CN113312790A - Radiation dose analysis method and device, storage medium and electronic equipment - Google Patents
Radiation dose analysis method and device, storage medium and electronic equipment Download PDFInfo
- Publication number
- CN113312790A CN113312790A CN202110666372.8A CN202110666372A CN113312790A CN 113312790 A CN113312790 A CN 113312790A CN 202110666372 A CN202110666372 A CN 202110666372A CN 113312790 A CN113312790 A CN 113312790A
- Authority
- CN
- China
- Prior art keywords
- value
- dose
- test file
- spectrum
- file
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 230000005855 radiation Effects 0.000 title claims abstract description 126
- 238000004458 analytical method Methods 0.000 title abstract description 20
- 238000012360 testing method Methods 0.000 claims abstract description 214
- 238000000034 method Methods 0.000 claims abstract description 64
- 230000003595 spectral effect Effects 0.000 claims abstract description 37
- 230000005291 magnetic effect Effects 0.000 claims abstract description 21
- 238000012545 processing Methods 0.000 claims abstract description 18
- 238000011410 subtraction method Methods 0.000 claims abstract description 13
- 238000010276 construction Methods 0.000 claims abstract description 11
- 238000001228 spectrum Methods 0.000 claims description 124
- 239000003550 marker Substances 0.000 claims description 79
- 238000010606 normalization Methods 0.000 claims description 68
- 238000010521 absorption reaction Methods 0.000 claims description 18
- 238000000862 absorption spectrum Methods 0.000 claims description 12
- 238000004590 computer program Methods 0.000 claims description 7
- 230000007812 deficiency Effects 0.000 abstract description 3
- 238000004435 EPR spectroscopy Methods 0.000 description 30
- 239000002609 medium Substances 0.000 description 13
- 238000010586 diagram Methods 0.000 description 12
- 230000006870 function Effects 0.000 description 6
- 238000004364 calculation method Methods 0.000 description 5
- 230000001419 dependent effect Effects 0.000 description 3
- 210000000282 nail Anatomy 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000007547 defect Effects 0.000 description 2
- 238000000605 extraction Methods 0.000 description 2
- 210000004905 finger nail Anatomy 0.000 description 2
- 230000001678 irradiating effect Effects 0.000 description 2
- 231100000987 absorbed dose Toxicity 0.000 description 1
- 230000004071 biological effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000004980 dosimetry Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 239000012120 mounting media Substances 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000000704 physical effect Effects 0.000 description 1
- 230000008707 rearrangement Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000004611 spectroscopical analysis Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012800 visualization Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
Abstract
The embodiment of the application discloses a radiation dose analysis method and device, a storage medium and electronic equipment. The method comprises the following steps: obtaining at least two test files with known radiation dose, standard files without radiation, maps of the test files and maps of the standard files; wherein the test file and the standard file comprise magnetic field values of radiation doses and first differential intensity values of the EPR signal; acquiring the map characteristic value of each map, and processing the map characteristic value of each map by adopting a preset rule to obtain a normalized value of the map characteristic value of each test file; and constructing a dose regression curve according to the radiation dose of each test file and the normalized value of the map characteristic value. According to the technical scheme, a dose regression curve is constructed by utilizing the normalized values of the radiation dose and the map characteristic value. The construction is completed through a program, the accuracy deficiency of the traditional spectral subtraction method is made up, and the linearity of a dose regression curve is improved.
Description
Technical Field
The embodiment of the application relates to the technical field of radiation analysis, in particular to a radiation dose analysis method and device, a storage medium and electronic equipment.
Background
As nuclear energy utilization increases, the hazards presented by the nucleus and radiation also continue to grow. Rapid, effective retrospective dosimetry at the time of an accident is becoming more important.
Electron Paramagnetic Resonance (EPR) spectroscopy, which is based on the analysis of biological or physical effects caused by radiation, is one of the methods for assessing absorbed dose. A certain amount of free radicals are generated after the fingernail of a human body is irradiated, and the concentration of the free radicals is represented by the second integral (the area enclosed by absorption spectral lines) of spectral lines in an EPR spectrogram (first differential spectral line). The higher the irradiation dose and the higher the concentration of the nail, the linear relation between the dose and the area enclosed by the spectral line, namely a dose regression curve, can be established by irradiating the known dose, and the dose regression curve is estimated after the accident occurs. Currently, dose regression curves are constructed mainly by using spectral subtraction. The traditional spectral subtraction method is to use a signal peak value and a Marker peak value to carry out fitting to obtain a dose regression curve.
The traditional spectral subtraction method has insufficient precision and lower linearity of a dose regression curve. And no related art can achieve visualization of dose regression curves.
Disclosure of Invention
The embodiment of the application provides a radiation dose analysis method and device, a storage medium and electronic equipment, wherein a dose regression curve is constructed by utilizing a radiation dose and a normalization value of a map characteristic value. The construction is completed through a program, the accuracy deficiency of the traditional spectral subtraction method is made up, and the linearity of a dose regression curve is improved. Dose regression curves can also be visualized.
In a first aspect, an embodiment of the present application provides a method for analyzing radiation dose, including:
obtaining at least two test files with known radiation dose, standard files without radiation, maps of the test files and maps of the standard files; wherein the test file and the standard file comprise magnetic field values of radiation doses and first differential intensity values of the EPR signal;
acquiring the map characteristic value of each map, and processing the map characteristic value of each map by adopting a preset rule to obtain a normalized value of the map characteristic value of each test file;
and constructing a dose regression curve according to the radiation dose of each test file and the normalized value of the map characteristic value.
In a second aspect, embodiments of the present application provide an apparatus for analyzing radiation dose, the apparatus including:
the file and map acquisition module is used for acquiring at least two test files obtained by known radiation doses, standard files which are not radiated, maps of the test files and maps of the standard files; wherein the test file and the standard file comprise magnetic field values of radiation doses and first differential intensity values of the EPR signal;
the normalization value obtaining module is used for obtaining the map characteristic value of each map, and processing the map characteristic value of each map by adopting a preset rule to obtain the normalization value of the map characteristic value of each test file;
and the dose regression curve construction module is used for constructing a dose regression curve according to the radiation dose of each test file and the normalized value of the map characteristic value.
In a third aspect, embodiments of the present application provide a computer-readable storage medium, on which a computer program is stored, which when executed by a processor, implements a method for analyzing a radiation dose as described in embodiments of the present application.
In a fourth aspect, embodiments of the present application provide an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the method for analyzing a radiation dose according to embodiments of the present application.
