Radioactivity distribution modeling method integrating multi-mode imaging and three-dimensional laser scanning

Abstract

The invention relates to the technical field of modeling, in particular to a multi-mode imaging and three-dimensional laser scanning fused radioactive distribution modeling method. The method comprises the following steps: performing multi-angle detection on target three-dimensional space radioactive substances based on radioactive detection equipment to obtain a radioactive substance distribution two-dimensional image set; based on a laser scanning device, collecting three-dimensional point cloud data of a target three-dimensional space, assembling the three-dimensional point cloud data, and constructing a target three-dimensional space 3D model; based on the radioactive substance distribution two-dimensional image set, reducing a distribution image of the radioactive substance in the target three-dimensional space by adopting a statistical reconstruction algorithm; and based on the target three-dimensional space 3D model and the distribution image, combining to obtain a radioactive substance three-dimensional distribution modeling result. The technical effect of visually and accurately displaying the distribution condition of the radioactive substances in the three-dimensional space is achieved.

Description

Technical Field

[0001] The present invention relates to the field of modeling technology, and in particular to a radioactivity distribution modeling method integrating multi-mode imaging with three-dimensional laser scanning. Background Art

[0002] In the field of radioactive material distribution modeling, traditional modeling methods often employ only a single imaging modality. For example, relying solely on radioactive detection equipment to obtain radioactive material distribution information, or solely using laser scanning equipment to construct a geometric model of the target space, a single radioactive detection device can only obtain two-dimensional information on the distribution of radioactive materials, making it difficult to directly and accurately restore their distribution in three-dimensional space, and unable to comprehensively and intuitively display the specific location and intensity distribution of radioactive materials in three-dimensional space. While relying solely on laser scanning equipment can construct a three-dimensional geometric model of the target space, it cannot obtain radioactive material distribution information, nor can it integrate the distribution of radioactive materials with the geometric structure of the target space, resulting in a lack of spatial reference for radioactive material analysis. Traditional methods are unable to integrate multimodal information, resulting in inaccurate and incomplete modeling results, making it difficult to meet the needs of in-depth research and monitoring of radioactive materials, and suffering from technical issues such as inaccurate and unintuitive modeling. Summary of the Invention

[0003] The present invention aims to solve the technical problems of inaccurate and non-intuitive modeling in the prior art by providing a radioactivity distribution modeling method that integrates multi-mode imaging and three-dimensional laser scanning.

[0004] The technical solution of the present invention to solve the above technical problems is as follows: In a first aspect, the present invention provides a radioactive distribution modeling method that integrates multi-modal imaging and three-dimensional laser scanning, comprising: based on a radioactive detection device, performing multi-angle detection on radioactive materials in a target three-dimensional space to obtain a set of two-dimensional images of the radioactive material distribution; based on a laser scanning device, collecting three-dimensional point cloud data of the target three-dimensional space, assembling the three-dimensional point cloud data, and constructing a 3D model of the target three-dimensional space; based on the set of two-dimensional images of the radioactive material distribution, using a statistical reconstruction algorithm to restore the distribution image of the radioactive material in the target three-dimensional space; based on the 3D model of the target three-dimensional space and the distribution image, obtaining a three-dimensional distribution modeling result of the radioactive material based on a combination.

[0005] Optionally, based on a laser scanning device, three-dimensional point cloud data of the target three-dimensional space is collected, the three-dimensional point cloud data is assembled, and a 3D model of the target three-dimensional space is constructed, including: using the laser scanning device to scan the target three-dimensional space based on multiple positions to obtain multiple groups of point cloud data of the target three-dimensional space; based on feature point matching, obtaining the alignment positions of the multiple groups of point cloud data; based on the alignment positions, assembling the multiple groups of point cloud data into the 3D model of the target three-dimensional space.

[0006] Optionally, based on the set of two-dimensional images of radioactive material distribution, a statistical reconstruction algorithm is used to restore the distribution image of radioactive material in the target three-dimensional space, including: evenly dividing the target three-dimensional space to be reconstructed into multiple volume elements, wherein each volume element may contain radioactive material, and the radioactive material will emit radioactive rays; traversing the set of two-dimensional images of radioactive material distribution, calculating the multiple signal contributions of the radioactive rays of each volume element containing radioactive material to different pixel areas in multiple two-dimensional images of radioactive material distribution; based on the multiple signal contributions, inferring multiple initial volume element radioactive intensities of multiple volume elements, and constructing an initial volume element radioactive intensity array; calculating the theoretical pixel signal of the initial volume element radioactive intensity array in multiple two-dimensional images of radioactive material distribution, and iteratively optimizing the initial volume element radioactive intensity array based on the gap between the theoretical pixel signal and the actual pixel signal to obtain a volume element radioactive intensity array; converting the volume element radioactive intensity array into a distribution image of radioactive material in the target three-dimensional space.

[0007] Among them, the set of two-dimensional images of radioactive material distribution is traversed to calculate the multiple signal contributions of the radioactive rays of each volume element containing radioactive material to different pixel areas in multiple two-dimensional images of radioactive material distribution. The two-dimensional image of radioactive material distribution is formed by each volume element containing radioactive material emitting radioactive rays, which passes through the coding plate of the radioactive detection equipment. The two-dimensional image of radioactive material distribution contains multiple pixel areas and is affected by the intensity of the received radiation signal, including: based on the intensity of the radioactive rays received at different pixel areas in the two-dimensional image of radioactive material distribution, simulating and calculating the individual signal contribution of each volume element containing radioactive material to the intensity of the radioactive rays of multiple pixel areas of multiple two-dimensional images of radioactive material distribution; based on the individual signal contribution of the volume element to the intensity of the radioactive rays of the pixel areas of different two-dimensional images of radioactive material distribution, and the intensity of the radioactive rays received at different pixel areas in the two-dimensional image of radioactive material distribution, calculating and obtaining the signal contribution of the radioactive rays of each volume element to the pixel area of ​​the two-dimensional image of radioactive material distribution.

[0008] Among them, the theoretical pixel signal of the initial volume element radioactivity intensity array in multiple two-dimensional images of radioactive material distribution is calculated, and based on the gap between the theoretical pixel signal and the actual pixel signal, the initial volume element radioactivity intensity array is iteratively optimized to obtain the volume element radioactivity intensity array, including: calculating the theoretical pixel signal of the volume element radioactivity intensity array in multiple two-dimensional images of radioactive material distribution based on the initial volume element radioactivity intensity array; calculating the signal gap between the theoretical pixel signal and the actual pixel signal; when the signal gap is less than or equal to a signal gap threshold, using the initial volume element radioactivity intensity array as the volume element radioactivity intensity array; when the signal gap is greater than the signal gap threshold, adjusting the initial volume element radioactivity intensity array to obtain an adjusted volume element radioactivity intensity array, and calculating the signal gap between its theoretical pixel signal and the actual pixel signal to determine whether it is greater than the signal gap threshold. If so, continue to repeat the above steps until its signal gap is less than or equal to the signal gap threshold, and use the adjusted volume element radioactivity intensity array with a signal gap less than or equal to the signal gap threshold as the volume element radioactivity intensity array.

