Multi-modal imaging and three-dimensional laser scanning fusion-based radiopharmaceutical distribution modeling method

Abstract

The present application relates to the technical field of modeling, in particular to a kind of radioactive distribution modeling method of multi-mode imaging and three-dimensional laser scanning fusion.It is based on radioactive detection equipment, and radioactive material in target three-dimensional space is detected at multiple angles, obtains radioactive material distribution two-dimensional image set;Based on laser scanning equipment, three-dimensional point cloud data of target three-dimensional space is collected, three-dimensional point cloud data is assembled, and target three-dimensional space 3D model is constructed;Based on the two-dimensional image set of radioactive material distribution, the distribution image of radioactive material in target three-dimensional space is restored using statistical reconstruction algorithm;Based on target three-dimensional space 3D model and distribution image, radioactive material three-dimensional distribution modeling result is obtained by combination.It achieves the technical effect of intuitively and accurately showing the distribution of radioactive material in three-dimensional space.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of modeling, in particular to a radioactive distribution modeling method based on multi-mode imaging and three-dimensional laser scanning fusion. BACKGROUND

[0002] In the field of radioactive substance distribution modeling, traditional modeling methods often only use a single imaging mode, such as only relying on radioactive detection equipment to obtain the distribution information of radioactive substances, or only constructing a geometric model of the target space through a laser scanning device. A single radioactive detection device can only obtain two-dimensional information of the distribution of radioactive substances, and it is difficult to directly and accurately restore its distribution in three-dimensional space, and it is impossible to comprehensively and intuitively show the specific position and intensity distribution of radioactive substances in three-dimensional space. While relying only on a laser scanning device can construct a three-dimensional geometric model of the target space, it cannot obtain the distribution information of radioactive substances, and cannot combine the distribution of radioactive substances with the geometric structure of the target space, resulting in a lack of spatial reference for analyzing radioactive substances. The traditional method cannot realize the fusion of multi-mode information, so that the modeling result is not accurate and comprehensive, and it is difficult to meet the needs of in-depth research and monitoring of radioactive substances, and there is a technical problem of inaccurate and non-intuitive modeling. SUMMARY

[0003] The present application provides a radioactive distribution modeling method based on multi-mode imaging and three-dimensional laser scanning fusion to solve the technical problems of inaccurate and non-intuitive modeling in the prior art.

[0004] The technical solution of the present application to solve the above technical problems is as follows:

[0005] In a first aspect, the present application provides a radioactive distribution modeling method based on multi-mode imaging and three-dimensional laser scanning fusion, comprising: based on a radioactive detection device, multi-angle detection of radioactive substances in a target three-dimensional space is performed to obtain a set of two-dimensional images of the distribution of radioactive substances; 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; based on the set of two-dimensional images of the distribution of radioactive substances, a statistical reconstruction algorithm is used to restore the distribution image of radioactive substances in the target three-dimensional space; and based on the 3D model of the target three-dimensional space and the distribution image, a three-dimensional distribution modeling result of radioactive substances is obtained.

[0006] Optionally, based on the 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 three-dimensional 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 sets of point cloud data of the target three-dimensional space; based on feature point matching, obtaining the alignment position of the multiple sets of point cloud data; based on the alignment position, assembling the multiple sets of point cloud data into the three-dimensional model of the target three-dimensional space.

[0007] Optionally, based on the set of radioactive material distribution two-dimensional images, a statistical reconstruction algorithm is used to restore the distribution image of the radioactive material in the target three-dimensional space, including: uniformly dividing the target three-dimensional space to be reconstructed into a plurality of volume elements, wherein each volume element can contain radioactive material, and the radioactive material emits radioactive rays; traversing the set of radioactive material distribution two-dimensional images, calculating the signal contribution degree of the radioactive rays of each volume element containing radioactive material to different pixel regions in multiple radioactive material distribution two-dimensional images; based on the multiple signal contribution degrees, calculating the initial volume element radioactive intensity of the multiple volume elements to construct an initial volume element radioactive intensity array; calculating the theoretical pixel signal of the initial volume element radioactive intensity array in the multiple radioactive material distribution two-dimensional images, and based on the difference between the theoretical pixel signal and the actual pixel signal, iteratively optimizing the initial volume element radioactive intensity array to obtain a volume element radioactive intensity array; and converting the volume element radioactive intensity array into a distribution image of the radioactive material in the target three-dimensional space.

[0008] In the method, the set of radioactive material distribution two-dimensional images is traversed to calculate the signal contribution degree of the radioactive rays of each volume element containing radioactive material to different pixel regions in multiple radioactive material distribution two-dimensional images. The radioactive material distribution two-dimensional image is formed by the radioactive rays emitted by each volume element containing radioactive material after passing through the encoding plate of the radioactive detection device. The radioactive material distribution two-dimensional image contains multiple pixel regions and is affected by the received radioactive signal intensity. The method includes: based on the radioactive ray intensity received by different pixel regions in the radioactive material distribution two-dimensional image, simulating and calculating the individual signal contribution degree of each volume element containing radioactive material to the radioactive ray intensity of multiple pixel regions of multiple radioactive material distribution two-dimensional images; based on the individual signal contribution degree of the volume element to the pixel region radioactive ray intensity of different radioactive material distribution two-dimensional images and the radioactive ray intensity received by different pixel regions in the radioactive material distribution two-dimensional image, the signal contribution degree of the radioactive rays of each volume element to the pixel region of the radioactive material distribution two-dimensional image is calculated and obtained.

[0009] The method comprises the following steps: calculating theoretical pixel signals of an initial volume element radioactivity intensity array in a plurality of radioactivity distribution two-dimensional images; 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, comprising: calculating theoretical pixel signals of the volume element radioactivity intensity array in a plurality of radioactivity distribution two-dimensional images based on the initial volume element radioactivity intensity array; calculating a signal difference between the theoretical pixel signals and actual pixel signals; when the signal difference is less than or equal to a signal difference threshold, taking the initial volume element radioactivity intensity array as the volume element radioactivity intensity array; when the signal difference is greater than the signal difference threshold, adjusting the initial volume element radioactivity intensity array to obtain an adjusted volume element radioactivity intensity array, calculating a signal difference between the theoretical pixel signals and actual pixel signals of the adjusted volume element radioactivity intensity array, and judging whether the signal difference is greater than the signal difference threshold; if yes, repeatedly performing the above steps until the signal difference is less than or equal to the signal difference threshold, and taking the adjusted volume element radioactivity intensity array with the signal difference less than or equal to the signal difference threshold as the volume element radioactivity intensity array.

