Exposure control method of DR imaging system and DR imaging system

Abstract

The invention relates to an exposure control method of a digital radiography (DR) imaging system and the DR imaging system, and the method comprises the following steps: obtaining a pre-established corresponding relation between reference voltage and a digital radiography (DR) characteristic index, the DR feature index is determined according to at least one image feature of a gray scale entropy feature, a texture feature, a noise feature, a gradient feature and a divergence feature extracted from a DR image; determining a reference voltage corresponding to the target DR characteristic index based on the corresponding relation; x-rays are emitted to a target part of a target object, so that the X-rays penetrate through the target part; receiving the X-ray passing through the target part, and obtaining a voltage signal according to the X-ray passing through the target part; and when the voltage signal reaches the reference voltage, stopping exposure. And determining the reference voltage of exposure control according to the target DR characteristic index. The accuracy of exposure control can be improved.

Description

Technical Field

[0001] The present invention relates to the field of medical image technology, and more particularly to an exposure control method of a DR imaging system and a DR imaging system. Background Art

[0002] Digital Radiography (DR) images are a common type of medical digital images and are widely used in physical examinations and routine medical imaging diagnosis. With the development of digital X-ray detectors and digital image processing systems, DR images can often present diagnostic image effects within a wide range of exposure doses. However, this process often relies on the experience of the operator to grasp the final image effect, and the accuracy of the judgment is easily affected by various factors such as experience differences, subjective differences, and post-processing.

[0003] At present, in the process of DR imaging, doctors often use ionization chamber automatic exposure control technology to control the exposure cutoff time to achieve the purpose of automatic exposure, and obtain DR images that meet the requirements while reducing the difference in subjective experience. Automatic exposure technology converts X-rays that pass through the human body into voltage signals through an ionization chamber. As the exposure dose increases, the voltage value of the ionization chamber output signal will also increase. When the voltage value reaches the set reference voltage, the exposure ends. However, in actual use, the reference voltage is often set according to the image grayscale information, which is difficult to accurately reflect the exposure dose. Summary of the invention

[0004] A series of simplified concepts are introduced in the Summary of the Invention, which will be further described in detail in the Detailed Description of the Invention. The Summary of the Invention does not mean to attempt to define the key features and essential technical features of the claimed technical solution, nor does it mean to attempt to determine the scope of protection of the claimed technical solution.

[0005] An embodiment of the present invention provides an exposure control method for a DR imaging system, the method comprising:

[0006] Acquiring a correspondence between a pre-established reference voltage and a digital X-ray photography DR feature index, wherein the DR feature index is determined based on at least one image feature of a grayscale entropy feature, a texture feature, a noise feature, a gradient feature, and a divergence feature extracted from a DR image;

[0007] Based on the corresponding relationship, determining a reference voltage corresponding to the target DR characteristic index;

[0008] emitting X-rays to a target part of a target object so that the X-rays pass through the target part;

[0009] receiving X-rays after passing through the target part, and obtaining a voltage signal according to the X-rays after passing through the target part;

[0010] When the voltage signal reaches the reference voltage, the exposure is stopped.

[0011] In one embodiment, the method further includes: acquiring current imaging conditions; and acquiring the correspondence between the pre-established reference voltage and the digital X-ray photography DR characteristic index includes acquiring a correspondence that matches the current imaging conditions.

[0012] In one embodiment, the imaging condition includes at least one of the following: exposure parameter, imaging position, imaging site, age of the target object, gender of the target object, and body shape of the target object.

[0013] In one embodiment, the exposure parameters include tube voltage and / or tube current.

[0014] In one embodiment, the correspondence between the reference voltage and the DR characteristic index can be pre-established in the following manner: under at least one imaging condition, exposure is performed based on different reference voltages to obtain DR images corresponding to different reference voltages; the reference voltage and DR characteristic index corresponding to the DR image are extracted to obtain the correspondence between the reference voltage and the DR characteristic index under the at least one imaging condition.

[0015] A second aspect of an embodiment of the present invention provides an exposure control method for a DR imaging system, the method comprising:

[0016] Acquiring a correspondence between a pre-established reference current and a digital X-ray photography DR feature index, wherein the DR feature index is determined based on at least one image feature of a grayscale entropy feature, a texture feature, a noise feature, a gradient feature, and a divergence feature extracted from a DR image;

[0017] Based on the corresponding relationship, determining a reference current corresponding to the target DR characteristic index;

[0018] emitting X-rays to a target part of a target object so that the X-rays pass through the target part;

[0019] receiving X-rays after passing through the target part, generating image data according to the X-rays after passing through the target part, and obtaining a current signal according to the X-rays after passing through the target part;

[0020] When the current signal reaches the reference current, the exposure is stopped.

[0021] A third aspect of an embodiment of the present invention provides an exposure control method for a DR image, the method comprising:

[0022] Acquiring a pre-established correspondence between an exposure time and a digital X-ray photography DR feature index, wherein the DR feature index is determined based on at least one image feature of a grayscale entropy feature, a texture feature, a noise feature, a gradient feature, and a divergence feature extracted from a DR image;

[0023] Based on the corresponding relationship, determining the target exposure time corresponding to the target DR characteristic index;

[0024] emitting X-rays to a target part of a target object and determining an exposure time of the target part;

[0025] When the exposure time reaches the target exposure time, the exposure is stopped.

[0026] In one embodiment, the method further includes: acquiring current imaging conditions; and acquiring the pre-established correspondence between exposure time and digital X-ray photography DR characteristic index includes acquiring a correspondence matching the current imaging conditions.

[0027] In one embodiment, the imaging condition includes at least one of the following: exposure parameter, imaging position, imaging site, age of the target object, gender of the target object, and body shape of the target object.

[0028] In one embodiment, the method further includes: acquiring current imaging conditions; and determining the target DR feature index corresponding to the current imaging conditions.

[0029] In one embodiment, the method also includes: performing a calibration operation on the target DR feature index; based on the calibration operation, acquiring multiple frames of reference DR images, and acquiring the DR feature index of each frame of the reference DR image; performing statistics on the DR feature index of the multiple frames of reference DR images to obtain statistical results, and updating the target DR feature index according to the statistical results.

[0030] In one embodiment, acquiring multiple frames of reference DR images based on the calibration operation includes: acquiring historical DR images acquired within a preset time range as the reference DR images.

[0031] In one embodiment, acquiring multiple frames of reference DR images based on the calibration operation includes: displaying historical DR images acquired within a preset time range; performing a selection operation on the historical DR images, and determining the historical DR image indicated by the selection operation as the reference DR image.

[0032] In one embodiment, the step of extracting the grayscale entropy feature from the DR image includes: obtaining a first probability statistical distribution of each grayscale source in the DR image; determining a first probability statistical distribution of non-redundant grayscale sources from the first probability statistical distribution of the grayscale sources according to the size of the first probability statistical distribution; obtaining a second probability statistical distribution of each non-redundant grayscale source according to the ratio of the first probability statistical distribution of each non-redundant grayscale source to the sum of the first probability statistical distributions of all non-redundant grayscale sources; and obtaining the grayscale entropy feature by calculating the entropy of the second probability statistical distribution of the non-redundant grayscale sources.

[0033] In one embodiment, the step of extracting the texture feature from the DR image includes: obtaining a texture feature description matrix based on the grayscale value of each pixel in the DR image, wherein the texture feature description matrix describes the distance between different pixel points in the DR image and the change in grayscale value in the direction between different pixel points; extracting at least one two-dimensional component of the texture feature description matrix as the texture feature.

