CN114001707B - Method for measuring depth of radiation hotspot based on four-eye coding gamma camera - Google Patents
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Abstract
The invention discloses a method for measuring the depth of a radiation hotspot based on a four-eye coding gamma camera, which comprises the following steps: 1) four projection data are obtained through a four-eye encoding gamma camera, and four reconstructed images are obtained after the four projection data are subjected to bilinear interpolation; 2) respectively determining the sub-pixel coordinates of a radiation hotspot according to each reconstructed image; 3) connecting and extending the vertex of each camera in the four-eye encoding gamma camera with the position of a radiation hot spot in a reconstructed image corresponding to the camera to obtain four straight lines in space; connecting coordinate points on four straight lines at different depths to form a quadrangle, calculating the area of the quadrangle, and carrying out parabolic fitting on the changes of the areas of the quadrangle at different depths; and taking the depth corresponding to the vertex of the parabola obtained by fitting as the distance from the radiation hot spot to the detector. The invention improves the range and precision of distance measurement and reduces the measurement error.
Description
Technical Field
The invention belongs to the field of nuclear safety and the field of nuclear radiation imaging, relates to measurement of radiation hotspot distances by a four-eye coding gamma camera, and particularly relates to a method for performing depth measurement on radiation hotspots based on the four-eye coding gamma camera.
Background
The coded aperture gamma camera provides relevant gamma ray information through interaction of gamma rays and coded aperture equipment and analyzes and processes the gamma ray information, so that the position or intensity information of a gamma ray source in the environment is displayed in a numerical value or two-dimensional image mode, the coded aperture gamma camera has high detection efficiency, high sensitivity and high position resolution, and is widely applied to the fields of aerospace, nuclear power, security and the like.
The coded aperture gamma camera adopts a code plate with a specific coding mode to code and modulate gamma rays generated by radioactive nuclides, a rear-end detector records the modulated projection count, the structure and the azimuth information of a measured object are displayed in a 'photographing' mode by utilizing a decoding reconstruction algorithm, and then the structure and the azimuth information are fused with an optical image to visually and accurately display the position of a radiation hot spot so as to achieve the detection purpose.
The imaging system provides a 2D (two-dimensional) radiation image that, although fused with an optical image of the corresponding environment, lacks depth information and cannot determine the exact location of the source in the actual environment (e.g., inside or behind the box, in front of or behind a wall). If the depth information of the source distance detector can be obtained, the specific position of the radioactive source in the surrounding environment can be accurately judged, so that the method has important significance in the fields of radiation environment monitoring, unknown radioactive substance detection, searching and the like.
The invention provides a radioactive point source distance measuring method which can realize high distance measuring range and high distance measuring precision under the equipment conditions of low resolution and low distance.
At present, the method for measuring the distance of a radiation hotspot based on a gamma camera uses the principle of binocular camera distance measurement in optics for reference, and estimates the distance between a radioactive source and the gamma camera by calibrating the position coordinates of the two gamma cameras and utilizing the parallax of the radioactive source on the reconstructed images of the left and right gamma cameras and a triangulation method.
Takeuchi et al in the article "Stereo Compton cameras" for the 3-D localization of radioisotopes "achieves the determination of the radiation source position within an accuracy of 2 meters by simulating the distance measurement of the radiation hot spot by triangulation based on two scintillator Compton cameras, by calibrating two Compton cameras at a distance of about 10 m.
Paradiso et al in article "3-D localTriangulation method is used to estimate the distance between the radiation source and the gamma camera based on two iPIX semiconductor code cameras in the animation of radioactive targets via gamma cameras, and the CMOS ASIC of the triangulation method is composed of 256 × 256 pixels with a side length of 55 μm, providing 14 × 14mm2The global detection area of (2). The distance measurement precision is higher, but the measurement range is shorter, and is generally within 4 meters.
In the above-described radiation source distance measurement, there are several problems as follows:
(1) and (4) selecting a detector. In the fields of detection, search and the like of unknown radioactive substances in radiation environment detection, the position of a radioactive source is generally required to be positioned with higher precision within a larger distance measurement range. The resolution of the Compton camera is low, and the range deviation is large; the semiconductor coding camera has small pixel side length, high resolution and high range finding precision, but has small detection area (mm)2Magnitude) and thus the ranging range is small.
