CN117017326A - Method for generating dual-energy X-ray for detecting bone density based on K-edge filtering - Google Patents
Method for generating dual-energy X-ray for detecting bone density based on K-edge filtering Download PDFInfo
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Abstract
The application relates to the technical field of medical equipment, in particular to a method for detecting bone mineral density by generating dual-energy X-rays based on K-edge filtering, which comprises the following steps: s1: generation of primary X-rays: inputting a constant voltage into an X-ray bulb tube to generate original X-rays; s2: generation of dual energy X-rays: the original X-rays are emitted to a K-edge filter, so that two rays with high energy and low energy are separated; s3: coupling of rays and wire harness: dual energy X-rays are emitted to a collimator. The application overcomes the defects of the prior art, and enhances the image by using a method of sharpening a mask, so that noise can be well restrained under the condition of not losing details, the edge contrast of the image is obvious and clear, the noise is hardly seen in a flat area, the application has good universality, and can help medical staff to identify bone details in the image, thereby improving the diagnosis accuracy and diagnosis efficiency of the medical staff on patients.
Description
Technical Field
The application relates to the technical field of medical equipment, in particular to a method for detecting bone density by generating dual-energy X-rays based on K-edge filtering.
Background
The incidence of osteoporosis and osteoporotic fractures is increasing. In particular, in female patients, osteoporosis is more pronounced. In addition, there is a risk of glucocorticoid-related osteoporosis in patients with rheumatic diseases, especially in patients who have long-term need for glucocorticoid. Osteoporosis has become a common disorder in residents following hypertension, diabetes, and coronary heart disease.
When the bone density is detected, the existing method for detecting the bone density by generating dual-energy X-rays based on K-edge filtering is easy to capture images with the problems of unclear details, blurred edges, noise and the like due to the interference of detection environments, so that the diagnosis result and the diagnosis efficiency of doctors on patients are affected.
Disclosure of Invention
The application aims to solve or at least alleviate the problems of unclear details, blurred edges, noise and the like of the shot images in the prior art, thereby influencing the diagnosis result and the diagnosis efficiency of doctors on patients.
In order to achieve the above purpose, the present application provides the following technical solutions: a method for generating dual energy X-rays for detecting bone density based on K-edge filtering, comprising the steps of:
s1: generation of primary X-rays: inputting a constant voltage into an X-ray bulb tube to generate original X-rays;
s2: generation of dual energy X-rays: the original X-rays are emitted to a K-edge filter, so that two rays with high energy and low energy are separated;
s3: coupling of rays and wire harness: transmitting the dual-energy X-rays to a collimator so as to couple the dual-energy X-rays with the maximum efficiency optically, and transmitting the coupled dual-energy X-rays to an electron beam limiter so as to limit the radiation range of the dual-energy X-rays;
s4: irradiation of dual-energy X-rays: scanning the to-be-detected part of the detected patient by using the coupled and harness dual-energy X-rays;
s5: and (3) data acquisition: the high-energy detector records the intensity of the attenuated high-energy X-rays passing through the detection part of the patient at each moment, and the low-energy detector records the intensity of the attenuated bottom-energy X-rays passing through the detection part of the patient at each moment;
s6: data processing and imaging: transmitting the data acquired by the data of the high-energy detector and the low-energy detector to a computer to remove the influence of partial soft tissues on a measurement result, and then transmitting the data to a data acquisition system through an analog-to-digital converter to generate a required digital image;
s7: processing of generating an image: the method of using the unsharp mask is used for image enhancement, and noise of the image is reduced.
Optionally, the X-ray ball in the step S1 is a latent energy X-ray ball tube, so that a high voltage of alookv is applied to the X-ray ball tube to generate a universal energy spectrum X-ray with continuous 100 keV.
Optionally, in the step S2, the edge filter selects a rare earth filter containing heavy samarium Sm or cerium Ce to filter the X-ray beam. So that the X-ray beam after filtering through the K-edge becomes a dual energy X-ray containing two specific energy spectrum peaks (45 keV and 80 keV).
Optionally, the high-energy detector and the low-energy detector in the step S5 are both detectors with discriminators, and the discriminators are scintillators made of NaI materials, so that different specification characteristics can generate different scintillation brightness according to X-rays with different energy spectrum sections, and the electric signals are amplified and output after being detected by a photomultiplier according to the scintillation.