[0034] In one embodiment, the step of extracting the noise feature from the DR image includes: filtering the DR image to obtain a high-frequency image; calculating the root mean square of the neighborhood of each pixel point in the high-frequency image to obtain a noise distribution image; and statistically analyzing the distribution of noise values ​​in the noise distribution image to obtain the noise feature.

[0035] In one embodiment, the step of extracting the gradient feature from the DR image includes: determining the regional distribution of different tissues in the DR image; and obtaining the clarity of the boundary of the regional distribution of different tissues as the gradient feature.

[0036] In one embodiment, the step of extracting the divergence feature from the DR image includes: determining the regional distribution of different tissues in the DR image; and obtaining the transition strength and / or trend consistency of the boundaries of the regional distribution of different tissues as the divergence feature.

[0037] A fourth aspect of an embodiment of the present invention provides a DR imaging system, comprising: an X-ray source, a flat-panel detector, an ionization chamber, a processor and an output device; the X-ray source is used to emit X-rays to a target part of a target object so that the X-rays pass through the target part; the flat-panel detector is used to receive the X-rays after passing through the target part; the ionization chamber is used to obtain a voltage signal or a current signal based on the X-rays after passing through the target part; the processor is used to execute the exposure control method of the DR characteristic index as described above to generate a DR image; and the output device is used to output the DR image.

[0038] A fifth aspect of an embodiment of the present invention provides a DR imaging system, comprising: an X-ray source, a flat-panel detector, a processor and an output device; the X-ray source is used to emit X-rays to a target part of a target object so that the X-rays pass through the target part; the flat-panel detector is used to receive the X-rays after passing through the target part; the processor is used to execute the exposure control method of the DR characteristic index as described above to generate a DR image; and the output device is used to output the DR image.

[0039] The exposure control method of the DR imaging system and the DR imaging system of the embodiment of the present invention determine the reference voltage for exposure control according to the target DR characteristic index, so that the DR characteristic index of the DR image obtained by exposure control based on the reference voltage is close to the target characteristic index, thereby improving the accuracy of exposure control. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The above and other purposes, features and advantages of the present invention will become more apparent by describing the embodiments of the present invention in more detail in conjunction with the accompanying drawings. The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings, the same reference numerals generally represent the same components or steps.

[0041] Figure 1 A schematic flow chart showing an exposure control method of a DR imaging system according to an embodiment of the present invention;

[0042] Figure 2 A schematic flow chart showing an exposure control method of a DR imaging system according to another embodiment of the present invention;

[0043] Figure 3 A schematic flow chart showing an exposure control method of a DR imaging system according to another embodiment of the present invention;

[0044] Figure 4 A schematic block diagram of a DR imaging system according to an embodiment of the present invention is shown;

[0045] Figure 5 A schematic block diagram of a DR imaging system according to another embodiment of the present invention is shown. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical scheme and advantages of the present invention more obvious, the exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments of the present invention, and it should be understood that the present invention is not limited to the exemplary embodiments described herein. Based on the embodiments of the present invention described in the present invention, all other embodiments obtained by those skilled in the art without creative work should fall within the protection scope of the present invention.

[0047] In the following description, a large number of specific details are provided to provide a more thorough understanding of the present invention. However, it is apparent to those skilled in the art that the present invention can be implemented without one or more of these details. In other examples, in order to avoid confusion with the present invention, some technical features well known in the art are not described.

[0048] It should be understood that the present invention can be implemented in different forms and should not be interpreted as limited to the embodiments set forth herein. On the contrary, these embodiments are provided to make the disclosure thorough and complete and to fully convey the scope of the present invention to those skilled in the art.

[0049] The purpose of the terms used herein is only to describe specific embodiments and is not intended to be limiting of the present invention. When used herein, the singular forms "one", "an" and "said / the" are also intended to include plural forms, unless the context clearly indicates otherwise. It should also be understood that the terms "consisting of" and / or "comprising", when used in this specification, determine the presence of the features, integers, steps, operations, elements and / or parts, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, parts and / or groups. When used herein, the term "and / or" includes any and all combinations of the relevant listed items.

[0050] In order to fully understand the present invention, a detailed structure will be proposed in the following description to illustrate the technical solution proposed by the present invention. The optional embodiments of the present invention are described in detail as follows, but in addition to these detailed descriptions, the present invention may also have other implementations.

[0051] Next, first refer to Figure 1 The exposure control method 100 of the DR imaging system according to one embodiment of the present invention is described. Figure 1 As shown, the exposure control method 100 of the DR imaging system may include the following steps:

[0052] In step S110, a correspondence between a pre-established reference voltage and a digital X-ray photography DR feature index is obtained, wherein the DR feature index is determined based on at least one image feature of a grayscale entropy feature, a texture feature, a noise feature, a gradient feature, and a divergence feature extracted from a DR image;

[0053] In step S120, based on the corresponding relationship, a reference voltage corresponding to the target DR characteristic index is determined;

[0054] In step S130, X-rays are emitted to a target part of the target object, so that the X-rays pass through the target part;

[0055] In step S140, receiving the X-ray after passing through the target part, and obtaining a voltage signal according to the X-ray after passing through the target part;

[0056] In step S150, when the voltage signal reaches the reference voltage, the exposure is stopped.

[0057] The exposure control method 100 of the DR imaging system of an embodiment of the present invention determines the reference voltage for exposure control according to the target DR characteristic index, so that the DR characteristic index of the DR image obtained by exposure control based on the reference voltage is close to the target characteristic index, thereby improving the accuracy of exposure control.

[0058] Specifically, the correspondence between the pre-established reference voltage and the DR characteristic index is obtained. Among them, the reference voltage is the reference voltage when the automatic exposure control is performed based on the ionization chamber. The ionization chamber is a detection device that uses the ionization effect to measure ionizing radiation. It is usually placed between the flat-panel detector and the target object to detect the X-ray dose reaching the flat-panel detector. Exemplarily, the ionization chamber is mainly composed of a collector and a high-voltage electrode, and the collector and the high-voltage electrode are filled with gases such as argon or helium. When the ionization chamber is irradiated with X-rays, the X-rays interact with the molecules in the gas to produce ion pairs consisting of an electron and a positive ion. When a DC polarization voltage is applied to the collector and the high-voltage electrode to form an electric field, the electrons and positive ions will be attracted by the positive and negative poles respectively, and collected to form an output electrical signal in the external circuit. The electrical signal is proportional to the number of ion pairs and is therefore proportional to the X-ray intensity. When the voltage signal output by the ionization chamber reaches the reference voltage, the exposure is triggered to stop.

[0059] The pre-established correspondence between the reference voltage and the DR characteristic index is used to reflect the DR characteristic index of the DR image obtained by exposure based on different reference voltages. Since the radiation dose of X-rays is different when exposure is performed under different reference voltages, when the reference voltage is higher, the radiation dose of X-rays is higher, and the DR characteristic index of the generated DR image is correspondingly increased, and when the reference voltage is lower, the radiation dose of X-rays is lower, and the DR characteristic index of the generated DR image is correspondingly reduced. Exemplarily, a human body model can be exposed based on different reference voltages to obtain DR images corresponding to different reference voltages, and the DR characteristic index of the DR image can be extracted, thereby establishing a correspondence between the reference voltage and the DR characteristic index.

