A method, system, apparatus and storage medium for acquiring radiological images

Abstract

Embodiments of the present application disclose a method, system and device for acquiring a radiographic image and a storage medium. The method can include at least one of the following operations. A control instruction can be received, the control instruction including a pre-imaging start instruction and an imaging start instruction. The target object can be pre-imaged based on the control instruction, and a first exposure parameter can be acquired. The target object can be imaged again based on the first exposure parameter, and a radiographic image of the target object can be acquired. The method disclosed in the present application can reduce the number of times of ray delivery and the amount of delivered rays, and can acquire a high-quality radiographic image, thereby improving the user experience.

Description

[0001] Case Analysis

[0002] This application is a divisional application of Chinese Patent Application No. 201910697400.5, entitled “A method, system, apparatus and storage medium for acquiring radiographic images”, filed on July 30, 2019. Technical Field

[0003] This application relates to the field of image processing, and in particular to a method, system, apparatus and storage medium for acquiring high-quality radiographic images. Background Technology

[0004] Currently, X-ray imaging equipment is used in numerous fields, such as medical diagnosis and treatment, industrial material testing, and security inspection. At certain points during the use of X-ray imaging equipment, it is necessary to acquire an image of the object to be imaged for reference in subsequent processes or as archival evidence of the entire process. For example, in surgery, X-ray imaging equipment needs to acquire a low-noise, high-contrast image at specific stages of the procedure and save it as a reference for subsequent surgery or as archival evidence of the surgical outcome. Therefore, this application provides a method for acquiring radiographic images of an object to be imaged. Summary of the Invention

[0005] One aspect of this application provides a method for acquiring a radiographic image. The method may include at least one of the following operations: receiving a control command; pre-imaging a target object with rays based on the control command to obtain first exposure parameters; and re-imaging the target object with rays based on the first exposure parameters to acquire a radiographic image of the target object.

[0006] In some embodiments, the first exposure parameter is the pre-imaging exposure parameter that makes the difference between the brightness of the pre-imaging image and the brightness of the set first target satisfy a preset condition.

[0007] In some embodiments, obtaining the first exposure parameter may include at least one of the following operations: Pre-imaging exposure parameters and the brightness of at least one frame of a pre-imaging image may be obtained. The brightness may be compared with a set first target brightness. The pre-imaging exposure parameters may be updated based on the comparison result and the ABS curve to ensure that the difference between the pre-imaging image brightness and the first target brightness meets a preset condition, and the updated pre-imaging exposure parameters are used as the first exposure parameter.

[0008] In some embodiments, the step of re-imagering the target object based on the first exposure parameters to obtain a radiographic image of the target object may include at least one of the following operations: A second exposure parameter may be generated based on the first exposure parameter. An image of the target object may be re-imagered based on the second exposure parameter to obtain a radiographic image of the target object.

[0009] In some embodiments, the first exposure parameter and the second exposure parameter include tube voltage, tube current, and layup duration. Determining the second parameter based on the first parameter may include at least one of the following operations: At least one of the tube voltage, tube current, and layup duration included in the first exposure parameter may be adjusted to obtain the second exposure parameter.

[0010] In some embodiments, determining the second exposure parameter based on the first exposure parameter may include at least one of the following operations: The equivalent thickness of the target object may be determined based on the first exposure parameter and the first target brightness. The second exposure parameter may be determined based on the equivalent thickness of the target object and the second target brightness.

[0011] In some embodiments, determining the equivalent thickness of the target object may include at least one of the following operations: The equivalent thickness of the target object may be determined based on a first exposure parameter, a first target brightness, and a brightness-thickness-parameter model; wherein the brightness-thickness-parameter model includes at least the correlation between image brightness, object thickness, and exposure parameters.

[0012] In some embodiments, determining the brightness-thickness-parameter model may include at least one of the following operations: The exposure parameters corresponding to multiple test targets of different thicknesses when their image brightness reaches multiple different brightness levels can be obtained. Multiple fitting functions between the thicknesses of multiple test targets and their corresponding exposure parameters at different brightness levels can be determined, and these fitting functions can be used as the brightness-thickness-parameter model. Alternatively, a trained brightness-thickness-parameter model can be obtained by training an initial model based on the thicknesses of multiple test targets, exposure parameters, and the brightness of the corresponding images; the initial model is a statistical model or a machine learning model.

[0013] In some embodiments, the exposure parameters in the brightness-thickness-parameter model include tube voltage and tube current; the relationship between tube voltage and tube current follows the ABS curve.

[0014] In some embodiments, the method is applied to a C-arm X-ray imaging system.

[0015] In some embodiments, the C-arm X-ray imaging system includes a mobile C-arm or a digital subtraction angiography (DSA) device.

[0016] In some embodiments, the control commands originate from the exposure handbrake.

[0017] Another aspect of this application provides a system for acquiring radiographic images, the system comprising an acquisition module, a parameter determination module, and an image acquisition module. The parameter receiving module is used to receive control commands. The parameter determination module is used to pre-image a target object with delivered radiation based on the control commands, acquiring first exposure parameters. The image acquisition module is used to image the target object again with delivered radiation based on the first exposure parameters under the control commands, acquiring a radiographic image of the target object.

[0018] In some embodiments, the first exposure parameter is the pre-imaging exposure parameter that makes the difference between the brightness of the pre-imaging image and the brightness of the set first target satisfy a preset condition.

[0019] In some embodiments, to obtain the first exposure parameter, the parameter acquisition module is further configured to perform at least one of the following operations: acquiring pre-imaging exposure parameters and the brightness of at least one frame of pre-imaging image; comparing the brightness with a set first target brightness; updating the pre-imaging exposure parameters based on the comparison result and the ABS curve, so that the difference between the pre-imaging image brightness and the first target brightness meets a preset condition, and using the updated pre-imaging exposure parameters as the first exposure parameter.

[0020] In some embodiments, in order to image the target object again by delivering rays based on the first exposure parameters and obtain a radiographic image of the target object, the parameter determination module is further configured to generate a second exposure parameter based on the first exposure parameter, and the image acquisition module is further configured to image the target object again by delivering rays based on the second exposure parameter and obtain a radiographic image of the target object.

[0021] In some embodiments, the first exposure parameter and the second exposure parameter include tube voltage, tube current, and layup duration. To determine the second exposure parameter based on the first exposure parameter, the parameter determination module is further configured to perform at least one of the following operations: Adjusting at least one of the tube voltage, tube current, and layup duration included in the first exposure parameter to obtain the second exposure parameter.

[0022] In some embodiments, to determine the second parameter, the parameter determination module is further configured to perform at least one of the following operations: determining the equivalent thickness of the target object based on the first exposure parameter and the first target brightness; and determining the second exposure parameter based on the equivalent thickness of the target object and the second target brightness.

[0023] In some embodiments, to determine the equivalent thickness of the target object, the parameter determination module is further configured to perform at least one of the following operations: determining the equivalent thickness of the target object based on a first exposure parameter, a first target brightness, and a brightness-thickness-parameter model; wherein the brightness-thickness-parameter model includes at least the correlation between image brightness, object thickness, and exposure parameters.

[0024] In some embodiments, the system further includes a model determination module configured to perform at least one of the following operations: acquiring exposure parameters corresponding to multiple test targets of different thicknesses when their image brightness reaches multiple different brightness levels; determining multiple fitting functions between the multiple test target thicknesses and their corresponding exposure parameters at different brightness levels, and using the fitting functions as the brightness-thickness-parameter model; or training an initial model based on the multiple test target thicknesses, exposure parameters, and corresponding image brightness to obtain a trained brightness-thickness-parameter model; wherein the initial model is a statistical model or a machine learning model.