[0009] Among them, calculating the signal gap between the theoretical pixel signal and the actual pixel signal includes: calculating multiple differences between each theoretical pixel signal and each corresponding actual pixel signal in the first two-dimensional image, obtaining multiple first differences after eliminating outliers, and calculating the average value of the multiple first differences; obtaining the maximum value of the multiple first differences, and calculating the first correction coefficient based on the maximum value of the first differences; multiplying the first correction coefficient by the average value of the first differences to obtain the first signal gap; calculating multiple first signal gaps of multiple two-dimensional images in the set of two-dimensional images of radioactive material distribution, finding the average value of the multiple first signal gaps, and obtaining the signal gap.

[0010] Optionally, based on the target three-dimensional space 3D model and the distribution image, a combination is used to obtain a three-dimensional distribution modeling result of the radioactive material, including: aligning the spatial coordinates of the target three-dimensional space 3D model and the distribution image of the radioactive material in the target three-dimensional space; using the radioactivity distribution data as the attribute layer of the target three-dimensional space 3D model, and attaching the radioactivity distribution data to multiple faces of the target three-dimensional space 3D model; obtaining the radioactivity intensity of all volume elements in the multiple faces, and calculating the average thereof as the radioactivity activity value of the multiple faces; using the radioactivity activity of the multiple faces as the attribute of the multiple faces; and coloring the multiple faces of the target three-dimensional space 3D model based on the radioactivity activity values ​​of the multiple faces to form a heat map effect.

[0011] In a second aspect, the present invention provides a radioactivity distribution modeling system integrating multi-modal imaging and three-dimensional laser scanning, comprising: A radioactive detection module is used to perform multi-angle detection of radioactive materials in the target three-dimensional space based on radioactive detection equipment to obtain a set of two-dimensional images of the distribution of radioactive materials; A spatial modeling module is used to collect three-dimensional point cloud data of the target three-dimensional space based on a laser scanning device, assemble the three-dimensional point cloud data, and construct a 3D model of the target three-dimensional space; a radioactivity modeling module, configured to restore the distribution image of the radioactive material in the target three-dimensional space using a statistical reconstruction algorithm based on the set of two-dimensional images of the radioactive material distribution; The modeling fusion module is used to obtain a three-dimensional distribution modeling result of the radioactive material based on the target three-dimensional space 3D model and the distribution image.

[0012] By implementing the present invention, it is possible to perform multi-angle detection of radioactive materials in a target three-dimensional space based on radioactive detection equipment, and obtain a set of two-dimensional images of the radioactive material distribution. Multi-angle detection can obtain more comprehensive radioactive material distribution data, avoiding the information loss that may occur in single-angle detection, and providing rich raw data support for the subsequent restoration of the radioactive material distribution in three-dimensional space. By implementing the present invention, it is possible to collect three-dimensional point cloud data of the target three-dimensional space based on a laser scanning device, assemble the three-dimensional point cloud data, and construct a 3D model of the target three-dimensional space. Subsequently, the radioactive material distribution image is combined with the target three-dimensional space to provide an accurate spatial carrier, so that the distribution of the radioactive material can be reflected in a specific spatial structure. By implementing the present invention, it is possible to restore the distribution image of the radioactive material in the target three-dimensional space using a statistical reconstruction algorithm based on the set of two-dimensional images of the radioactive material distribution. The statistical reconstruction algorithm can be used to deduce the distribution of the radioactive material in the three-dimensional space from the two-dimensional image, thus realizing the conversion from two-dimensional information to three-dimensional information. By implementing the present invention, it is possible to obtain a three-dimensional distribution modeling result of radioactive material based on the 3D model of the target three-dimensional space and the distribution image, combine the distribution information of the radioactive material with the geometric structure of the target three-dimensional space, so that the three-dimensional distribution of the radioactive material can be displayed in a specific spatial model, and form a heat map effect through coloring and other methods, so as to more intuitively present the radioactive activity of different areas and facilitate the intuitive display of the distribution of radioactive material.

[0013] In summary, by implementing the present invention, it is possible to achieve high-precision three-dimensional distribution modeling of radioactive substances in the target three-dimensional space, and to intuitively and accurately display the technical effect of the distribution of radioactive substances in the three-dimensional space. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1A schematic flow chart of the radioactivity distribution modeling method integrating multi-modal imaging and 3D laser scanning provided by the present invention; Figure 2 This is a structural schematic diagram of the radioactivity distribution modeling system that integrates multi-mode imaging and three-dimensional laser scanning provided by the present invention.

[0015] In the accompanying drawings, the components represented by the reference numerals are as follows: Radioactivity detection module 11, space modeling module 12, radioactivity modeling module 13, modeling fusion module 14. DETAILED DESCRIPTION

[0016] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative efforts shall fall within the scope of protection of the present invention.

[0017] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of technical features indicated. Therefore, features specified as "first" or "second" may explicitly or implicitly include one or more features. In the description of the present invention, "plurality" means two or more, unless otherwise specifically defined.

[0018] In the description of the present invention, the term "for example" is used to mean "used as an example, illustration or explanation". Any embodiment of the present invention described as "for example" is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is given to enable any person skilled in the art to implement and use the present invention. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art can recognize that the present invention can be implemented without using these specific details. In other examples, well-known structures and processes are not elaborated in detail to avoid obscuring the description of the present invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed herein.

[0019] Example 1, as Figure 1 As shown, an embodiment of the present invention provides a radioactivity distribution modeling method based on the fusion of multi-modal imaging and three-dimensional laser scanning, including: S100: Using radioactive detection equipment, perform multi-angle detection of radioactive materials in the target three-dimensional space to obtain a set of two-dimensional images of the distribution of radioactive materials; S200: Collecting three-dimensional point cloud data of the target three-dimensional space based on a laser scanning device, assembling the three-dimensional point cloud data, and constructing a 3D model of the target three-dimensional space; S300: Based on the set of two-dimensional images of the radioactive material distribution, a statistical reconstruction algorithm is used to restore the distribution image of the radioactive material in the target three-dimensional space; S400: Based on the target three-dimensional space 3D model and the distribution image, a three-dimensional distribution modeling result of radioactive material is obtained.