According to the technical scheme provided by the embodiment of the application, at least two test files and standard files which are obtained by known radiation doses and are not radiated are obtained, and the maps of the test files and the maps of the standard files are obtained; the test file and the standard file comprise magnetic field values of radiation doses and first differential strength values of EPR signals; acquiring the map characteristic value of each map, and processing the map characteristic value of each map by adopting a preset rule to obtain a normalized value of the map characteristic value of each test file; and constructing a dose regression curve according to the radiation dose of each test file and the normalized value of the map characteristic value. According to the technical scheme, a dose regression curve is constructed by utilizing the normalized values of the radiation dose and the map characteristic value. The construction is completed through a program, the defect of the precision of the traditional spectral subtraction method is made up, and the linearity of a dose regression curve is improved. Dose regression curves can also be visualized.
Drawings
FIG. 1 is a flow chart of a method for analyzing radiation dose provided in an embodiment of the present application;
FIG. 2 is a schematic diagram of a test file storage provided in an embodiment of the present application;
FIG. 3 is a diagram of a test document atlas provided in an embodiment of the present application;
FIG. 4 is a diagram of the feature values of the atlas provided in the first embodiment of the application;
FIG. 5 is a graph of a dose regression curve provided in accordance with an embodiment of the present application.
FIG. 6 is a schematic diagram of a process for analyzing radiation dose provided in example two of the present application;
FIG. 7 is a schematic structural diagram of an apparatus for analyzing a radiation dose provided in the third embodiment of the present application;
fig. 8 is a schematic structural diagram of an electronic device according to a fifth embodiment of the present application.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the application and are not limiting of the application. It should be further noted that, for the convenience of description, only some of the structures related to the present application are shown in the drawings, not all of the structures.
Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the steps as a sequential process, many of the steps can be performed in parallel, concurrently or simultaneously. In addition, the order of the steps may be rearranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like.
Example one
Fig. 1 is a flowchart of a radiation dose analysis method provided in an embodiment of the present application, where the present embodiment is applicable to a case of analyzing a radiation dose, and the method may be executed by a radiation dose analysis apparatus provided in an embodiment of the present application, where the apparatus may be implemented by software and/or hardware, and may be integrated in a device such as an intelligent terminal for radiation dose analysis.
As shown in fig. 1, the method for analyzing the radiation dose includes:
s110, obtaining at least two test files and standard files which are not radiated and obtained by known radiation doses, and obtaining the atlas of each test file and the atlas of each standard file; wherein the test file and the standard file comprise magnetic field values of radiation doses and first differential intensity values of the EPR signal;
in the scheme, the fingernail of the human body can generate certain free radicals after being irradiated, and the concentration of the free radicals is represented by the quadratic integral of spectral lines in an EPR (expression-dependent reflection) spectrum. The higher the irradiation dose and the higher the concentration of the nail, the linear relation of the area enclosed by the dose and the absorption spectral line, namely a dose regression curve can be established by irradiating the known dose, and the dose regression curve is estimated after the accident occurs. The water-treated nail EPR signal contains RIS (radiation-induced signals) and BKG (background signals). Both are in the same position (g values are almost the same) and are superimposed and cannot be distinguished. The fitting method is that the EPR spectral line is regarded as linear superposition of the BKG and the RIS, the BKG and the RIS are simulated by utilizing a mathematical model to obtain two model functions, and the two model functions are combined to fit the EPR signal through the linear superposition. The EPR map is stored in the form of an ACS file, and the test file, the standard file which is not radiated, the map of each test file and the map of the standard file can be visually displayed on the basis of the QT platform. Wherein QT is the C + + graphical user interface application development framework.
The file storage name may include the sample mass and the radiation dose. The content stored in the file comprises the absolute path of the file, the file creation time, the magnetic field value of the radiation dose and the first order differential strength value of the EPR signal, the first column is the magnetic field value of the radiation dose, and the second column is the first order differential strength value of the EPR signal. The content in the test file is generated based on the radiation induced signal. The content of the standard file is generated based on the background signal.
In this embodiment, the test file and the standard file may be directly read from the database and displayed based on the QT platform. And displaying the test files and the standard files in a map form according to the contents of the test files and the standard files. And taking the magnetic field value of the radiation dose as the abscissa of the map, and taking the primary differential intensity value of the EPR signal as the ordinate of the map, so as to obtain the map of each test file and the map of the standard file.
For example, fig. 2 is a schematic diagram of a test file storage provided in an embodiment of the present application. QT reads the test file and stores two columns of data in two double-type containers (vector) of C + + and visualizes through a drawing library QCustomplot of QT. Storing in an ACS file storage format. As shown in fig. 2, the first column of the test file is the magnetic field value of the radiation dose and the second column is the first differential intensity value of the EPR signal. The file storage name includes an absolute path of the file and a file creation time. X [ G ] denotes the magnetic field value in gauss (G) and intensity denotes the EPR strength. Fig. 2 shows that the original data obtained after EPR measurement is not processed, that is, after the ASC file is obtained, the file is opened and processed by QT, and the processing includes extraction, storage, feature search, and the like of two columns of data. Wherein, the standard file and the test file are stored in the same form.
Illustratively, fig. 3 is a schematic diagram of a test file map provided in the first embodiment of the present application. As shown in fig. 3, the abscissa of the plot is the magnetic field value of the radiation dose and the ordinate is the first differential intensity value of the EPR signal.
S120, obtaining the map characteristic value of each map, and processing the map characteristic value of each map by adopting a preset rule to obtain a normalized value of the map characteristic value of each test file;
in this embodiment, the map characteristic value may refer to a signal peak value, a signal line width, a Marker peak value, and a Marker line width. The signal peak value and the signal line width are generated based on the radiation induced signal, and the Marker peak value and the Marker line width are generated based on the background signal. The map characteristic values of the maps can be obtained by extracting the contents of the test file and the standard file.
Illustratively, fig. 4 is a schematic diagram of a feature value of an atlas provided in the first embodiment of the present application. As shown in fig. 4, the signal peak value, the signal line width, the Marker peak value, and the Marker line width can be more visually checked based on the map.
In the scheme, the normalized value of the map characteristic value of each test file can be obtained by multiplying the signal peak value by the signal line width, multiplying the Marker peak value by the Marker line width, and normalizing the area obtained by multiplying. The signal spectral line can also be fitted by a nonlinear least square fitting method by using the signal peak value and the signal line width as conditions, so as to obtain the normalized value of the map characteristic value of each test file.
S130, constructing a dose regression curve according to the radiation dose of each test file and the normalization value of the map characteristic value.
Wherein the radiation dose can be obtained by reading the name of each test file.
In the scheme, the radiation dose can be used as an abscissa, the normalized value of the graph characteristic value is used as an ordinate, a coordinate pair is generated, and a dose regression curve is constructed.