[0025] In some embodiments, the exposure parameters in the brightness-thickness-parameter model include tube voltage and tube current; the relationship between tube voltage and tube current follows the ABS curve.

[0026] In some embodiments, the system is applied to a C-arm X-ray imaging system.

[0027] In some embodiments, the C-arm X-ray imaging system includes a mobile C-arm or a digital subtraction angiography (DSA) device.

[0028] In some embodiments, the control commands originate from the exposure handbrake.

[0029] One aspect of this application provides an apparatus for acquiring radiographic images, the apparatus including a processor and a memory; the memory is used to store instructions, characterized in that, when the instructions are executed by the processor, the apparatus causes to perform any of the operations described above for acquiring radiographic images.

[0030] One aspect of this application provides a computer-readable storage medium, characterized in that the storage medium stores computer instructions, and when a computer reads the computer instructions in the storage medium, the computer performs any of the operations described above to acquire radiographic images. Attached Figure Description

[0031] This application will be further described by way of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting; in these embodiments, the same reference numerals denote the same structures, wherein:

[0032] Figure 1 This is an exemplary flowchart illustrating the acquisition of radiographic images according to some embodiments of this application;

[0033] Figure 2 This is a block diagram of an exemplary processing apparatus according to some embodiments of this application;

[0034] Figure 3 This is an exemplary flowchart illustrating the acquisition of first exposure parameters according to some embodiments of this application;

[0035] Figure 4 This is an exemplary flowchart illustrating the acquisition of second exposure parameters according to some embodiments of this application;

[0036] Figure 5 This is an exemplary schematic diagram of an ABS curve according to some embodiments of this application. Detailed Implementation

[0037] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are merely some examples or embodiments of this application. For those skilled in the art, these drawings can be applied to other similar scenarios without creative effort. Unless obvious from the context or otherwise specified, the same reference numerals in the drawings represent the same structures or operations.

[0038] It should be understood that the terms “system,” “device,” “unit,” and / or “module” used herein are one way to distinguish different components, elements, parts, sections, or assemblies at different levels. However, if other terms can achieve the same purpose, they may be replaced by other expressions.

[0039] As indicated in this application and claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" do not specifically refer to the singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of explicitly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0040] Flowcharts are used in this application to illustrate the operations performed by the system according to embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, the steps can be processed in reverse order or simultaneously. Furthermore, other operations can be added to these processes, or one or more steps can be removed from them.

[0041] This application discloses a method for acquiring high-quality (e.g., low-noise, high-contrast) radiographic images. The processing device implementing this method, upon receiving a single control command, can complete the steps of finding and / or converting exposure parameters, and then irradiate the target with appropriate exposure parameters to acquire a radiographic image. The method integrates the finding and conversion of exposure parameters with the final imaging process, controlled by a single command, ensuring accurate exposure parameters for each imaging session. Simultaneously, it reduces the number of radiation exposures, improving the user experience (e.g., the operator of the exposure equipment) and further ensuring user safety. In some embodiments, the methods, systems, devices, and storage media disclosed in this application can be applied to various scenarios such as medical diagnosis and treatment, industrial material testing, and security inspection. It should be understood that the application scenarios of the systems and methods in this application are merely some examples or embodiments of this application. For those skilled in the art, without creative effort, this application can be applied to other similar scenarios based on these figures.

[0042] Figure 1 This is an exemplary flowchart of a method for acquiring radiographic images according to some embodiments of this application. In some embodiments, process 100 can be executed by processing logic, which may include hardware (e.g., circuitry, dedicated logic, programmable logic, microcode, etc.), software (instructions running on a processing device to execute hardware simulations), and any combination thereof. Figure 1 One or more operations in the process 100 shown for acquiring radiographic images can be performed via Figure 2 The processing device 200 shown is implemented as such. For example, process 100 can be stored in a storage device as instructions and invoked and / or executed by the processing device 200. Figure 1 As shown, process 100 may include at least one of the following operations.

[0043] Step 110: Obtain control commands. In some embodiments, step 110 may be performed by the command receiving module 210.

[0044] In some embodiments, the control command may be acquired at a first moment. The first moment can refer to any point in a complete related process involving the target to be imaged. For illustrative purposes only, assuming the target to be imaged is a patient, the related process involving the patient may include diagnosis, treatment, rehabilitation, etc. The first moment can be any point in time during the patient's diagnosis, pre-operative, intra-operative, post-operative, and recovery periods. As another example, assuming the target to be imaged is a material, the related process involving the material may include detection, repair, and post-repair confirmation, etc. The first moment can be any point in time during the material's flaw detection, defect repair, and post-repair confirmation. In some embodiments, the first moment can be a point in time during the patient's surgery.

[0045] In some embodiments, the control command may be an instruction to control the X-ray imaging device to irradiate the target and acquire a radiographic image. The control command may originate from an exposure control switch, such as the exposure control device of the X-ray imaging device. The X-ray imaging device may include medical X-ray imaging equipment, industrial X-ray inspection machines, flaw detectors, security scanners, etc. The medical X-ray imaging device may include, but is not limited to, computed tomography (CT), single-photon emission computed tomography (SPECT), positron emission tomography (PET), digital radiography (DR), computed radiography (CR), screen-film X-ray machines, gastrointestinal machines, digital subtraction angiography (DSA), mobile X-ray equipment (such as a mobile C-arm machine), linear accelerators, etc., or any combination thereof. Preferably, the medical X-ray imaging device may be a C-arm machine. Exemplary rays may include X-rays, gamma rays, beta rays, electron beams, proton beams, etc., or any combination thereof. Rays passing through the object to be imaged can be detected, for example, by the detector of the imaging device in the form of projected data. After data processing (e.g., denoising, smoothing, enhancement, reconstruction, etc.), a radiographic image of the target can be obtained.

[0046] In some embodiments, the control instructions may include a pre-imaging start instruction and an imaging start instruction. Pre-imaging may refer to the process of applying an appropriate amount of radiation to the target to be imaged to form at least one image to determine or find appropriate pre-imaging exposure parameters or exposure parameters. The image obtained during the pre-imaging process may be referred to as a pre-imaging image. Imaging may refer to the process of acquiring an image of the target to be imaged based on the pre-imaging exposure parameters of the pre-imaging process or based on the exposure parameters determined by the pre-imaging process. The imaging exposure parameters used during the imaging process may be the same as or different from the pre-imaging exposure parameters. The image obtained after the imaging process is completed may be archived as the official or final imaging result of the target to be imaged, may serve as a reference during other parts of the related process, or may be retained as an ongoing record. In some embodiments, pre-imaging may be fluoroscopy, and imaging may be single-frame image acquisition. In some embodiments, the control instructions may be input by a user of the X-ray imaging device (e.g., a physician). For example, a physician may press an image acquisition button on the operating panel of the X-ray imaging device to send a control instruction. Upon receiving the control instruction, a processing device, such as processing device 200 in the X-ray imaging device, may start the pre-imaging and imaging processes based on the start instruction contained within the control instruction.

[0047] Step 120: Based on the control command, pre-image the target object using delivered rays to obtain first exposure parameters. In some embodiments, step 120 may be performed by parameter determination module 220.

[0048] In some embodiments, the target object can refer to the object to be imaged, including a patient, a phantom, industrial materials, items to be inspected, etc. The target object can also be a part or organ of the patient, such as the head, chest, abdomen, or limbs. The first exposure parameter can be a pre-imaging exposure parameter that ensures the difference between the brightness of the pre-imaging image and the set first target brightness meets a preset condition. The first target brightness can refer to the brightness that enables the pre-imaging image to achieve the desired clarity. In some embodiments, the first target brightness can be pre-stored in the processing device 200, input by the user, or adjusted according to different application scenarios; this application does not impose specific limitations.