[0020] In step S100 of the embodiment of the present application, radioactive substances in the target three-dimensional space are detected from multiple angles based on radioactive detection equipment to obtain a set of two-dimensional images of the distribution of radioactive substances. Specifically, radioactive detection equipment with multi-angle detection capabilities, such as a gamma camera, is selected. Based on the size and shape of the target three-dimensional space, the radioactive detection equipment is deployed at multiple different positions around the target three-dimensional space to ensure that the radioactive substances in the target three-dimensional space can be detected from multiple angles. For example, detection points are set at different positions around, above, below, and other locations in the target space. After completing the detection at each detection angle, the corresponding two-dimensional image of the distribution of radioactive substances is obtained. Due to multi-angle detection, multiple two-dimensional images at different angles are obtained, and these images together constitute a set of two-dimensional images of the distribution of radioactive substances.

[0021] The radioactive detection equipment can sense the rays (such as gamma rays) emitted by radioactive substances and convert them into electrical signals or image signals.

[0022] When capturing two-dimensional images of the distribution of radioactive material, it is necessary to record the shooting position of the radioactive detection device (such as a gamma camera), i.e., the coordinates (x, y, z) and attitude (pitch angle, yaw angle, roll angle), so as to achieve the conversion of the two-dimensional image data of the radioactive material distribution in the coordinate system of the radioactive detection device into the target three-dimensional space 3D model subsequently obtained by the laser scanning device through coordinate transformation (translation, rotation).

[0023] For example, if the target space is a rectangular hall of 10m×8m×6m, the shooting position mark can be: shooting position A: upper left corner of the hall, coordinates (2,0,3)m, and the posture is tilted 45° (yaw angle 0°, pitch angle 0°).

[0024] In step S200 of the embodiment of the present application, three-dimensional point cloud data of the target three-dimensional space is collected based on a laser scanning device, and the three-dimensional point cloud data is assembled to construct a 3D model of the target three-dimensional space, including: Scanning a target three-dimensional space based on multiple positions using the laser scanning device to obtain multiple sets of point cloud data of the target three-dimensional space; Based on feature point matching, obtaining alignment positions of the multiple sets of point cloud data; Based on the alignment positions, the multiple sets of point cloud data are assembled into the target three-dimensional space 3D model.

[0025] In this embodiment, the point cloud data is acquired using a high-precision 3D laser scanner (such as the FARO Focus or Leica P series) or a mobile scanning device. The appropriate range can be selected based on the size of the target space (e.g., within 50 meters for indoor scenarios and over 200 meters for outdoor scenarios), ensuring that the point cloud density (e.g., 50 points / square meter) and accuracy (e.g., ±2 mm) meet modeling requirements.

[0026] For example, in indoor scenarios, 3D laser scanners can be deployed at multiple locations within a target 3D space (e.g., a hall) and at corridor intersections. Adjacent scanning locations must overlap by 30% to 50% to ensure that feature points are repeatedly visible. The point cloud data scanned at each location is a set of point cloud data. Multiple sets of point cloud data are collected to obtain multiple sets of point cloud data for the target 3D space.

[0027] For example, scanning position A yields point cloud A (containing 100,000 3D points, such as points (1,2,3), (2,3,4), etc.), while scanning position B yields point cloud B (containing 80,000 points, such as points (5,6,7), (6,7,8), etc.). In this case, the two sets of point cloud data are spatially misaligned due to their different locations.

[0028] Furthermore, it is necessary to obtain the alignment positions of the multiple sets of point cloud data based on feature point matching. First, the feature points in the point cloud data need to be extracted. Specifically, PCS software (such as CloudCompare or the PCL library) can be used to preprocess each set of point cloud data. Statistical Outlier Removal filtering is then used to remove noise points and retain true surface points. Finally, SIFT (Scale-Invariant Feature Transform), SURF (Speeded Robust Features), or ISS (Iterative Scale Space) algorithms are used to extract corners, edges, or points of curvature mutation (such as wall corners and cylindrical turning points) from the point cloud as feature points. A multidimensional description vector (such as a 3D-SIFT descriptor) is calculated for each feature point, containing information such as the spatial distribution of neighboring points and curvature changes, for cross-set point cloud feature matching.

[0029] Next, an algorithm is used to match common feature points (such as obvious geometric features like corners and pillar vertices) in different sets of point cloud data to determine the spatial alignment of each set of point cloud data. Based on the alignment obtained from feature point matching, for example, feature points P1 (1, 2, 3) and P2 (3, 4, 5) are extracted from point cloud A, and feature points Q1 (5, 6, 7) and Q2 (7, 8, 9) are extracted from point cloud B. The algorithm calculates that after translating point cloud B by -4 on the X-axis, -4 on the Y-axis, and -4 on the Z-axis, and rotating it by 0 degrees, P1 and Q1, and P2 and Q2, are almost aligned. This transformation is then determined as the alignment position.

[0030] Based on the aforementioned alignment positions, multiple sets of point cloud data are merged into the same coordinate system through coordinate transformation (translation, rotation, etc.), and finally assembled into a complete 3D model of the target three-dimensional space.

[0031] In step S300 of the embodiment of the present application, based on the set of two-dimensional images of the radioactive material distribution, a statistical reconstruction algorithm is used to restore the distribution image of the radioactive material in the target three-dimensional space, including: Evenly dividing the target three-dimensional space to be reconstructed into a plurality of volume elements, wherein each volume element may contain radioactive material that emits radioactive rays; Traversing the set of two-dimensional images of radioactive material distribution, calculating a plurality of signal contributions of radioactive rays of each volume element containing radioactive material to different pixel areas in a plurality of two-dimensional images of radioactive material distribution; Based on the multiple signal contributions, calculating multiple initial volume element radioactivity intensities of the multiple volume elements, and constructing an initial volume element radioactivity intensity array; Calculating theoretical pixel signals of an initial volume element radioactivity intensity array in a plurality of two-dimensional images of radioactive material distribution, and iteratively optimizing the initial volume element radioactivity intensity array based on a difference between the theoretical pixel signals and actual pixel signals to obtain a volume element radioactivity intensity array; The volume element radioactivity intensity array is converted into a distribution image of the radioactive material in the target three-dimensional space.

[0032] The volume element is the smallest cubic unit obtained by evenly dividing the target three-dimensional space, referred to as a "voxel." It is the basic unit of a three-dimensional spatial model, similar to the extension of a pixel in a two-dimensional image in three-dimensional space. In the embodiment of the present application, to evenly divide the target three-dimensional space to be reconstructed into multiple volume elements, it is first necessary to define the boundary of the target three-dimensional space. If the target space is a 10m×8m×5m room, the boundary coordinates can be defined as: x∈[0,10], y∈[0,8], z∈[0,5].