[0010] The method comprises the following steps: calculating theoretical pixel signals of an initial volume element radioactivity intensity array in a plurality of radioactivity distribution two-dimensional images; 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, comprising: calculating theoretical pixel signals of the volume element radioactivity intensity array in a plurality of radioactivity distribution two-dimensional images based on the initial volume element radioactivity intensity array; calculating a signal difference between the theoretical pixel signals and actual pixel signals; when the signal difference is less than or equal to a signal difference threshold, taking the initial volume element radioactivity intensity array as the volume element radioactivity intensity array; when the signal difference is greater than the signal difference threshold, adjusting the initial volume element radioactivity intensity array to obtain an adjusted volume element radioactivity intensity array, calculating a signal difference between the theoretical pixel signals and actual pixel signals of the adjusted volume element radioactivity intensity array, and judging whether the signal difference is greater than the signal difference threshold; if yes, repeatedly performing the above steps until the signal difference is less than or equal to the signal difference threshold, and taking the adjusted volume element radioactivity intensity array with the signal difference less than or equal to the signal difference threshold as the volume element radioactivity intensity array.

[0011] Optionally, the radioactivity distribution modeling result is obtained by combining the target three-dimensional space 3D model and the distribution image, comprising: aligning the target three-dimensional space 3D model and the spatial coordinates of the distribution image of the radioactivity in the target three-dimensional space; taking the radioactivity distribution data as an attribute layer of the target three-dimensional space 3D model, and attaching the radioactivity distribution data to a plurality of surfaces of the target three-dimensional space 3D model; obtaining the radioactivity intensity of all volume elements in the plurality of surfaces, and calculating the average value as the radioactivity activity value of the plurality of surfaces; taking the radioactivity activity of the plurality of surfaces as the attribute of the plurality of surfaces; coloring the plurality of surfaces based on the radioactivity activity value to form a heat map effect.

[0012] In a second aspect, the present application provides a radioactivity distribution modeling system combining multi-mode imaging and three-dimensional laser scanning, comprising:

[0013] The radioactive detection module is used for multi-angle detection of radioactive substances in a target three-dimensional space based on a radioactive detection device to obtain a two-dimensional image set of radioactive substance distribution;

[0014] The space modeling module is used for collecting three-dimensional point cloud data of the target three-dimensional space based on the laser scanning device, assembling the three-dimensional point cloud data, and constructing a target three-dimensional space 3D model.

[0015] The radioactive modeling module is used for restoring the distribution image of the radioactive substances in the target three-dimensional space based on the two-dimensional image set of the radioactive substance distribution by using a statistical reconstruction algorithm.

[0016] The modeling fusion module is used for combining the target three-dimensional space 3D model and the distribution image to obtain a three-dimensional distribution modeling result of the radioactive substances.

[0017] By implementing the present application, multi-angle detection of radioactive substances in a target three-dimensional space can be performed based on a radioactive detection device to obtain a two-dimensional image set of radioactive substance distribution, and more comprehensive radioactive substance distribution data can be obtained through multi-angle detection to avoid information loss that may exist in single-angle detection, thereby providing rich original data support for subsequent restoration of the distribution of radioactive substances in a three-dimensional space.

[0018] By implementing the present application, three-dimensional point cloud data of a target three-dimensional space can be collected based on a laser scanning device, the three-dimensional point cloud data can be assembled, and a target three-dimensional space 3D model can be constructed, thereby providing an accurate space carrier by combining the distribution image of the radioactive substances with the target three-dimensional space in the subsequent process, so that the distribution of the radioactive substances can be embodied in a specific space structure.

[0019] By implementing the present application, the distribution image of the radioactive substances in the target three-dimensional space can be restored based on the two-dimensional image set of the radioactive substance distribution by using a statistical reconstruction algorithm, so that the distribution of the radioactive substances in the three-dimensional space can be derived from the two-dimensional image through the statistical reconstruction algorithm, thereby realizing conversion from planar information to stereoscopic information.

[0020] By implementing the present application, the three-dimensional distribution modeling result of the radioactive substances can be obtained by combining the target three-dimensional space 3D model and the distribution image, so that the distribution information of the radioactive substances is combined with the geometric structure of the target three-dimensional space, the three-dimensional distribution of the radioactive substances can be displayed in a specific space model, and a heat map effect is formed through coloring or the like, thereby more intuitively presenting the radioactivity of different regions and facilitating intuitive display of the distribution of the radioactive substances.

[0021] In summary, by implementing the present application, high-precision three-dimensional distribution modeling of radioactive substances in a target three-dimensional space can be achieved, and the distribution of radioactive substances in the three-dimensional space can be intuitively and accurately displayed. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1 A flowchart of a radioactive distribution modeling method provided by the present application is shown in the figure.

[0023] Figure 2 A structure diagram of a radioactive distribution modeling system provided by the present application is shown in the figure.

[0024] In the drawings, the components represented by the respective reference numerals are as follows:

[0025] The radioactive detection module 11, the space modeling module 12, the radioactive modeling module 13, and the modeling fusion module 14. DETAILED DESCRIPTION

[0026] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0027] In the description of the present application, the terms “first” and “second” are used only for the purpose of description, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as “first” and “second” can explicitly or implicitly include one or more features. In the description of the present application, the meaning of “a plurality of” is two or more, unless otherwise specifically limited.

[0028] In the description of the present application, the term “for example” is used to indicate “as an example, illustration or explanation”. Any embodiment described as “for example” in the present application is not necessarily interpreted as more preferred or more advantageous than other embodiments. The following description is given in order to enable any person skilled in the art to implement and use the present application. In the following description, details are listed for the purpose of explanation. It should be understood that those skilled in the art can recognize that the present application can be implemented without using these specific details. In other examples, well-known structures and processes will not be described in detail in order to avoid unnecessary details making the description of the present application obscure. Therefore, the present application is not intended to be limited to the shown embodiments, but is consistent with the broadest scope of principles and features disclosed.

[0029] Embodiment one, as shown in Figure 1 The embodiment of the present application provides a radioactive distribution modeling method based on multi-mode imaging and three-dimensional laser scanning fusion, which comprises the following steps:

[0030] S100: based on a radioactive detection device, multi-angle detection of radioactive substances in a target three-dimensional space is performed to obtain a set of radioactive substance distribution two-dimensional images; S200: 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;

[0032] S300: based on the set of radioactive substance distribution two-dimensional images, a statistical reconstruction algorithm is used to restore the distribution image of radioactive substances in the target three-dimensional space;

[0033] S400: based on the 3D model of the target three-dimensional space and the distribution image, a radioactive substance three-dimensional distribution modeling result is obtained.