[0049] During pre-imaging, a processing device, such as processing device 200 in a X-ray imaging device, can acquire at least one pre-imaging image (e.g., 3 to 5 frames). Each pre-imaging image will have different brightness due to different exposure parameters. Generally, exposure parameters may include tube voltage, tube current, and firing duration. The tube can refer to a radiation source tube, such as an X-ray tube. The tube voltage refers to the voltage applied between the two poles of the radiation tube to form a particle (e.g., electron) acceleration field and determines the intensity (or photon energy) of the radiation. The tube current refers to the accelerated particle beam (e.g., electron beam). The tube current is determined by the tube voltage and the radiation tube current. The firing duration can refer to the duration of radiation emission. The product of the tube current and the firing duration determines the amount of radiation (or the number of photons), and the product of the tube voltage, tube current, and firing duration determines the energy input to the radiation tube. Because different pre-imaging exposure parameters result in different energies of emitted radiation, the energy of the radiation received by the radiation detector after passing through the target object is also different, resulting in different image brightness. In some embodiments, the brightness of a pre-image can be subtracted from the brightness of the first target image to obtain the difference between the two, which can be designated as the difference. The preset condition can refer to the absolute value of the difference not exceeding a preset brightness difference threshold, such as 1, 5, 10, etc. When the preset condition is met, the pre-image exposure parameters used to form the pre-image of that brightness can be designated as the first exposure parameters. In some embodiments, the first exposure parameters may include a first tube voltage, a first tube current, and a first wire feeding duration.

[0050] In some embodiments, the first exposure parameters can be determined based on a comparison between the brightness of the pre-image and the brightness of the first target, and an ABS (automatic brightness stabilization) curve. The ABS curve can be a curve composed of parameters that maintain image brightness consistency under different conditions (e.g., different thickness conditions, different application scenarios) while ensuring image quality requirements. (Reference) Figure 5 , Figure 5 This is a schematic diagram of exemplary ABS curves according to some embodiments of this application. Figure 5As shown, the ABS curve represents tube current (mA) on the x-axis and tube voltage (kV) on the y-axis. Using parameters indicated by points on the same curve, for the same target object (i.e., constant thickness) and the same casting time, the exposure parameters corresponding to points on the right side of the curve result in a brighter image than those corresponding to points on the left. This can be understood as follows: to maintain constant brightness, under the same casting time, the exposure parameters used for a thinner target object correspond to a point on the curve that is further to the left than those used for a thicker target object. Similarly, the ABS curve can also reflect the relationship between the exposure parameters (e.g., tube voltage and the current-time product (tube voltage multiplied by casting time)) used to maintain constant image brightness for target objects with different casting times (i.e., different thicknesses). Figure 5 The ABS curves shown contain three curves, each corresponding to different application requirements. LD represents low dose, a mode that reduces the radiation dose compared to the standard mode. Parameters affecting image brightness can include tube voltage, tube current, and cable loading time. Increasing tube voltage increases radiation penetration, resulting in more radiation reaching the radiation detector of the imaging device, while reducing the amount of radiation absorbed by the target object (e.g., the human body). Therefore, to maintain the same brightness at different thicknesses, the tube voltage can be significantly increased or decreased, while the tube current can be slightly increased or decreased to maintain brightness. S represents standard mode. This curve meets most application requirements, providing a moderate radiation dose to the human body while ensuring brightness. HC represents high contrast mode. High contrast requires a high-contrast image, necessitating a larger tube current and a longer loading time.

[0051] Return to reference Figure 1 In some embodiments, the processing device, such as processing device 200, can arbitrarily select a point on the ABS curve as the initial pre-imaging exposure parameter to expose the target object and acquire the brightness of the pre-imaging image. Then, the difference between the brightness of the pre-imaging image and the brightness of the first target is determined. Based on the comparison result (e.g., the brightness of the pre-imaging image is less than the first target brightness, or the brightness of the pre-imaging image is greater than the first target brightness), the processing device 200 can find the next point along the ABS curve (e.g., move left or right along the curve) and perform the next imaging with the corresponding exposure parameter, and compare the brightness of the newly acquired pre-imaging image with the first target brightness until the difference between the brightness of the pre-imaging image and the first target brightness meets a preset condition. The pre-imaging parameter at this time can be used as the first exposure parameter. For a detailed description of acquiring the first exposure parameter, please refer to other parts of this application (e.g., Figure 3(This will not be elaborated upon here.)

[0052] Step 130: Image the target object again by delivering rays according to the first exposure parameters to obtain a radiographic image of the target object. In some embodiments, step 130 may be performed by the image acquisition module 230.

[0053] It is understood that in some embodiments, the amount of radiation delivered to the target object during the pre-imaging process is relatively small, while the amount of radiation delivered to the target object is relatively large due to the requirement for high resolution in the single-frame radiation image to be obtained during the imaging process. Based on this, a processing device such as processing device 200 can first determine a second exposure parameter based on the first exposure parameter, and then image the target object using the delivered radiation based on the second exposure parameter to obtain a radiation image of the target object. Similar to the first exposure parameter, the second exposure parameter may include a second tube voltage, a second tube current, and a second wire laying duration. The processing device such as processing device 200 can adjust at least one of the first tube voltage, the first tube current, and the first wire laying duration in the first exposure parameter to obtain the second exposure parameter. In some embodiments, the first tube voltage can be directly specified as the second tube voltage, i.e., keeping the tube voltage unchanged. The first tube current can be increased by a first increment to obtain the second tube current. The first wire laying duration can be directly specified as the second wire laying duration. In some embodiments, the first tube voltage can be directly specified as the second tube voltage. The first tube current can be directly specified as the second tube current. The first wire laying duration can be increased by a second increment to obtain the second wire laying duration. In some embodiments, the first tube voltage can be directly specified as the second tube voltage. The first tube current can be increased by a third increment to obtain the second tube current. The first discharge duration can be increased by a fourth increment to obtain the second discharge duration. The first, second, third, and fourth increments can be determined based on the brightness of the radiographic image to be acquired during the imaging process and the brightness of the first target. For example, assuming the brightness of the radiographic image to be acquired during the imaging process is A, and the brightness of the first target is B, then the amount of radiation required during the imaging process is A / B times the amount of radiation emitted during the pre-imaging process. Therefore, if the tube voltage remains unchanged, the product of the second tube current and the second discharge duration is A / B times the product of the first tube current and the first discharge duration. Based on the above relationship, the first, second, third, and fourth increments can be determined. The first, second, third, and fourth increments can also be preset values ​​of the processing device, such as processing device 200, or values ​​input by a user (e.g., a doctor). This application does not limit this.

[0054] In some embodiments, a parameter determination model can be used to determine the second exposure parameter. The parameter determination model can be obtained by training multiple sample data pairs. A sample data pair may include an exposure parameter, the thickness of an object to be imaged, and the brightness of the corresponding image. The exposure parameters used may include tube voltage, tube current, wire release time, etc., and the relationship between tube voltage, tube current, and wire release time follows an ABS curve. For example, a point on the ABS curve indicating the exposure parameter and the image brightness maintained at different thicknesses can be considered a sample data pair. In some embodiments, the parameter determination model can be multiple fitting functions obtained by fitting the sample data pairs, or it can be a statistical model trained on the sample data pairs, such as a multiple regression model, or a machine learning model, such as a neural network model. The parameter determination model can determine the remaining value based on any two values ​​between the input exposure parameter, thickness, and image brightness. For example, the parameter determination model can determine the brightness of the image obtained by imaging based on the exposure parameter and thickness. In some embodiments, the parameter determination model can be a single overall model or may include multiple sub-models. After the first exposure parameter is determined, combining it with the first target brightness and inputting both into the parameter determination model can determine the thickness of the target object. After the thickness of the target object is determined, the brightness of the radiometric image required for the imaging process (such as the brightness of the second target) can be combined with the input parameters to determine the model and obtain the second exposure parameters. For a detailed description of obtaining the second exposure parameters, please refer to other parts of this application (e.g., Figure 4 (This will not be elaborated upon here.)