In this technical solution, optionally, a dose regression curve is constructed according to the radiation dose of each test file and the normalized value of the map feature value, including:
acquiring the radiation dose of each test file;
constructing a coordinate pair by the radiation dose of each test file and the normalized value of the map characteristic value of the test file, and projecting the coordinate pair into a coordinate system;
and performing linear fitting on the projection points of the test files in the coordinate system to obtain a dose regression curve.
In this embodiment, the radiation dose of each test file is used as the abscissa, the normalized value of the map feature value corresponding to the test dose is used as the ordinate, a coordinate pair is constructed, and linear fitting is performed on each test file in a coordinate system to obtain a dose regression curve.
Illustratively, fig. 5 is a schematic view of a dose regression curve provided in a first embodiment of the present application. As shown in fig. 5, on the QT page, dots represent coordinate pairs constructed from normalized values of radiation dose and pattern feature values of the test document, and straight lines represent dose regression curves.
The dose regression curve is obtained by linearly fitting the projection points of each test file in the coordinate system, construction can be completed by using a program, and the linearity of the regression curve can be improved.
In this technical solution, optionally, after performing linear fitting on the projection points of each test file in the coordinate system to obtain a dose regression curve, the method further includes:
and determining a decision coefficient of the radiation dose of each test file and the normalized value of the characteristic value of the spectrum so as to evaluate the linear correlation degree of the dose regression curve.
Wherein the decision coefficient is numerically equal to the square of the correlation coefficient. What percentage of the fluctuation of y is reflected can be described by the fluctuation of x, i.e. what percentage of the variation characterizing the dependent variable y is accounted for by the independent variable x being controlled. The greater the goodness of fit, the greater the interpretation of the independent variable on the dependent variable, and the higher the percentage of the total variation that is accounted for by the variations caused by the independent variable. The denser the observation points are near the regression line.
By determining the decision coefficient of the radiation dose of each test file and the normalization value of the map characteristic value, the evaluation of the linear correlation degree of the dose regression curve can be realized according to the decision coefficient, and the linearity of the dose regression curve is improved.
In this technical solution, optionally, after performing linear fitting on the projection points of each test file in the coordinate system to obtain a dose regression curve, the method further includes:
and determining the prediction standard error of the projection point of each test file and the dose regression curve so as to evaluate the prediction accuracy of the dose regression curve.
Wherein the standard error can be set according to the radiation dose analysis requirement. Preferably, the standard error may be
Where a and b are coefficients of a dose regression curve, xiAnd yiRespectively, for the abscissa and ordinate of the dose regression curve.
By determining the projection point of each test file and the prediction standard error of the dose regression curve, the accuracy degree of prediction of the dose regression curve can be evaluated according to the standard error, and the linearity of the dose regression curve is improved.
In this embodiment, optionally, after the dose regression curve is constructed, the method further includes:
acquiring an actually measured unknown dose map, and extracting the first differential intensity of an EPR signal in the map;
and calculating the radiation dose of the actually measured object according to the actually measured unknown dose atlas and the dose regression curve.
In this embodiment, the first differential intensity of the EPR signal may be obtained by reading the ordinate in the unknown dose profile.
Through the dose regression curve, the radiation dose of the actually measured object can be calculated, the radiation dose calculation efficiency is greatly improved, and the time in the data processing process is reduced.
In this technical solution, optionally, calculating the radiation dose received by the actually measured object according to the actually measured unknown dose atlas and the dose regression curve includes:
and (4) bringing the first differential intensity of the EPR signal of the actually measured unknown dose spectrum into the dose regression curve, and calculating the unknown dose.
Through the dose regression curve, the radiation dose of the actually measured object can be calculated, the radiation dose calculation efficiency is greatly improved, and the time in the data processing process is reduced.
According to the technical scheme provided by the embodiment of the application, at least two test files and standard files which are obtained by known radiation doses and are not radiated are obtained, and the maps of the test files and the maps of the standard files are obtained; the test file and the standard file comprise magnetic field values of radiation doses and first differential strength values of EPR signals; acquiring the map characteristic value of each map, and processing the map characteristic value of each map by adopting a preset rule to obtain a normalized value of the map characteristic value of each test file; and constructing a dose regression curve according to the radiation dose of each test file and the normalized value of the map characteristic value. By executing the technical scheme, a dose regression curve is constructed by utilizing the radiation dose and the normalization value of the map characteristic value. The construction is completed through a program, the defect of the precision of the traditional spectral subtraction method is made up, and the linearity of a dose regression curve is improved. Dose regression curves can also be visualized.
Example two
Fig. 6 is a schematic diagram of an analysis process of radiation dose provided in the second embodiment of the present application, and the second embodiment is further optimized based on the first embodiment. The concrete optimization is as follows: acquiring the atlas characteristic values of each atlas, and processing the atlas characteristic values of each atlas by adopting a preset rule to obtain the normalized values of the atlas characteristic values of each test file, wherein the normalized values comprise: for each test file, acquiring a signal peak value, a signal line width, a Marker peak value and a Marker line width of the graph, and determining the difference value of the area normalization value of each test file and the area normalization value of the standard file by adopting a spectral subtraction method to obtain the normalization value of the graph characteristic value of each test file; or acquiring a signal peak value and a signal line width of a map of the standard file, and fitting to obtain a theoretical background spectrum; fitting the signal peak value and the signal line width of the atlas of the target dose test file to obtain a theoretical target dose spectrum; and obtaining the normalization value of the spectrum characteristic value of each test file according to the theoretical background spectrum and the theoretical target dose spectrum. The details which are not described in detail in this embodiment are shown in the first embodiment. As shown in fig. 6, the method comprises the steps of:
s610, obtaining at least two test files and standard files which are obtained by known radiation doses, and obtaining the maps of the test files and the maps of the standard files; wherein the test file and the standard file comprise magnetic field values of radiation doses and first differential intensity values of the EPR signal;
s620, for each test file, acquiring a signal peak value, a signal line width, a Marker peak value and a Marker line width of the graph, and determining a difference value between the area normalization value of each test file and the area normalization value of the standard file by adopting a spectral subtraction method to obtain a normalization value of the graph characteristic value of each test file;
alternatively, the first and second electrodes may be,
acquiring a signal peak value and a signal line width of a map of a standard file, and fitting to obtain a theoretical background spectrum; fitting the signal peak value and the signal line width of the atlas of the target dose test file to obtain a theoretical target dose spectrum; and obtaining the normalization value of the spectrum characteristic value of each test file according to the theoretical background spectrum and the theoretical target dose spectrum.
In this embodiment, the second integral of the spectrum is proportional to the square of the peak-to-peak value multiplied by the line width, and the absorption line area can be determined according to the signal peak-to-peak value and the signal line width. And determining the Marker area according to the Marker peak value and the Marker line width. And dividing the area of the absorption spectrum line by the area of the Marker to determine the area normalization value of each test file. And subtracting the area normalization value of each test file from the area normalization value of the standard file to determine the normalization value of the map characteristic value of each test file.