[0033] Next, the target 3D space needs to be evenly divided into multiple volume elements. For example, the side length of each volume element can be set (such as 0.1m), and the space can be divided evenly along the x, y, and z axes, so that each volume element is a cube. The spatial coordinates of each volume element are based on the lower-left vertex and are assigned a unique index (such as i, j, k) for subsequent processing.

[0034] In step S300 of the embodiment of the present application, the set of two-dimensional images of the radioactive material distribution is traversed to calculate the signal contributions of the radioactive rays of each volume element containing the radioactive material to the multiple pixel areas in the two-dimensional images of the radioactive material distribution. The two-dimensional image of the radioactive material distribution is formed by the radioactive rays emitted by each volume element containing the radioactive material and passing through the encoding plate of the radioactive detection device. The two-dimensional image of the radioactive material distribution contains multiple pixel areas and is affected by the intensity of the received radiation signal, including: Based on the radioactive ray intensities received by different pixel areas in the two-dimensional image of the radioactive material distribution, the individual signal contribution of each volume element containing the radioactive material to the radioactive ray intensities of multiple pixel areas in multiple two-dimensional images of the radioactive material distribution is simulated and calculated; Based on the individual signal contribution of the volume element to the radioactive ray intensity of the pixel area of ​​the two-dimensional image of different radioactive material distributions, and the radioactive ray intensity received by different pixel areas in the two-dimensional image of the radioactive material distribution, the signal contribution of the radioactive ray of each volume element to the pixel area of ​​the two-dimensional image of the radioactive material distribution is calculated.

[0035] In the embodiments of this application, a pixel region is a local area composed of multiple pixels in a two-dimensional image, or the smallest unit of a single pixel, used to record the intensity of radioactive radiation. Assuming the two-dimensional image generated by the radiation detection device is 100×100 pixels, each pixel is 1mm×1mm in size. If one pixel is defined as a pixel region, then in this example, the pixel region is a 1mm×1mm square area.

[0036] The signal intensity of a pixel is the intensity of the radioactive radiation received by that pixel. It is usually expressed as a count rate (such as counts per second, cps) or energy value. A higher value indicates more radiation received by that area. If a pixel receives 200 gamma-ray photons in 1 second, its signal intensity is 200 cps.

[0037] In the embodiments of this application, the two-dimensional image captured by a radioactivity detection device (such as a gamma camera) is essentially the superposition of radiation emitted by each volume element in three-dimensional space, projected through the coded plate. The signal intensity at each pixel is a comprehensive reflection of the radiation contributions from all volume elements. By mathematically decomposing this superposition relationship, the individual signal contribution of each volume element to each pixel can be inferred.

[0038] For example, the calculation principle is to assume that a volume element V contains only radioactive material, while other volume elements are non-radioactive. The radioactive rays emitted by volume element V diffuse in all directions and pass through the encoding plate (e.g., collimator, coded aperture) of the radiation detection device. The encoding plate then modulates (e.g., blocks or deflects) the rays so that they reach the detector only at specific angles, forming a signal for a specific pixel area in the two-dimensional image, i.e., the individual signal contribution.

[0039] The above assumes that radioactive material exists solely in a certain volume element V, while other volume elements are non-radioactive. Specifically, when radiation passes through the encoding plate, it reaches the radioactivity detector only through specific holes, generating pixel signals in the 2D image. For example, if the position of volume element V aligns with hole P1 in the encoding plate, radiation can pass through hole P1, generating a signal at pixel P1' in the 2D image. However, other holes block the radiation due to angular deviations, resulting in no signal at the corresponding pixels.

[0040] Assume that the target space has two volume elements V1 and V2, and the two-dimensional image has one pixel area P. When V1 emits radiation alone with a radiation intensity of 1 Bq, the intensity received by P is 100 cps, which is recorded as V1's individual contribution to P = 100 cps / Bq (i.e., 1 Bq of V1 generates 100 cps at P). When V2 emits radiation alone with an actual radiation intensity of 1 Bq, the intensity received by P is 50 cps, which is recorded as V2's individual contribution to P = 50 cps / Bq (i.e., 1 Bq of V2 generates 50 cps at P). If V1's radiation intensity is 2Bq and V2 is off (radioactivity = 0), then V1's contribution to P's individual signal is 100cps / Bq × 2Bq = 200cps. If V2's radiation intensity is 3Bq and V1 is off, then V2's contribution to P's individual signal is 50cps / Bq × 3Bq = 150cps.

[0041] The individual signal contribution represents the signal contribution of each volume element to a pixel region when acting alone. This serves as a fundamental parameter for subsequently inferring the actual radioactivity intensity of that volume element. The above method can be used to determine the individual signal contributions of multiple volume elements containing radioactive material to the radioactivity intensity of multiple pixel regions in a 2D image of the distribution of radioactive material.

[0042] The radioactive ray intensity (Bq) is the rate of nuclear decay, which is determined by the properties of the radioactive substance itself. The method for obtaining it is an existing technology and will not be repeated here.

[0043] Furthermore, it is necessary to calculate the signal contribution of the radioactive rays of each volume element to the pixel area of ​​the two-dimensional image of the radioactive material distribution based on the individual signal contribution of the volume element to the radioactive ray intensity of the pixel area of ​​the two-dimensional image of the radioactive material distribution, and the radioactive ray intensity received by different pixel areas in the two-dimensional image of the radioactive material distribution.

[0044] Based on the above example, assume that V1's individual contribution to P's signal is 100 cps / Bq, V2's individual contribution to P's signal is 50 cps / Bq, and the measured signal intensity is 350 cps. Assume that the radioactivity intensity of both V1 and V2 is 1 Bq, and that the initial radioactivity intensity of all volume elements is 1 Bq.

[0045] Then the signal contribution of V1 to P = 1Bq×100cps / Bq=100cps (that is, assuming that the intensity of V1 radioactive rays is 1Bq, the contribution to P1 is 100cps).

[0046] The signal contribution of V2 to P = 1Bq × 50cps / Bq = 50cps (that is, assuming that the intensity of V2 radioactive rays is 1Bq, the contribution to P1 is 50cps).

[0047] By using the above method, the signal contribution of the radioactive rays of each volume element to the pixel area of ​​the two-dimensional image of the radioactive material distribution can be calculated.