[0055] In some embodiments, the processing device, such as processing device 200, can directly deliver rays to the target object based on the first exposure parameters to obtain a radiation image. For example, when the requirements for the radiation image obtained during the imaging process are not high, or when the principle of combining a small amount of rays in the pre-imaging process with a high quality of the radiation image obtained during the imaging process is met, the target object can be directly imaged based on the first exposure parameters.

[0056] It should be noted that the above description of process 100 is merely for illustration and explanation, and does not limit the scope of this application. Those skilled in the art can make various modifications and changes to process 100 under the guidance of this application. However, these modifications and changes are still within the scope of this application. For example, step 120 can be divided into a brightness comparison process and a process for obtaining the first exposure parameters. Step 130 can be divided into a parameter conversion process and a process for obtaining the X-ray image.

[0057] Figure 2 This is a block diagram of a processing apparatus 200 according to some embodiments of this application. For example... Figure 2As shown, the processing module 200 may include an instruction receiving module 210, a parameter determination module 220, an image acquisition module 230, and a model acquisition module 240.

[0058] The instruction receiving module 210 can receive control instructions. The instruction receiving module 210 can acquire control instructions at a first moment. The first moment can refer to any point in a complete related process involving the target to be imaged. For illustrative purposes only, assuming the target to be imaged is a patient, the related process involving the patient can include diagnosis, treatment, rehabilitation, etc. The first moment can be any point in time during the patient's diagnosis, pre-operative, intra-operative, post-operative, or recovery period. The control instructions can be instructions to control the X-ray imaging device to irradiate the target and acquire a radiographic image, and may include pre-imaging initiation instructions and imaging initiation instructions. Pre-imaging can refer to the process of applying an appropriate amount of radiation to the target to form at least one image to determine or find appropriate pre-imaging exposure parameters or exposure parameters. Imaging can refer to the process of acquiring an image of the target based on the pre-imaging exposure parameters or the exposure parameters determined by the pre-imaging process.

[0059] The parameter determination module 220 can perform pre-imaging on the target object using the delivered ray based on the control command to obtain first exposure parameters. In some embodiments, the parameter determination module 220 can obtain pre-imaging exposure parameters and the brightness of at least one frame of pre-imaging image, and compare the brightness with a set first target brightness. After obtaining the comparison result, the parameter determination module 220 can update the pre-imaging exposure parameters based on the comparison result and the ABS curve, so that the difference between the pre-imaging image brightness and the first target brightness meets a preset condition, and use the updated pre-imaging exposure parameters as the first exposure parameters. The pre-imaging exposure parameters may refer to the preset exposure parameters used in the pre-imaging process on the target object, including tube current, tube voltage, and wire laying time. The parameter determination module 220 can compare the brightness value of the image (e.g., the pre-imaging image) obtained using the preset exposure parameters with the value of the first target brightness to obtain a comparison result, including the brightness of the pre-imaging image being less than the first target brightness, the brightness of the pre-imaging image being equal to the first target brightness, or the brightness of the pre-imaging image being greater than the first target brightness. When the brightness of the pre-image is less than the first target brightness, the parameter determination module 220 can move to the right (e.g., in the direction of increasing horizontal coordinate) along the ABS curve to determine the next point. When the brightness of the pre-image is greater than the first brightness, the parameter determination module 220 can move to the left (e.g., in the direction of decreasing horizontal coordinate) along the ABS curve to determine the next point. After re-determining a point and its corresponding exposure parameters (e.g., tube voltage and tube current), the parameter determination module 220 can control the X-ray imaging device to acquire a new pre-image of the target object and its corresponding image brightness based on the updated pre-image exposure parameters. It then compares this image with the first target brightness again to obtain a comparison result. This process is repeated until the difference between the updated pre-image brightness and the first target brightness meets a preset condition. When the difference meets the preset condition, the updated pre-image exposure parameters can be used as the first exposure parameters. The difference can refer to the value between the brightness of the pre-image and the value of the first target brightness. The preset condition can refer to the absolute value of the difference between the two brightness values ​​being less than or equal to a brightness difference threshold. When the brightness of the pre-image is equal to the first target brightness, the parameter determination module 220 can directly use the pre-image exposure parameters as the first exposure parameters. In some embodiments, the parameter determination module 220 can transform the data contained in the first exposure parameters to obtain second exposure parameters, for example, by changing at least one of the tube voltage, tube current, and wire laying time. In some embodiments, the parameter determination module 220 can determine the equivalent thickness of the target object based on the first exposure parameters and the first target brightness, and determine the second exposure parameters based on the equivalent thickness of the target object and the second target brightness.The parameter determination module 220 inputs the first exposure parameters and the first target brightness into the brightness-thickness-parameter model to obtain the equivalent thickness of the target object. It then combines the equivalent thickness of the target object with the second target brightness and inputs both into the brightness-thickness-parameter model to obtain the second exposure parameters. The second exposure parameters may include the second tube voltage, the second tube current, the second wire laying time, etc.

[0060] The image acquisition module 230 can image the target object using determined exposure parameters (e.g., a first exposure parameter or a second exposure parameter) to obtain a radiographic image of the target object. For example, when the requirements for the radiographic image obtained during the imaging process are not high, or when the principle of combining a small amount of radiation in the pre-imaging process with a high quality of radiation image obtained during the imaging process is met, the image acquisition module 230 can directly image the target object based on the first exposure parameter. Alternatively, under conditions requiring higher performance, the image acquisition module 230 can image the target object based on a second exposure parameter determined by other components of the processing device 200 (e.g., the parameter determination module 220).

[0061] The model acquisition module 240 can acquire a brightness-thickness-parameter model. The model acquisition module 240 can acquire the exposure parameters corresponding to the image brightness of test targets of different thicknesses when the brightness reaches multiple different brightness levels. The exposure parameters may include tube voltage, tube current, and cable laying time, where the points corresponding to tube voltage and tube current are located on the ABS curve. Then, the model acquisition module 240 can determine multiple fitting functions between the thicknesses of multiple test targets and their corresponding exposure parameters at different brightness levels, and use these fitting functions as the brightness-thickness-parameter model. Alternatively, the model acquisition module 240 can train an initial model based on the thicknesses of multiple test targets, exposure parameters, and the brightness of the corresponding images to obtain a trained brightness-thickness-parameter model. The initial model can be a statistical model, such as a multiple regression model, or a machine learning model, such as a neural network model. The model acquisition module 240 can also use a statistical model obtained by statistically analyzing data on multiple thicknesses, brightness levels, and corresponding exposure parameters as the brightness-thickness-parameter model. The brightness-thickness-parameter model can be predetermined and stored in a storage device (e.g., the memory built into the processing device 200, or an external storage device connected to the processing device 200 via a wired or wireless connection). The model acquisition module 240 can communicate with the storage device to obtain the brightness-thickness-parameter model. Alternatively, the brightness-thickness-parameter model can be obtained by the model acquisition module 240 through statistical analysis of the exposure parameters corresponding to image brightness levels of test targets of different thicknesses at multiple different brightness levels.