Optionally, the dual-energy X-ray scanning method in step S4 is a cone scanning method. Compared with a linear scanning mode, the conical scanning mode can effectively improve the efficiency of the whole scanning process, and further improve the efficiency of the whole bone mineral density detection.
Optionally, the method for increasing the image in step S7 includes the following steps:
s71: combining the two images, each position being regarded as a vector, thereby obtaining an image with each pixel as a vector;
s72: calculating a covariance matrix of the current window;
s73: obtaining eigenvalues lambda in matrix 1 And lambda (lambda) 2 ；
S74: judging eigenvalue lambda in matrix 1 -λ 2 Whether or not it is greater than a threshold T 1 If |lambda 1 -λ 2 |≥T 1 Then the current pixel is used as a boundary, and the gain value K of the current pixel is obtained from the substitution formula; if |lambda 1 -λ 2 |<T 1 And lambda is 2 >T 2 Then the current pixel is a flat region and the gain value can be set to a minimum value of 1; if |lambda 1 -λ 2 |<T 1 . And lambda is 2 ≤T 2 Then the current pixel is noise, the point should be suppressed, and the gain value may be set to 0, so that the noise pixel corresponding to the high frequency portion will not be superimposed on the original image:
s75: will be% 1 -λ 2 And carrying out normalization processing according to a formula, obtaining a gain coefficient K, and then substituting the gain coefficient K into a sharpening mask algorithm of the high-energy image and the low-energy image respectively, so as to obtain the enhanced image.
Optionally, the formula in step S74 is:
optionally, the formula in the step S75 is
Optionally, the step of removing the influence of the removed part of the soft tissue on the measurement result in the step S6 is:
s61: acquiring quadrants of two X-rays obtained under X-rays with different energies;
s62: energy subtraction is performed on each quadrant of two X-rays obtained under X-rays of different energies.
Compared with the prior art, the application has the beneficial effects that:
(1) The method for enhancing the image by using the anti-sharpening mask can well inhibit noise under the condition of not losing details, has obvious edge contrast of the image, is quite clear, almost does not see noise in a flat area, has good universality, can help medical staff to identify skeleton details in the image, and further improves the diagnosis accuracy and diagnosis efficiency of the medical staff on patients.
(2) According to the application, the coupled dual-energy X-rays are emitted into the electron beam limiter, so that the radiation range of the dual-energy X-rays can be effectively limited, normal tissues outside a target area are protected, key points are made, and organs are protected from radiation injury.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely, and it is apparent that the described embodiments are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
A method for generating dual energy X-rays for detecting bone density based on K-edge filtering, comprising the steps of: s1: generation of primary X-rays: inputting a constant voltage into an X-ray bulb tube to generate original X-rays; the X-ray ball in the step S1 is a potential type X-ray ball tube, so that the X-ray ball tube is added with high voltage of lOOkV, and a universal energy spectrum X-ray with continuous 100keV is generated.
S2: generation of dual energy X-rays: the original X-rays are transmitted to a K-edge filter, the X-ray bundle is filtered by a rare earth filter containing samarium Sm or cerium Ce in the step S2, so that the X-ray bundle filtered by the K-edge is changed into dual-energy X-rays containing two specific energy spectrum peaks (45 keV and 80 keV), when specific X-rays pass through an object, bone density measurement is carried out on different absorption amounts of tissues with different energies, wherein the imaging resolution ratio of the low-energy X-rays to soft tissues is highest, the imaging resolution ratio of the high-energy X-rays to the soft tissues is highest, the difference between the high-energy X-rays and the low-energy X-rays is small when the X-rays penetrate through a human body and the difference between the high-energy X-rays and the soft tissues is large, the high-energy X-rays and the low-energy X-rays are subjected to calculation treatment after the corresponding detection probes are used for collecting signals, and the effects of the soft tissues on bone density measurement can be eliminated;
s3: coupling of rays and wire harness: the dual-energy X-ray is emitted to the collimator, so that the optical coupling of the dual-energy X-ray with the maximum efficiency is realized, and then the coupled dual-energy X-ray is emitted to the electron beam limiter to limit the radiation range of the dual-energy X-ray, so that normal tissues outside a target area are protected, key points are made, and organs are protected from radiation injury.