[0060] The DR feature index of the embodiment of the present invention is determined based on at least one image feature of the grayscale entropy feature, texture feature, noise feature, gradient feature and divergence feature extracted from the DR image, which can reflect the basic feature information content of the DR image and can reflect the comprehensive level between the radiation dose of the X-ray and the image quality of the DR image. The DR feature index can also be called a DR feature index, a DR objectification index, or any other suitable name. Among them, the grayscale entropy feature, texture feature, noise feature, gradient feature and divergence feature respectively reflect the grayscale information, texture information, noise information, gradient information and divergence information of the DR image. The multi-dimensional image features are conducive to obtaining a more accurate DR feature index, which can more comprehensively and accurately reflect the imaging effect of the DR image compared with conventional evaluation indicators such as grayscale indicators.

[0061] In one embodiment, the grayscale entropy feature is the information content obtained by statistically screening out redundant grayscale information sources in the DR image. According to the transmission characteristics of X-ray quanta converted into digital signals by the detector of the DR system, each independent grayscale in the DR image can be regarded as a source, and the DR imaging process can be regarded as a process of transmitting information through grayscale information sources. Among all the grayscales, there are some grayscales that do not have grayscale values, so they are regarded as redundant grayscale information sources. Since the extraction process of the grayscale entropy feature of the embodiment of the present invention screens out redundant grayscale information sources, more effective image information can be extracted.

[0062] For example, the grayscale entropy feature can be extracted from the DR image in the following manner:

[0063] First, the first probability statistical distribution pH(i) of each grayscale source in the DR image is obtained, where i is the image grayscale value of the DR image. Then, according to the size of the first probability statistical distribution, the first probability statistical distribution pNH(i) of the non-redundant grayscale source is determined from the first probability statistical distribution pH(i) of the grayscale source. Exemplarily, if the first probability statistical distribution pH(i) is greater than 0, it is determined to be the first probability statistical distribution pNH(i) of the non-redundant grayscale source. Conversely, if the first probability statistical distribution pH(i) is greater than 0, it is determined to be the first probability statistical distribution pNH(i) of the non-redundant grayscale source, that is:

[0064]

[0065] After obtaining the first probability statistical distribution pNH(i) of the non-redundant grayscale information source, the second probability statistical distribution pH'(i) of each non-redundant grayscale information source is obtained according to the ratio of the first probability statistical distribution pNH(i) of each non-redundant grayscale information source to the sum of the first probability statistical distributions ∑pNH(i) of all non-redundant grayscale information sources, that is:

[0066] pH'(i)=pNH(i) / ∑pNH(i) Formula (2)

[0067] Finally, entropy is calculated based on the second probability statistical distribution pH'(i) of the non-redundant grayscale information source to obtain the grayscale entropy feature H(Image). The method of calculating entropy includes but is not limited to taking the natural logarithm ln with e as the base or taking the logarithm with other values ​​as the base, which is expressed as follows:

[0068]

[0069] Thus, the grayscale entropy feature can be obtained after filtering out the redundant grayscale signal sources.

[0070] Texture features represent the spatial variation relationship of different grayscale values ​​on the DR image, which can reflect the abstract features of the law of changes in human tissue. For example, a statistical method can be used to extract the texture features of the DR image, which obtains the statistical characteristics of the texture area based on the grayscale attributes of the pixel and its neighborhood. The following mainly describes the specific details of the statistical method for extracting texture features, but the method for extracting texture features can also include geometric methods, model methods or other suitable texture feature extraction methods.

[0071] Exemplarily, when using statistical methods to extract texture features from a DR image, a texture feature description matrix is ​​first obtained based on the grayscale value of each pixel in the DR image; then, at least one two-dimensional component of the texture feature description matrix is ​​extracted as at least one texture feature.

[0072] In one embodiment, the texture feature description matrix describes the distance between different pixels and the change of grayscale values ​​in the direction between different pixels in the DR image. Assuming that the DR image Image = f(x, y), its texture feature description matrix P(i, j) is:

[0073] P(i,j)=#{(x1,y1),(x2,y2)∈M*N|f(x1,y1)=i,f(x2,y2)=j} Formula (4)

[0074] Among them, #(x) represents the number of elements in the set x. Assuming that the distance between two points (x1, y1) and (x2, y2) in the image is k, the texture feature description matrix in different directions l can be expanded to P(i, j, k, l). The texture feature description matrix can be expanded by counting the changes in grayscale values ​​at different distances and directions to obtain information in more dimensions. For example, in order to calculate the actual eigenvalues ​​at different angles, super-resolution interpolation can be performed on the DR image in each direction to obtain the sub-pixel grayscale values ​​corresponding to the new target position, and the texture feature description matrix in different directions can be obtained according to the sub-pixel grayscale values.

[0075] After obtaining the texture feature description matrix, extract at least one two-dimensional component of the texture feature description matrix to obtain a texture feature, where the texture feature reflects the key characteristics of the texture feature description matrix. Exemplarily, the texture feature includes at least one of the following:

[0076] The first texture feature P1 is used to count the value distribution of the texture feature description matrix and the overall distribution of texture changes in the DR image; the value of P1 can reflect the clarity of the DR image and the depth of the texture grooves. The deeper the texture grooves, the larger the P1 value, and vice versa, the shallower the grooves, the smaller the P1 value;

[0077] The second texture feature P2 is used to count the similarity between the value distribution in the texture feature description matrix and the parallel and normal directions in the DR image. The larger the P2 value, the greater the similarity of the grayscale of the image in different directions.

[0078] The third texture feature P3 is used to count the value distribution in the texture feature description matrix and the uniformity of the grayscale change distribution in the DR image. The size of the P3 value can reflect the uniformity of the image grayscale distribution and the coarseness of the texture. The larger the P3 value, the more stable the texture change of the DR image.

[0079] The fourth texture feature P4 is used to measure the distribution of values ​​in the texture feature description matrix and the local texture variation of the DR image. The larger the P4 value is, the stronger the regularity of the texture is.

[0080] The texture features extracted from the texture feature description matrix are not limited to the above four types. In other embodiments, other two-dimensional components of the texture feature description matrix may also be extracted as texture features.

[0081] Image noise mainly includes X-ray quantum noise, and the distribution of X-ray quanta obeys Poisson distribution, and its variance is proportional to the average number of quantum detections. Based on this characteristic of X-ray quantum noise, the fluctuation degree of X-ray quanta can be statistically analyzed from the DR image as the noise feature, that is, the noise feature reflects the fluctuation degree of X-ray quanta in the DR image.

[0082] In one embodiment, extracting noise features from a DR image includes the following steps: filtering the DR image to obtain a high-frequency image, wherein the high-frequency image obtained from the DR image mainly contains noise information; calculating the root mean square of the neighborhood of each pixel point in the high-frequency image to obtain a noise distribution image; and statistically analyzing the distribution of noise values ​​in the noise distribution image to obtain the noise features.

[0083] As an implementation, filtering the DR image to obtain a high-frequency image includes: performing low-frequency filtering on the DR image I to filter out the low-frequency components therein to obtain a low-frequency image I1; and obtaining the high-frequency image I2 according to the difference between the low-frequency image and the DR image. In other implementations, the DR image I may also be directly subjected to high-frequency filtering to obtain the high-frequency image I2.