(2) The spacing between the binocular cameras. If the distance is too large, the carrying and the operation are not facilitated in the actual measurement; if the distance is too small, the range of actual detection is affected.
(3) The binocular camera has certain measurement error in ranging, so that the ranging result is unstable, and the fluctuation is large.
Disclosure of Invention
In order to solve the problems, the invention discloses a method for measuring the depth of a radiation hotspot based on a four-eye coding gamma camera. The invention designs a novel radiation hotspot distance measuring method based on a four-eye coding scintillator detector (namely a four-eye coding gamma camera), and realizes higher distance measuring range and precision under the conditions of smaller distance and lower resolution of the detector.
The whole ranging algorithm flow of the invention is as follows: firstly, carrying out interpolation on projection data acquired by a four-eye encoding gamma camera on a radiation hotspot and then reconstructing the projection data; secondly, determining the sub-pixel position coordinates of the radiation hot spot in the reconstructed image; and finally, estimating the distance of the radiation hot spot by using a distance estimation algorithm of the four-eye radiation hot spot.
Furthermore, projection data obtained on the four-eye detector is subjected to bilinear interpolation, and a decoding matrix is reconstructed in a fine sampling balance decoding mode, so that artificial fine sampling is realized.
Further, after reconstruction data of the four-eye detector are obtained, the method for reconstructing the radiation hotspot 10 in the image is realized by respectively adopting a one-dimensional position weight method, a two-dimensional position weight method, a one-dimensional Gaussian fitting method and a two-dimensional Gaussian fitting method-3Magnitude sub-pixel positioning accuracy.
Further, in a four-eye radiation hotspot distance estimation algorithm, dividing a four-eye camera into four binocular cameras, solving a parallax average value of the four binocular cameras, and then bringing the parallax average value into a binocular distance measurement algorithm to obtain an estimated distance; from the point of view of the whole, the estimated distance is obtained by a minimum area method.
The technical scheme of the invention is as follows:
a method for measuring the depth of a radiation hotspot based on a four-eye coding gamma camera comprises the following steps:
1) acquiring radiation hotspots by a four-eye encoding gamma camera to obtain four projection data, and reconstructing the four projection data after bilinear interpolation to obtain four reconstructed images;
2) respectively determining the sub-pixel coordinates of a radiation hotspot according to each reconstructed image;
3) connecting and extending the vertex of each camera in the four-eye encoding gamma camera with the position of a radiation hot spot in a reconstructed image corresponding to the camera to obtain four straight lines in space; connecting coordinate points on four straight lines at different depths to form a quadrangle, calculating the area of the quadrangle, and carrying out parabolic fitting on the changes of the areas of the quadrangle at different depths; and taking the depth corresponding to the vertex of the parabola obtained by fitting as the distance from the radiation hot spot to the detector.
A method for measuring the depth of a radiation hotspot based on a four-eye coding gamma camera comprises the following steps:
1) acquiring radiation hotspots by a four-eye encoding gamma camera to obtain four projection data, and reconstructing each projection data after bilinear interpolation to obtain four reconstructed images;
2) respectively determining the sub-pixel coordinates of a radiation hotspot according to each reconstructed image;
3) dividing the four-eye encoding gamma camera into four binocular cameras from two dimensions, wherein the two cameras corresponding to the upper, lower, left and right cameras respectively form the four binocular cameras;
4) according to
Calculating four binocular parallax mean values
Then according to
Determining the distance from the radiation hot spot to the four-eye encoding gamma camera; wherein, DeltaL is the side length of a single pixel of a reconstructed image on the crystal array plane,
the difference between the pixel numbers of the radiation hot spots in the two reconstructed images corresponding to the ith binocular camera is b, the baseline distance between the two cameras in the four-mesh encoding gamma camera is b, and the distance from the crystal array in the four-mesh encoding gamma camera to the vertex of the four-mesh encoding gamma camera is l.