[0034] In step S100 of the embodiment, based on a radioactive detection device, multi-angle detection of radioactive substances in a target three-dimensional space is performed to obtain a set of radioactive substance distribution two-dimensional images. Specifically, a radioactive detection device with multi-angle detection capability is selected, for example, a gamma camera. According to the size and shape of the target three-dimensional space, the radioactive detection device 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 such as the four corners, top and bottom of the target space. After detection from each detection angle is completed, the corresponding radioactive substance distribution two-dimensional image is obtained. Since it is multi-angle detection, multiple two-dimensional images at different angles are obtained, which together constitute the set of radioactive substance distribution two-dimensional images.

[0035] The radioactive detection device can perceive the radiation (such as gamma rays) emitted by the radioactive substances and convert it into an electrical signal or an image signal.

[0036] When taking the radioactive substance distribution two-dimensional image, the shooting position of the radioactive detection device (such as a gamma camera), i.e. the coordinates (x, y, z) and the attitude (pitch angle, yaw angle, roll angle), needs to be recorded, so as to realize the conversion of the radioactive substance distribution two-dimensional image data in the coordinate system of the radioactive detection device into the 3D model of the target three-dimensional space obtained subsequently through the laser scanning device by coordinate transformation (translation, rotation).

[0037] For example, the target space is a rectangular hall with a size of 10m x 8m x 6m, and the shooting position markers can be as follows: shooting position A: left upper corner of the hall, coordinates (2, 0, 3) m, attitude is diagonal 45° (yaw angle 0°, pitch angle 0°).

[0038] In step S200 of the embodiment of the present application, based on the 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:

[0039] The target three-dimensional space is scanned based on a plurality of positions using the laser scanning device, and a plurality of sets of point cloud data of the target three-dimensional space are obtained;

[0040] Based on feature point matching, the aligned positions of the plurality of sets of point cloud data are obtained;

[0041] Based on the aligned positions, the plurality of sets of point cloud data are assembled into the 3D model of the target three-dimensional space.

[0042] In the embodiment of the present application, the point cloud data can be collected and obtained using a high-precision three-dimensional laser scanner (such as FARO Focus, Leica P series) or a mobile scanning device. Specifically, a suitable range (such as 50 meters for indoor scenes and more than 200 meters for outdoor scenes) can be selected according to the size of the target space to ensure that the point cloud density (such as 50 points per square meter) and the accuracy (such as ±2 mm) meet the modeling requirements.

[0043] For example, in an indoor scene, a three-dimensional laser scanner can be deployed at multiple positions such as the corners of a target three-dimensional space (such as a hall) and the intersections of corridors, and the adjacent scanning positions need to overlap 30% to 50% of the field of view to ensure that the feature points are repeatedly visible. The point cloud data scanned at each position is a set of point cloud data, and a plurality of sets of point cloud data are collected to obtain a plurality of sets of point cloud data of the target three-dimensional space.

[0044] For example, position A scanning obtains point cloud A (containing 100,000 three-dimensional points such as points (1, 2, 3) and (2, 3, 4)). Position B scanning obtains point cloud B (containing 80,000 points such as points (5, 6, 7) and (6, 7, 8)), and at this time, the two sets of point cloud data are spatially misaligned due to different positions.

[0045] Further, based on the feature point matching, the alignment position of the multiple sets of point cloud data is obtained. First, the feature points in the point cloud data need to be extracted. Specifically, the PCS software (such as CloudCompare, PCL library) can be used to preprocess each set of point cloud data; then the statistical outlier removal is used to remove the noise points and retain the real surface points; finally, the SIFT (scale-invariant feature transform), SURF (speeded up robust features) or ISS (iterative scale space) algorithm is used to extract the corner points, edge points or curvature mutation points (such as wall corners, column turning points) in the point cloud as the feature points. A multi-dimensional description vector (such as 3D-SIFT descriptor) is calculated for each feature point, which contains the spatial distribution of the neighborhood points, the curvature change and other information, and is used for cross-set point cloud feature matching.

[0046] Then, the same feature points (such as wall corners, column vertexes and other obvious geometric features) in different sets of point cloud data are matched by an algorithm to determine the alignment position of each set of point cloud data in space. According to the alignment position obtained by the feature point matching, for example, the feature points P1 (1, 2, 3) and P2 (3, 4, 5) are extracted from the point cloud A, and the feature points Q1 (5, 6, 7) and Q2 (7, 8, 9) are extracted from the point cloud B. It is found by algorithm calculation that after the point cloud B is translated by-4 along the X axis, -4 along the Y axis, -4 along the Z axis and rotated by 0 degrees, P1 and Q1, P2 and Q2 almost coincide, and at this time, the transformation is determined as the alignment position.

[0047] Based on the multiple alignment positions, the multiple sets of point cloud data are combined into the same coordinate system through coordinate transformation (translation, rotation, etc.) to finally assemble a complete target three-dimensional space 3D model.

[0048] In step S300 of the embodiment, based on the set of radioactive material distribution two-dimensional images, a statistical reconstruction algorithm is used to restore the distribution image of the radioactive material in the target three-dimensional space, including:

[0049] The target three-dimensional space to be reconstructed is uniformly divided into multiple volume elements, wherein each volume element can contain radioactive material, and the radioactive material emits radioactive rays;

[0050] The set of radioactive material distribution two-dimensional images is traversed to calculate the multiple signal contribution degrees of the radioactive rays of each volume element containing radioactive material to different pixel regions in the multiple radioactive material distribution two-dimensional images;

[0051] Based on the multiple signal contribution degrees, the multiple initial volume element radioactive intensities of the multiple volume elements are calculated to construct an initial volume element radioactive intensity array;

[0052] calculating theoretical pixel signals of the initial volume element radioactivity intensity array in a plurality of radioactivity distribution two-dimensional images, iteratively optimizing the initial volume element radioactivity intensity array based on a difference between the theoretical pixel signals and actual pixel signals, and obtaining a volume element radioactivity intensity array;

[0053] converting the volume element radioactivity intensity array into a distribution image of the radioactive material in the target three-dimensional space.

[0054] In the embodiment, the target three-dimensional space is uniformly divided into a plurality of volume elements, and first, the boundary of the target three-dimensional space is defined. For example, if the target space is a room with a size of 10 m x 8 m x 5 m, the boundary coordinates can be defined as x ∈ [0, 10], y ∈ [0, 8], and z ∈ [0, 5].

