a , the distance d s-a The distance threshold d th For comparison, if d s-a <d th , then the corresponding scattering point position (x s ,y s ,z s ) and the corresponding absorption point position (x a ,y a ,z a ) are deleted from the Compton scattering event data and the Compton absorption event data, respectively.

[0092] The obtained Compton scattering event data and Compton absorption event data are filtered, and for each event, the scattering point position (x s ,y s ,z s ) and the absorption point position (x a ,y a ,z a ) between s-a According to the Compton scattering characteristics and the noise statistics obtained through experiments and theoretical analysis, a suitable distance threshold d is pre-set. th , the distance d s-a The distance threshold d th To make a comparison, when d s-a <d th When the event is determined to be a noise event or an interference event, the corresponding scattering point position (x s ,y s ,zs ) and the corresponding absorption point position (x a ,y a ,z a ) are deleted from the Compton scattering event data and the Compton absorption event data respectively. After the distance filtering, higher purity data is obtained, thereby improving the imaging accuracy of the image.

[0093] Further, S05: performing angle calculation on the filtered Compton scattering event data and the Compton absorption event data to obtain a scattering angle θ i ,include:

[0094] From the filtered Compton scattering event data and Compton absorption event data, the scattering angle θ is calculated using the Compton scattering angle calculation formula according to the deposition energy Es at the scattering point and the deposition energy Ea at the absorption point. i , the formula is:

[0095] Among them, m e c 2 represents the electron rest energy.

[0096] Further, S08: Calculate the propagation direction of the fluorescent photon according to the projection The intersection coordinates of the fluorescent photon and the voxel, the path length d of the fluorescent photon in the voxel ij and the energy deposition ratio e ij , and update the system matrix to obtain the system matrix element a ij ,include:

[0097] Calculate the fluorescence photon from the scattering point position (x s ,y s ,z s ) to the absorption point position (x a ,y a ,z a ) direction vector The formula is: For the direction vector Normalization is performed to obtain the propagation direction of the fluorescence photon The formula is:

[0098]

[0099] Let the coordinates of the scattering point be (x s ,y s ,z s ), the absorption point coordinates are (x a ,y a ,z a), then the fluorescence photon is scattered from the position (x s ,y s ,z s ) to the absorption point position (x a ,y a ,z a ) direction vector for For this direction vector Normalization is performed to obtain the unit vector representing the propagation direction of the fluorescence photon

[0100] Calculate the intersection coordinates of the fluorescent photon and the voxel, where the position of the voxel can be expressed as (x j ,y j ,z j );

[0101] The range of the voxel in the X-axis, Y-axis, and Z-axis directions is calculated using the range formula. j1 =X j +0.5×ΔX,X j2 =X j +1×ΔX,Y j1 =Y j +0.5×ΔY,Y j2 =Y j +1×ΔY,Z j1 =Z j +0.5×ΔZ,Z j2 =Z j +1×ΔZ, where X j1 and X j2 Indicates the range of the voxel in the X-axis direction, Y j1 and Y j2 Indicates the range of the voxel in the Y-axis direction, Z j1 and Z j2 represents the range of the voxel in the Z-axis direction, ΔX, ΔY, and ΔZ represent the variable range of the voxel in the X-axis, Y-axis, and Z-axis respectively, and j represents the index of the voxel;

[0102] Through the photon propagation formula The value range of the parameter t on the X-axis, Y-axis, and Z-axis is calculated by the voxel boundary inequality formula:

[0103] X0+td x ∈[X j1 ,X j2 ],Y0+td y ∈[Y j1 ,Y j2 ],Z0+td z ∈[Z j1 ,Zj2 ],in, Represents the position vector of the fluorescent photon at the initial position, X0, Y0, X0 respectively represent The components on the X-axis, Y-axis, and Z-axis, d x d y d z Respectively Components on the X-axis, Y-axis, and Z-axis;

[0104] Substitute the value range of parameter t on the X-axis, Y-axis and Z-axis into the photon propagation formula respectively Calculation is performed to obtain the coordinates of the intersection of the fluorescent photon and the voxel.