Optionally, the method for obtaining the reconstructed image includes: and carrying out bilinear interpolation on the projection data, carrying out correlation operation on the interpolated projection data and the decoding matrix of the fine sampling balance decoding by adopting a fine sampling balance decoding mode on the decoding matrix to obtain a reconstructed image.
Optionally, different methods are used for determining the sub-pixel coordinates of the radiation hot spot in the reconstructed image of the four-eye encoding camera; the adopted method comprises the following steps: a one-dimensional position weight method, a two-dimensional position weight method, a one-dimensional Gaussian fitting method, and a two-dimensional Gaussian fitting method.
Optionally, the method for determining the position of the radiation hot spot in the reconstructed image by using the one-dimensional position weighting method includes: in the reconstructed image, let the maximum value coordinate of the radiation intensity be (x)max,ymax) Where y is equal to ymaxIn the one-dimensional region of (1), select xmaxTaking the left and right N pixels as radiation hot spot areas, taking the radiation intensity of each pixel as a weight, and taking a weighted average value of the position coordinates x of each pixel to determine the position of the radiation hot spot in the x direction; for the same reason, x ismaxWithin a one-dimensional region of (1), select ymaxAnd taking the upper and lower N pixels as radiation hot spot areas, taking the radiation intensity of each pixel of the radiation hot spot areas as a weight, and taking a weighted average value of the position coordinates y of the radiation hot spot areas so as to determine the position of the radiation source in the y direction.
Optionally, the method for determining the position of the radiation hot spot in the reconstructed image by using the two-dimensional position weighting method includes: in the reconstructed image, let the maximum value coordinate of the radiation intensity be (x)max,ymax) (ii) a With x ═ xmaxN pixels on the left and right, y ═ ymaxThe upper N pixels and the lower N pixels form a two-dimensional radiation hot spot area; and calculating the weighted average value of the position coordinates of each pixel point in the two-dimensional radiation hotspot region by taking the radiation intensity of each pixel in the two-dimensional radiation hotspot region as the weight, and taking the weighted average value as the radiation hotspot position in the reconstructed image.
Optionally, the method for determining the position of the radiation hot spot in the reconstructed image by using a one-dimensional gaussian fitting method includes: in the reconstructed image, let the maximum value coordinate of the radiation intensity be (x)max,ymax) (ii) a Each at y ═ ymaxAnd x ═ xmaxIn the one-dimensional region of (a), one-dimensional Gaussian fitting is performed to obtain (x)max,ymax) As fitting parameter (. mu.)x,μy) A priori estimate of (u), obtained after fittingx,μy) As the location of the radiation hot spot in the reconstructed image.
Optionally, the method for determining the position of the radiation hot spot in the reconstructed image by using a two-dimensional gaussian fitting method includes: in the reconstructed image, let the maximum value coordinate of the radiation intensity be (x)max,ymax) (ii) a Will (x)max,ymax) As fitting parameter (. mu.)x,μy) Performing two-dimensional Gaussian fitting on the whole reconstructed image, and fitting the obtained parameter (mu) after fittingx,μy) As the location of the radiation hot spot in the reconstructed image.
Optionally, the four-eye encoding gamma camera is divided into four binocular cameras from two dimensions, wherein the two cameras corresponding to the upper, lower, left and right sides respectively form a binocular camera; according to
Obtaining the depth of each binocular camera, wherein i is 1,2,3, 4; determining a depth range according to the obtained depth information, and calculating the area of a quadrangle in the depth range; wherein, DeltaL is the side length of a single pixel of a reconstructed image on the crystal array plane,
the difference between the number of pixels of the radiation hot spot in the two reconstructed images corresponding to the ith binocular camera is shown, b is a baseline distance between two cameras in the four-eye encoding camera, and l is a distance from a crystal array in the four-eye encoding gamma camera to the vertex of the four-eye encoding gamma camera.
Optionally, the method for determining the depth range includes: the minimum value of the four obtained depths is ZminMaximum value of ZmaxThe depth range is
The invention has the following advantages:
(1) the invention selects the scintillator coding aperture detector with lower resolution ratio to carry out distance measurement, thereby realizing higher distance measurement range and precision.