[0055] Next, the target three-dimensional space is uniformly divided into a plurality of volume elements. For example, the length of each volume element (for example, 0.1 m) can be set, and the space is equally divided along the x, y, and z axes, so that each volume element is a cube. The spatial coordinates of each volume element are taken as the lower left corner of the vertex, and a unique index (for example, i, j, and k) is assigned for subsequent processing.

[0056] In step S300 of the embodiment, the set of radioactivity distribution two-dimensional images is traversed, and the signal contribution degree of the radioactive rays of each volume element containing radioactive material to different pixel regions in a plurality of radioactivity distribution two-dimensional images is calculated. The radioactive rays emitted by each volume element containing radioactive material pass through the encoding plate of the radioactive detection device to form the radioactivity distribution two-dimensional image. The radioactivity distribution two-dimensional image contains a plurality of pixel regions and is affected by the received radioactivity signal intensity, and includes the following aspects.

[0057] Based on the radioactivity ray intensity received by different pixel regions in the radioactivity distribution two-dimensional image, the signal contribution degree of each volume element containing radioactive material to the radioactivity ray intensity of the pixel regions of the plurality of radioactivity distribution two-dimensional images is simulated and calculated.

[0058] Based on the signal contribution degree of the volume element to the radioactivity ray intensity of the pixel regions of different radioactivity distribution two-dimensional images and the radioactivity ray intensity received by different pixel regions in the radioactivity distribution two-dimensional image, the signal contribution degree of the radioactive rays of each volume element to the pixel regions of the radioactivity distribution two-dimensional image is calculated and obtained.

[0059] In the embodiments of the present application, the pixel region is a local region composed of multiple pixels in a two-dimensional image or a minimum unit of a single pixel, used to record the intensity of radioactive rays. Assuming that the two-dimensional image generated by the radioactive detection device is 100x100 pixels, each pixel size is 1mmx1mm, and if one pixel is defined as a pixel region, then in this example, the pixel region is a 1mmx1mm square region.

[0060] The signal intensity of the pixel region is the intensity value of the radioactive rays received by the pixel region, which is usually expressed in count rate (such as counts per second, cps) or energy value, and the larger the value, the more rays the region receives. If a certain pixel region receives 200 gamma ray photons in 1 second, its signal intensity is 200cps.

[0061] In the embodiments of the present application, the two-dimensional image obtained by the radioactive detection device (such as a gamma camera) is essentially the superimposed result of the rays emitted by each volume element in a three-dimensional space after being projected by the encoding plate. The signal intensity of each pixel region is a comprehensive reflection of the contribution of all volume elements. By mathematical modeling to decompose this superimposed relationship, the individual signal contribution of each volume element to each pixel can be deduced.

[0062] For example, the calculation principle is that assuming that a certain volume element V has radioactive material alone and other volume elements have no radioactivity. The radioactive rays emitted by the volume element V diffuse in all directions and pass through the encoding plate (such as a collimator, an encoding aperture) of the radioactive detection device; then the rays are modulated (such as blocked, deflected) by the encoding plate, so that the rays can only reach the detector at a specific angle, forming a signal of a specific pixel region in the two-dimensional image, i.e., individual signal contribution.

[0063] In the above-mentioned assumption that a certain volume element V has radioactive material alone and other volume elements have no radioactivity, in the specific operation, the rays can only pass through a specific hole to reach the radioactive detector when passing through the encoding plate, forming a pixel signal in the two-dimensional image. For example, the position of the volume element V is aligned with the encoding plate hole P1, and the rays can pass through the hole P1 to produce a signal at the two-dimensional image pixel P1'; and other holes block the rays due to angle deviation, and there is no signal in the corresponding pixel.

[0064] 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 rays alone and the radioactive ray intensity is 1 Bq, the intensity received by P is 100 cps, which is recorded as the individual contribution of V1 to P, that is, 100 cps / Bq (1 Bq of V1 produces 100 cps at P).

[0065] If the radioactive ray intensity of V1 is 2 Bq and V2 is off (i.e., the radioactive ray intensity = 0), the individual signal contribution of V1 to P is 100 cps / Bq x 2 Bq = 200 cps. If the radioactive ray intensity of V2 is 3 Bq and V1 is off, the individual signal contribution of V2 to P is 50 cps / Bq x 3 Bq = 150 cps.

[0066] The individual signal contribution represents the signal contribution of each volume element when it "acts alone" on the pixel area, and is a basic parameter for subsequent back-calculation of the actual radioactive intensity of the volume element. Through the above method, the individual signal contribution of each volume element containing radioactive material to the radioactive ray intensity of each pixel area of the radioactive material distribution two-dimensional image can be obtained.

[0067] The radioactive ray intensity (Bq) is the rate of nuclear decay, which is determined by the nature of the radioactive material itself, and its acquisition method is prior art, which will not be described here.

[0068] Further, based on the individual signal contribution of the volume element to the radioactive ray intensity of the pixel area of the different radioactive material distribution two-dimensional image, and the radioactive ray intensity received by the different pixel area of the radioactive material distribution two-dimensional image, the signal contribution of the radioactive ray of each volume element to the pixel area of the radioactive material distribution two-dimensional image is calculated and obtained.

[0069] Based on the foregoing case, assume that the individual signal contribution of V1 to P is 100 cps / Bq, and the individual signal contribution of V2 to P is 50 cps / Bq. The measured signal intensity is 350 cps. Assume that the radioactive ray intensity of V1 and V2 is 1 Bq, and the initial radioactive intensity of all volume elements is 1 Bq.

[0070] The signal contribution of V1 to P is 1 Bq x 100 cps / Bq = 100 cps (i.e., the contribution of V1 to P1 is 100 cps when the radioactive ray intensity of V1 is 1 Bq).

[0071] The signal contribution degree of V2 to P = 1Bq x 50cps / Bq = 50cps (i.e. assuming that the radioactive ray intensity of V2 is 1Bq, the contribution to P1 is 50cps).

[0072] Through the above method, the signal contribution degree of the radioactive ray of each volume element to the pixel area of the radioactivity distribution two-dimensional image can be calculated and obtained.

[0073] Further, based on the plurality of signal contribution degrees, the plurality of initial volume element radioactive intensities of the plurality of volume elements are calculated to construct an initial volume element radioactive intensity array.

[0074] Specifically, it can be assumed that the initial radioactive intensities of all volume elements are the same (such as 1Bq), or the initial values are set according to prior knowledge (such as the distribution rule of radioactive substances), and the initial radioactive intensities of all volume elements are arranged according to the spatial coordinates to form an initial volume element radioactive intensity array (such as a three-dimensional matrix).