[0084] Exemplarily, the DR image I can be subjected to Gaussian low-pass filtering to obtain a low-frequency image I1. Since the image is a two-dimensional signal, a two-dimensional Gaussian function is used for Gaussian low-pass filtering, and the two-dimensional Gaussian filter kernel is:

[0085]

[0086] The high-frequency image I2 can be obtained by calculating the difference between the low-frequency image I1 and the image I, that is, I2=I1-I. The noise distribution image I3 can be obtained by extracting the effective information in the high-frequency image I2. In one embodiment, the noise distribution image I3 is an image formed by calculating the root mean square of the neighborhood of each pixel point in the high-frequency image. The method for calculating the root mean square includes using the L1 norm or other approximate or equivalent measures, for example:

[0087]

[0088] Among them, I3(i,j) is the value of the noise distribution image I3 at the pixel point (i,j), and I2(l,k) is the value of the high frequency I2 at the pixel point (l,k).

[0089] After acquiring the noise distribution image I3, the noise value distribution thereof is statistically analyzed to obtain the acoustic feature. For example, the noise value interval with the highest noise value distribution probability in the noise distribution image can be determined, and the noise value of the noise value interval with the highest noise value distribution probability is used as the noise feature.

[0090] Specifically, first, the pixel values ​​of the noise distribution image I3 are divided into M intervals, the pixel value interval of each interval is d, the initialization histogram vector is h, the length is M, and each component h(i) of the initialization histogram represents the number of pixel values ​​in the i-th interval. For the pixel point (i, j) in the noise distribution image I3, the interval corresponding to the pixel value of this point is R[I3(i, j)]. After traversing each pixel point of the noise distribution image I3 and counting h(R(I3(i, j))), after obtaining h, the maximum value of its main peak is max(h), corresponding to the interval R0=arg max(h), then the noise distribution probability R0*d is calculated as the noise feature.

[0091] In some embodiments, the image features also include gradient features. Due to the different absorption coefficients of X-rays after penetrating different tissues of the human body, regional distributions of different tissues will be formed in the DR image, and there will be different degrees of boundaries between different tissue regions. The clarity of these boundaries can be quantified by extracting gradient features, that is, gradient features are used to characterize the clarity of boundaries between different tissues in the DR image. In one embodiment, extracting gradient features from a DR image includes: determining the regional distribution of different tissues in the DR image; obtaining the clarity of the boundaries of different tissue regional distributions as gradient features.

[0092] Exemplarily, the gradient feature can be calculated as follows:

[0093]

[0094] Among them, Grad(x,y) is used to represent the gradient size at the coordinates (x,y), and Image(x,y) is used to represent the pixel value at the coordinates (x,y).

[0095] In some embodiments, the image features also include divergence features. In DR images, the boundaries of different tissues are not strict boundaries, but there is a certain degree of transition. The strength and / or trend consistency of this transition can be quantified by extracting the divergence features, that is, the divergence features are used to characterize the strength and / or trend consistency of the transition of the boundaries of different tissues in the DR image. In one embodiment, extracting the divergence features from the DR image includes: determining the regional distribution of different tissues in the DR image; obtaining the strength and / or trend consistency of the transition of the boundaries of the regional distribution of different tissues as the divergence features.

[0096] For example, the divergence feature can be calculated as follows:

[0097]

[0098] Among them, Diver(x,y) is used to represent the divergence size at the coordinates (x,y), Image(x,y) is used to represent the pixel value at the coordinates (x,y), and actan represents the inverse tangent function.

[0099] In some embodiments, in addition to at least one of the above image features, other image features can also be extracted from the DR image for obtaining the DR feature index, such as grayscale gradient, grayscale mean, variance, pixel value information, signal-to-noise ratio, contrast-to-noise ratio, etc. The specific features can be determined according to actual conditions and are not specifically limited here.

[0100] After extracting the above-mentioned image features from the DR image, the image features can be input into a pre-trained target model, and the DR feature index output by the target model can be obtained. In the model training stage, first, a DR image set is obtained, and the DR image set includes multiple sample DR images, that is, DR images used as training samples. An image feature set can be obtained based on the DR image set, and the image feature set includes sample image features extracted from multiple sample DR images. Exemplarily, for each sample DR image in the DR image set, at least one sample image feature of grayscale entropy features, texture features, noise features, gradient features, and divergence features is extracted respectively, and multiple sample image features extracted from multiple sample DR images in the DR image set together constitute an image feature set, and each sample DR image in the DR image set corresponds to at least one sample image feature in the image feature set.

[0101] A scoring set can also be obtained according to the DR image set, and the scoring set includes the scores obtained by evaluating multiple sample DR images. Exemplarily, if the sample DR images in the DR image set are DR original images, the multiple sample DR images in the DR image set can be image processed separately to obtain multiple DR diagnostic images, that is, visual images used by doctors for diagnosis, and the multiple DR diagnostic images constitute a DR diagnostic image set, and the above-mentioned scoring set is obtained according to the DR diagnostic image set, and the scoring set includes the scores obtained by evaluating multiple DR diagnostic images. In some embodiments, clinical experts can evaluate the DR diagnostic images in the DR diagnostic image set according to the quality of the DR diagnostic images and give expert scores. The higher the score of the DR diagnostic image, the more basic feature information content is contained in the corresponding DR original image; conversely, the lower the score of the DR diagnostic image, the less basic feature information content is contained in the corresponding DR original image. The expert scores of the DR diagnostic images constitute the expert scoring set. Optionally, if the DR images in the DR image set are visual images used by doctors for diagnosis, the scoring set can be directly obtained according to the DR image set.

[0102] Afterwards, the initial model is trained using the acquired image feature set and score set as a training sample set to obtain a target model. The target model may be a traditional machine learning model or a deep learning model, including but not limited to a neural network, a support vector machine, a linear discriminant analysis, etc. The training method includes but is not limited to model training methods such as linear regression and gradient descent. Exemplarily, an optimal mapping function from image features to scores can be learned so that the error between the DR feature index obtained by the image feature mapping and the actual calibrated expert score is minimized.

[0103] In one embodiment, when the image feature set, the parameter feature set and the score set are used for classification and regression training, the classification and regression training formula used is:

[0104]

[0105] Among them, x is the feature vector, {x i} i＝1,...,m is the support vector, α i is the weighting coefficient, b is the bias, k is the kernel function, and each value of the eigenvector x needs to be obtained through the linear transfer function:

[0106]

[0107] in, is the input feature, w and s are the scaling and translation parameter vectors respectively, and the kernel function k can be or

[0108] It should be noted that the embodiments of the present invention do not limit the linear transfer function, kernel function or parameters used in the regression training method.

[0109] After obtaining the trained target model in the model training stage, in the actual application process, at least one image feature among the grayscale entropy feature, texture feature, noise feature, gradient feature and divergence feature extracted from the DR image is input into the trained network model to obtain the DR feature index. Optionally, the image features can also be comprehensively calculated according to a preset function to obtain the DR feature index. The DR feature index can characterize the basic feature information content of the DR image, and can also characterize the comprehensive level between the radiation dose of X-rays received by the target object and the image quality of the DR image. The comprehensive level refers to the quality of the image of the DR image, and the comprehensive level of the radiation dose of the X-rays received. If the user thinks that the image quality is good and meets the requirements, the DR feature index can be lowered to achieve the effect of reducing the radiation dose of the X-rays received; similarly, if the image quality is considered to be poor, the DR feature index can be increased to achieve the effect of improving the image quality.