(2) The four-eye detector has small distance between the detectors, and realizes higher range and precision of distance measurement under the condition of small distance between the detectors.
(3) The four-eye detector is adopted, and compared with the unstable measurement result of the binocular detector, the four-eye detector reduces the measurement error.
Drawings
Fig. 1 is a general flow chart of the radiation hotspot distance measurement of the invention.
FIG. 2 is a contrast map of a reconstructed image before and after "artificial" fine sampling; wherein (a) is an artificial reconstructed image before fine sampling, and (b) is an artificial reconstructed image after fine sampling (right).
FIG. 3 is a reconstructed image of a four-eye camera with the radiation source at a distance of 20m from the four-eye center detector; wherein (a) is the camera 1 reconstructed image, (b) is the camera 2 reconstructed image, (c) is the camera 3 reconstructed image, and (d) is the camera 4 reconstructed image.
FIG. 4 shows the result of one-dimensional Gaussian fitting; wherein (a) is the fitting result in the x direction, and (b) is the fitting result in the y direction.
Fig. 5 shows the two-dimensional gaussian fitting results.
FIG. 6 is a schematic view of a four-eye camera; the four-eye camera is divided into an upper dimension binocular camera and a lower dimension binocular camera, and the four-eye camera is divided into a left dimension binocular camera and a right dimension binocular camera.
Fig. 7 is a binocular camera ranging diagram.
FIG. 8 is a schematic diagram of a minimum area method.
Fig. 9 is a parabolic fit.
Detailed Description
The invention will be described in further detail with reference to the following drawings, which are given by way of example only for the purpose of illustrating the invention and are not intended to limit the scope of the invention.
The invention provides a novel method for determining sub-pixel coordinates of a radiation hotspot in a reconstructed image based on a four-eye coding gamma camera and a distance estimation method of the radiation hotspot. The total flow of the radiation hot spot distance measurement is shown in fig. 1. The respective steps will be described separately below.
1. Reconstructing projection data after interpolation
The reconstructed image (i.e. the reconstructed data and the reconstruction matrix) of the four-view coded gamma camera can be obtained by correlating the projection matrix (i.e. the projection data) with the decoding matrix, as shown in the conventional formula (1), wherein O is the reconstructed data, R is the projection matrix, G is the decoding matrix, and as the correlation operator.
O＝R⊙G
The projection data dimension of each gamma camera in the four-view coding gamma camera is 44 x 44, the projection data dimension is subjected to bilinear interpolation, and the dimension is changed into 220 x 220 after 5 times of interpolation; the dimension of the decoding matrix is changed from 44 x 44 to 220 x 220 by adopting a fine sampling balance decoding mode; and then the projection data after bilinear interpolation and the decoding matrix of the fine sampling balance decoding are subjected to correlation operation to obtain a reconstructed image.
The operation is equivalent to artificial fine sampling, and the sampling precision is increased, so that the reconstructed image is smoother and has higher precision. The reconstructed images before and after the "artificial" fine sampling are shown in fig. 2.
2. Determining sub-pixel coordinates of radiation hotspots in reconstructed images
An important step before estimating the distance of the radiation hot spot from the detector is to determine the sub-pixel location coordinates of the radiation hot spot in the reconstructed image. The distance between the modules of the four-eye camera is about 28cm and less than 30 cm. With such a smaller pitch design, when the radiation source is located at a certain position within the field of view, it can be seen in the reconstructed image of the four-eye camera that the position of the hot spot varies a little, on the order of an integer, as shown in fig. 3. In order to realize high range finding range and high precision, the position judgment of the radiation hot spot is required to be more accurate, so that the method 10 for reconstructing the radiation hot spot in the image is realized by a one-dimensional position weight method, a two-dimensional position weight method, one-dimensional Gaussian fitting and two-dimensional Gaussian fitting-3Magnitude sub-pixel positioning accuracy.