[0062] It should be understood that Figure 2 The systems and modules shown can be implemented in various ways. For example, in some embodiments, the systems and modules can be implemented by hardware, software, or a combination of both. The hardware portion can be implemented using dedicated logic; the software portion can be stored in memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated-design hardware. Those skilled in the art will understand that the methods and systems described above can be implemented using computer-executable instructions and / or included in processor control code, for example, on a carrier medium such as a disk, CD, or DVD-ROM, a programmable memory such as read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The systems and modules of this application can be implemented not only by hardware circuits such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field-programmable gate arrays, programmable logic devices, etc., but also by software executed by various types of processors, or by a combination of the aforementioned hardware circuits and software (e.g., firmware).

[0063] It should be noted that the above description of the candidate display and determination system and its modules is for convenience only and should not limit this application to the scope of the embodiments described. It is understood that those skilled in the art, after understanding the principle of this system, may arbitrarily combine the various modules or construct subsystems connected to other modules without departing from this principle. For example, in some embodiments, for example, Figure 2 The acquisition module 210, parameter determination module 220, and image acquisition module 230 disclosed herein can be different modules within a single system, or a single module can implement the functions of two or more of the aforementioned modules. For example, the acquisition module 210 and parameter determination module 220 can be two separate modules, or a single module can simultaneously possess the functions of acquiring instructions and determining parameters. Furthermore, the modules can share a single storage module, or each module can have its own dedicated storage module. Such variations are all within the scope of protection of this application.

[0064] Figure 3 This is an exemplary flowchart illustrating the acquisition of first exposure parameters according to some embodiments of this application. In some embodiments, process 300 can be executed by processing logic, which may include hardware (e.g., circuitry, dedicated logic, programmable logic, microcode, etc.), software (instructions running on a processing device to execute hardware simulations), and any combination thereof. Figure 3 One or more operations in the process 300 shown for obtaining the first exposure parameters can be performed by... Figure 2The processing device 200 shown (e.g., parameter determination module 220) implements this. For example, process 300 can be stored in a storage device as instructions and invoked and / or executed by the processing device 200. Figure 3 As shown, process 300 may include at least one of the following operations.

[0065] Step 310: Obtain the pre-imaging exposure parameters and the brightness of at least one frame of the pre-imaging image.

[0066] In some embodiments, the pre-imaging exposure parameters may refer to pre-set exposure parameters used in the pre-imaging process of the target object, including tube current, tube voltage, and wire placement time. In some embodiments, the pre-imaging exposure parameters may be stored in a processing device such as processing device 200 (e.g., in the processing device 200's own storage device), in the storage device of the X-ray imaging device itself or an external storage device, or in a cloud storage device. In use, processing device 200 can access the storage device to obtain the pre-imaging exposure parameters. In some embodiments, the pre-imaging exposure parameters may be set and input by a user (e.g., a doctor or nurse). In some embodiments, the correspondence between the tube voltage, tube current, and wire placement time included in the pre-imaging exposure parameters may conform to the ABS curve. For example, the tube voltage, tube current, and wire placement time included in the pre-imaging exposure parameters may be the tube voltage, tube current, and wire placement time corresponding to a point on the ABS curve.

[0067] In some embodiments, the pre-image can be an image formed by the rays passing through the target object and received by the imaging device after rays are delivered to the target object according to pre-image exposure parameters during the pre-image process. The imaging device may include a ray detector (e.g., a gas detector, scintillation detector, semiconductor detector, etc.) in a ray imaging apparatus, which converts ray energy into a recordable electrical signal. The projection data contained in the electrical signal is processed to obtain an image. The obtained image can be called the pre-image. The brightness can be an attribute of the pre-image, and the brightness can be directly obtained after obtaining the pre-image.

[0068] Step 320: Compare the brightness with the set first target brightness.

[0069] In some embodiments, the first target brightness may refer to a standard brightness set during the pre-imaging process that meets the requirements. For example, the first target brightness may be the minimum brightness that ensures the pre-imagined image is sufficiently clear. In this case, when the pre-imagined image is at the first target brightness, the amount of radiation delivered by the X-ray imaging device is less, which is less harmful to the target object (e.g., a patient) as a living organism. In some embodiments, the first target brightness may be a default value of the X-ray imaging device, pre-stored in a processing device such as processing device 200 (e.g., in the processing device 200's own storage device), in the X-ray imaging device's own or external storage device, or in a cloud storage device, or determined by user input (e.g., a doctor). This application does not specifically limit this.

[0070] In some embodiments, the processing device 200 can directly compare the brightness value with the value of the first target brightness. Specifically, the processing device 200 can compare whether the brightness value is greater than, less than, or equal to the first target brightness, and determine the comparison result.

[0071] Step 330: Update the pre-imaging exposure parameters based on the comparison results and the ABS curve so that the difference between the brightness of the pre-imaging image and the brightness of the first target meets the preset conditions, and use the updated pre-imaging exposure parameters as the first exposure parameters.

[0072] In some embodiments, the ABS curve can reflect the exposure parameters (e.g., tube voltage and tube current data pairs) of different brightness obtained by imaging an object of the same thickness under the same laying time. On the same ABS curve, along the curve trend, the image brightness obtained using the exposure parameters corresponding to the points on the right is higher than the image brightness obtained using the exposure parameters corresponding to the points on the left. Different ABS curves can be used for different thicknesses and different application scenarios. For example, there are corresponding ABS curves for the patient's hand and head, respectively. The ABS curve can also include a general ABS curve. The general ABS curve can be applied to most thickness ranges, for example, the thickness range applicable to most human body parts. Exemplary ABS curves and their descriptions can be found in [reference]. Figure 5 And its description.

[0073] In conjunction with step 320, the comparison result may include the brightness of the pre-image being less than the first target brightness, the brightness of the pre-image being equal to the first target brightness, or the brightness of the pre-image being greater than the first target brightness. In some embodiments, when the brightness of the pre-image is less than the first target brightness, it indicates that the amount of rays passing through the target object is less than the amount of rays required to make the brightness of the pre-image reach the first target brightness, and the amount of delivered rays needs to be increased. In this case, the tube current can be increased. The processing device 200 can move to the right (e.g., in the direction of increasing horizontal axis) along the ABS curve to determine the next point and its corresponding increased tube voltage and tube current. When the brightness of the pre-image is greater than the first brightness, it indicates that the amount of rays passing through the target object is greater than the amount of rays required to make the brightness of the pre-image reach the first target brightness, and the amount of delivered rays needs to be reduced. In this case, the tube current can be reduced. The processing device 200 can move to the left (e.g., in the direction of decreasing horizontal axis) along the ABS curve to determine the next point and its corresponding reduced tube voltage and tube current. Then, the processing device 200 can control the X-ray imaging device to acquire a new pre-image of the target object and its corresponding image brightness based on the updated pre-image exposure parameters. This image brightness is then compared again with the first target brightness to obtain a comparison result. This process is repeated until the difference between the updated pre-image brightness and the first target brightness meets a preset condition. When the difference meets the preset condition, the updated pre-image exposure parameters can be used as the first exposure parameters. The difference can refer to the value between the brightness of the pre-image and the brightness of the first target. The preset condition can refer to the absolute value of the difference between the two brightness values ​​being less than or equal to a brightness difference threshold. The brightness difference threshold can be a default value of the X-ray imaging device, pre-stored in the processing device (e.g., the processing device 200's own storage device), in the X-ray imaging device's own or an external storage device, or in a cloud storage device, or determined by user input (e.g., a doctor). This application does not specifically limit this. It should be noted that during the first comparison, if the difference between the brightness value of the pre-image and the brightness value of the first target already meets the preset condition, the pre-image exposure parameters do not need to be updated, and the pre-image exposure parameters of the first pre-image can be directly used as the first exposure parameters.

[0074] When the brightness of the pre-image is equal to the brightness of the first target, the processing device 200 can directly use the pre-image exposure parameters as the first exposure parameters.