[0110] For example, due to the differences in attenuation coefficient and thickness between human tissues, when X-rays pass through different tissues of the human body, the attenuation degree is different. Therefore, when establishing the correspondence between the reference voltage and the DR characteristic index, the correspondences matching different imaging conditions can be established respectively. In actual application, the correspondence matching the current imaging conditions can be selected to improve the accuracy of the correspondence.

[0111] The imaging conditions may include conditions related to the target object, such as imaging position, imaging part, age of the target object, gender of the target object, body shape of the target object, etc. Exemplarily, when the DR imaging system has a camera device or other measuring device, the imaging conditions such as imaging part, imaging position, body shape of the target object, etc. may be obtained based on the visualized image obtained by the measuring device of the DR imaging system. Alternatively, the imaging conditions may also be obtained based on user input.

[0112] Exemplarily, the imaging conditions also include exposure parameters, and the exposure parameters include at least one of tube current and tube voltage. Specifically, the X-ray source of the DR imaging system mainly includes a high-voltage generator and a tube. The high-voltage generator provides a tube voltage to the tube, so that the electrons generated by the filament in the tube are accelerated under the action of the tube voltage, bombarding the target material to generate X-rays, and the electrons received by the target material form a tube current. Generally speaking, the tube voltage controls the energy and quality of the X-ray beam generated by the tube, which in turn determines the penetration ability of the X-rays. The strength of the penetration ability determines the amount of radiation irradiated on the flat-panel detector, thereby determining the contrast of the DR image. The tube current controls the number of X-ray beams, and the number of X-rays determines the upper limit of the amount of X-rays that may irradiate the detector during DR imaging, thereby determining the density of the DR image. Too high a tube voltage and tube current will result in too many X-rays penetrating the human body, increasing image noise; too low a tube voltage and tube current will result in too few X-rays penetrating the human body, and the image details cannot be clearly displayed.

[0113] Among them, the corresponding relationship matching the imaging conditions can be pre-established in the following manner: under at least one imaging condition, exposure is performed based on different reference voltages to obtain DR images corresponding to different reference voltages; the reference voltage and DR characteristic index corresponding to the DR image are extracted to obtain the corresponding relationship between the reference voltage and the DR characteristic index under at least one imaging condition.

[0114] Exemplarily, a human body model can be used when establishing a corresponding relationship, and a certain imaging part of the human body model is exposed under different exposure parameters to obtain DR images corresponding to different reference voltages under different exposure parameters for the same imaging part. Initially, the tube voltage and tube current values ​​are set to KV1 and mA1 respectively, and the human body model is exposed according to different reference voltages to obtain DR images corresponding to different exposure parameters, and the DR characteristic index of the DR image is extracted according to the above method to obtain the corresponding relationship between the reference voltage and the DR characteristic index when the tube voltage and tube current are (KV1, mA1). Next, the tube current mA2 is maintained, the tube voltage is changed to KV1, and exposure is performed again according to different reference voltages to obtain the corresponding relationship between the reference voltage and the DR characteristic index when the tube voltage and tube current are (KV2, mA1). The tube voltage is changed and the above process is repeated to obtain the corresponding relationship between the reference voltage and the DR characteristic index under the same tube current and different tube voltage conditions. After that, the tube voltage is kept unchanged, and the tube current is changed and the above process is repeated to obtain the corresponding relationship between the reference voltage and the DR characteristic index under the same tube voltage and different tube current conditions. Furthermore, human models of different body types (obese, thin, normal, etc.) may be exposed under different exposure parameters to obtain corresponding relationships matching different body types.

[0115] After the above data is obtained by exposure under different imaging conditions, the reference voltage and DR characteristic index corresponding to each DR image can be associated and stored in the memory of the DR imaging system, or in a cloud server, and the data storage form is not limited to a corresponding relationship table, etc. Alternatively, model training can be performed based on the reference voltage and DR characteristic index to obtain a model that characterizes the corresponding relationship between the reference voltage and the DR characteristic index.

[0116] Next, based on the above correspondence, the reference voltage corresponding to the target DR characteristic index is determined. The target DR characteristic index is the DR characteristic index that the desired DR image can achieve. Since there is a certain correlation between the DR characteristic index and the reference voltage, when the reference voltage corresponding to the target DR characteristic index is used for exposure, the DR characteristic index of the DR image can be made close to the target DR characteristic index.

[0117] Exemplarily, the reference voltage corresponding to the target DR characteristic index can be determined from a pre-stored correspondence relationship. For example, the reference voltage corresponding to the target DR characteristic index can be searched in a correspondence table. Alternatively, the target DR characteristic index can be input into the model to obtain the reference voltage output by the model.

[0118] Since the DR characteristic index of the DR image expected to be achieved under different imaging conditions is different, the current imaging conditions can also be obtained to obtain the target DR characteristic index corresponding to the imaging conditions, and the imaging conditions include exposure parameters, imaging parts, imaging positions, body shape of the target object, age of the target object, gender of the target object, etc. That is, in some embodiments, the imaging conditions can be used to select the corresponding relationship between the reference voltage and the DR characteristic index, and can also be used to obtain the target DR characteristic index.

[0119] For example, the target DR characteristic index can be obtained by statistically analyzing the DR images of a batch of patients, or by comprehensive consideration of the exposure assessment standard of the DR image and the DR characteristic index by an expert. The target DR characteristic index may fluctuate. For example, if a hospital requires a uniform reduction in the exposure dose of X-rays, the target DR characteristic index may decrease accordingly. Therefore, in some embodiments, the target DR characteristic index may be calibrated as needed to better meet clinical needs.

[0120] In one embodiment, calibrating the target DR feature index includes: performing a calibration operation on the target DR feature index; based on the calibration operation, acquiring multiple frames of reference DR images, and acquiring the DR feature index of each frame of the reference DR image; performing statistics on the DR feature index of the multiple frames of reference DR images to obtain statistical results, and updating the target DR feature index according to the statistical results. The calibration operation can be triggered by the user, and there can be many ways to trigger the calibration operation, such as touch control, button control, remote control control, gesture control or voice control. Alternatively, the calibration operation can also be automatically triggered, such as regularly calibrating the target DR feature index.

[0121] Exemplarily, the multiple reference DR images may be historical DR images acquired within a preset time range. For example, when performing a calibration operation, the historical DR images acquired by the DR imaging system within the past month are acquired, the DR feature index of each frame of the historical DR image is extracted, and the statistical values ​​such as the average or median of the DR feature index of the multiple frames of the historical DR image are calculated and set as the new target DR feature index.

[0122] Alternatively, since abnormal images may exist in historical DR images, in order to avoid the influence of abnormal images on the target DR feature index, historical DR images collected within a preset time range can also be displayed. In-hospital experts can observe the image quality of historical DR images, select historical DR images, and determine the selected historical DR images as reference DR images for calculating the target DR feature index.

[0123] After determining the reference voltage corresponding to the target DR characteristic index, DR imaging is performed according to the reference voltage. Specifically, the DR imaging system is controlled to emit X-rays to the target tissue part of the target object so that the X-rays pass through the target tissue part; the X-rays that pass through the target part are received, and a voltage signal is obtained according to the X-rays that pass through the target part; when the voltage signal reaches the reference voltage, the exposure is stopped. Among them, the ionization chamber of the DR imaging system obtains a voltage signal according to the X-rays that pass through the target part, and outputs the voltage signal; the high-voltage generator compares the voltage signal with the reference voltage, and when the voltage signal reaches the reference voltage, the high-voltage generator is turned off to end the exposure. At the same time, the flat-panel detector arranged behind the ionization chamber receives the X-rays that pass through the target tissue part, and processes the X-rays that pass through the target tissue part to obtain a digital X-ray photography DR image.