[0105] Determine the intersection of the fluorescence photon and the voxel. For each voxel, its position can be expressed as (x j ,y j ,z j ). Taking the X axis as an example, the range of the voxel in the X axis direction is X j1 and X j2 They are

[0106] X j1 =X j +0.5×ΔX,X j2 =X j +1×ΔX, and the photon propagation formula Joint,

[0107] And the photon propagation equation The X-axis component X0, The X-axis component d x Substituting into the voxel boundary inequality, we get X0+td x ∈[X j1 ,X j2 ], solving the inequality to determine the range of values ​​for the parameter t. Similar calculations are performed for the Y and Z axes. If a t value satisfies the boundary inequality along all three axes, the fluorescence photon intersects the voxel. Substituting the t value into the photon propagation formula yields the coordinates of the intersection point.

[0108] Calculate the path length d of the fluorescent photon in the voxel according to the intersection coordinates ij , the formula is:

[0109] in, and represents the boundary intersection point when the fluorescence photon intersects the voxel;

[0110] According to the Beer-Lambert law, the intensity attenuation of the fluorescent photons after passing through the voxel and the energy deposition ratio e of the fluorescent photons in the voxel are calculated.ij , the formula is:

[0111] Where I0 and I represent the energy of the fluorescence photon before and after attenuation in the voxel, μ j represents the attenuation coefficient of fluorescence photons in the voxel;

[0112] According to the propagation direction Intersection coordinates, path length d ij and the energy deposition ratio e ij Update the system matrix to obtain the system matrix element a ij , the formula is:

[0113] Furthermore, according to the system matrix element a ij The intensity value f of the voxel is calculated using the MLEM algorithm. j Perform iterative updates to obtain the reconstruction result matrix, including:

[0114] Initialize the algorithm parameters, including the number of iterations n, the initial voxel intensity estimate f j (0) , assign an initial value to the weight of each voxel in the voxel space, and iteratively update the voxel intensity value f of the voxel in combination with the MLEM algorithm j , the formula is:

[0115] Wherein, i represents the index of the observation data detected by the double-layer Compton camera detector, j represents the index of the voxel, and f j represents the intensity value of voxel j, f j (n) represents the intensity value of voxel j at n iterations, f j (n+1) represents the intensity value of voxel j at the next iteration, and m represents the upper limit of the observed data.

[0116] Update the voxel intensity value f by combining the MLEM iterative formula j , which closely combines the voxel intensity update with the actual element distribution, thereby improving the spatial resolution and being able to more accurately identify the element types, especially for low-concentration elements, which can also be clearly displayed, improving the ability to resolve the details of the element distribution.

[0117] Furthermore, adjusting iteration parameters in real time according to the reconstructed image until the reconstructed image meets preset requirements includes:

[0118] Adjust the preset distance threshold d th: If artifacts occur, increase the preset distance threshold d th If the noise events increase, reduce the preset distance threshold d th , where the scattering point position (x s ,y s ,z s ) and the absorption point position (x a ,y a ,z a ) between s-a Less than the preset distance threshold d th The event is judged as a noise event;

[0119] Adjust the attenuation coefficient μ of fluorescent photons in voxels j Value: Set different attenuation coefficients μ according to different elements j Numeric value;

[0120] Adjust the initial voxel intensity estimate f according to the element concentration in the reconstructed image j (0) .