[0048] Furthermore, it is necessary to calculate a plurality of initial volume element radioactivity intensities of a plurality of volume elements based on the plurality of signal contributions, and construct an initial volume element radioactivity intensity array; Specifically, it can be assumed that the initial radioactivity intensity of all volume elements is the same (e.g., 1 Bq), or the initial value can be set based on prior knowledge (e.g., the distribution law of radioactive materials), and the initial radioactivity intensity of all volume elements can be arranged according to spatial coordinates to form an array of initial volume element radioactivity intensities (e.g., a three-dimensional matrix). In step S300 of the embodiment of the present application, the theoretical pixel signals of the initial volume element radioactivity intensity array in the multiple two-dimensional images of radioactive material distribution are calculated, and based on the difference between the theoretical pixel signals and the actual pixel signals, the initial volume element radioactivity intensity array is iteratively optimized to obtain the volume element radioactivity intensity array, including: Based on the initial volume element radioactivity intensity array, calculating theoretical pixel signals of the volume element radioactivity intensity array in a plurality of two-dimensional images of radioactive material distribution; Calculating a signal difference between the theoretical pixel signal and the actual pixel signal; When the signal gap is less than or equal to a signal gap threshold, using the initial volume element radioactivity intensity array as the volume element radioactivity intensity array; When the signal gap is greater than the signal gap threshold, the initial volume element radioactivity intensity array is adjusted to obtain the adjusted volume element radioactivity intensity array, and the signal gap between its theoretical pixel signal and the actual pixel signal is calculated to determine whether it is greater than the signal gap threshold. If so, the above steps are repeated until the signal gap is less than or equal to the signal gap threshold. The adjusted volume element radioactivity intensity array with a signal gap less than or equal to the signal gap threshold is used as the volume element radioactivity intensity array.

[0049] In the embodiment of the present application, the theoretical pixel signal refers to the radioactive ray intensity of each pixel area in the two-dimensional image obtained by calculation based on the initial element radioactive intensity array. The theoretical pixel signal represents the radioactive ray intensity "if the volume element radioactive intensity is distributed according to the current array, the signal intensity that the detector should receive", reflecting the mathematical mapping relationship between the distribution of radioactive material and detector imaging.

[0050] Through the above steps, the initial volume element radioactivity intensity array and the individual signal contribution of each volume element to each pixel area have been obtained. The theoretical pixel signal can be calculated as follows: theoretical pixel signal = ∑(volume element radioactivity intensity × individual contribution of the volume element to the pixel area).

[0051] For example, if the radioactivity intensity of the volume element radioactivity intensity V1 = radioactivity intensity 2 + radioactivity intensity Bq, and its individual contribution to the pixel area radioactivity intensity P1 = radioactivity intensity 100 + radioactivity intensity cps / Bq + radioactivity intensity, then the signal contribution of the radioactivity intensity V1 to the radioactivity intensity P1 = radioactivity intensity 2 × 100 = 200 + radioactivity intensity cps.

[0052] The volume element radioactive ray intensity V2 radioactive ray intensity = radioactive ray intensity 3 radioactive ray intensity Bq, and its independent contribution to the pixel area radioactive ray intensity P1 radioactive ray intensity = radioactive ray intensity 50 radioactive ray intensity cps / Bq radioactive ray intensity, then the signal contribution of V2 radioactive ray intensity to the radioactive ray intensity P1 radioactive ray intensity = radioactive ray intensity 3×50=150 radioactive ray intensity cps.

[0053] Then the theoretical pixel signal radioactive ray intensity of the radioactive ray intensity of the pixel area P1 = radioactive ray intensity 200 + 150 = 350 radioactive ray intensity cps.

[0054] By using the above method, the theoretical pixel signals of the volume element radioactivity intensity array in multiple two-dimensional images of radioactive material distribution can be calculated.

[0055] In step S300 of the embodiment of the present application, calculating the signal difference between the theoretical pixel signal and the actual pixel signal includes: Calculating multiple differences between each theoretical pixel signal and each corresponding actual pixel signal in the first two-dimensional image, obtaining multiple first differences after removing outliers, and calculating an average of the multiple first differences; Obtaining a maximum value of a plurality of first difference values, and calculating a first correction coefficient based on the maximum value of the first difference values; Multiplying the first difference average by the first correction coefficient to obtain a first signal gap; A plurality of first signal gaps of a plurality of two-dimensional images in the set of two-dimensional images of the distribution of radioactive material are calculated, and an average value of the plurality of first signal gaps is obtained to obtain the signal gap.

[0056] In the embodiment of the present application, the actual pixel signal refers to the radioactive ray intensity of each pixel area in the two-dimensional image directly collected by the radioactive detection device through the detector. The unit is usually counting radioactive ray intensity / radioactive ray intensity second (cps). Specifically, after the rays emitted by the radioactive material pass through the coding plate, the electrical signal generated on the detector is converted into a pixel value, reflecting the ray counting rate (cps) received in the area, which can be directly obtained from the radioactive detection device.

[0057] Next, for each pixel region in the first two-dimensional image, a first difference between the theoretical pixel signal and the actual pixel signal is calculated to obtain multiple first difference values. The calculation method is: first difference = theoretical pixel signal - actual pixel signal. Multiple first difference values ​​can be calculated using the above method.

[0058] Furthermore, it is also necessary to calculate an average value of a plurality of first difference values, a maximum value of a plurality of first difference values, a first correction coefficient, and a first signal gap.

[0059] Assume that a first two-dimensional image has a pixel region with a radioactive radiation intensity of 5. The differences between the theoretical pixel signal and the actual pixel signal are: [2, radioactive radiation intensity 4, radioactive radiation intensity 10, radioactive radiation intensity 3, radioactive radiation intensity 20]. After removing outliers (outliers are extremely large or small values ​​that deviate significantly from the general level; assume that radioactive radiation intensity 20 is an outlier), the following remains: [2, radioactive radiation intensity 4, radioactive radiation intensity 10, radioactive radiation intensity 3]. Calculation shows that the average first difference is (2 + 4 + 10 + 3) / 4 = 4.75 cps; the maximum first difference is 10 cps. The first correction coefficient can be the ratio of the maximum first difference to the average first difference, that is, 10 / 4.75 ≈ 2.105 cps; the first signal gap is 4.75 × 2.105 ≈ 10 cps.

[0060] Furthermore, if there are three first two-dimensional images with radioactive ray intensities, and the first signal differences are respectively 10 cps, 8 cps, and 12 cps, then the signal difference is (10+8+12) / 3=10 cps.

[0061] By using the above method, the signal gap between the theoretical pixel signal and the actual pixel signal can be calculated.