[0075] In step S300 of the embodiment of the present application, the theoretical pixel signals of the initial volume element radioactive intensity array in the plurality of radioactivity distribution two-dimensional images are calculated, and based on the difference 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, including:

[0076] Based on the initial volume element radioactive intensity array, the theoretical pixel signals of the volume element radioactive intensity array in the plurality of radioactivity distribution two-dimensional images are calculated.

[0077] The signal difference between the theoretical pixel signals and the actual pixel signals is calculated.

[0078] When the signal difference is less than or equal to the signal difference threshold, the initial volume element radioactive intensity array is taken as the volume element radioactive intensity array.

[0079] When the signal difference is greater than the signal difference threshold, the initial volume element radioactive intensity array is adjusted to obtain an adjusted volume element radioactive intensity array, and the signal difference between the theoretical pixel signals and the actual pixel signals of the adjusted volume element radioactive intensity array is calculated to determine whether it is greater than the signal difference threshold. If yes, the above steps are repeatedly continued until the signal difference is less than or equal to the signal difference threshold, and the adjusted volume element radioactive intensity array with the signal difference less than or equal to the signal difference threshold is taken as the volume element radioactive intensity array.

[0080] In the embodiment of the present application, the theoretical pixel signal refers to the radioactive ray intensity of each pixel region in the two-dimensional image obtained by calculation based on the initial element radioactive intensity array. The theoretical pixel signal represents the signal intensity that the detector should receive if the volume element radioactive intensity is distributed according to the current array, and reflects the mathematical mapping relationship between the radioactive material distribution and the detector imaging.

[0081] Through the foregoing steps, the initial volume element radioactive intensity array and the individual signal contribution of each volume element to each pixel region have been obtained. Therefore, the calculation method of the theoretical pixel signal can be as follows: theoretical pixel signal = ∑ (volume element radioactive intensity × individual contribution of the volume element to the pixel region).

[0082] For example, if the volume element radioactive ray intensity V1 is radioactive ray intensity 1 Bq, the individual contribution of the pixel region radioactive ray intensity P1 to the pixel region is radioactive ray intensity 100 cps / Bq, then the signal contribution of the volume element radioactive ray intensity V1 to the pixel region radioactive ray intensity P1 is radioactive ray intensity 2 × 100 = 200 cps.

[0083] The volume element radioactive ray intensity V2 is radioactive ray intensity 3 Bq, and the individual contribution of the pixel region radioactive ray intensity P1 to the pixel region is radioactive ray intensity 50 cps / Bq. Therefore, the signal contribution of the volume element radioactive ray intensity V2 to the pixel region radioactive ray intensity P1 is radioactive ray intensity 3 × 50 = 150 cps.

[0084] Therefore, the theoretical pixel signal of the pixel region radioactive ray intensity P1 is radioactive ray intensity 200 + 150 = 350 cps.

[0085] Through the foregoing method, the theoretical pixel signal of the volume element radioactive intensity array in multiple radioactive material distribution two-dimensional images can be calculated.

[0086] In step S300 of the embodiment of the present application, the signal difference between the theoretical pixel signal and the actual pixel signal is calculated, including:

[0087] The plurality of difference values between each theoretical pixel signal in the first two-dimensional image and each corresponding actual pixel signal are calculated. After removing outliers, a plurality of first difference values are obtained, and the average value of the plurality of first difference values is calculated.

[0088] obtaining a maximum value of the plurality of first difference values, calculating a first correction coefficient based on the maximum value of the first difference values;

[0089] multiplying the first difference average value by the first correction coefficient to obtain a first signal gap;

[0090] calculating a plurality of first signal gaps of a plurality of two-dimensional images in the set of two-dimensional images of the radioactive substance distribution, obtaining the signal gap by calculating an average value of the plurality of first signal gaps.

[0091] In the embodiments of the present application, the actual pixel signal refers to the radioactive ray intensity of each pixel region in the two-dimensional image directly collected by the radiation detection device through the detector, and the unit is usually counts of radioactive ray intensity / second of radioactive ray intensity (cps). Specifically, the electric signal generated on the detector after the radioactive ray emitted by the radioactive substance passes through the encoding plate is converted to form a pixel value, reflecting the ray count rate (cps) received by the region, which can be directly obtained from the radiation detection device.

[0092] Then, for each pixel region in the first two-dimensional image, the first difference value between the theoretical pixel signal and the actual pixel signal needs to be calculated to obtain a plurality of first difference values. The calculation method is first difference value = theoretical pixel signal - actual pixel signal, and a plurality of first difference values can be calculated by the above method.

[0093] Further, the average value of the plurality of first difference values, the maximum value of the plurality of first difference values, the first correction coefficient and the first signal gap also need to be calculated.

[0094] Suppose that a first two-dimensional image has 5 pixel regions with radioactive ray intensity, and the difference values between the theoretical pixel signal and the actual pixel signal are [2, 4, 10, 3, 20] respectively. Eliminating outliers (outliers are extreme large or small values that deviate significantly from the general level, and suppose that the radioactive ray intensity 20 is an outlier), then [2, 4, 10, 3] are retained. Calculation can obtain that the first difference average value is (2+4+10+3) / 4=4.75cps, the first difference maximum value is 10cps, the first correction coefficient can be the ratio of the first difference maximum value to the first difference average value, i.e. 10 / 4.75≈2.105cps, and the first signal gap is 4.75×2.105≈10cps.

[0095] Further, if there are three radioactive ray intensities 3, 10, 8, 12, and the first signal difference is 10 cps, 8 cps, 12 cps, respectively, then the signal difference is (10+8+12) / 3=10 cps.

[0096] By the above method, the signal difference between the theoretical pixel signal and the actual pixel signal can be calculated.

[0097] When the signal difference is less than or equal to the signal difference threshold, the initial volume element radioactive intensity array is taken as the volume element radioactive intensity array.

[0098] When the signal difference is greater than the signal difference threshold, the initial volume element radioactive intensity array is adjusted to obtain an adjusted volume element radioactive intensity array, and the signal difference between the theoretical pixel signal and the actual pixel signal is calculated. If it is greater than the signal difference threshold, the above steps are repeated until the signal difference is less than or equal to the signal difference threshold. The adjusted volume element radioactive intensity array with the signal difference less than or equal to the signal difference threshold is taken as the volume element radioactive intensity array.