[0075] It should be noted that the above description of process 300 is merely for illustration and explanation, and does not limit the scope of this application. Those skilled in the art can make various modifications and changes to process 300 under the guidance of this application. However, these modifications and changes are still within the scope of this application. For example, step 330 can be divided into multiple steps, including, for example, a judgment step to determine whether the difference between the brightness of the pre-image and the brightness of the first target meets a preset condition; an update step to update the pre-image exposure parameters based on the result of the judgment step combined with the ABS curve and return to step 310 to perform a new iteration; and a determination step to use the updated pre-image exposure parameters as the first exposure parameters if the difference between the brightness of the pre-image and the brightness of the first target meets the preset condition.

[0076] Figure 4 This is a flowchart illustrating the acquisition of second exposure parameters according to some embodiments of this application. In some embodiments, process 400 can be executed by processing logic, which may include hardware (e.g., circuitry, dedicated logic, programmable logic, microcode, etc.), software (instructions running on a processing device to execute hardware simulations), and any combination thereof. Figure 4 One or more operations in the process 400 shown for obtaining the first exposure parameters can be performed via Figure 2 The processing device 200 shown (e.g., parameter determination module 220) implements this. For example, process 400 can be stored in a storage device as instructions and invoked and / or executed by the processing device 200. Figure 4 As shown, process 400 may include at least one of the following operations.

[0077] Step 410: Determine the equivalent thickness of the target object based on the first exposure parameters and the first target brightness.

[0078] In some embodiments, the equivalent thickness may refer to a calculated numerical value representing the average thickness of the target object. The equivalent thickness can be determined based on a first exposure parameter, a first target brightness, and a brightness-thickness-parameter model. In some embodiments, the brightness-thickness-parameter model can be obtained by training multiple brightness-thickness-parameter data pairs. Each brightness-thickness-parameter data pair consists of an exposure parameter, the thickness of a target to be imaged, and the corresponding brightness of the resulting image. The three values ​​in each brightness-thickness-parameter data pair are one-to-one and interrelated. Knowing any two values ​​allows the determination of the remaining value. Therefore, the brightness-thickness-parameter model at least reflects the relationship between image brightness, object thickness, and exposure parameter. In some embodiments, the processing device 200 can directly input the first exposure parameter and the first target brightness into the brightness-thickness-parameter model to obtain the equivalent thickness of the target object.

[0079] In some embodiments, the brightness-thickness-parameter model can be determined in a variety of ways, including function fitting, model training, or any combination thereof.

[0080] In some embodiments, the processing device 200 (e.g., model acquisition module 240) can acquire the exposure parameters corresponding to different brightness levels of the image of a test target with different thicknesses. In this application, a water phantom or PMMA phantom with a similar attenuation degree to the target object for rays (e.g., X-rays) can be used to perform multiple ray deliveries to acquire the exposure parameters corresponding to different brightness levels of the ray images of the water phantom or phantom with different thicknesses. The processing device 200 can use the acquired data to perform function fitting or model training to obtain the brightness-thickness-parameter model. In some embodiments, the exposure parameters used in the process of acquiring the brightness-thickness-parameter model (fitting or training) include tube voltage and tube current, and the relationship between the two can conform to the ABS curve. For example, the same image brightness obtained at the same thickness can correspond to multiple exposure parameters, such as different tube voltages, tube currents, and wire laying times. The points corresponding to the tube voltage and tube current are located on the ABS curve.

[0081] In some embodiments, the processing device 200 (e.g., model acquisition module 240) can determine multiple fitting functions for the thickness of multiple test targets and their corresponding exposure parameters under different brightness levels, and use the fitting functions as the brightness-thickness-parameter model. Exemplary data fitting methods include linear fitting, quadratic function fitting, nth-degree polynomial fitting of data, exponential function data fitting, multivariate linear function data fitting, etc., or combinations thereof. As an example only, the data fitting process may include: plotting a scatter plot of the three sets of data—brightness, thickness, and exposure parameters; determining a suitable fitting function model based on the distribution of the scatter plot, wherein the function can be fitted using the least squares method. In some embodiments, the data fitting process can be performed in software such as Origin, MATLAB, and SPSS. The fitting function model determined through fitting is the brightness-thickness-parameter model.

[0082] In some embodiments, the processing device 200 (e.g., the model acquisition module 240) can train an initial model based on multiple test target thicknesses, exposure parameters, and the corresponding image brightness to obtain a trained brightness-thickness-parameter model. The initial model can be a statistical model or a machine learning model. Exemplary statistical models may include multiple regression models, cluster analysis models, discriminant analysis models, principal component analysis models, factor analysis models, and time series analysis models. Exemplary machine learning models may include linear classifiers (such as LR), neural network models, support vector machines (SVM), Naive Bayes (NB), K-nearest neighbors (KNN), decision trees (DT), ensemble models (RF / GDBT, etc.), etc. As an example only, the processing device 200 can select a portion of the brightness, exposure parameters, and thickness data as training data and another portion as test data to train the initial model. In some embodiments, the trained brightness-thickness-parameter model can be a single overall model or may include multiple sub-models. Inputting any two values ​​from the image brightness, target thickness, and exposure parameters yields the remaining value.

[0083] In some embodiments, the processing device 200 (e.g., the model acquisition module 240) can perform statistical analysis on the exposure parameters corresponding to the image brightness of test targets of different thicknesses when the brightness reaches multiple different brightness levels. The resulting statistical model can be used as the brightness-thickness-parameter model.

[0084] In some embodiments, the brightness-thickness-parameter model may be a pre-determined statistical model stored in a storage device (e.g., the memory built into the processing device 200, or an external storage device connected to the processing device 200 via a wired or wireless connection). The model acquisition module 240 may communicate with the storage device to obtain the brightness-thickness-parameter model. In some embodiments, the first exposure parameter and the first target brightness may be input into the aforementioned determined brightness-thickness-parameter model to obtain the equivalent thickness of the target object.

[0085] Step 420: Determine the second exposure parameters based on the equivalent thickness of the target object and the second target brightness.

[0086] In some embodiments, the second target brightness refers to the brightness required for the radiographic image acquired during the imaging process. The brightness of the radiographic image, i.e., the second target brightness, can meet the requirements for diagnosis and / or judgment. For example, it needs to meet the requirements for disease diagnosis and / or surgical progress comparison and judgment in medical procedures. The second target brightness can be a default value of the X-ray imaging device, pre-stored in a processing device such as processing device 200 (e.g., in the processing device 200's own storage device), in the X-ray imaging device's own or external storage device, or in a cloud storage device, or determined by a user (e.g., a doctor). This application does not specifically limit this. In some embodiments, after determining the equivalent thickness of the target object, the second target brightness can be combined with the second target brightness, and both can be input into a brightness-thickness-parameter model to obtain the second exposure parameters. The second exposure parameters may include the second tube voltage, the second tube current, the second wire extension duration, etc.

[0087] It should be noted that the above description of process 400 is merely for illustration and explanation, and does not limit the scope of this application. Those skilled in the art can make various modifications and changes to process 400 under the guidance of this application. However, these modifications and changes are still within the scope of this application.