[0062] When the signal gap is less than or equal to a signal gap threshold, using the initial volume element radioactivity intensity array as the volume element radioactivity intensity array; When the signal gap is greater than the signal gap threshold, the initial volume element radioactivity intensity array is adjusted to obtain the adjusted volume element radioactivity intensity array, and the signal gap between its theoretical pixel signal and the actual pixel signal is calculated to determine whether it is greater than the signal gap threshold. If so, the above steps are repeated until the signal gap is less than or equal to the signal gap threshold. The adjusted volume element radioactivity intensity array with a signal gap less than or equal to the signal gap threshold is used as the volume element radioactivity intensity array.

[0063] In the embodiment of the present application, when the signal gap is less than or equal to the signal gap threshold, it indicates that the theoretical pixel signal is sufficiently close to the measured pixel signal, and the initial volume element radioactivity intensity array meets the requirements and is directly adopted. When the signal gap is greater than the signal gap threshold, it indicates that the theoretical pixel signal is significantly different from the measured pixel signal, and the volume element radioactivity intensity array needs to be adjusted and the signal gap recalculated until the signal gap threshold is met. The signal gap threshold can be determined according to the actual modeling requirements, for example, it can be set to 10 radioactivity intensity cps.

[0064] The specific adjustment method involves adjusting the volume element intensity proportionally to the signal gap. For example, if the original radioactivity intensity of a volume element is 10 Bq, the corresponding theoretical pixel signal is 200 cps, and the measured pixel signal is 300 cps (signal gap = 100 cps). The adjustment factor = 100 / 200 = 0.5, resulting in an adjustment amplitude of 10 × 0.5 = 5 Bq. This means the adjusted radioactivity intensity is either 10-5 = 5 Bq or 10+5 = 15 Bq, depending on the direction. If the signal gap increases after adjustment, adjust in the opposite direction.

[0065] The specific adjustment process can be, for example, in the above example, assuming that the signal difference radioactive ray intensity = radioactive ray intensity 50 radioactive ray intensity cps, the threshold radioactive ray intensity = radioactive ray intensity 10 radioactive ray intensity cps, and the difference radioactive ray intensity > the radioactive ray intensity threshold, and adjustment is required, then the adjustment method can be to adjust the radioactive ray intensity of the estimated volume element radioactive ray intensity V1 from radioactive ray intensity 2 radioactive ray intensity Bq to radioactive ray intensity 3 radioactive ray intensity Bq, and the radioactive ray intensity of V2 from radioactive ray intensity 3 radioactive ray intensity Bq to radioactive ray intensity 2.5 radioactive ray intensity Bq. Then, recalculate the signal difference. If the signal difference radioactive ray intensity = radioactive ray intensity 15 radioactive ray intensity cps is still greater than the threshold, then continue to adjust the radioactive ray intensity of V1 to 3.5 radioactive ray intensity Bq and V2 to 2.8 radioactive ray intensity Bq. Recalculate the signal difference. If the signal difference radioactive ray intensity = radioactive ray intensity 8 radioactive ray intensity cps is less than the threshold, then use the adjusted radioactive ray intensity array as the volume element radioactive ray intensity array.

[0066] In step S400 of the embodiment of the present application, based on the target three-dimensional space 3D model and the distribution image, a three-dimensional distribution modeling result of the radioactive material is obtained, including: Aligning the spatial coordinates of the 3D model of the target three-dimensional space and the distribution image of the radioactive material in the target three-dimensional space; The radioactivity distribution data is used as an attribute layer of the target three-dimensional space 3D model, and the radioactivity distribution data is attached to multiple faces of the target three-dimensional space 3D model; Obtain the radioactivity intensity of all volume elements in multiple surfaces and calculate their average value as the radioactivity value of multiple surfaces; using the radioactivity of the plurality of surfaces as attributes of the plurality of surfaces; Multiple faces of the target three-dimensional space 3D model are colored based on the radioactivity values ​​of the multiple faces to form a heat map effect.

[0067] In an embodiment of the present application, the spatial coordinates of the target three-dimensional space 3D model and the distribution image of the radioactive material in the target three-dimensional space are aligned, that is, the coordinate system of the target three-dimensional space 3D model constructed by laser scanning is aligned with the coordinate system of the radioactive distribution image. Specifically, with the origin of the three-dimensional laser scanner as the reference, the radioactive distribution image is rotated and translated so that the positions of the feature points such as corners and columns of the two coincide.

[0068] At least three common feature points (such as wall corners and pipe interfaces) are identified in the 3D model of the target three-dimensional space and the distribution image of the original radioactive material in the target three-dimensional space. Finally, the coordinate information of all volume elements of the radioactive material distribution image is converted into coordinates in the 3D model of the target three-dimensional space.

[0069] Next, the radioactivity distribution data needs to be used as the attribute layer of the target three-dimensional space 3D model, and the radioactivity distribution data needs to be attached to multiple faces of the target three-dimensional space 3D model, so that the wall area in the target three-dimensional space 3D model corresponds to the set of volume elements in the distribution image, and the radioactivity intensity of the volume elements is assigned to the wall.

[0070] Furthermore, it's necessary to extract all volume elements within each surface of the target 3D model and calculate the average radioactivity intensity of these volume elements, which serves as the activity value for that surface (e.g., Bq / m2). For example, a wall surface contains 100 volume elements with a total intensity of 200 Bq, and the average is 200 ÷ 100 = 2 Bq / m2. The radioactivity value for each surface is then recorded as its attribute parameter. For example, the attribute for wall A is "Radioactivity = 2 Bq / m2," and for wall B it is "1.5 Bq / m2."

[0071] Finally, the surface of the target three-dimensional space 3D model can be color-coded according to the activity value. For example, high activity (such as >5Bq) is marked as red; medium activity (2-5Bq) is marked as yellow, and low activity (<2Bq) is marked as blue. The surface of the target three-dimensional space 3D model finally generated presents a heat map effect, which can intuitively show the intensity of radioactivity distribution. Example 2, such as Figure 2 As shown, based on the same inventive concept as the radioactivity distribution modeling method for integrating multi-modal imaging and 3D laser scanning provided in Example 1, an embodiment of the present invention also provides a radioactivity distribution modeling system for integrating multi-modal imaging and 3D laser scanning, including: The radioactive detection module 11 is used to perform multi-angle detection of radioactive materials in the target three-dimensional space based on radioactive detection equipment to obtain a set of two-dimensional images of the distribution of radioactive materials; A spatial modeling module 12 is configured to collect three-dimensional point cloud data of a target three-dimensional space based on a laser scanning device, assemble the three-dimensional point cloud data, and construct a 3D model of the target three-dimensional space; A radioactive modeling module 13 is configured to restore the distribution image of the radioactive material in the target three-dimensional space using a statistical reconstruction algorithm based on the set of two-dimensional images of the radioactive material distribution; The modeling fusion module 14 is used to obtain a three-dimensional distribution modeling result of the radioactive material based on the target three-dimensional space 3D model and the distribution image.