[0099] In the embodiments of the present application, when the signal difference is less than or equal to the signal difference threshold, it indicates that the theoretical pixel signal and the measured pixel signal are close enough, and the initial volume element radioactive intensity array meets the requirements and is directly used. When the signal difference is greater than the signal difference threshold, it indicates that the theoretical pixel signal and the measured pixel signal have a large difference, and the volume element radioactive intensity array needs to be adjusted, and the signal difference is recalculated until the signal difference threshold is met. The signal difference threshold can be determined according to the actual modeling requirements, for example, it can be set to 10 cps.

[0100] The specific adjustment method can be to adjust the volume element intensity in proportion to the signal difference. For example, if the original radioactive 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 difference=100 cps), then the adjustment coefficient=100 / 200=0.5, the adjustment amplitude of the radioactive intensity=10×0.5=5 Bq, that is, the adjusted radioactive intensity is 10-5=5 Bq, or 10+5=15 Bq, and one direction is selected. If the signal difference becomes larger after adjustment, then adjust in the opposite direction.

[0101] The specific adjustment process can be, for example, in the above example, assuming that the signal difference gap radioactive ray intensity = radioactive ray intensity 50 radioactive ray intensity cps, the threshold radioactive ray intensity = radioactive ray intensity 10 radioactive ray intensity cps, the difference radioactive ray intensity > radioactive ray intensity threshold, adjustment is required, the adjustment method can be to adjust the radioactive intensity of the estimated volume element radioactive ray intensity V1 from radioactive ray intensity 2 radioactive ray intensity Bq to 3 radioactive ray intensity Bq, and the radioactive intensity of V2 from radioactive ray intensity 3 radioactive ray intensity Bq to 2.5 radioactive ray intensity Bq. Then, the signal difference is recalculated, such as signal difference radioactive ray intensity = radioactive ray intensity 15 radioactive ray intensity cps, which is still greater than the threshold, and the adjustment is continued, V1 radioactive ray intensity is adjusted to 3.5 radioactive ray intensity Bq, and V2 is adjusted to 2.8 radioactive ray intensity Bq, and the signal difference is recalculated, such as signal difference radioactive ray intensity = radioactive ray intensity 8 radioactive ray intensity cps, which is less than the threshold, and the adjusted radioactive intensity array is used as the volume element radioactive intensity array.

[0102] In step S400 of the embodiment of the present application, the radioactive material three-dimensional distribution modeling result is obtained by combining the target three-dimensional space 3D model and the distribution image, including:

[0103] 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;

[0104] Attaching the radioactive distribution data to the plurality of faces of the target three-dimensional space 3D model as an attribute layer of the target three-dimensional space 3D model;

[0105] Obtaining the radioactive intensity of all volume elements in the plurality of faces and calculating the mean value as the radioactive activity value of the plurality of faces;

[0106] Taking the radioactive activity of the plurality of faces as the attribute of the plurality of faces;

[0107] Coloring the plurality of faces based on the radioactive activity value of the plurality of faces to form a heat map effect.

[0108] In the embodiment of the present application, 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 is to align the coordinate system of the target three-dimensional space 3D model constructed by laser scanning with the coordinate system of the radioactive distribution image, specifically, taking the origin of the three-dimensional laser scanner as the reference, rotating and translating the radioactive distribution image to make the positions of feature points such as wall corners and columns of the two coincide.

[0109] At least three common feature points (such as a wall corner, a pipe interface) 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, and finally the coordinate information of all volume elements of the radioactive material distribution image is converted into the coordinates in the 3D model of the target three-dimensional space.

[0110] Then, the radioactive distribution data needs to be taken as an attribute layer of the 3D model of the target three-dimensional space, and the radioactive distribution data is attached to multiple surfaces of the 3D model of the target three-dimensional space, that is, the wall surface area in the 3D model of the target three-dimensional space is made to correspond to the volume element set in the distribution image, and the radioactive intensity of the volume element is given to the wall surface.

[0111] Further, all volume elements in each surface of the 3D model of the target three-dimensional space need to be extracted, and the average value of the radioactive intensity of these volume elements is calculated as the activity value (such as Bq / square meter) of the surface, for example, a certain wall surface contains 100 volume elements, the total intensity is 200 Bq, and the average value is 200÷100=2 Bq / square meter. Then the radioactive activity value of each surface is recorded as its attribute parameter, for example, the attribute of wall surface A is "radioactive activity=2 Bq / square meter", and the attribute of wall surface B is "1.5 Bq / square meter".

[0112] Finally, the surfaces of the 3D model of the target three-dimensional space can be color-coded according to the activity value, for example, high activity (such as >5 Bq) is marked as red; medium activity (2-5 Bq) is marked as yellow, and low activity (<2 Bq) is marked as blue. The finally generated surface of the 3D model of the target three-dimensional space presents a heat map effect, which can directly display the radioactive distribution strength. As shown in Figure 2 Based on the same inventive concept of the radioactive distribution modeling method provided in embodiment one, the present embodiment also provides a radioactive distribution modeling system based on multi-mode imaging and three-dimensional laser scanning, which comprises:

[0113] The radioactive detection module 11 is configured to perform multi-angle detection on the radioactive material in the target three-dimensional space based on a radioactive detection device, and obtain a set of radioactive material distribution two-dimensional images.

[0114] The space modeling module 12 is configured 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.

[0115] The radioactive modeling module 13 is configured to restore a distribution image of the radioactive material in the target three-dimensional space based on the set of radioactive material distribution two-dimensional images by using a statistical reconstruction algorithm.

[0116] The modeling fusion module 14 is configured to combine the target three-dimensional space 3D model and the distribution image to obtain a radioactive material three-dimensional distribution modeling result.

[0117] Further, the space modeling module 12 includes the following steps: using the laser scanning device to scan the target three-dimensional space at multiple positions to obtain multiple sets of point cloud data of the target three-dimensional space; obtaining the alignment positions of the multiple sets of point cloud data based on feature point matching; and assembling the multiple sets of point cloud data into the target three-dimensional space 3D model based on the alignment positions.

[0118] Further, the radioactive modeling module 13 includes the following steps:

[0119] The target three-dimensional space to be reconstructed is uniformly divided into multiple volume elements, each of which may contain radioactive material that emits radioactive rays; the set of radioactive material distribution two-dimensional images is traversed, and the signal contribution of the radioactive rays of each volume element containing radioactive material to different pixel regions in the multiple radioactive material distribution two-dimensional images is calculated; based on the multiple signal contributions, the multiple initial volume element radioactive intensities of the multiple volume elements are calculated to construct an initial volume element radioactive intensity array; the theoretical pixel signals of the initial volume element radioactive intensity array in the multiple radioactive material distribution two-dimensional images are calculated, and the initial volume element radioactive intensity array is iteratively optimized based on the difference between the theoretical pixel signals and the actual pixel signals to obtain a volume element radioactive intensity array; and the volume element radioactive intensity array is converted into a distribution image of the radioactive material in the target three-dimensional space.