S4: irradiation of dual-energy X-rays: the dual-energy X-ray of the coupling and the wire harness scans the part to be detected of the detected patient, the mode of scanning the part to be detected of the detected patient by the dual-energy X-ray in the step S4 is a conical scanning mode, and the specific conical scanning mode can effectively improve the efficiency of the whole scanning process compared with a linear scanning mode, so that the efficiency of detecting the whole bone density is improved.
S5: and (3) data acquisition: the high-energy detector records the intensity of the attenuated high-energy X-rays passing through the patient detection part at each moment, the low-energy detector records the intensity of the attenuated bottom-energy X-rays passing through the patient detection part at each moment, and the high-energy detector and the low-energy detector in the step S5 are both detectors with discriminators, wherein the discriminators are scintillators made of NaI materials, so that the scintillation brightness of the X-rays with different specification characteristics can be different according to the X-rays with different energy bands, and the electric signals are amplified and output after the scintillation is detected by the photomultiplier.
S6: data processing and imaging: the data collected by the data of the high-energy detector and the low-energy detector are transmitted to a computer to remove the influence of part of soft tissues on the measurement result, and the step S6 of removing the influence of part of soft tissues on the measurement result specifically comprises the following steps: s61: acquiring quadrants of two X-rays obtained under X-rays with different energies; s62: energy subtraction is carried out on each quadrant of two X-rays obtained under X-rays with different energies, and a specific calculation formula is as follows:wherein I is h I is the incident intensity measurement of the high energy X-ray pixel l For measuring the emission intensity of low-energy X-ray pixels, I o,h High energy X-ray incident intensity measurement, I o,l For low energy X-ray incident intensity measurement, m t The surface density of the bone is g/cm2, m s Surface Density of Soft tissue g/cm2, mu th Bone mass absorption coefficient cm2/g, mu for high energy X-ray tl Mass absorption coefficient cm2/g, mu of bone to low energy X-ray sh For soft tissue to high-energy X-raysMass absorption coefficient cm2/g, mu sl The mass absorption coefficient of the soft tissue team low energy X-ray is cm < 2 >/g. Then the digital images are sent to a data acquisition system through an analog-to-digital converter to generate the required digital images;
s7: processing of generating an image: the method of using the unsharp mask to enhance the image and reduce the noise of the image specifically includes the following steps: s71: the two images are combined, each position is regarded as a vector, so that an image with each pixel as the vector is obtained, the local variance is generally obtained in the image, a small local window is used for sliding on the image in sequence, and the variance of the pixels in the window is obtained to be the local variance. Assuming an image X, the window size is M wood N, then the local variance is calculated as:the information reflected by the center pixel of the current window can be described according to the magnitude of the local variance: if the variance value is small, the fluctuation of the pixels in the current window is not large, and the current pixels are supposed to be flat areas; conversely, if the variance value is large, the current pixel may be boundary or noise, so that the current pixel can be processed according to the property of the pixel.
S72: the covariance matrix of the current window is calculated, specific values and variances are generally used for describing one-dimensional data, but in real life, people often encounter the situation that the data contains multidimensional data, and although the independent variances of each one-dimensional data can be calculated according to the method, the inherent relation between each one-dimensional data is stripped, and when a certain problem cannot be processed independently and a plurality of factors need to be comprehensively considered, a new comprehensive variable is needed. Covariance is a statistic used to measure the relationship between two random variables, and can be defined as a formula by mimicking the definition of varianceAs shown. Obviously, there is not only one covariance for multidimensional data, covarianceAlmost, a covariance matrix is formed, e.g., for two-dimensional data z= { (x) 1 ,y 1 ),(x 2 ,y 2 ),(x 3 ,y 3 ) …, a covariance matrix C can be obtained by solving a plurality of covariance values as formulaAs shown, each dimension of two-dimensional data can be considered as a vector, and then each element in the covariance matrix is the covariance between the vector elements, which is a natural generalization from scalar random variables to high-dimensional random vectors. The covariance matrix is a symmetric matrix, and the value of the main diagonal is the variance in each dimension. The covariance in the image can be obtained in the form of local variances: considering each image as one-dimensional data, then forming multidimensional data vectors by a plurality of images, and solving covariance moment;
s73: obtaining eigenvalues lambda in matrix 1 And lambda (lambda) 2 The method comprises the steps of carrying out a first treatment on the surface of the The specific dual-energy X-ray security inspection equipment can generate two images with high energy and low energy, and certain relation exists between the two images, so that the two images are combined and considered in the enhancement process, details which cannot be found in independent processing are enhanced according to the unique characteristics of the two images, the influence of noise is reduced, and the images have better visual effects. The two images reflect information of the same part of the object at the same position, so that the two images can be combined, and each position is regarded as a vector, so that an image with each pixel as a vector is obtained. If the local variance is used to judge the information of the current pixel, the two-dimensional vector in the local window can not be used to obtain the variance, but can only be used to obtain the covariance matrix.