In this embodiment, the theoretical background spectrum can be obtained by fitting the signal spectral line by the nonlinear least square fitting method using the signal peak value and the signal line width of the standard file spectrum as conditions. And fitting the signal spectral line by using the signal peak value and the signal line width of the graph of each test file as conditions through a nonlinear least square fitting method to obtain a theoretical target dose spectrum. And taking the signal peak value and the signal line width of the atlas of the target dose test file as input, and processing the theoretical background spectrum and the theoretical target dose spectrum through a preset rule to obtain a normalized value of the atlas characteristic value of each test file.
In the technical scheme, optionally, for each test file, obtaining a signal peak value, a signal line width, a Marker peak value and a Marker line width of the graph, and determining a difference value between an area normalization value of each test file and an area normalization value of a standard file by using a spectral subtraction method to obtain a normalization value of the graph characteristic value of each test file, including:
acquiring a signal peak value and a signal line width of a map, and determining the area of an absorption spectral line according to the signal peak value and the signal line width;
normalizing the area of the absorption spectrum line and the Marker area determined by the Marker peak value and the Marker line width to obtain a normalized area;
the normalized area is proportional to the quality of the current test file to obtain an area normalized value of the current test file;
and determining the difference value between the area normalization value of the current test file and the area normalization value of the standard file to obtain the normalization value of the map characteristic value of each test file.
In the scheme, the area of an absorption spectrum line can be obtained by multiplying the signal peak value by the square of the signal line width, the area of a Marker is obtained by multiplying the Marker peak value by the square of the Marker line width, the normalized area is obtained by dividing the area of the absorption spectrum line by the area of the Marker after the area of the absorption spectrum line and the area of the Marker is obtained, and the normalized area is divided by the quality of the current test file to obtain the area normalized value of the current test file.
The normalized value of the spectrogram characteristic value of each test file is obtained by using spectral subtraction through the signal peak value, the signal line width, the Marker peak value and the Marker line width, the area is used for replacing the signal peak value, the accuracy is higher compared with the estimation by using the peak value, meanwhile, the time for processing spectrogram data is reduced by programming, and the calculation efficiency is improved.
In this technical solution, optionally, the absorption line area is calculated by using the following formula:
Ssignal∝SDy*SHpp2；
Wherein S isSignalFor the absorption line area, SDy is the signal peak value, SHpp is the signal line width;
the Marker area is calculated by adopting the following formula:
SMarker∝MDy*MHpp2；
wherein S isMarkerAnd MDy is the Marker area, MDy is the Marker peak value, and MHpp is the Marker line width.
It will be appreciated that the second integral of the spectrum is proportional to the peak-to-peak value times the square of the line width, and the absorption line area can be determined from the signal peak-to-peak value and the signal line width. And determining the Marker area according to the Marker peak value and the Marker line width.
The normalized value of the map characteristic value of each test file is obtained by using spectral subtraction through the signal peak value, the signal line width, the Marker peak value and the Marker line width, the area is used for replacing the signal peak value, and compared with the estimation by using the peak value, the accuracy is higher.
In the technical scheme, optionally, a signal peak value and a signal line width of a map of a standard file are obtained and fitted to obtain a theoretical background spectrum; fitting the signal peak value and the signal line width of the atlas of the target dose test file to obtain a theoretical target dose spectrum; and obtaining a normalization value of the spectrum characteristic value of each test file according to the theoretical background spectrum and the theoretical target dose spectrum, wherein the normalization value comprises the following steps:
acquiring a signal peak value and a signal line width of a map of a standard file, and fitting to obtain a theoretical background spectrum;
fitting the signal peak value and the signal line width of the atlas of the target dose test file to obtain a theoretical target dose spectrum; the target dose test file is a test file with a dose within a preset dose range;
determining a fitting coefficient according to the theoretical background spectrum and the theoretical target dose spectrum;
and determining the normalization value of the map characteristic value of each test file according to the fitting coefficient.
Wherein the preset dose range can be set according to the radiation dose analysis requirement.
In this embodiment, a signal spectral line may be fitted by a nonlinear least squares fitting method using a signal peak value and a signal line width of a spectrum of a standard file as conditions, so as to obtain a theoretical background spectrum. And fitting the signal spectral line by using the signal peak value and the signal line width of the graph of each test file as conditions through a nonlinear least square fitting method to obtain a theoretical target dose spectrum. And performing least square fitting on the theoretical background spectrum and the theoretical target dose spectrum by using the signal peak value and the signal line width of the spectrum of the target dose test file as input and using a preset rule to obtain a fitting coefficient. And after the fitting coefficient is determined, multiplying the fitting coefficient by the area determined by the signal peak value and the signal line width, and dividing the area by the Marker area determined by the Marker peak value and the Marker line width for normalization to obtain a normalized value of the map characteristic value of each test file.
The program is used to complete the fitting method and improve the linearity of the regression curve.
In this technical solution, optionally, before obtaining a peak value of a signal peak and a line width of a signal of a spectrum of a standard file, and fitting to obtain a theoretical background spectrum, the method further includes:
determining distribution positions of characteristic parts of the atlas;
correspondingly, obtaining a signal peak value and a signal line width of a map of the standard file, and fitting to obtain a theoretical background spectrum, wherein the theoretical background spectrum comprises the following steps:
fitting the standard file by taking the distribution positions, the signal peak value and the signal line width of the atlas of the standard file as the input of nonlinear least squares to obtain a theoretical background spectrum;
correspondingly, fitting the signal peak value and the signal line width of the atlas of the target dose test file to obtain a theoretical target dose spectrum, which comprises the following steps:
and fitting the target dose test file by taking the distribution position, the signal peak value and the signal line width of the graph of the target dose test file as the input of nonlinear least squares to obtain a theoretical target dose spectrum.
Wherein, the distribution position may refer to a specific g value, i.e. the lambdad factor. Since the baseline of each measured profile is not at 0, the up and down amplitude of the profile needs to be adjusted, with the level adjustment controlled by the profile position. Preferably, the distribution position may be 2.005, i.e., the level adjustment is made according to the distribution position. The theoretical background spectrum and the theoretical target dose spectrum can be obtained by fitting on the same distribution positions.
The fitting of the dose regression curve is facilitated by fitting the theoretical background spectrum and the theoretical target dose spectrum on the same distribution position, and the fitting precision of the dose regression curve is improved.
In this technical solution, optionally, the method includes:
fitting is performed by using the following fitting formula:
F＝Ao*LBKG+Bo*LRIS；
wherein, F is an experimental spectrum to be fitted, and Ao and Bo are fitting coefficients of LBKG and LRIS respectively; LBKG is the theoretical background spectrum and LRIS the theoretical target dose spectrum.