[0120] The set of radioactive material distribution two-dimensional images is traversed, and the signal contribution of the radioactive rays of each volume element containing radioactive material to different pixel regions in the multiple radioactive material distribution two-dimensional images is calculated, the radioactive material distribution two-dimensional image is formed by the radioactive rays emitted by each volume element containing radioactive material after passing through the encoding plate of the radioactive detection device, the radioactive material distribution two-dimensional image contains multiple pixel regions and is affected by the received radioactive signal intensity, and includes:

[0121] Based on the radioactive ray intensity received by different pixel regions in the radioactive material distribution two-dimensional image, the individual signal contribution of each volume element containing radioactive material to the radioactive ray intensity of the multiple pixel regions of the multiple radioactive material distribution two-dimensional images is simulated and calculated; and based on the individual signal contribution of the volume element to the pixel region radioactive ray intensity of different radioactive material distribution two-dimensional images and the radioactive ray intensity received by different pixel regions in the radioactive material distribution two-dimensional image, the signal contribution of the radioactive rays of each volume element to the pixel regions of the radioactive material distribution two-dimensional image is calculated and obtained.

[0122] The method comprises: calculating theoretical pixel signals of an initial volume element radioactivity intensity array in a plurality of radioactivity distribution two-dimensional images; 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, comprising:

[0123] The method comprises: calculating theoretical pixel signals of an initial volume element radioactivity intensity array in a plurality of radioactivity distribution two-dimensional images; 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, comprising:

[0124] The method comprises: calculating theoretical pixel signals of an initial volume element radioactivity intensity array in a plurality of radioactivity distribution two-dimensional images; 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, comprising:

[0125] The method comprises: calculating theoretical pixel signals of an initial volume element radioactivity intensity array in a plurality of radioactivity distribution two-dimensional images; 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, comprising:

[0126] Further, the modeling fusion module 14 comprises the following execution steps:

[0127] 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; taking the radioactive distribution data as an attribute layer of the target three-dimensional space 3D model, and attaching the radioactive distribution data to a plurality of surfaces of the target three-dimensional space 3D model; obtaining the radioactivity intensity of all volume elements in the plurality of surfaces and calculating the average value thereof as the radioactivity value of the plurality of surfaces; taking the radioactivity of the plurality of surfaces as the attribute of the plurality of surfaces; coloring the plurality of surfaces of the target three-dimensional space 3D model based on the radioactivity value of the plurality of surfaces to form a heat map effect.

[0128] It should be noted that in the above embodiments, the description of each embodiment focuses on different aspects, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments.

[0129] Those skilled in the art will appreciate that embodiments of the application can be a method, a system or a computer program product. Accordingly, the application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the application can take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage devices, etc.) embodying computer-readable program code.

[0130] The application is described with reference to flowcharts and / or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It should be understood that each flow and / or block 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 apparatus to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing apparatus produce a device that implements the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more functions specified in the flowchart and / or block diagram. Figure 1 one or more functions specified in the flowchart and / or block diagram.

[0131] These computer program instructions can also be stored in a computer-readable memory that can direct the computer or other programmable data processing apparatus to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including instruction devices that implement the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more functions specified in the flowchart and / or block diagram. Figure 1 one or more functions specified in the flowchart and / or block diagram.

[0132] These computer program instructions can also be loaded into a computer or other programmable data processing apparatus, so that a series of operation steps are performed on the computer or other programmable data processing apparatus to produce a computer-implemented process, so that the instructions executed on the computer or other programmable data processing apparatus provide a process for implementing the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more functions specified in the flowchart and / or block diagram. Figure 1 one or more functions specified in the flowchart and / or block diagram.

[0133] Although the preferred embodiments of the application have been described, those skilled in the art can make additional changes and modifications to the embodiments once they know the basic inventive concept.

[0134] It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the spirit or scope of the application. Thus, it is intended that the present application cover modifications and variations of this application provided they come within the scope of the application and their equivalent technology.

Claims

1. A method of radioactivity distribution modeling by fusion of multi-modal imaging and three-dimensional laser scanning, characterized in that, The method comprises: Based on the radioactive detection device, the radioactive material in the target three-dimensional space is detected at multiple angles to obtain a set of radioactive material distribution two-dimensional images; Based on the 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; Based on the set of radioactive material distribution two-dimensional images, a statistical reconstruction algorithm is used 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, a radioactive material three-dimensional distribution modeling result is obtained by combination; Wherein, based on the set of radioactive material distribution two-dimensional images, a statistical reconstruction algorithm is used to restore the distribution image of the radioactive material in the target three-dimensional space, comprising: The target three-dimensional space to be reconstructed is uniformly divided into a plurality of volume elements, wherein each volume element contains radioactive material, and the radioactive material emits radioactive rays; Iterate through the set of radioactive material distribution two-dimensional images to calculate the signal contribution of the radioactive rays of each volume element containing radioactive material to different pixel regions in multiple radioactive material distribution two-dimensional images; Based on the multiple signal contributions, the initial volume element radioactive intensity of the multiple volume elements is calculated to construct an initial volume element radioactive intensity array; The theoretical pixel signal of the initial volume element radioactive intensity array in the multiple radioactive material distribution two-dimensional images is calculated, and the initial volume element radioactive intensity array is iteratively optimized based on the difference between the theoretical pixel signal and the actual pixel signal 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; Wherein, iterating through the set of radioactive material distribution two-dimensional images to calculate the signal contribution of the radioactive rays of each volume element containing radioactive material to different pixel regions in multiple radioactive material distribution two-dimensional images, the radioactive material distribution two-dimensional image is formed by the radioactive rays emitted by each volume element containing radioactive material after passing through the encoding plate of the radioactive detection device, the radioactive material distribution two-dimensional image contains multiple pixel regions, and is affected by the received radioactive signal intensity, comprising: Based on the radioactive ray intensity received by different pixel regions in the radioactive material distribution two-dimensional image, the individual signal contribution of each volume element containing radioactive material to the radioactive ray intensity of multiple pixel regions in multiple radioactive material distribution two-dimensional images is simulated and calculated; Based on the individual signal contribution of the volume element to the pixel region radioactive ray intensity of different radioactive material distribution two-dimensional images and the radioactive ray intensity received by different pixel regions in the radioactive material distribution two-dimensional image, the signal contribution of the radioactive rays of each volume element to the pixel region of the radioactive material distribution two-dimensional image is calculated.