Specifically, a local window is selected in the image, and a 3 x 3 module is selected in the experiment, so that a new matrix is obtained, and each element in the matrix is two-dimensional, such asIn the formula, X is a pixel in a high-energy image, and Y is a low-energy imageIs included in the display panel. The covariance matrix is calculated for F to obtain a matrix of 2 x 2 as the formula +.>As shown. Wherein each covariance is in accordance withAnd calculating, wherein elements on main diagonal lines of the covariance matrix are variances of the high-energy and low-energy images respectively, and the other two elements are correlations of the high-energy and low-energy images. In order to be able to better combine the information of the two images, representing them with fewer parameters, one needs to reduce the correlation of the two images, and all the elements other than the main diagonal can be converted to 0 according to the formula |λi-a|=0. The two elements on the principal diagonal are the eigenvalues lambda of the covariance matrix 1 And lambda (lambda) 2 Based on the two eigenvalues, a corresponding eigenvector V can be obtained 1 And V 2 . Two eigenvalues reflect the reassigned image information, assuming λ 1 Greater than lambda 2 Then lambda is 1 Lambda representing the vast majority of information of the current pixel 2 Redundant or noise information representing the current pixel and therefore can be used with |lambda 1 -λ 2 The i value represents the structural information of the current pixel, and because redundancy and noise contained in the pixel are removed, the image structural information extracted with respect to the local variance has better detail and less noise. The local variance and covariance matrix-based methods are used to extract structural information of the image, respectively, and in the same display range, the structural information of the image extracted by using the covariance matrix eigenvalue can display more image details, such as the middle part of the image, more clearly detectable by thin lines and less noise influence in flat areas compared with the local variance alone in the high-energy image.
S74: judging eigenvalue lambda in matrix 1 -λ 2 Whether or not it is greater than a threshold T 1 If |lambda 1 -λ 2 |≥T 1 Then the current pixel is used as a boundary, and the gain value K of the current pixel is calculated from the substitution formula, which comprises the following stepsThe K value formula in S74 is:if |lambda 1 -λ 2 |<T 1 And lambda is 2 >T 2 Then the current pixel is a flat region and the gain value can be set to a minimum value of 1; if |lambda 1 -λ 2 |<T 1 . And lambda is 2 ≤T 2 Then the current pixel is noise, the point should be suppressed, and the gain value may be set to 0, so that the noise pixel corresponding to the high frequency portion will not be superimposed on the original image:
s75: will be% 1 -λ 2 Normalization processing is performed according to the formula, where the formula in step S75 isAfter the gain coefficient K is obtained, the gain coefficient K is substituted into a sharpening mask algorithm of the high-energy image and the low-energy image respectively, so that the enhanced image is obtained.
The foregoing description is only a preferred embodiment of the present application, and the present application is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present application has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.
Claims (9)
1. A method for generating dual-energy X-rays for detecting bone density based on K-edge filtering, characterized by: the method comprises the following steps:
s1: generation of primary X-rays: inputting a constant voltage into an X-ray bulb tube to generate original X-rays;
s2: generation of dual energy X-rays: the original X-rays are emitted to a K-edge filter, so that two rays with high energy and low energy are separated;
s3: coupling of rays and wire harness: transmitting the dual-energy X-rays to a collimator so as to couple the dual-energy X-rays with the maximum efficiency optically, and transmitting the coupled dual-energy X-rays to an electron beam limiter so as to limit the radiation range of the dual-energy X-rays;
s4: irradiation of dual-energy X-rays: scanning the to-be-detected part of the detected patient by using the coupled and harness dual-energy X-rays;
s5: and (3) data acquisition: the high-energy detector records the intensity of the attenuated high-energy X-rays passing through the detection part of the patient at each moment, and the low-energy detector records the intensity of the attenuated bottom-energy X-rays passing through the detection part of the patient at each moment;
s6: data processing and imaging: transmitting the data acquired by the data of the high-energy detector and the low-energy detector to a computer to remove the influence of partial soft tissues on a measurement result, and then transmitting the data to a data acquisition system through an analog-to-digital converter to generate a required digital image;
s7: processing of generating an image: the method of using the unsharp mask is used for image enhancement, and noise of the image is reduced.