In the scheme, the signal peak value and the signal line width of the map of the standard file and the signal peak value and the signal line width of the map of the target dose test file are obtained, a theoretical background spectrum is obtained according to the signal peak value and the signal line width of the map of the standard file in a fitting mode, and a theoretical target dose spectrum is obtained according to the signal peak value and the signal line width of the map of the target dose test file in a fitting mode. And a fitting formula is utilized to carry out nonlinear least square fitting on the data.
The theoretical background spectrum and the theoretical target dose spectrum are used as known conditions for formula fitting to fit the known dose spectrum, and fitting coefficients can be obtained, so that the normalization value of the spectrum characteristic value of each test file is determined, fitting of a dose regression curve is facilitated, and the linearity of the dose regression curve is improved.
In this embodiment, optionally, determining a fitting coefficient according to the theoretical background spectrum and the theoretical target dose spectrum includes:
and determining a fitting coefficient Bo according to the theoretical background spectrum, the theoretical target dose spectrum and a fitting coefficient Ao in a predefined fitting formula.
It can be understood that the fitting coefficient Bo can be calculated according to the fitting formula according to the theoretical background spectrum, the theoretical target dose spectrum and the fitting coefficient in the fitting formula.
By determining the fitting coefficients Bo, the construction of a dose regression curve can be achieved based on the fitting coefficients.
In this technical solution, optionally, determining a normalized value of the feature value of the atlas of each test file according to the fitting coefficient includes:
determining a spectrum characteristic value of each test file according to the fitting coefficient Bo, and determining an initial absorption spectrum line area;
normalizing the area of the initial absorption spectrum line and the Marker area determined by the Marker peak value and the Marker line width to obtain a normalized area;
and the normalized area is proportional to the quality of the current test file to obtain an area normalized value of the current test file.
In the scheme, the fitting coefficient can be multiplied by the square of the signal peak value and the signal line width of each test file to obtain the area of the initial absorption spectral line.
Specifically, after the initial absorption spectral line area is obtained, the initial absorption spectral line area is divided by the Marker area to obtain a normalized area, and the normalized area is divided by the quality of the current test file to obtain an area normalized value of the current test file.
By determining the area normalization values for the current test files, a dose fitting regression curve may be constructed based on the area normalization values for each current test file. The program is used to complete the fitting method, and the linearity of the dose regression curve is improved.
S630, constructing a dose regression curve according to the radiation dose of each test file and the normalization value of the map characteristic value.
According to the technical scheme provided by the embodiment of the application, at least two test files and standard files which are obtained by known radiation doses and are not radiated are obtained, and the maps of the test files and the maps of the standard files are obtained; the test file and the standard file comprise magnetic field values of radiation doses and first differential strength values of EPR signals; for each test file, acquiring a signal peak value, a signal line width, a Marker peak value and a Marker line width of the graph, and determining the difference value of the area normalization value of each test file and the area normalization value of the standard file by adopting a spectral subtraction method to obtain the normalization value of the graph characteristic value of each test file; or acquiring a signal peak value and a signal line width of a map of the standard file, and fitting to obtain a theoretical background spectrum; fitting the signal peak value and the signal line width of the atlas of the target dose test file to obtain a theoretical target dose spectrum; obtaining a normalized value of the spectrum characteristic value of each test file according to the theoretical background spectrum and the theoretical target dose spectrum; and constructing a dose regression curve according to the radiation dose of each test file and the normalized value of the map characteristic value. By executing the technical scheme, a dose regression curve is constructed by utilizing the radiation dose and the normalization value of the map characteristic value. Construction is completed through a program, and the linearity of a dose regression curve is improved. Dose regression curves can also be visualized.
EXAMPLE III
Fig. 7 is a schematic structural diagram of an apparatus for analyzing a radiation dose according to a third embodiment of the present application, and as shown in fig. 7, the apparatus for analyzing a radiation dose includes:
the file acquisition module 710 is configured to acquire at least two test files and standard files which are obtained with known radiation doses and are not radiated, and maps of the test files and maps of the standard files; wherein the test file and the standard file comprise magnetic field values of radiation doses and first differential intensity values of the EPR signal;
a normalized value obtaining module 720, configured to obtain an atlas feature value of each atlas, and process the atlas feature value of each atlas by using a preset rule to obtain a normalized value of the atlas feature value of each test file;
and a dose regression curve construction module 730, configured to construct a dose regression curve according to the radiation dose of each test file and the normalized value of the map feature value.
In this embodiment, the apparatus for analyzing radiation dose further includes a spectrum display module, configured to display the spectrum of each test file and the spectrum of the standard file.
In this technical solution, optionally, the normalization value obtaining module 720 includes:
a normalization value obtaining unit, configured to obtain a signal peak value, a signal line width, a Marker peak value, and a Marker line width of the graph for each test file, and determine a difference value between the area normalization value of each test file and the area normalization value of the standard file by using a spectral subtraction method to obtain a normalization value of the graph characteristic value of each test file;
alternatively, the first and second electrodes may be,
the fitting normalization value obtaining unit is used for obtaining a signal peak value and a signal line width of a map of the standard file, and fitting to obtain a theoretical background spectrum; fitting the signal peak value and the signal line width of the atlas of the target dose test file to obtain a theoretical target dose spectrum; and obtaining the normalization value of the spectrum characteristic value of each test file according to the theoretical background spectrum and the theoretical target dose spectrum.
In this technical solution, optionally, the normalization value obtaining unit includes:
the absorption spectral line area determining subunit is used for acquiring a signal peak value and a signal line width of the atlas and determining the absorption spectral line area according to the signal peak value and the signal line width;
the normalized area obtaining subunit is used for carrying out normalization processing on the absorption spectral line area and a Marker area determined by a Marker peak value and a Marker line width to obtain a normalized area;
the area normalization value obtaining subunit is used for making a proportion between the normalization area and the quality of the current test file to obtain an area normalization value of the current test file;
and the normalization value obtaining subunit is used for determining the difference value between the area normalization value of the current test file and the area normalization value of the standard file to obtain the normalization value of the map characteristic value of each test file.
In this technical solution, optionally, the absorption line area is calculated by using the following formula:
Ssignal∝SDy*SHpp2；
Wherein S isSignalFor the absorption line area, SDy is the signal peak value, SHpp is the signal line width;
the Marker area is calculated by adopting the following formula:
SMarker∝MDy*MHpp2；
wherein S isMarkerAnd MDy is the Marker area, MDy is the Marker peak value, and MHpp is the Marker line width.