[0121] During the iteration process, pay close attention to the intermediate results. After each iteration, check the changes in the region of interest in the reconstructed image, including whether the shape, size, intensity, and other characteristics of the region are gradually becoming stable and accurate, and whether the noise in the background area is gradually decreasing. If anomalies are found, such as increased artifacts in certain areas or unreasonable element concentration distribution, adjust the iteration parameters or check whether there are any problems in the data acquisition process. Adjustments should mainly focus on the following aspects:

[0122] Adjust the preset distance threshold d th :By adjusting the appropriate distance threshold d th , the scattering point position (x s ,y s ,z s ) and the absorption point position (x a ,y a ,z a ) between s-a Less than the preset distance threshold d th The event is determined as a noise event or an interference event, and the corresponding scattering point position (x s ,y s ,z s ) and the corresponding absorption point position (x a ,y a ,z a) are removed from the Compton scattering event data and the Compton absorption event data, respectively, to improve the data purity. If a large number of Compton scattering events and Compton absorption events are mistakenly identified as noise events or interference events, it will lead to the loss of image information and the generation of artifacts. In this case, the preset distance threshold d should be appropriately relaxed. th On the contrary, if noise events or interference events still exist in large quantities, the image quality will be affected. In this case, the preset distance threshold d can be reduced. th To improve the image quality. Each time the distance threshold d is adjusted th After that, it is necessary to re-filter the data and perform subsequent iterative calculations, and observe the changes in image quality to determine the optimal distance threshold d th .

[0123] Adjust the attenuation coefficient μ of fluorescent photons in voxels j Value: When different elements are involved, the attenuation coefficient μ j The values ​​are different. You need to re-check the relevant physics manual or experimental data and use the corresponding attenuation coefficient μ j Numeric value.

[0124] Adjust the initial voxel intensity estimate f according to the element concentration in the reconstructed image j (0) : As the starting point of the iterative algorithm, the initial voxel intensity estimate f j (0) It has an important impact on the subsequent iteration process and the final imaging results. If the element concentration distribution is found to be significantly different from the actual situation during the iteration process, the initial voxel intensity estimate f needs to be adjusted. j (0) For example, if it is known that a certain area should contain a high concentration of a certain element, and the current reconstruction result image shows that the concentration of the element in this area is too low, the f j (0) Increase the estimated value from a low value (such as 0.1) to a more reasonable value (such as 1.0 or higher), and then restart the iteration. If the approximate range of the element concentration in the sample 2 is known, and the current initial voxel intensity estimate f j (0) If it deviates significantly from this range, it will be corrected according to the actual situation to make it closer to this range. After adjustment, it will be iterated again to observe the improvement of the element concentration distribution and ensure that the adjusted initial voxel intensity estimate f j (0) It can guide the iteration in the right direction, thereby improving imaging accuracy.

[0125] It should also be noted that the terms "comprise," "include," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, product, or apparatus comprising a list of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, product, or apparatus. Without further limitation, the phrase "comprises a..." does not preclude the presence of additional identical elements in the process, method, product, or apparatus comprising the elements. Terms such as "first," "second," and the like are used to designate names and do not imply any particular order. The above illustrative description of the present invention and its embodiments is non-limiting. The present invention may be embodied in other specific forms without departing from the spirit or essential features of the present invention. The drawings illustrate only one embodiment of the present invention; the actual structure is not limited thereto. Any reference numerals in the claims should not limit the claims to which they relate. Therefore, if a person of ordinary skill in the art is inspired by this and, without departing from the spirit of the present invention, devises structures and embodiments similar to the present invention without inventiveness, they shall fall within the scope of protection of this patent.