[0072] Furthermore, the spatial modeling module 12 includes the following execution steps: using the laser scanning device to scan the target three-dimensional space based on multiple positions to obtain multiple sets of point cloud data of the target three-dimensional space; based on feature point matching, obtaining the alignment positions of the multiple sets of point cloud data; based on the alignment positions, assembling the multiple sets of point cloud data into a 3D model of the target three-dimensional space.

[0073] Furthermore, the radioactivity modeling module 13 includes the following execution steps: The target three-dimensional space to be reconstructed is evenly divided into multiple volume elements, wherein each volume element may contain radioactive material, and the radioactive material will emit radioactive rays; the set of two-dimensional images of the radioactive material distribution is traversed, and the multiple signal contributions of the radioactive rays of each volume element containing the radioactive material to different pixel areas in the multiple two-dimensional images of the radioactive material distribution are calculated; based on the multiple signal contributions, multiple initial volume element radioactive intensities of the multiple volume elements are deduced, and an initial volume element radioactive intensity array is constructed; the theoretical pixel signals of the initial volume element radioactive intensity array in the multiple two-dimensional images of the radioactive material distribution are calculated, and based on the gap between the theoretical pixel signals and the actual pixel signals, the initial volume element radioactive intensity array is iteratively optimized to obtain a volume element radioactive intensity array; the volume element radioactive intensity array is converted into a distribution image of the radioactive material in the target three-dimensional space.

[0074] The method comprises traversing the set of two-dimensional images of radioactive material distribution, calculating the contribution of the radioactive rays of each volume element containing radioactive material to multiple signals of different pixel areas in the multiple two-dimensional images of radioactive material distribution, wherein the two-dimensional images of radioactive material distribution are formed by the radioactive rays emitted by each volume element containing radioactive material and passing through the coding plate of the radioactive detection device, and the two-dimensional images of radioactive material distribution contain multiple pixel areas and are affected by the intensity of the received radioactive signal, including: Based on the radioactive ray intensity received by different pixel areas in the two-dimensional image of the radioactive material distribution, the individual signal contribution of each volume element containing radioactive material to the radioactive ray intensity of multiple pixel areas of multiple two-dimensional images of the radioactive material distribution is simulated and calculated; based on the individual signal contribution of the volume element to the radioactive ray intensity of the pixel areas of different two-dimensional images of the radioactive material distribution, and the radioactive ray intensity received by different pixel areas in the two-dimensional image of the radioactive material distribution, the signal contribution of the radioactive ray of each volume element to the pixel area of ​​the two-dimensional image of the radioactive material distribution is calculated.

[0075] The method comprises calculating theoretical pixel signals of the initial volume element radioactivity intensity array in a plurality of two-dimensional images of radioactive material distribution, and iteratively optimizing the initial volume element radioactivity intensity array based on the difference between the theoretical pixel signals and the actual pixel signals to obtain the volume element radioactivity intensity array, including: Based on the initial volume element radioactivity intensity array, the theoretical pixel signal of the volume element radioactivity intensity array in multiple two-dimensional images of radioactive material distribution is calculated; the signal gap between the theoretical pixel signal and the actual pixel signal is calculated; when the signal gap is less than or equal to the signal gap threshold, the initial volume element radioactivity intensity array is used as the volume element radioactivity intensity array; when the signal gap is greater than the signal gap threshold, the initial volume element radioactivity intensity array is adjusted to obtain an adjusted volume element radioactivity intensity array, and the signal gap between its theoretical pixel signal and the actual pixel signal is calculated to determine whether it is greater than the signal gap threshold. If so, the above steps are repeated until its signal gap is less than or equal to the signal gap threshold, and the adjusted volume element radioactivity intensity array with a signal gap less than or equal to the signal gap threshold is used as the volume element radioactivity intensity array.

[0076] Calculating the signal difference between the theoretical pixel signal and the actual pixel signal includes: Calculate multiple differences between each theoretical pixel signal and each corresponding actual pixel signal in the first two-dimensional image, obtain multiple first differences after eliminating outliers, and calculate the average of the multiple first differences; obtain the maximum value of the multiple first differences, and calculate a first correction coefficient based on the maximum value of the first differences; multiply the first correction coefficient by the average value of the first differences to obtain a first signal gap; calculate multiple first signal gaps of multiple two-dimensional images in the set of two-dimensional images of radioactive material distribution, find the average value of the multiple first signal gaps, and obtain the signal gap.

[0077] Furthermore, the modeling fusion module 14 includes the following execution steps: The spatial coordinates of the target three-dimensional space 3D model and the distribution image of the radioactive material in the target three-dimensional space are aligned; the radioactivity distribution data is used as the attribute layer of the target three-dimensional space 3D model, and the radioactivity distribution data is attached to multiple faces of the target three-dimensional space 3D model; the radioactivity intensity of all volume elements in the multiple faces is obtained, and the average thereof is calculated as the radioactivity activity value of the multiple faces; the radioactivity activity of the multiple faces is used as the attribute of the multiple faces; and the multiple faces of the target three-dimensional space 3D model are colored based on the radioactivity activity values ​​of the multiple faces to form a heat map effect.

[0078] It should be noted that, in the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0079] Those skilled in the art will appreciate that embodiments of the present invention may provide methods, systems, or computer program products. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROMs, optical storage, etc.) containing computer-usable program code.

[0080] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0081] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0082] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0083] Although preferred embodiments of the present invention have been described, additional changes and modifications to these embodiments may occur to those skilled in the art once the basic inventive concepts become known.

[0084] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the present invention and its equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A radioactivity distribution modeling method integrating multi-modal imaging and 3D laser scanning, characterized in that: The method comprises: Based on the radioactive detection equipment, the radioactive materials in the target three-dimensional space are detected from multiple angles to obtain a set of two-dimensional images of the distribution of radioactive materials; Collecting three-dimensional point cloud data of the target three-dimensional space based on a laser scanning device, assembling the three-dimensional point cloud data, and constructing a 3D model of the target three-dimensional space; Based on the set of two-dimensional images of the radioactive material distribution, a statistical reconstruction algorithm is used to restore the distribution image of the radioactive material in the target three-dimensional space; Based on the target three-dimensional space 3D model and the distribution image, a three-dimensional distribution modeling result of radioactive material is obtained.