In this embodiment, optionally, the dose regression curve constructing module 730 includes:
the radiation dose acquisition unit is used for acquiring the radiation dose of each test file;
the coordinate pair construction unit is used for constructing the radiation dose of each test file and the normalized value of the map characteristic value of the test file into a coordinate pair and projecting the coordinate pair into a coordinate system;
and the dose regression curve obtaining unit is used for performing linear fitting on the projection points of the test files in the coordinate system to obtain a dose regression curve.
In this embodiment, optionally, the dose regression curve constructing module 730 further includes:
and the decision coefficient determining unit is used for determining the decision coefficient of the radiation dose of each test file and the normalized value of the map characteristic value so as to evaluate the linear correlation degree of the dose regression curve.
In this embodiment, optionally, the dose regression curve constructing module 730 further includes:
and the prediction standard error determining unit is used for determining the projection points of each test file and the prediction standard error of the dose regression curve so as to evaluate the prediction accuracy of the dose regression curve.
In this technical solution, optionally, the fitting the normalized value to obtain the unit includes:
a theoretical background spectrum obtaining subunit, configured to obtain a signal peak value and a signal line width of a spectrum of the standard file, and perform fitting to obtain a theoretical background spectrum;
a theoretical target dose spectrum obtaining subunit, configured to fit a signal peak value and a signal line width of a spectrum of the target dose test file to obtain a theoretical target dose spectrum; the target dose test file is a test file with a dose within a preset dose range;
the fitting coefficient determining subunit is used for determining a fitting coefficient according to the theoretical background spectrum and the theoretical target dose spectrum;
and fitting the normalized value to obtain a subunit, which is used for determining the normalized value of the map characteristic value of each test file according to the fitting coefficient.
In this technical solution, optionally, the fitting the normalized value to obtain the unit further includes:
a distribution position determining subunit for determining a distribution position of the characteristic portion of the map;
correspondingly, the theoretical background spectrum yields subunits specifically for:
fitting the standard file by taking the distribution positions, the signal peak value and the signal line width of the atlas of the standard file as the input of nonlinear least squares to obtain a theoretical background spectrum;
accordingly, the theoretical target dose spectrum yields subunits specifically for:
and fitting the target dose test file by taking the distribution position, the signal peak value and the signal line width of the graph of the target dose test file as the input of nonlinear least squares to obtain a theoretical target dose spectrum.
In this technical solution, optionally, the apparatus includes:
fitting is performed by using the following fitting formula:
F＝Ao*LBKG+Bo*LRIS；
wherein, F is an experimental spectrum to be fitted, and Ao and Bo are fitting coefficients of LBKG and LRIS respectively; LBKG is the theoretical background spectrum and LRIS the theoretical target dose spectrum.
In this technical solution, optionally, the fitting coefficient determining subunit is specifically configured to:
and determining a fitting coefficient Bo according to the theoretical background spectrum, the theoretical target dose spectrum and a fitting coefficient Ao in a predefined fitting formula.
In this technical solution, optionally, the fitting normalization value obtains a subunit, which is specifically configured to:
determining a spectrum characteristic value of each test file according to the fitting coefficient Bo, and determining an initial absorption spectrum line area;
normalizing the area of the initial absorption spectrum line and the Marker area determined by the Marker peak value and the Marker line width to obtain a normalized area;
and the normalized area is proportional to the quality of the current test file to obtain an area normalized value of the current test file.
In this technical solution, optionally, the apparatus further includes:
the primary differential intensity extraction module of the EPR signal is used for acquiring an actually measured unknown dose map and extracting the primary differential intensity of the EPR signal in the map;
and the radiation dose calculation module is used for calculating the radiation dose of the actually measured object according to the actually measured unknown dose atlas and the dose regression curve.
In this technical solution, optionally, the radiation dose calculation module is specifically configured to:
and (4) bringing the first differential intensity of the EPR signal of the actually measured unknown dose spectrum into the dose regression curve, and calculating the unknown dose.
The product can execute the method provided by the embodiment of the application, and has the corresponding functional modules and beneficial effects of the execution method.
Example four
Embodiments of the present application also provide a storage medium containing computer-executable instructions, which when executed by a computer processor, perform a method of radiation dose analysis, the method comprising:
obtaining at least two test files with known radiation dose, standard files without radiation, maps of the test files and maps of the standard files; wherein the test file and the standard file comprise magnetic field values of radiation doses and first differential intensity values of the EPR signal;
acquiring the map characteristic value of each map, and processing the map characteristic value of each map by adopting a preset rule to obtain a normalized value of the map characteristic value of each test file;
and constructing a dose regression curve according to the radiation dose of each test file and the normalized value of the map characteristic value.
Storage medium-any of various types of memory devices or storage devices. The term "storage medium" is intended to include: mounting media such as CD-ROM, floppy disk, or tape devices; computer system memory or random access memory such as DRAM, DDR RAM, SRAM, EDO RAM, Lanbas (Rambus) RAM, etc.; non-volatile memory such as flash memory, magnetic media (e.g., hard disk or optical storage); registers or other similar types of memory elements, etc. The storage medium may also include other types of memory or combinations thereof. In addition, the storage medium may be located in the computer system in which the program is executed, or may be located in a different second computer system connected to the computer system through a network (such as the internet). The second computer system may provide the program instructions to the computer for execution. The term "storage medium" may include two or more storage media that may reside in different locations, such as in different computer systems that are connected by a network. The storage medium may store program instructions (e.g., embodied as a computer program) that are executable by one or more processors.
Of course, the storage medium provided in the embodiments of the present application contains computer-executable instructions, and the computer-executable instructions are not limited to the analysis operation of the radiation dose as described above, and may also perform related operations in the analysis method of the radiation dose provided in any embodiments of the present application.
EXAMPLE five
The embodiment of the application provides electronic equipment, and the analysis device of the radiation dose provided by the embodiment of the application can be integrated in the electronic equipment. Fig. 8 is a schematic structural diagram of an electronic device according to a fifth embodiment of the present application. As shown in fig. 8, the present embodiment provides an electronic device 800, which includes: one or more processors 820; storage 810 for storing one or more programs that, when executed by the one or more processors 820, cause the one or more processors 820 to implement a method for analyzing radiation dose provided by an embodiment of the present application, the method comprising:
obtaining at least two test files with known radiation dose, standard files without radiation, maps of the test files and maps of the standard files; wherein the test file and the standard file comprise magnetic field values of radiation doses and first differential intensity values of the EPR signal;
acquiring the map characteristic value of each map, and processing the map characteristic value of each map by adopting a preset rule to obtain a normalized value of the map characteristic value of each test file;
and constructing a dose regression curve according to the radiation dose of each test file and the normalized value of the map characteristic value.
Of course, those skilled in the art will appreciate that the processor 820 may also implement aspects of the radiation dose analysis methods provided in any of the embodiments of the present application.