2. The method for detecting bone density based on generating dual energy X-rays by K-edge filtering according to claim 1, wherein: the X-ray ball in the step S1 is a potential type X-ray ball tube, so that the X-ray ball tube is added with high voltage of lOOkV, and a universal energy spectrum X-ray with continuous 100keV is generated.
3. The method for detecting bone density based on generating dual energy X-rays by K-edge filtering according to claim 1, wherein: and in the step S2, a rare earth filter containing heavy samarium Sm or cerium Ce is selected as an edge filter to filter the X-ray beam. So that the X-ray beam after filtering through the K-edge becomes a dual energy X-ray containing two specific energy spectrum peaks (45 keV and 80 keV).
4. The method for detecting bone density based on generating dual energy X-rays by K-edge filtering according to claim 1, wherein: the high-energy detector and the low-energy detector in the step S5 are both detectors with discriminators, and the discriminators are scintillators made of NaI materials, so that different specification characteristics can generate different scintillation brightness due to X rays in different energy spectrum sections, and the electric signals are amplified and output after being detected by photomultiplier tubes according to the scintillation.
5. The method for detecting bone density based on generating dual energy X-rays by K-edge filtering according to claim 1, wherein: the dual-energy X-ray scanning method in step S4 is a cone scanning method. Compared with a linear scanning mode, the conical scanning mode can effectively improve the efficiency of the whole scanning process, and further improve the efficiency of the whole bone mineral density detection.
6. The method for detecting bone density based on generating dual energy X-rays by K-edge filtering according to claim 1, wherein: the image adding method in the step S7 includes the following steps:
s71: combining the two images, each position being regarded as a vector, thereby obtaining an image with each pixel as a vector;
s72: calculating a covariance matrix of the current window;
s73: obtaining eigenvalues lambda in matrix 1 And lambda (lambda) 2 ；
S74: judging eigenvalue lambda in matrix 1 -λ 2 Whether or not it is greater than a threshold T 1 If |lambda 1 -λ 2 |≥T 1 Then the current pixel is used as a boundary, and the gain value K of the current pixel is obtained from the substitution formula; if |lambda 1 -λ 2 |＜T 1 And lambda is 2 >T 2 Then the current pixel is a flat region and the gain value can be set to a minimum value of 1; if |lambda 1 -λ 2 |<T 1 . And lambda is 2 ≤T 2 Then the current pixel is noise, the point should be suppressed, and the gain value may be set to 0, so that the noise pixel corresponding to the high frequency portion will not be superimposed on the original image:
s75: will be% 1 -λ 2 Normalization processing is carried out according to a formula, and gain coefficients K are obtained and then are respectively substituted into high valuesCan be used in a de-sharpening masking algorithm with the low energy image to obtain an enhanced image.
7. The method for detecting bone density based on K-edge filtering to generate dual energy X-rays according to claim 6, wherein: the formula in step S74 is:
8. the method for detecting bone density based on generating dual energy X-rays by K-edge filtering according to claim 1, wherein: the formula in the step S75 is
9. The method for detecting bone density by generating dual-energy X-rays based on K-edge filtering according to claim 1, wherein the step of removing the influence of the removed part of the soft tissue on the measurement result in the step S6 is:
s61: acquiring quadrants of two X-rays obtained under X-rays with different energies;
s62: energy subtraction is performed on each quadrant of two X-rays obtained under X-rays of different energies.
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| CN117257333A (en) * | 2023-11-17 | 2023-12-22 | 深圳翱翔锐影科技有限公司 | True dual-energy X-ray bone densitometer based on semiconductor detector |
| CN117257333B (en) * | 2023-11-17 | 2024-02-20 | 深圳翱翔锐影科技有限公司 | True dual-energy X-ray bone densitometer based on semiconductor detector |
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