[0088] Figure 5 This is a schematic diagram of ABS curves according to some embodiments of this application. For example... Figure 5As shown, the ABS curve's horizontal axis represents tube current (mA), and the vertical axis represents tube voltage (kV). The figure shows three curves corresponding to different applications. LD represents low-dose mode, indicating changes in tube voltage and current at low doses. S represents standard mode, indicating changes in tube voltage and current under standard conditions. HC represents high-contrast mode, indicating changes in tube voltage and current at high contrast. The trend of the ABS curve reflects the changing trends of tube voltage and current while maintaining the same brightness at different thicknesses. To maintain constant image brightness, for different thicknesses, in low-dose mode, the ABS curve shows a significant increase in tube voltage and a slight increase in tube current to keep the output radiation dose low. In standard mode, the ABS curve shows a steady increase in tube current and tube voltage, consistent with parameter changes made to maintain brightness in most cases. In high-contrast mode, the ABS curve shows a rapid increase in tube current and a steady increase in tube voltage. High contrast requires receiving a higher radiation dose to ensure the clarity of the obtained X-ray image. Therefore, the tube current will increase relatively quickly. It should be noted that the above description and selection of the ABS curve are merely illustrative, and the scope of protection of this application is not limited thereto.

[0089] The methods and systems disclosed in the embodiments of this application can be applied to various X-ray imaging devices, such as CT, PET, SPECT, DR, CR, C-arm, etc. Preferably, the methods and systems disclosed in the embodiments of this application can be applied to C-arm X-ray imaging systems. The C-arm X-ray imaging system may include a movable C-arm and / or a digital subtraction angiography (DSA) device. Compared with the prior art, the beneficial effects that the above embodiments of this application may bring include, but are not limited to:

[0090] (1) The pre-imaging process (perspective process) and the imaging process (single frame acquisition) are combined into one operation, which ensures the accuracy of the exposure parameters used in the imaging process, reduces the number of imaging times (e.g., exposure times), and improves the user experience.

[0091] (2) Two operations can be completed with one instruction transmission, which reduces the radiation time and is beneficial to the patient's health.

[0092] It should be noted that different embodiments may produce different beneficial effects. In different embodiments, the beneficial effects may be any one or a combination of the above, or any other possible beneficial effects.

[0093] The foregoing describes this application and / or some other examples. Based on the foregoing, this application can also be modified in various ways. The subject matter disclosed in this application can be implemented in different forms and examples, and this application can be applied to a wide range of applications. All applications, modifications, and alterations claimed in the following claims are within the scope of this application.

[0094] Furthermore, this application uses specific terms to describe embodiments of the application. For example, "an embodiment," "one embodiment," and / or "some embodiments" refer to a particular feature, structure, or characteristic related to at least one embodiment of the application. Therefore, it should be emphasized and noted that "an embodiment," "one embodiment," or "an alternative embodiment" mentioned twice or more in different locations in this specification do not necessarily refer to the same embodiment. In addition, certain features, structures, or characteristics in one or more embodiments of the application can be appropriately combined.

[0095] Those skilled in the art will understand that the content disclosed herein can be varied and modified in many ways. For example, the different system components described above are implemented using hardware devices, but they may also be implemented using only software solutions. For example, installing the system on an existing server. Furthermore, the provision of the location information disclosed herein may be achieved through firmware, a combination of firmware and software, a combination of firmware and hardware, or a combination of hardware / firmware / software.

[0096] All software, or parts thereof, may sometimes communicate via networks, such as the Internet or other communication networks. Such communication enables the loading of software from one computer device or processor to another. For example, loading software from a management server or host computer of a radiotherapy system to a hardware platform of a computer environment, or another computer environment implementing the system, or a system with similar functionality related to providing the information needed to determine the target structural parameters of a wheelchair. Therefore, another medium capable of transmitting software elements can also be used as a physical connection between local devices, such as light waves, radio waves, electromagnetic waves, etc., propagated through cables, fiber optic cables, or air. Physical media used for carrier waves, such as cables, wireless connections, or fiber optic cables, can also be considered as media carrying software. In this context, unless limited to tangible "storage" media, the term "readable medium" for a computer or machine refers to the medium involved in the execution of any instructions by the processor.

[0097] The computer program code required for the operation of each part of this application can be written in any one or more programming languages, including object-oriented programming languages ​​such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB.NET, Python, etc., conventional procedural programming languages ​​such as C, Visual Basic, Fortran 2003, Perl, COBOL 2002, PHP, ABAP, dynamic programming languages ​​such as Python, Ruby, and Groovy, or other programming languages. This program code can run entirely on the user's computer, or as a standalone software package on the user's computer, or partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter case, the remote computer can be connected to the user's computer through any network, such as a local area network (LAN) or wide area network (WAN), or connected to an external computer (e.g., via the Internet), or in a cloud computing environment, or used as a service such as Software as a Service (SaaS).

[0098] Furthermore, unless expressly stated in the claims, the order of processing elements and sequences, the use of numbers and letters, or other names described in this application are not intended to limit the order of the processes and methods of this application. Although the foregoing disclosure has discussed some currently considered useful embodiments of the invention through various examples, it should be understood that such details are for illustrative purposes only, and the appended claims are not limited to the disclosed embodiments; rather, the claims are intended to cover all modifications and equivalent combinations that conform to the substance and scope of the embodiments of this application. For example, while the system components described above can be implemented using hardware devices, they can also be implemented solely through software solutions, such as installing the described system on existing servers or mobile devices.

[0099] Similarly, it should be noted that, in order to simplify the description of the present application and thus aid in the understanding of one or more embodiments of the invention, the foregoing description of the embodiments of the present application sometimes combines multiple features into a single embodiment, drawing, or description thereof. However, this disclosure method does not imply that the subject matter of the application requires more features than those mentioned in the claims. In fact, the embodiments contain fewer features than all the features of the single embodiments disclosed above.

[0100] In some embodiments, numbers describing attributes and quantities are used. It should be understood that such numbers used in the description of embodiments are modified in some examples with the terms "approximately," "approximately," or "generally." Unless otherwise stated, "approximately," "approximately," or "generally" indicates that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may be changed depending on the characteristics required by individual embodiments. In some embodiments, numerical parameters should take into account specified significant digits and employ a general method of digit reservation. Although the numerical ranges and parameters used to confirm their breadth of range in some embodiments of this application are approximate values, in specific embodiments, such values ​​are set as precisely as feasible.

[0101] For each patent, patent application, patent application publication, and other material such as articles, books, specifications, publications, documents, and objects referenced in this application, the entire contents of that patent are incorporated herein by reference. This excludes historical application documents that are inconsistent with or conflict with the content of this application, as well as documents that limit the broadest scope of the claims in this application (currently or subsequently appended to this application). It should be noted that if there are any inconsistencies or conflicts between the descriptions, definitions, and / or terminology used in the supplementary materials of this application and the content of this application, the descriptions, definitions, and / or terminology used in this application shall prevail.

[0102] Finally, it should be understood that the embodiments described in this application are merely illustrative of the principles of the embodiments of this application. Other modifications may also fall within the scope of this application. Therefore, alternative configurations of the embodiments of this application are considered as examples and not limitations, and are regarded as consistent with the teachings of this application. Accordingly, the embodiments of this application are not limited to the embodiments explicitly described and illustrated in this application.

Claims

1. A method for acquiring radiographic images, characterized in that, The method includes: Receive control commands; Based on the control commands: Pre-image the target object using delivery rays to obtain first exposure parameters; and Based on the first exposure parameters, the target object is imaged again by delivering rays to obtain a radiographic image of the target object; The step of pre-imaging the target object with delivered rays to obtain first exposure parameters includes: Obtain the pre-imaging exposure parameters and the brightness of at least one frame of the pre-imaging image corresponding to the pre-imaging exposure parameters; The brightness is compared with the set first target brightness; Based on the comparison results and the Automatic Brightness Stabilization (ABS) curve, updated pre-imaging exposure parameters are obtained. The difference between the brightness of the pre-imaging image corresponding to the updated pre-imaging exposure parameters and the brightness of the first target image meets a preset condition. The horizontal axis of the ABS curve represents tube current, and the vertical axis represents tube voltage. Exposure is performed using exposure parameters indicated by points on the same ABS curve. Under the conditions of constant body thickness and the same laying time, along the curve trend, the image brightness corresponding to the exposure parameters at the point corresponding to the first horizontal axis is higher than the image brightness obtained by the exposure parameters at the point corresponding to the second horizontal axis, and the first horizontal axis is greater than the second horizontal axis. The process of obtaining updated pre-imaging exposure parameters based on the comparison results and the ABS curve includes: When the brightness of the pre-image is greater than the brightness of the first target image, the system moves along the curve trend and the direction of decreasing horizontal coordinate on the ABS curve to determine the next point and its corresponding reduced tube current and tube voltage; and When the brightness of the pre-image is less than the brightness of the first target image, the system moves along the curve trend and the direction of increasing horizontal coordinate on the ABS curve to determine the next point and its corresponding increased tube current and tube voltage; and The updated pre-imaging exposure parameters are used as the first exposure parameters.