The electronic device 800 shown in fig. 8 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
As shown in fig. 8, the electronic device 800 includes a processor 820, a storage 810, an input device 830, and an output device 840; the number of the processors 820 in the electronic device may be one or more, and one processor 820 is taken as an example in fig. 8; the processor 820, the storage 810, the input 830, and the output 840 in the electronic device may be connected by a bus or other means, such as the bus 850 in fig. 8.
The storage device 810 is a computer-readable storage medium for storing software programs, computer-executable programs, and module units, such as program instructions corresponding to the method for analyzing radiation dose in the embodiments of the present application.
The storage device 810 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal, and the like. Further, the storage 810 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, storage 810 may further include memory located remotely from processor 820, which may be connected via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device 830 may be used to receive input numbers, character information, or voice information, and generate key signal inputs related to user settings and function control of the electronic apparatus. The output device 840 may include a display screen, a speaker, and other electronic devices.
The electronic equipment provided by the embodiment of the application can achieve the purposes of making up the deficiency of the precision of the traditional spectral subtraction method and improving the linearity of a regression curve.
The radiation dose analysis device, the storage medium and the electronic device provided in the above embodiments may perform the radiation dose analysis method provided in any embodiment of the present application, and have corresponding functional modules and beneficial effects for performing the method. The details of the technique not described in detail in the above examples can be found in the method for analyzing the radiation dose provided in any of the examples of the present application.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present application and the technical principles employed. It will be understood by those skilled in the art that the present application is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the application. Therefore, although the present application has been described in more detail with reference to the above embodiments, the present application is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present application, and the scope of the present application is determined by the scope of the appended claims.
Claims (17)
1. A method of analyzing radiation dose, comprising:
obtaining at least two test files with known radiation dose, standard files without radiation, maps of the test files and maps of the standard files; wherein the test file and the standard file comprise magnetic field values of radiation doses and first differential intensity values of the EPR signal;
acquiring the map characteristic value of each map, and processing the map characteristic value of each map by adopting a preset rule to obtain a normalized value of the map characteristic value of each test file;
and constructing a dose regression curve according to the radiation dose of each test file and the normalized value of the map characteristic value.
2. The method according to claim 1, wherein obtaining the atlas feature value of each atlas, and processing the atlas feature value of each atlas by using a preset rule to obtain a normalized value of the atlas feature value of each test document comprises:
for each test file, acquiring a signal peak value, a signal line width, a Marker peak value and a Marker line width of the graph, and determining the difference value of the area normalization value of each test file and the area normalization value of the standard file by adopting a spectral subtraction method to obtain the normalization value of the graph characteristic value of each test file;
alternatively, the first and second electrodes may be,
acquiring a signal peak value and a signal line width of a map of a standard file, and fitting to obtain a theoretical background spectrum; fitting the signal peak value and the signal line width of the atlas of the target dose test file to obtain a theoretical target dose spectrum; and obtaining the normalization value of the spectrum characteristic value of each test file according to the theoretical background spectrum and the theoretical target dose spectrum.
3. The method of claim 2, wherein obtaining a peak-to-peak signal value, a line width signal value, a peak-to-peak Marker value, and a line width Marker of the graph for each test file, and determining a difference between the area normalization value of each test file and the area normalization value of the standard file by using spectral subtraction to obtain the normalization value of the graph feature value of each test file comprises:
acquiring a signal peak value and a signal line width of a map, and determining the area of an absorption spectral line according to the signal peak value and the signal line width;
normalizing the area of the absorption spectrum line and the Marker area determined by the Marker peak value and the Marker line width to obtain a normalized area;
the normalized area is proportional to the quality of the current test file to obtain an area normalized value of the current test file;
and determining the difference value between the area normalization value of the current test file and the area normalization value of the standard file to obtain the normalization value of the map characteristic value of each test file.
4. The method of claim 3, wherein the absorption line area is calculated using the following equation:
Ssignal∝SDy*SHpp2；
Wherein S isSignalFor the absorption line area, SDy is the signal peak value, SHpp is the signal line width;
the Marker area is calculated by adopting the following formula:
SMarker∝MDy*MHpp2；
wherein S isMarkerAnd MDy is the Marker area, MDy is the Marker peak value, and MHpp is the Marker line width.
5. The method of claim 1, wherein constructing a dose regression curve based on the normalized values of radiation dose and profile feature values for each test file comprises:
acquiring the radiation dose of each test file;
constructing a coordinate pair by the radiation dose of each test file and the normalized value of the map characteristic value of the test file, and projecting the coordinate pair into a coordinate system;
and performing linear fitting on the projection points of the test files in the coordinate system to obtain a dose regression curve.
6. The method of claim 5, wherein after linearly fitting the projected points of each test file in the coordinate system to obtain a dose regression curve, the method further comprises:
and determining a decision coefficient of the radiation dose of each test file and the normalized value of the characteristic value of the spectrum so as to evaluate the linear correlation degree of the dose regression curve.
7. The method of claim 5, wherein after linearly fitting the projected points of each test file in the coordinate system to obtain a dose regression curve, the method further comprises:
and determining the prediction standard error of the projection point of each test file and the dose regression curve so as to evaluate the prediction accuracy of the dose regression curve.
8. The method according to claim 2, wherein the signal peak value and the signal line width of the map of the standard file are obtained and fitted to obtain a theoretical background spectrum; fitting the signal peak value and the signal line width of the atlas of the target dose test file to obtain a theoretical target dose spectrum; and obtaining a normalization value of the spectrum characteristic value of each test file according to the theoretical background spectrum and the theoretical target dose spectrum, wherein the normalization value comprises the following steps:
acquiring a signal peak value and a signal line width of a map of a standard file, and fitting to obtain a theoretical background spectrum;
fitting the signal peak value and the signal line width of the atlas of the target dose test file to obtain a theoretical target dose spectrum; the target dose test file is a test file with a dose within a preset dose range;
determining a fitting coefficient according to the theoretical background spectrum and the theoretical target dose spectrum;
and determining the normalization value of the map characteristic value of each test file according to the fitting coefficient.
9. The method of claim 8, wherein before obtaining the peak signal value and the line width of the signal of the standard document, and fitting the peak signal value and the line width of the signal to obtain a theoretical background spectrum, the method further comprises:
determining distribution positions of characteristic parts of the atlas;
correspondingly, obtaining a signal peak value and a signal line width of a map of the standard file, and fitting to obtain a theoretical background spectrum, wherein the theoretical background spectrum comprises the following steps:
fitting the standard file by taking the distribution positions, the signal peak value and the signal line width of the atlas of the standard file as the input of nonlinear least squares to obtain a theoretical background spectrum;
correspondingly, fitting the signal peak value and the signal line width of the atlas of the target dose test file to obtain a theoretical target dose spectrum, which comprises the following steps:
and fitting the target dose test file by taking the distribution position, the signal peak value and the signal line width of the graph of the target dose test file as the input of nonlinear least squares to obtain a theoretical target dose spectrum.