[0124] During the DR imaging process, the X-rays emitted by the X-ray source are attenuated to varying degrees after passing through the human body and are received by the flat-panel detector. Exemplarily, the upper layer of the flat-panel detector is an X-ray conversion medium, which has photoconductivity and can convert X-rays into electronic signals, generating positive and negative charges. These charges move along the electric field in the form of current under the action of the bias voltage and are collected by the detection unit array of the flat-panel detector. Each detection unit corresponds to a pixel of the DR image. A digital signal, i.e., a DR original image, can be obtained by amplifying and processing the electrical signal and performing analog-to-digital conversion. The DR original image can be a grayscale image that has not been post-processed by contrast adjustment, brightness adjustment, etc. The processed image of the DR original image can be an image of the DR original image after a certain transformation relationship, or an image of post-processing such as image contrast and image brightness adjustment. The DR image involved in the embodiment of the present invention can be a DR original image or a processed DR image, which is not specifically limited here.

[0125] Based on the above description, the exposure control method 100 of the DR imaging system according to an embodiment of the present invention determines the reference voltage for exposure control according to the target DR characteristic index, so that the DR characteristic index of the DR image obtained by exposure control based on the reference voltage is close to the target characteristic index, thereby improving the accuracy of exposure control.

[0126] Another aspect of the present invention provides an exposure control method for a DR imaging system. Figure 2 As shown, the exposure control method 200 of the DR imaging system includes the following steps:

[0127] In step S210, a correspondence between a pre-established reference current and a digital X-ray photography DR feature index is obtained, wherein the DR feature index is determined based on at least one image feature of a grayscale entropy feature, a texture feature, a noise feature, a gradient feature, and a divergence feature extracted from a DR image;

[0128] In step S220, based on the corresponding relationship, a reference current corresponding to the target DR characteristic index is determined;

[0129] In step S230, X-rays are emitted to a target part of the target object, so that the X-rays pass through the target part;

[0130] In step S240, receiving the X-ray after passing through the target part, generating image data according to the X-ray after passing through the target part, and obtaining a current signal according to the X-ray after passing through the target part;

[0131] In step S250, when the current signal reaches the reference current, the exposure is stopped.

[0132] The exposure control method 200 of the DR imaging system of the embodiment of the present invention is substantially similar to the exposure control method 100 of the DR imaging system described above, except that in the exposure control method 200 of the DR imaging system, the ionization chamber performs automatic exposure control based on the reference current, and the exposure is stopped when the current signal output by the ionization chamber reaches the reference current; the pre-established correspondence is the correspondence between the reference current and the DR characteristic index. More identical or similar details can be referred to the relevant description above, which will not be repeated here.

[0133] Another aspect of the present invention provides an exposure control method for a DR imaging system. Figure 3 As shown, the exposure control method 300 of the DR imaging system includes the following steps:

[0134] In step S310, a correspondence between a pre-established exposure time and a digital X-ray photography DR feature index is obtained, wherein the DR feature index is determined based on at least one image feature of a grayscale entropy feature, a texture feature, a noise feature, a gradient feature, and a divergence feature extracted from a DR image;

[0135] In step S320, based on the corresponding relationship, a target exposure time corresponding to the target DR characteristic index is determined;

[0136] In step S330, X-rays are emitted to a target part of the target object, and an exposure time of the target part is determined;

[0137] In step S340, when the exposure time reaches the target exposure time, the exposure is stopped.

[0138] The exposure control method 300 of the DR imaging system of the embodiment of the present invention performs automatic exposure control based on the exposure time, first obtains the target exposure time corresponding to the target DR characteristic index, and automatically stops the exposure when the exposure time reaches the target exposure time. Therefore, in the exposure control method 300 of the DR imaging system, automatic exposure can be performed without setting an ionization chamber, thereby avoiding the need to increase the X-ray dose of the X-ray source due to the absorption of X-rays by the ionization chamber, and avoiding the ionization chamber from generating artifacts in the DR image.

[0139] Exemplarily, the method of establishing the correspondence between exposure time and DR characteristic index is similar to the method of establishing the correspondence between reference voltage and DR characteristic index in the above text, that is, exposure is performed based on different exposure times, DR images corresponding to different exposure times are obtained, and the DR characteristic index of the DR image is extracted, and the DR characteristic index is associated with the exposure time and stored, or model training is performed based on the DR characteristic index and exposure time.

[0140] Furthermore, the correspondence between the exposure time and the DR characteristic index may include a correspondence matching different imaging conditions. In practical applications, the current imaging condition may also be obtained, and a correspondence matching the current imaging condition may be obtained. Exemplarily, the imaging condition includes at least one of the following: exposure parameter, imaging position, imaging part, age of the target object, gender of the target object, and body shape of the target object. Exemplarily, the exposure parameter includes at least one of tube current and tube voltage.

[0141] Since the DR characteristic index that the DR image is expected to achieve under different imaging conditions is different, the current imaging conditions can also be obtained to obtain the target DR characteristic index corresponding to the imaging conditions, and the imaging conditions include exposure parameters, imaging parts, imaging positions, body shape of the target object, age of the target object, gender of the target object, etc. That is, in some embodiments, the imaging conditions can be used to select the corresponding relationship between the exposure time and the DR characteristic index, and can also be used to obtain the target DR characteristic index.

[0142] Furthermore, the target DR characteristic index can be calibrated as needed to make it more in line with clinical needs.

[0143] In one embodiment, calibrating the target DR feature index includes: performing a calibration operation on the target DR feature index; based on the calibration operation, acquiring multiple frames of reference DR images, and acquiring the DR feature index of each frame of the reference DR image; performing statistics on the DR feature index of the multiple frames of reference DR images to obtain statistical results, and updating the target DR feature index according to the statistical results.

[0144] Exemplarily, the multiple reference DR images may be historical DR images acquired within a preset time range. For example, when performing a calibration operation, the historical DR images acquired by the DR imaging system within the past month are acquired, the DR feature index of each frame of the historical DR image is extracted, and the statistical values ​​such as the average or median of the DR feature index of the multiple frames of the historical DR image are calculated and set as the new target DR feature index.

[0145] Alternatively, since abnormal images may exist in historical DR images, in order to avoid the influence of abnormal images on the target DR feature index, historical DR images collected within a preset time range can also be displayed. In-hospital experts can observe the image quality of historical DR images, select historical DR images, and determine the selected historical DR images as reference DR images for calculating the target DR feature index.

[0146] The exposure control method 300 of the DR imaging system of the embodiment of the present invention has many identical or similar details to the exposure control method 100 of the DR imaging system described above, which can be specifically referred to above and will not be described in detail here. The exposure control method 300 of the DR imaging system of the embodiment of the present invention determines the target exposure time according to the target DR characteristic index, so that the DR characteristic index of the DR image obtained by performing exposure control based on the target exposure time is close to the target characteristic index, thereby improving the accuracy of exposure control.

[0147] Another embodiment of the present invention provides a DR imaging system, see Figure 4 The DR imaging system 400 includes: an X-ray source 410, a flat panel detector 420, an ionization chamber 430, a processor 440 and an output device 450, wherein the processor 440 is communicatively connected with the X-ray source 410, the flat panel detector 420, the ionization chamber 430 and the output device 450; the X-ray source 410 is used to generate X-rays, emit X-rays to a target tissue part of a target object, and control the X-rays to pass through the target tissue part; the flat panel detector 420 is used to receive the X-rays after passing through the target tissue part, and the ionization chamber 430 is used to obtain a voltage signal or a current signal according to the X-rays after passing through the target part; the processor 440 is used to process the X-rays after passing through the target tissue part to obtain a digital X-ray photography DR image, and the output device 450 is used to output the DR image.