2. The method according to claim 1, characterized in that, The step of imaging the target object by delivering rays again based on the first exposure parameters to obtain a radiographic image of the target object further includes: Generate a second exposure parameter based on the first exposure parameter; Based on the second exposure parameters, the target object is imaged again by delivering rays to obtain a radiographic image of the target object.

3. The method according to claim 2, characterized in that, The step of generating the second exposure parameter based on the first exposure parameter includes: Adjust at least one of the tube voltage, tube current, and wire laying time included in the first exposure parameters to obtain the second exposure parameters.

4. The method according to claim 2, characterized in that, The step of determining the second exposure parameter based on the first exposure parameter includes: Based on the first exposure parameters and the first target brightness, the equivalent thickness of the target object is determined; The second exposure parameter is determined based on the equivalent thickness of the target object and the brightness of the second target.

5. The method according to claim 4, characterized in that, Determining the equivalent thickness of the target object includes: Based on the first exposure parameter, the first target brightness, and the brightness-thickness-parameter model, the equivalent thickness of the target object is determined; wherein, the brightness-thickness-parameter model includes at least the relationship between image brightness, object thickness, and exposure parameters.

6. The method according to claim 5, characterized in that, The brightness-thickness-parameter model was determined based on the following method: Obtain the exposure parameters corresponding to the image brightness of multiple test targets with different thicknesses when the brightness reaches multiple different levels; Determine multiple fitting functions for the thickness of multiple test targets and their corresponding exposure parameters under different brightness levels, and use these fitting functions as the brightness-thickness-parameter model; or Based on the thickness, exposure parameters, and corresponding image brightness of multiple test targets, an initial model is trained to obtain a trained brightness-thickness-parameter model; the initial model is a statistical model or a machine learning model.

7. The method according to claim 5, characterized in that, The exposure parameters in the brightness-thickness-parameter model include tube voltage and tube current; the relationship between tube voltage and tube current follows the ABS curve.

8. The method according to claim 1, characterized in that, The method is applied to a C-arm X-ray imaging system.

9. The method according to claim 8, characterized in that, The C-arm X-ray imaging system includes a mobile C-arm or a digital subtraction angiography (DSA) device.

10. The method according to claim 9, characterized in that, The control command comes from the exposure handbrake.

11. A system for acquiring radiographic images, characterized in that, The system includes an instruction receiving module, a parameter determination module, and an image acquisition module. The instruction receiving module is used to receive control instructions; The parameter determination module is used to pre-image the target object delivery ray based on the control command and obtain the first exposure parameters. Obtaining the first exposure parameter includes: Obtain the pre-imaging exposure parameters and the brightness of at least one frame of the pre-imaging image corresponding to the pre-imaging exposure parameters; The brightness is compared with the set first target brightness; Based on the comparison results and the Automatic Brightness Stabilization (ABS) curve, updated pre-imaging exposure parameters are obtained. The difference between the brightness of the pre-imaging image corresponding to the updated pre-imaging exposure parameters and the brightness of the first target image meets a preset condition. The horizontal axis of the ABS curve represents tube current, and the vertical axis represents tube voltage. Exposure is performed using exposure parameters indicated by points on the same ABS curve. Under the conditions of constant body thickness and the same laying time, along the curve trend, the image brightness corresponding to the exposure parameters at the point corresponding to the first horizontal axis is higher than the image brightness obtained by the exposure parameters at the point corresponding to the second horizontal axis, and the first horizontal axis is greater than the second horizontal axis. The process of obtaining updated pre-imaging exposure parameters based on the comparison results and the ABS curve includes: When the brightness of the pre-image is greater than the brightness of the first target image, the system moves along the curve trend and the direction of decreasing horizontal coordinate on the ABS curve to determine the next point and its corresponding reduced tube current and tube voltage; and When the brightness of the pre-image is less than the brightness of the first target, the ABS curve is moved along the curve trend and the direction of increasing horizontal coordinate to determine the next point and its corresponding increased tube current and tube voltage. as well as The updated pre-imaging exposure parameters are used as the first exposure parameters; The image acquisition module is used to image the target object again by delivering rays according to the first exposure parameters under the control command, thereby acquiring a radiation image of the target object.

12. The system according to claim 11, characterized in that, To image the target object by delivering rays again based on the first exposure parameters, and to obtain a radiographic image of the target object, The parameter determination module is further configured to generate a second exposure parameter based on the first exposure parameter: The image acquisition module is further configured to image the target object by delivering rays again based on the second exposure parameters, thereby acquiring a radiographic image of the target object.

13. The system according to claim 12, characterized in that, To generate a second exposure parameter based on the first exposure parameter, the parameter determination module is further configured to: Adjust at least one of the tube voltage, tube current, and wire laying time included in the first exposure parameters to obtain the second exposure parameters.

14. The system according to claim 12, characterized in that, To determine the second parameter, the parameter determination module is further configured as follows: Based on the first exposure parameters and the first target brightness, the equivalent thickness of the target object is determined; The second exposure parameter is determined based on the equivalent thickness of the target object and the brightness of the second target.

15. The system according to claim 14, characterized in that, To determine the equivalent thickness of the target object, the parameter determination module is further configured to: Based on the first exposure parameter, the first target brightness, and the brightness-thickness-parameter model, the equivalent thickness of the target object is determined; wherein, the brightness-thickness-parameter model includes at least the relationship between image brightness, object thickness, and exposure parameters.

16. The system according to claim 15, characterized in that, The system further includes a model acquisition module, which is configured to: Acquire the exposure parameters corresponding to the image brightness of multiple test targets with different thicknesses when the brightness reaches multiple different levels; Determine multiple fitting functions for the thickness of multiple test targets and their corresponding exposure parameters under different brightness levels, and use these fitting functions as the brightness-thickness-parameter model; or Based on the thickness, exposure parameters, and corresponding image brightness of multiple test targets, an initial model is trained to obtain a trained brightness-thickness-parameter model; the initial model is a statistical model or a machine learning model.

17. The system according to claim 15, characterized in that, The exposure parameters in the brightness-thickness-parameter model include tube voltage and tube current; the relationship between tube voltage and tube current follows the ABS curve.

18. The system according to claim 11, characterized in that, The system is used in C-arm X-ray imaging systems.

19. The system according to claim 18, characterized in that, The C-arm X-ray imaging system includes a mobile C-arm or a digital subtraction angiography (DSA) device.

20. The system according to claim 18, characterized in that, The control command comes from the exposure handbrake.

21. An apparatus for acquiring radiographic images, characterized in that, The device includes a processor and a memory; the memory is used to store instructions, characterized in that, when the instructions are executed by the processor, they cause the device to perform the method as described in any one of claims 1 to 10.

22. A computer-readable storage medium, characterized in that, The storage medium stores computer instructions. When the computer reads the computer instructions from the storage medium, the computer executes the method described in any one of claims 1 to 10.

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