Claims

1. A Compton camera XFCT imaging system image reconstruction method, characterized in that: The Compton camera XFCT imaging system includes: a ray source and two sets of double-layer Compton camera detectors. The two sets of double-layer Compton camera detectors are arranged in a straight line at intervals, and the radiation source is located beside the straight line. The two sets of double-layer Compton camera detectors are symmetrical about the radiation source, and the radiation source is a gamma ray source. Both sets of double-layer Compton camera detectors include scattering detectors and absorption detectors. The scattering detectors are used to record the location where Compton scattering occurs and the deposited energy of the recoil electrons; the absorption detectors are used to receive scattered photons and record the absorption location and deposited energy. The sample to be tested is placed on a straight line between two sets of double-layer Compton camera detectors arranged at intervals, and the two sets of double-layer Compton camera detectors are symmetrical about the straight line connecting the ray source and the sample to be tested, including: S01: irradiating the sample to be tested with gamma rays emitted by the ray source, so that the gamma rays interact with the elements in the sample to produce fluorescent photons; wherein the fluorescent photons are incident on the scattering detector to generate Compton scattering events, and the fluorescent photons after Compton scattering are absorbed by the absorption detector to generate Compton absorption events; S02: Receive and record the fluorescence photons when the Compton scattering event occurs through the corresponding scattering detector to obtain Compton scattering event data, wherein the Compton scattering event data includes the scattering point position (x) when the fluorescence photons undergo Compton scattering. s ,y s ,z s ) and the deposited energy E s ; S03: Receive and record the fluorescence photons when the Compton absorption event occurs through the corresponding absorption detector to obtain Compton absorption event data, wherein the Compton absorption event data includes the absorption point position (x a ,y a ,z a ) and the deposited energy E a ; S04: filtering the Compton scattering event data and the Compton absorption event data; Calculate the scattering point position (x s ,y s ,z s ) and the absorption point position when the corresponding fluorescence photon undergoes Compton absorption (x a ,y a ,z a ) The distance d between s-a , the distance d s-a The distance threshold d th For comparison, if d s-a <d th , then the corresponding scattering point position (x s ,y s ,z s ) and the corresponding absorption point position (x a ,y a ,z a ) are deleted from the Compton scattering event data and the Compton absorption event data respectively; S05: performing angle calculation on the filtered Compton scattering event data and the Compton absorption event data to obtain a scattering angle θ i ; S06: dividing the space where the sample to be tested and the two sets of double-layer Compton camera detectors are located into a plurality of cubic units to obtain a voxel space, wherein each cubic unit serves as a voxel; S07: According to the scattering angle θ i Back-projecting the filtered Compton scattering event data and the Compton absorption event data into the voxel space; S08: Calculating the propagation direction of the fluorescent photon according to the projection , the intersection coordinates of the fluorescent photon and the voxel, and the path length d of the fluorescent photon in the voxel ij and the energy deposition ratio e ij , and update the system matrix to get the system matrix element ; S09: According to the system matrix elements The intensity value f of the voxel is calculated using the MLEM algorithm. j Perform iterative updates to obtain a reconstruction result matrix, perform three-dimensional volume reconstruction on the reconstruction result matrix using a visualization software tool to obtain a reconstruction result image, and adjust the iteration parameters in real time according to the reconstruction result image until the reconstruction result image meets the preset requirements.

2. The image reconstruction method of a Compton camera XFCT imaging system according to claim 1, characterized in that: The distance between the scattering detector and the sample to be measured is 60 mm, and the distance between the scattering detector and the absorption detector is 20 mm.

3. The image reconstruction method of a Compton camera XFCT imaging system according to any one of claims 1-2, characterized in that: The scattering detector is made of silicon and has a size of 20 mm×20 mm×5 mm.

4. The image reconstruction method of a Compton camera XFCT imaging system according to any one of claims 1-2, characterized in that: The absorption detector is made of cadmium zinc telluride and has a size of 50 mm×50 mm×5 mm.

5. The image reconstruction method of a Compton camera XFCT imaging system according to claim 1, characterized in that: S05: performing angle calculation on the filtered Compton scattering event data and the Compton absorption event data to obtain a scattering angle θ i ,include: From the filtered Compton scattering event data and Compton absorption event data, the scattering angle θ is calculated using the Compton scattering angle calculation formula according to the deposition energy Es at the scattering point and the deposition energy Ea at the absorption point. i , the formula is: Among them, m e c 2 represents the electron rest energy.