[0148] Exemplarily, the X-ray source 410 includes a tube for emitting X-rays; the flat panel detector 420 includes an X-ray conversion medium located in the upper layer and a detection unit array located in the lower layer. The X-ray conversion medium converts X-rays into electronic signals, generates positive and negative charges, and these charges move along the electric field in the form of current under the action of the bias voltage, are collected by the detection unit array, and converted into electrical signals. The flat panel detector 420 includes but is not limited to amorphous silicon, amorphous selenium, CCD, etc. When using the DR imaging system 400 for image acquisition, the position of the X-ray source 410 and the position of the flat panel detector 420 need to be fixed in a specified manner, so that the X-rays emitted by the X-ray source 410 can irradiate the flat panel detector 420 after passing through the target tissue, so that the flat panel detector 420 can collect the X-rays after passing through the target tissue site to obtain a DR image.

[0149] The ionization chamber 430 is usually arranged between the flat panel detector 420 and the target object, and is used to detect the X-ray dose reaching the flat panel detector 420. Exemplarily, the ionization chamber 430 is mainly composed of a collector and a high voltage electrode, and a gas such as argon or helium is filled between the collector and the high voltage electrode. When the ionization chamber 430 is irradiated with X-rays, the X-rays interact with the molecules in the gas to produce ion pairs consisting of an electron and a positive ion. When a DC polarization voltage is applied to the collector and the high voltage electrode to form an electric field, the electrons and positive ions will be attracted by the positive and negative electrodes respectively, and collected to form an output electrical signal in the external circuit. The electrical signal is proportional to the number of ion pairs and therefore proportional to the X-ray intensity. When the voltage signal output by the ionization chamber 430 reaches the reference voltage, it triggers the exposure to stop.

[0150] The processor 440 is used to process the X-rays after passing through the target tissue site to obtain a digital X-ray photography DR image. The processor 440 is also used to execute the steps of the exposure control method 100 or the exposure control method 200 of the DR imaging system; the output device 450 is used to output the DR image. The specific details of the exposure control method 100 and the exposure control method 200 of the DR imaging system can be referred to above.

[0151] The DR imaging system 400 of the embodiment of the present invention determines the reference voltage for exposure control according to the target DR characteristic index, so that the DR characteristic index of the DR image obtained by performing exposure control based on the reference voltage is close to the target characteristic index, thereby improving the accuracy of exposure control.

[0152] Another embodiment of the present invention provides a DR imaging system, see Figure 5 The DR imaging system 500 includes: an X-ray source 510, a flat panel detector 520, a processor 530 and an output device 540, wherein the processor 530 is in communication with the X-ray source 510, the flat panel detector 520 and the output device 540; the X-ray source 510 is used to generate X-rays, emit X-rays to the target tissue part of the target object, and control the X-rays to pass through the target tissue part; the flat panel detector 520 is used to receive the X-rays after passing through the target tissue part; the processor 530 is used to process the X-rays after passing through the target tissue part to obtain a digital X-ray photography DR image, and the processor 530 is also used to perform the steps of the exposure control method 300 of the DR imaging system; the output device 540 is used to output the DR image. The specific details of the exposure control method 300 of the DR imaging system can be referred to above. The DR imaging system 500 of the embodiment of the present invention determines the target exposure time of exposure control according to the target DR characteristic index, so that the DR characteristic index of the DR image obtained by exposure control based on the target exposure time is close to the target characteristic index, thereby improving the accuracy of exposure control.

[0153] In addition, according to an embodiment of the present invention, a computer storage medium is also provided, on which program instructions are stored, and when the program instructions are executed by a computer or a processor, the corresponding steps of the exposure control method of the DR imaging system of any embodiment of the present invention are executed. In some embodiments, the computer storage medium is a non-volatile computer-readable storage medium, which may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required by at least one function; the data storage area may store data created during the execution of program instructions, etc. In addition, the non-volatile computer-readable storage medium may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the non-volatile computer-readable storage medium may optionally include a memory remotely arranged relative to the processor.

[0154] Exemplarily, the computer storage medium may include, for example, a hard disk of a personal computer, a storage component of a tablet computer, a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a portable compact disk read-only memory (CD-ROM), a USB memory, a memory card of a smart phone, or any combination of the above storage media. The computer-readable storage medium may be any combination of one or more computer-readable storage media.

[0155] In addition, according to an embodiment of the present invention, a computer program is also provided, which can be stored in a cloud or local storage medium. When the computer program is run by a computer or a processor, it is used to execute the corresponding steps of the exposure control method of the DR imaging system of the embodiment of the present invention.

[0156] Although example embodiments have been described herein with reference to the accompanying drawings, it should be understood that the above example embodiments are merely exemplary and are not intended to limit the scope of the present invention thereto. Various changes and modifications may be made therein by one of ordinary skill in the art without departing from the scope and spirit of the present invention. All such changes and modifications are intended to be included within the scope of the present invention as required by the appended claims.

[0157] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0158] In the several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of the units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed.

[0159] In the description provided herein, a large number of specific details are described. However, it is understood that embodiments of the present invention can be practiced without these specific details. In some instances, well-known methods, structures and techniques are not shown in detail so as not to obscure the understanding of this description.

[0160] Similarly, it should be understood that in order to streamline the present invention and help understand one or more of the various inventive aspects, in the description of the exemplary embodiments of the present invention, the various features of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof. However, the method of the present invention should not be interpreted as reflecting the following intention: the claimed invention requires more features than the features explicitly stated in each claim. More specifically, as reflected in the corresponding claims, the inventive point is that the corresponding technical problem can be solved with less than all the features of a single disclosed embodiment. Therefore, the claims following the specific embodiment are hereby expressly incorporated into the specific embodiment, wherein each claim itself serves as a separate embodiment of the present invention.

[0161] It will be understood by those skilled in the art that, except for mutually exclusive features, all features disclosed in this specification (including the accompanying claims, abstracts and drawings) and all processes or units of any method or device disclosed in this specification may be combined in any combination. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstracts and drawings) may be replaced by an alternative feature that provides the same, equivalent or similar purpose.

[0162] In addition, those skilled in the art will appreciate that, although some embodiments described herein include certain features included in other embodiments but not other features, the combination of features of different embodiments is meant to be within the scope of the present invention and form different embodiments. For example, in the claims, any one of the claimed embodiments may be used in any combination.

[0163] The various component embodiments of the present invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It should be understood by those skilled in the art that a microprocessor or a digital signal processor (DSP) may be used in practice to implement some or all of the functions of some modules in the article analysis device according to an embodiment of the present invention. The present invention may also be implemented as a device program (e.g., a computer program and a computer program product) for executing part or all of the methods described herein. Such a program for implementing the present invention may be stored on a computer-readable medium, or may have the form of one or more signals. Such a signal may be downloaded from an Internet website, or provided on a carrier signal, or provided in any other form.