In the reconstructed image, the coordinate of the maximum value of the radiation intensity (the pixel point with the maximum gray value) is set as (x)max,ymax) Where y is equal to ymaxIn the one-dimensional region of (1), select xmaxThe left pixel and the right pixel are respectively 20 pixels as radiation hot spot areas, the radiation intensity of each pixel is taken as a weight, the weighted average value of the position coordinates x of the pixel is taken so as to determine the position of the radiation source in the x direction, and the calculation process is shown as formula (1), wherein R (x, y) is the radiation intensity of the (x, y) position in the reconstructed image.
For the same reason, x ismaxWithin a one-dimensional region of (1), select ymaxThe upper and lower 20 pixels are radiation hot spot areas, the radiation intensity of each pixel is taken as the weight, the weighted average value of the position coordinate y is taken to determine the position of the radiation source in the y direction, and the calculation process is shown as the formula (2)
Where x is xmax20 pixels on the left and right, y ═ ymaxThe upper and lower 20 pixels form a two-dimensional radiation hotspot area, the radiation intensity of each pixel of the two-dimensional radiation hotspot area is taken as the weight, the weighted average value of the position coordinates x and y is respectively taken, and the positions of the radioactive source in the x direction and the y direction are determined, and the calculation process is shown in formulas (3) and (4).
Each at y ═ ymaxAnd x ═ xmaxIn the one-dimensional region of (a), one-dimensional gaussian fitting is performed to (x)max,ymax) As a fitting parameter (mu)x,μy) A priori estimate of (u), obtained after fittingx,μy) I.e. the sub-pixel position coordinates of the radioactive source, and the calculation process is as followsThe fitting results are shown in fig. 4, as shown in the formulas (5) and (6).
In the whole reconstructed image, a two-dimensional Gaussian fitting is performed with a fitting parameter (μ)x,μy) I.e. the position coordinates of the radiation source, the calculation process is shown in formula (7), and the fitting result is shown in fig. 5.
In the formulas (5), (6) and (7), x and y are both 0,1,2, …,199, 200; f. ofX(x)、fY(y)、fX,Y(x, y) is the radiation intensity at the corresponding location in the reconstructed image when x and y take different values.
3. Four-eye radiation hotspot distance estimation algorithm
The four-eye radiation hotspot distance estimation algorithm is divided into two types, namely a radiation hotspot depth measurement method based on a parallax mean value and a radiation hotspot depth measurement method based on a minimum area.
3.1 radiation hotspot depth measurement based on parallax mean
As shown in fig. 6, the four-eye camera has two cameras, i.e., an upper camera, a lower camera, a left camera and a right camera, and four binocular cameras are formed from two dimensions. As shown in FIG. 7, the distance b between the two gamma cameras is about 28cm, the distance from the crystal array to the vertex of the camera is l, and the sub-pixel coordinate x of the radiation hot spot can be obtained in the reconstructed images of the left camera and the right camera through step 2lAnd xrWhere xlAnd xrThe length of a side Δ L of a single pixel of a reconstructed image on a plane of a crystal array of the detector can be obtained by formula (8) (the number of pixels of the reconstructed image is 201 × 201). Binocular camera parallax, i.e. the distance between the radiation sources in the reconstructed images of the left and right cameras, is DeltaLxr-xlIf the distance Z is greater than the threshold value, the distance Z is calculated by using the equation (10) to calculate the distance Z of the radiation source.
3.2 minimum area based depth measurement of radiation hot spot
After obtaining the four parallax differences corresponding to the four binocular cameras in the above 3.1, the depth Z can be obtained by substituting the four parallax differences into the equation (11)1、Z2、Z3、Z4Taking the minimum value of the four depths as ZminMaximum value of ZmaxAnd further obtaining a depth range of
As shown in FIG. 8, each of the four gamma cameras has an O1、O2、O3、O4The four vertexes can be used for positioning the position of the radiation hot spot in the reconstructed image, and the vertex of each gamma camera and the reconstructed image are combinedThe positions of the radiation sources are connected and extended, and ideally intersect at a point in space, which is the position of the radiation source. We find that the distance from near to far, at different depths of the Z axis, the area of a quadrangle formed by the four lines in the space should be reduced and then increased, wherein the depth corresponding to the point with the smallest area is the distance from the radioactive source to the detector.