2. The multi-modal imaging and three-dimensional laser scanning fused radioactivity distribution modeling method of claim 1, wherein, Based on the 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, comprising: 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; Aligning positions of the multiple sets of point cloud data based on feature point matching; Assembling the multiple sets of point cloud data into the target three-dimensional space 3D model based on the aligning positions.

3. The multi-modal imaging and three-dimensional laser scanning fused radioactivity distribution modeling method of claim 1, wherein, Calculating theoretical pixel signals of an initial volume element radioactivity intensity array in multiple radioactivity distribution two-dimensional images, iteratively optimizing the initial volume element radioactivity intensity array based on a difference between the theoretical pixel signals and actual pixel signals, and obtaining a volume element radioactivity intensity array, including: Calculating theoretical pixel signals of the initial volume element radioactivity intensity array in the multiple radioactivity distribution two-dimensional images; Calculating a signal difference between the theoretical pixel signals and the actual pixel signals; When the signal difference is less than or equal to a signal difference threshold, taking the initial volume element radioactivity intensity array as the volume element radioactivity intensity array; When the signal difference is greater than the signal difference threshold, adjusting the initial volume element radioactivity intensity array to obtain an adjusted volume element radioactivity intensity array, calculating a signal difference between theoretical pixel signals of the adjusted volume element radioactivity intensity array and actual pixel signals, and judging whether the signal difference is greater than the signal difference threshold, if yes, continuing to repeat the above steps until the signal difference is less than or equal to the signal difference threshold, and taking the adjusted volume element radioactivity intensity array with the signal difference less than or equal to the signal difference threshold as the volume element radioactivity intensity array.

4. The multi-modal imaging and three-dimensional laser scanning fused radioactivity distribution modeling method of claim 3, wherein, Calculating the signal difference between the theoretical pixel signals and the actual pixel signals, including: Calculating multiple difference values of each theoretical pixel signal in a first two-dimensional image and each corresponding actual pixel signal, obtaining multiple first difference values after removing outliers, and calculating an average value of the multiple first difference values; Obtaining a maximum value of the multiple first difference values, calculating a first correction coefficient based on the maximum value of the first difference values; Multiplying the first difference average value by the first correction coefficient to obtain a first signal difference; Calculating multiple first signal differences of the multiple two-dimensional images in the set of radioactivity distribution two-dimensional images, calculating an average value of the multiple first signal differences to obtain the signal difference.

5. The multi-modal imaging and three-dimensional laser scanning fused radioactivity distribution modeling method of claim 1, wherein, Based on the target three-dimensional space 3D model and the distribution image, combining to obtain a radioactivity substance three-dimensional distribution modeling result, including: Aligning spatial coordinates of the target three-dimensional space 3D model and the distribution image of the radioactivity substance in the target three-dimensional space; Taking the radioactivity distribution data as an attribute layer of the target three-dimensional space 3D model, and attaching the radioactivity distribution data to multiple surfaces of the target three-dimensional space 3D model; Obtaining radioactivity intensities of all volume elements in the multiple surfaces, and calculating an average value of the radioactivity intensities as a radioactivity activity value of the multiple surfaces; Taking the radioactivity activity of the multiple surfaces as an attribute of the multiple surfaces; Coloring the multiple surfaces of the target three-dimensional space 3D model based on the radioactivity activity values of the multiple surfaces to form a heat map effect.

6. A multi-modal imaging and three-dimensional laser scanning fused radioactive distribution modeling system, characterized in that, The system includes: A radioactivity detection module configured to detect radioactivity of a target three-dimensional space from multiple angles based on a radioactivity detection device, and obtain a set of radioactivity distribution two-dimensional images. The spatial modeling module is used to collect three-dimensional point cloud data of the target three-dimensional space based on laser scanning equipment, assemble the three-dimensional point cloud data, and construct a 3D model of the target three-dimensional space. The radioactivity modeling module is used to reconstruct the distribution image of the radioactive material in the target three-dimensional space based on the set of two-dimensional images of the radioactive material distribution and using a statistical reconstruction algorithm. The modeling and fusion module is used to combine the target three-dimensional spatial 3D model and the distribution image to obtain the three-dimensional distribution modeling result of radioactive materials; Specifically, based on the set of two-dimensional images of radioactive material distribution, a statistical reconstruction algorithm is used to reconstruct the distribution image of radioactive material in the target three-dimensional space, including: The three-dimensional space of the target to be reconstructed is uniformly divided into multiple volume elements, each of which contains radioactive material that emits radioactive rays. Traverse the set of two-dimensional images of radioactive material distribution and calculate the contribution of radioactive rays of each volume element containing radioactive material to multiple signals in different pixel regions of multiple two-dimensional images of radioactive material distribution. Based on the contribution of the multiple signals, the radioactivity intensity of multiple initial volume elements of multiple volume elements is calculated, and an array of initial volume element radioactivity intensities is constructed. Calculate the theoretical pixel signal of the initial volume element radioactivity intensity array in multiple two-dimensional images of radioactive material distribution. Based on the difference between the theoretical pixel signal and the actual pixel signal, iteratively optimize the initial volume element radioactivity intensity array to obtain the volume element radioactivity intensity array. The array of radioactive intensity of the volume elements is converted into a distribution image of radioactive material in the three-dimensional space of the target. Specifically, the set of two-dimensional images of radioactive material distribution is traversed, and the contribution of radioactive rays from each volume element containing radioactive material to multiple signal regions in different pixel areas of the multiple two-dimensional images of radioactive material distribution is calculated. The two-dimensional images of radioactive material distribution are formed by radioactive rays emitted from each volume element containing radioactive material, passing through the encoding plate of the radioactive detection device. Each two-dimensional image of radioactive material distribution contains multiple pixel regions and is affected by the intensity of the received radioactive signal, including: Based on the intensity of radioactive rays received in different pixel regions of a two-dimensional image of radioactive material distribution, the individual signal contribution of each volume element containing radioactive material to the intensity of radioactive rays in multiple pixel regions of multiple two-dimensional images of radioactive material distribution is simulated and calculated. Based on the individual signal contribution of volume elements to the intensity of radioactive rays in pixel regions of two-dimensional images of radioactive material distribution, and the intensity of radioactive rays received in different pixel regions of two-dimensional images of radioactive material distribution, the signal contribution of radioactive rays of each volume element to the pixel regions of two-dimensional images of radioactive material distribution is calculated.

Images