[0164] It should be noted that the above embodiments illustrate the present invention rather than limit it, and that those skilled in the art may devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference symbol between brackets shall not be construed as a limitation on the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "one" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present invention may be implemented by means of hardware comprising a number of different elements and by means of a suitably programmed computer. In a unit claim enumerating a number of devices, several of these devices may be embodied by the same hardware item. The use of the words first, second, and third, etc., does not indicate any order. These words may be interpreted as names.

[0165] The above is only a specific embodiment of the present invention or an explanation of a specific embodiment, and the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. The protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. An exposure control method for a DR imaging system, characterized in that: The method comprises: Acquiring a correspondence between a pre-established reference voltage and a digital X-ray photography DR feature index, wherein the DR feature index is determined based on at least one image feature of a grayscale entropy feature, a texture feature, a noise feature, a gradient feature, and a divergence feature extracted from a DR image; Based on the corresponding relationship, determining a reference voltage corresponding to the target DR characteristic index; emitting X-rays to a target part of a target object so that the X-rays pass through the target part; receiving X-rays after passing through the target part, and obtaining a voltage signal according to the X-rays after passing through the target part; When the voltage signal reaches the reference voltage, the exposure is stopped.

2. The method according to claim 1, characterized in that The method further includes: acquiring current imaging conditions; The acquiring of the correspondence between the pre-established reference voltage and the digital X-ray photography DR characteristic index includes acquiring the correspondence that matches the current imaging condition.

3. The method according to claim 2, characterized in that The imaging condition includes at least one of the following: exposure parameter, imaging position, imaging part, age of the target object, gender of the target object, and body shape of the target object.

4. The method according to claim 2, characterized in that The exposure parameters include tube voltage and / or tube current.

5. The method according to claim 2, characterized in that The corresponding relationship between the reference voltage and the DR characteristic index can be pre-established in the following manner: Under at least one imaging condition, performing exposure based on different reference voltages to obtain DR images corresponding to different reference voltages; A reference voltage and a DR characteristic index corresponding to the DR image are extracted to obtain a corresponding relationship between the reference voltage and the DR characteristic index under the at least one imaging condition.

6. An exposure control method for a DR imaging system, characterized in that: The method comprises: Acquiring a correspondence between a pre-established reference current and a digital X-ray photography DR feature index, wherein the DR feature index is determined based on at least one image feature of a grayscale entropy feature, a texture feature, a noise feature, a gradient feature, and a divergence feature extracted from a DR image; Based on the corresponding relationship, determining a reference current corresponding to the target DR characteristic index; emitting X-rays to a target part of a target object so that the X-rays pass through the target part; receiving X-rays after passing through the target part, generating image data according to the X-rays after passing through the target part, and obtaining a current signal according to the X-rays after passing through the target part; When the current signal reaches the reference current, the exposure is stopped.

7. A DR image exposure control method, characterized in that: The method comprises: Acquiring a pre-established correspondence between an exposure time and a digital X-ray photography DR feature index, wherein the DR feature index is determined based on at least one image feature of a grayscale entropy feature, a texture feature, a noise feature, a gradient feature, and a divergence feature extracted from a DR image; Based on the corresponding relationship, determining the target exposure time corresponding to the target DR characteristic index; emitting X-rays to a target part of a target object and determining an exposure time of the target part; When the exposure time reaches the target exposure time, the exposure is stopped.

8. The method according to claim 7, characterized in that The method further comprises: Get current imaging conditions; The obtaining of the pre-established correspondence between the exposure time and the digital X-ray photography DR characteristic index includes obtaining a correspondence matching the current imaging condition.

9. The method according to claim 8, characterized in that The imaging condition includes at least one of the following: exposure parameter, imaging position, imaging part, age of the target object, gender of the target object, and body shape of the target object.

10. The method according to claim 1, 6 or 7, characterized in that: The method further comprises: Get current imaging conditions; The target DR feature index corresponding to the current imaging condition is determined.

11. The method according to claim 1, 6 or 7, characterized in that: The method further comprises: Performing a calibration operation on the target DR characteristic index; Based on the calibration operation, multiple frames of reference DR images are acquired, and a DR feature index of each frame of the reference DR image is acquired; Statistics are performed on the DR feature indexes of the multiple frames of reference DR images to obtain statistical results, and the target DR feature index is updated according to the statistical results.

12. The method according to claim 11, characterized in that The step of acquiring multiple frames of reference DR images based on the calibration operation includes: A historical DR image collected within a preset time range is obtained as the reference DR image.

13. The method according to claim 11, characterized in that The step of acquiring multiple frames of reference DR images based on the calibration operation includes: Display historical DR images collected within a preset time range; A selection operation is performed on the historical DR image, and the historical DR image indicated by the selection operation is determined as the reference DR image.

14. The method according to claim 1, 6 or 7, characterized in that: The step of extracting the grayscale entropy feature from the DR image comprises: Obtaining a first probability statistical distribution of each grayscale source in the DR image; Determining a first probability statistical distribution of a non-redundant grayscale information source from the first probability statistical distribution of the grayscale information source according to the size of the first probability statistical distribution; Obtaining a second probability statistical distribution of each non-redundant grayscale information source according to a ratio of the first probability statistical distribution of each non-redundant grayscale information source to the sum of the first probability statistical distributions of all non-redundant grayscale information sources; The entropy of the second probability statistical distribution of the non-redundant grayscale information source is calculated to obtain the grayscale entropy feature.

15. The method according to claim 1, 6 or 7, characterized in that The step of extracting the texture feature from the DR image comprises: A texture feature description matrix is ​​obtained according to the gray value of each pixel in the DR image, wherein the texture feature description matrix describes the distance between different pixel points and the change of the gray value in the direction between different pixel points in the DR image; At least one two-dimensional component of the texture feature description matrix is ​​extracted as the texture feature.

16. The method according to claim 1, 6 or 7, characterized in that The step of extracting the noise feature from the DR image comprises: Performing filtering on the DR image to obtain a high-frequency image; Calculating the root mean square of the neighborhood of each pixel in the high-frequency image to obtain a noise distribution image; The noise value distribution in the noise distribution image is statistically analyzed to obtain the noise feature.

17. The method according to claim 1, 6 or 7, characterized in that The step of extracting the gradient feature from the DR image comprises: Determining the regional distribution of different tissues in the DR image; The clarity of the boundaries of different tissue region distributions is obtained as the gradient feature.

18. The method according to claim 1, 6 or 7, characterized in that The step of extracting the divergence feature from the DR image comprises: Determining the regional distribution of different tissues in the DR image; The transition strength and / or trend consistency of the boundaries of different tissue region distributions are obtained as the divergence feature.

19. A DR imaging system, characterized in that: The DR imaging system comprises: an X-ray source, a flat panel detector, an ionization chamber, a processor and an output device; The X-ray source is used to emit X-rays to a target part of a target object so that the X-rays pass through the target part; The flat panel detector is used to receive X-rays after passing through the target part; The ionization chamber is used to obtain a voltage signal or a current signal according to the X-rays after passing through the target part; The processor is used to execute the exposure control method of the DR characteristic index according to any one of claims 1-6 and 10-18 to generate a DR image; The output device is used to output the DR image.

20. A DR imaging system, characterized in that: The DR imaging system comprises: an X-ray source, a flat panel detector, a processor and an output device; The X-ray source is used to emit X-rays to a target part of a target object so that the X-rays pass through the target part; The flat panel detector is used to receive X-rays after passing through the target part; The processor is used to execute the exposure control method of the DR characteristic index according to any one of claims 7 to 18 to generate a DR image; The output device is used to output the DR image.

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