Therefore we are in
In the depth range, 1cm is taken as a step length, different depths are taken, and the area of a quadrangle formed by four straight lines at different depths is calculated. As shown in fig. 9, the abscissa of the graph is different depths, and the ordinate of the graph is a quadrilateral area enclosed by the graph, it can be found that the change of the quadrilateral area is irregular, and the depth corresponding to the minimum area of the quadrilateral area is not the depth of the radioactive source, so we perform parabolic fitting after obtaining an area curve, and the depth corresponding to the minimum value of the fitted parabolic is the depth of the radioactive source.
Table 1 is the estimated distance when the source is at different distances from the detector and the percentage deviation of the true distance from the estimated distance.
TABLE 1 estimated distance and deviation under different distance conditions
| Actual distance/m | Estimated distance/m | Deviation from |
| 5 | 5.05 | 0.99％ |
| 8 | 8.03 | 0.39％ |
| 10 | 9.93 | -0.73％ |
| 12 | 11.54 | -3.82％ |
| 14 | 13.84 | -1.12％ |
| 15 | 14.90 | -0.69％ |
| 19 | 18.91 | -0.49％ |
| 20 | 19.78 | -1.12％ |
| 21 | 20.45 | -2.60％ |
| 23 | 22.96 | -0.15％ |
| 25 | 24.10 | -3.61％ |
| 26 | 26.06 | 0.23％ |
| 28 | 28.62 | 2.23％ |
| 30 | 31.58 | 5.27％ |
Although specific embodiments of the invention have been disclosed for purposes of illustration, and for purposes of aiding in the understanding of the contents of the invention and its implementation, those skilled in the art will appreciate that: various substitutions, alterations, and modifications are possible without departing from the spirit and scope of this disclosure and the appended claims. Therefore, it is intended that the invention not be limited to the particular embodiment disclosed as the best mode contemplated for carrying out this invention, but that the invention will include all embodiments falling within the scope of the appended claims.
Claims (10)
1. A method for measuring the depth of a radiation hotspot based on a four-eye coding gamma camera comprises the following steps:
1) acquiring radiation hotspots by a four-eye encoding gamma camera to obtain four projection data, and reconstructing the four projection data after bilinear interpolation to obtain four reconstructed images;
2) respectively determining the sub-pixel coordinates of a radiation hotspot according to each reconstructed image;
3) connecting and extending the vertex of each camera in the four-eye encoding gamma camera with the position of a radiation hot spot in a reconstructed image corresponding to the camera to obtain four straight lines in space; connecting coordinate points on four straight lines at different depths to form a quadrangle, calculating the area of the quadrangle, and carrying out parabolic fitting on the changes of the areas of the quadrangle at different depths; and taking the depth corresponding to the vertex of the parabola obtained by fitting as the distance from the radiation hot spot to the detector.
2. A method for measuring the depth of a radiation hotspot based on a four-eye coding gamma camera comprises the following steps:
1) acquiring radiation hotspots by a four-eye encoding gamma camera to obtain four projection data, and reconstructing each projection data after bilinear interpolation to obtain four reconstructed images;
2) respectively determining the sub-pixel coordinates of a radiation hot spot according to each reconstructed image;
3) dividing the four-eye encoding gamma camera into four binocular cameras from two dimensions, wherein the two cameras corresponding to the upper, lower, left and right cameras respectively form the four binocular cameras;
4) according to
Calculating four binocular parallax mean values
Then according to
Determining the distance from the radiation hot spot to the four-eye encoding gamma camera; wherein, DeltaL is the side length of a single pixel of a reconstructed image on the crystal array plane,
the difference between the number of pixels of the radiation hot spot in the two reconstructed images corresponding to the ith binocular camera is shown, b is a baseline distance between two cameras in the four-view coding gamma camera, and l is a distance from a crystal array in the four-view coding gamma camera to the vertex of the four-view coding gamma camera.