10. The method of claim 8, comprising:
fitting is performed by using the following fitting formula:
F＝Ao*LBKG+Bo*LRIS；
wherein, F is an experimental spectrum to be fitted, and Ao and Bo are fitting coefficients of LBKG and LRIS respectively; LBKG is the theoretical background spectrum and LRIS the theoretical target dose spectrum.
11. The method of claim 10, wherein determining a fitting coefficient based on the theoretical background spectrum and the theoretical target dose spectrum comprises:
and determining a fitting coefficient Bo according to the theoretical background spectrum, the theoretical target dose spectrum and a fitting coefficient Ao in a predefined fitting formula.
12. The method of claim 11, wherein determining a normalized value for the profile feature value for each test document based on the fitting coefficients comprises:
determining a spectrum characteristic value of each test file according to the fitting coefficient Bo, and determining an initial absorption spectrum line area;
normalizing the area of the initial absorption spectrum line and the Marker area determined by the Marker peak value and the Marker line width to obtain a normalized area;
and the normalized area is proportional to the quality of the current test file to obtain an area normalized value of the current test file.
13. The method of claim 1, wherein after constructing the dose regression curve, the method further comprises:
acquiring an actually measured unknown dose map, and extracting the first differential intensity of an EPR signal in the map;
and calculating the radiation dose of the actually measured object according to the actually measured unknown dose atlas and the dose regression curve.
14. The method of claim 13, wherein calculating the radiation dose to which the measured object is exposed based on the measured unknown dose map and the dose regression curve comprises:
and (4) bringing the first differential intensity of the EPR signal of the actually measured unknown dose spectrum into the dose regression curve, and calculating the unknown dose.
15. An apparatus for analyzing a radiation dose, comprising:
the file and map acquisition module is used for acquiring at least two test files obtained by known radiation doses, standard files which are not radiated, maps of the test files and maps of the standard files; wherein the test file and the standard file comprise magnetic field values of radiation doses and first differential intensity values of the EPR signal;
the normalization value obtaining module is used for obtaining the map characteristic value of each map, and processing the map characteristic value of each map by adopting a preset rule to obtain the normalization value of the map characteristic value of each test file;
and the dose regression curve construction module is used for constructing a dose regression curve according to the radiation dose of each test file and the normalized value of the map characteristic value.
16. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out a method of analyzing a radiation dose according to any one of claims 1-14.
17. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor, when executing the computer program, implements the method of analyzing a radiation dose according to any of claims 1-14.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110666372.8A CN113312790A (en) | 2021-06-16 | 2021-06-16 | Radiation dose analysis method and device, storage medium and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110666372.8A CN113312790A (en) | 2021-06-16 | 2021-06-16 | Radiation dose analysis method and device, storage medium and electronic equipment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113312790A true CN113312790A (en) | 2021-08-27 |
Family
ID=77378997
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110666372.8A Pending CN113312790A (en) | 2021-06-16 | 2021-06-16 | Radiation dose analysis method and device, storage medium and electronic equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113312790A (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040081673A1 (en) * | 2000-07-13 | 2004-04-29 | Rayner Timothy Edward | Compositions and methods for the treatment of skin damage |
| US20070173787A1 (en) * | 2005-11-01 | 2007-07-26 | Huang Mark C T | Thin-film nitinol based drug eluting stent |
| CN104136461A (en) * | 2011-09-22 | 2014-11-05 | 安姆根有限公司 | CD27l antigen binding proteins |
-
2021
- 2021-06-16 CN CN202110666372.8A patent/CN113312790A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040081673A1 (en) * | 2000-07-13 | 2004-04-29 | Rayner Timothy Edward | Compositions and methods for the treatment of skin damage |
| US20070173787A1 (en) * | 2005-11-01 | 2007-07-26 | Huang Mark C T | Thin-film nitinol based drug eluting stent |
| CN104136461A (en) * | 2011-09-22 | 2014-11-05 | 安姆根有限公司 | CD27l antigen binding proteins |
Non-Patent Citations (1)
| Title |
|---|
| 阎长鑫 等: ""指甲电子顺磁共振(EPＲ)波谱解析的数学模拟研究"", 《辐射防护》 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Vermeesch | Statistics for LA-ICP-MS based fission track dating | |
| Frank et al. | Chemometrics | |
| Berti et al. | Gravitational-wave spectroscopy of massive black holes with the space interferometer LISA | |
| López-Fernández et al. | LA-iMageS: a software for elemental distribution bioimaging using LA–ICP–MS data | |
| Fu et al. | High‐sensitivity moment magnetometry with the quantum diamond microscope | |
| Ivanov et al. | Heavy-to light-meson transition form factors | |
| Sharp et al. | Interpreting measurements of total alkalinity in marine and estuarine waters in the presence of proton-binding organic matter | |
| Ramsey | Improving the resolution of radiocarbon dating by statistical analysis | |
| Löffler et al. | A software package for the simulation of energy-loss magnetic chiral dichroism | |
| da Silva | Spreadsheet for designing valid least-squares calibrations: A tutorial | |
| McLean et al. | Algorithms and software for U‐Pb geochronology by LA‐ICPMS | |
| WO2020129895A1 (en) | Information processing device, method for controlling information processing device, and program | |
| CN104730042A (en) | Method for improving free calibration analysis precision by combining genetic algorithm with laser induced breakdown spectroscopy | |
| Tharaud et al. | uFREASI: user-FRiendly Elemental dAta procesSIng. A free and easy-to-use tool for elemental data treatment | |
| Parimbelli et al. | The effects of massive neutrinos on the linear point of the correlation function | |
| Milde et al. | Measurement uncertainty evaluation from correlated validation data: Determination of elemental impurities in pharmaceutical products by ICP-MS | |
| Yan et al. | An image features assisted line selection method in laser-induced breakdown spectroscopy | |
| WO2019223585A1 (en) | Seismic source inversion uncertainty analysis method, storage medium, and server | |
| Li et al. | Fundamental and practical aspects of machine learning for the peak picking of biomolecular NMR spectra | |
| Byun et al. | Constraining the growth rate of structure with phase correlations | |
| Marzocchi et al. | Characterisation, modelling and optimisation of the model of a HPGe detector with the aid of point sources | |
| Burkert | Electromagnetic excitations of baryon resonances | |
| CN113312790A (en) | Radiation dose analysis method and device, storage medium and electronic equipment | |
| Jeffries et al. | High-throughput studies of protein shapes and interactions by synchrotron small-angle X-ray scattering | |
| Haouet et al. | Validation of the Volhard method for chloride determination in food |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20210827 |