2. The radioactivity distribution modeling method of multimodal imaging and 3D laser scanning fusion according to claim 1, characterized in that: Based on a laser scanning device, three-dimensional point cloud data of a target three-dimensional space is collected, the three-dimensional point cloud data is assembled, and a 3D model of the target three-dimensional space is constructed, including: Scanning a target three-dimensional space based on multiple positions using the laser scanning device to obtain multiple sets of point cloud data of the target three-dimensional space; Based on feature point matching, obtaining alignment positions of the multiple sets of point cloud data; Based on the alignment positions, the multiple sets of point cloud data are assembled into the target three-dimensional space 3D model.

3. The radioactivity distribution modeling method of multi-modal imaging and 3D laser scanning fusion according to claim 1, characterized in that: Based on the set of two-dimensional images of the radioactive material distribution, a statistical reconstruction algorithm is used to restore the distribution image of the radioactive material in the target three-dimensional space, including: Evenly dividing the target three-dimensional space to be reconstructed into a plurality of volume elements, wherein each volume element may contain radioactive material that emits radioactive rays; Traversing the set of two-dimensional images of radioactive material distribution, calculating a plurality of signal contributions of radioactive rays of each volume element containing radioactive material to different pixel areas in a plurality of two-dimensional images of radioactive material distribution; Based on the multiple signal contributions, calculating multiple initial volume element radioactivity intensities of the multiple volume elements, and constructing an initial volume element radioactivity intensity array; Calculating theoretical pixel signals of an initial volume element radioactivity intensity array in a plurality of two-dimensional images of radioactive material distribution, and iteratively optimizing the initial volume element radioactivity intensity array based on a difference between the theoretical pixel signals and actual pixel signals to obtain a volume element radioactivity intensity array; The volume element radioactivity intensity array is converted into a distribution image of the radioactive material in the target three-dimensional space.

4. The radioactivity distribution modeling method of multi-modal imaging and 3D laser scanning fusion according to claim 3, characterized in that: Traversing the set of two-dimensional radioactive material distribution images, calculating multiple signal contributions of radioactive rays from each volume element containing radioactive material to different pixel areas in the multiple two-dimensional radioactive material distribution images, wherein the two-dimensional radioactive material distribution image is formed by radioactive rays emitted by each volume element containing radioactive material and passing through a coding plate of a radioactive detection device, and the two-dimensional radioactive material distribution image contains multiple pixel areas and is affected by the intensity of the received radioactive signal, including: Based on the radioactive ray intensities received by different pixel areas in the two-dimensional image of the radioactive material distribution, the individual signal contribution of each volume element containing the radioactive material to the radioactive ray intensities of multiple pixel areas in multiple two-dimensional images of the radioactive material distribution is simulated and calculated; Based on the individual signal contribution of the volume element to the radioactive ray intensity of the pixel area of ​​the two-dimensional image of different radioactive material distributions, and the radioactive ray intensity received by different pixel areas in the two-dimensional image of the radioactive material distribution, the signal contribution of the radioactive ray of each volume element to the pixel area of ​​the two-dimensional image of the radioactive material distribution is calculated.

5. The radioactivity distribution modeling method of multi-modal imaging and 3D laser scanning fusion according to claim 3, characterized in that: Calculating theoretical pixel signals of an initial volume element radioactivity intensity array in a plurality of two-dimensional images of radioactive material distribution, and iteratively optimizing the initial volume element radioactivity intensity array based on a difference between the theoretical pixel signals and actual pixel signals to obtain a volume element radioactivity intensity array, including: Based on the initial volume element radioactivity intensity array, calculating theoretical pixel signals of the volume element radioactivity intensity array in a plurality of two-dimensional images of radioactive material distribution; Calculating a signal difference between the theoretical pixel signal and the actual pixel signal; When the signal gap is less than or equal to a signal gap threshold, using the initial volume element radioactivity intensity array as the volume element radioactivity intensity array; When the signal gap is greater than the signal gap threshold, the initial volume element radioactivity intensity array is adjusted to obtain the adjusted volume element radioactivity intensity array, and the signal gap between its theoretical pixel signal and the actual pixel signal is calculated to determine whether it is greater than the signal gap threshold. If so, the above steps are repeated until the signal gap is less than or equal to the signal gap threshold. The adjusted volume element radioactivity intensity array with a signal gap less than or equal to the signal gap threshold is used as the volume element radioactivity intensity array.

6. The radioactivity distribution modeling method of multi-modal imaging and 3D laser scanning fusion according to claim 5, characterized in that: Calculating a signal difference between the theoretical pixel signal and the actual pixel signal includes: Calculating multiple differences between each theoretical pixel signal and each corresponding actual pixel signal in the first two-dimensional image, obtaining multiple first differences after removing outliers, and calculating an average of the multiple first differences; Obtaining a maximum value of a plurality of first difference values, and calculating a first correction coefficient based on the maximum value of the first difference values; Multiplying the first difference average by the first correction coefficient to obtain a first signal gap; A plurality of first signal gaps of a plurality of two-dimensional images in the set of two-dimensional images of the distribution of radioactive material are calculated, and an average value of the plurality of first signal gaps is obtained to obtain the signal gap.

7. The radioactivity distribution modeling method of multi-modal imaging and 3D laser scanning fusion according to claim 1, characterized in that: Based on the target three-dimensional space 3D model and the distribution image, a three-dimensional distribution modeling result of the radioactive material is obtained, including: Aligning the spatial coordinates of the 3D model of the target three-dimensional space and the distribution image of the radioactive material in the target three-dimensional space; Using the radioactivity distribution data as an attribute layer of the target three-dimensional space 3D model, and attaching the radioactivity distribution data to multiple faces of the target three-dimensional space 3D model; Obtain the radioactivity intensity of all volume elements in multiple surfaces and calculate their average value as the radioactivity value of multiple surfaces; using the radioactivity of the plurality of surfaces as attributes of the plurality of surfaces; Multiple faces of the target three-dimensional space 3D model are colored based on the radioactivity values ​​of the multiple faces to form a heat map effect.

8. Radioactivity distribution modeling system integrating multi-modal imaging and 3D laser scanning, characterized by: The system comprises: A radioactive detection module is used to perform multi-angle detection of radioactive materials in the target three-dimensional space based on radioactive detection equipment to obtain a set of two-dimensional images of the distribution of radioactive materials; A spatial modeling module is used to collect three-dimensional point cloud data of the target three-dimensional space based on a laser scanning device, assemble the three-dimensional point cloud data, and construct a 3D model of the target three-dimensional space; a radioactivity modeling module, configured to restore the distribution image of the radioactive material in the target three-dimensional space using a statistical reconstruction algorithm based on the set of two-dimensional images of the radioactive material distribution; The modeling fusion module is used to obtain a three-dimensional distribution modeling result of the radioactive material based on the target three-dimensional space 3D model and the distribution image.

Images