3. The method of claim 1 or 2, wherein the reconstructed image is obtained by: and performing bilinear interpolation on the projection data, wherein a fine sampling balance decoding mode is adopted for a decoding matrix, and correlation operation is performed on the projection data after interpolation and the decoding matrix of the fine sampling balance decoding to obtain a reconstructed image.
4. The method of claim 1 or 2, wherein the sub-pixel coordinates of the radiation hot spot in the reconstructed image are determined using different methods for the reconstructed image of the four-eye encoding gamma camera; the adopted method comprises the following steps: a one-dimensional position weight method, a two-dimensional position weight method, a one-dimensional Gaussian fitting method, and a two-dimensional Gaussian fitting method.
5. The method of claim 4, wherein the determining the location of the radiation hot spot in the reconstructed image using one-dimensional position weighting comprises: in the reconstructed image, let the maximum value coordinate of the radiation intensity be (x)max,ymax) Where y is equal to ymaxIn the one-dimensional region of (1), select xmaxTaking the left and right N pixels as radiation hot spot areas, taking the radiation intensity of each pixel as a weight, and taking a weighted average value of the position coordinates x of each pixel to determine the position of the radiation hot spot in the x direction; for the same reason, x ismaxWithin a one-dimensional region of (1), select ymaxAnd taking the upper and lower N pixels as radiation hot spot areas, taking the radiation intensity of each pixel of the radiation hot spot areas as a weight, and taking a weighted average value of the position coordinates y of the radiation hot spot areas so as to determine the position of the radiation source in the y direction.
6. The method of claim 4, wherein the determining the location of the radiation hot spot in the reconstructed image using a two-dimensional position weighting method comprises: in the reconstructed image, let the maximum value coordinate of the radiation intensity be (x)max,ymax) (ii) a With x ═ xmaxN pixels on the left and right, y ═ ymaxThe upper and lower N pixels form a two-dimensional radiation hot spot area; and calculating the weighted average value of the position coordinates of each pixel point in the two-dimensional radiation hotspot region by taking the radiation intensity of each pixel in the two-dimensional radiation hotspot region as the weight, and taking the weighted average value as the radiation hotspot position in the reconstructed image.
7. The method of claim 4, wherein the position of the radiation hot spot in the reconstructed image is determined by a one-dimensional Gaussian fitting method comprising: in the reconstructed image, let the maximum value coordinate of the radiation intensity be (x)max,ymax) (ii) a Each at y ═ ymaxAnd x ═ xmaxIn the one-dimensional region of (c), a one-dimensional Gaussian fitting is performed to obtain (x)max,ymax) As fitting parameter (. mu.)x,μy) A priori estimate of (u), obtained after fittingx,μy) As the location of the radiation hot spot in the reconstructed image.
8. The method of claim 4, wherein the position of the radiation hot spot in the reconstructed image is determined by a two-dimensional Gaussian fitting method comprising: in the reconstructed image, let the maximum value coordinate of the radiation intensity be (x)max,ymax) (ii) a Will (x)max,ymax) As fitting parameter (. mu.)x,μy) Performing two-dimensional Gaussian fitting on the whole reconstructed image, and fitting the obtained parameter (mu) after fittingx,μy) As the location of the radiation hot spot in the reconstructed image.
9. The method of claim 1, wherein the four-view encoding gamma camera is divided into four binocular cameras from two dimensions, wherein two cameras corresponding to the upper, lower, left and right cameras respectively constitute one binocular camera; according to
Obtaining the depth of each binocular camera, wherein i is 1,2,3, 4; determining a depth range according to the obtained depth information, and calculating the area of a quadrangle in the depth range; wherein, DeltaL is the side length of a single pixel of a reconstructed image on the crystal array plane,
the difference between the pixel numbers of the radiation hot spots in the two reconstructed images corresponding to the ith binocular camera,b is a baseline distance between two cameras in the four-eye encoding gamma camera, and l is a distance from a crystal array in the four-eye encoding gamma camera to a vertex of the four-eye encoding gamma camera.
10. The method of claim 9, wherein the depth range is determined by: the minimum value of the four obtained depths is ZminMaximum value of ZmaxThe depth range is
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