6. The image reconstruction method of a Compton camera XFCT imaging system according to claim 5, characterized in that: S08: Calculating the propagation direction of the fluorescent photon according to the projection , the intersection coordinates of the fluorescent photon and the voxel, and the path length d of the fluorescent photon in the voxel ij and the energy deposition ratio e ij , and update the system matrix to get the system matrix element ,include: Calculate the fluorescence photon from the scattered point position (x s ,y s ,z s ) to the absorption point position (x a ,y a ,z a ) direction vector , the formula is: , for the direction vector Normalization is performed to obtain the propagation direction of the fluorescence photon , the formula is: ， ; Calculate the intersection coordinates of the fluorescent photon and the voxel, where the position of the voxel can be expressed as ; The range of the voxel in the X-axis, Y-axis, and Z-axis directions is calculated using the range formula. j1 =X j +0.5×∆X,X j2 =X j +1×∆X,Y j1 =Y j +0.5×∆Y,Y j2 =Y j +1×∆Y,Z j1 =Z j +0.5×∆Z,Z j2 =Z j +1×∆Z, where X j1 and X j2 Indicates the range of the voxel in the X-axis direction, Y j1 and Y j2 Indicates the range of the voxel in the Y-axis direction, Z j1 and Z j2 represents the range of the voxel in the Z-axis direction, ∆X, ∆Y, and ∆Z represent the variable range of the voxel in the X-axis, Y-axis, and Z-axis respectively, and j represents the index of the voxel; Through the photon propagation formula The value range of the parameter t on the X-axis, Y-axis, and Z-axis is calculated by the voxel boundary inequality formula: X0+td x ∈[X j1 ,X j2 ],Y0+td y ∈[Y j1 ,Y j2 ],Z0+td z ∈[Z j1 ,Z j2 ],in, Represents the position vector of the fluorescent photon at the initial position, X0, Y0, and Z0 represent The components on the X-axis, Y-axis, and Z-axis, d x d y d z Respectively Components on the X-axis, Y-axis, and Z-axis; Substitute the value range of parameter t on the X-axis, Y-axis and Z-axis into the photon propagation formula respectively Performing calculations to obtain the coordinates of the intersection of the fluorescent photon and the voxel; Calculate the path length d of the fluorescent photon in the voxel according to the intersection coordinates ij , the formula is: ,in, and represents the boundary intersection point when the fluorescence photon intersects the voxel; According to the Beer-Lambert law, the intensity attenuation of the fluorescent photons after passing through the voxel and the energy deposition ratio e of the fluorescent photons in the voxel are calculated. ij , the formula is: ， ， Where I0 and I represent the energy of the fluorescence photon before and after decay in the voxel, represents the attenuation coefficient of fluorescence photons in the voxel; According to the propagation direction , intersection coordinates, path length d ij and the energy deposition ratio e ij Update the system matrix to get the system matrix elements , the formula is: 。 7. The image reconstruction method of a Compton camera XFCT imaging system according to claim 6, characterized in that: According to the system matrix elements The intensity value f of the voxel is calculated using the MLEM algorithm. j Perform iterative updates to obtain the reconstruction result matrix, including: Initialize the algorithm parameters, including the number of iterations n, the initial voxel intensity estimate f j (0) , assign an initial value to the weight of each voxel in the voxel space, and iteratively update the voxel intensity value f of the voxel in combination with the MLEM algorithm j , the formula is: ， Wherein, i represents the index of the observation data detected by the double-layer Compton camera detector, j represents the index of the voxel, and f j represents the intensity value of voxel j, f j (n) represents the intensity value of voxel j at n iterations, f j (n+1) represents the intensity value of voxel j at the next iteration, and m represents the upper limit of the observed data.

8. The image reconstruction method of a Compton camera XFCT imaging system according to claim 7, characterized in that: Adjusting iteration parameters in real time according to the reconstructed image until the reconstructed image meets preset requirements, including: Adjust the preset distance threshold d th : If artifacts occur, increase the preset distance threshold d th If the noise events increase, reduce the preset distance threshold d th , where the scattering point position (x s ,y s ,z s ) and the absorption point position (x a ,y a ,z a ) The distance d between s-a , is less than the preset distance threshold d th The event is judged as a noise event; Adjust the attenuation coefficient of fluorescence photons in voxels Value: Set different attenuation coefficients according to different elements Numeric value; Adjust the initial voxel intensity estimate f according to the element concentration in the reconstructed image j (0) .

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