A method, device, electronic device and storage medium for determining timing parameter value

Abstract

The embodiment of the present application provides a method, device, electronic device and storage medium for determining a timing parameter value, which relates to the field of timing control technology, wherein a method for determining a timing parameter value includes: generating an initial plurality of timing parameter groups to obtain a parameter group to be tested, configuring the timing parameter group to a flat panel detector, and controlling the flat panel detector to perform image acquisition, generating quality evaluation values ​​under each specified image quality index, obtaining the judgment value of the timing parameter group for each optimization target, iteratively generating a plurality of optimized timing parameter groups as new parameter groups to be tested according to a predetermined multi-objective optimization iteration method on the basis of the parameter group to be tested, and returning to the step of configuring the timing parameter group to the flat panel detector, and selecting a timing parameter group in response to satisfying a predetermined optimization end condition to obtain the timing parameter value of the flat panel detector. It can be seen that this scheme can improve the efficiency of determining the timing parameter value.

Description

Technical Field

[0001] The present application relates to the field of timing control technology, and in particular to a method, device, electronic device and storage medium for determining a timing parameter value. Background Art

[0002] A flat panel detector can also be called an X-ray flat panel detector. The flat panel detector can convert the collected X-ray image into an electrical signal and transmit it to a communicating host computer, so that the image data converted from the electrical signal can be displayed on a display unit of the host computer. The timing parameter values ​​of the timing signals of various timing types of the flat panel detector affect the detection effect of the flat panel detector. Therefore, there is a need to determine the timing parameter values ​​of various timing types of the flat panel detector, that is, to determine the timing parameter values ​​that can enable the flat panel detector to achieve a better detection effect.

[0003] In the related art, a tester can manually adjust the timing parameter value of the flat-panel detector until a timing parameter value is found that can make the image quality of the image data displayed on the display unit meet the standard; however, in the process of manually adjusting the timing parameter value of the flat-panel detector, it completely depends on the personal experience of the tester, and continuous adjustment is required, and the efficiency of determining the timing parameter value is low.

[0004] Currently, there is an urgent need for a method for determining a timing parameter value to improve the efficiency of determining the timing parameter value. Summary of the invention

[0005] The purpose of the embodiments of the present application is to provide a method, device, electronic device and storage medium for determining a timing parameter value, so as to improve the efficiency of determining a timing parameter value. The specific technical solution is as follows:

[0006] In a first aspect, an embodiment of the present application provides a method for determining a timing parameter value, which is applied to a host computer of a flat panel detector, and the method includes:

[0007] Generate an initial plurality of timing parameter groups to obtain parameter groups to be tested; wherein each timing parameter group includes timing parameter values ​​of various timing types for which parameter determination is to be performed on the flat panel detector, and the timing parameter values ​​of each timing type satisfy a predetermined value constraint condition;

[0008] For each timing parameter group in the parameter group to be tested, the timing parameter group is configured to a flat panel detector, and the flat panel detector is controlled to perform image acquisition, a target image acquired by the flat panel detector is obtained, and based on the target image, a quality evaluation value under each specified image quality index is generated, and a judgment value of the timing parameter group for each optimization target is obtained, where each optimization target is an optimization for a specified image quality index;

[0009] Based on the obtained evaluation values ​​of each timing parameter group for each optimization target, on the basis of the parameter group to be tested, according to a predetermined multi-objective optimization iteration method, iteratively generate multiple optimized timing parameter groups as new parameter groups to be tested, and return the step of configuring each timing parameter group in the parameter group to be tested to the flat panel detector;

[0010] In response to the predetermined optimization end condition being met, a timing parameter group is selected from the current parameter group to be tested to obtain timing parameter values ​​of each timing type of the flat panel detector.

[0011] In a second aspect, an embodiment of the present application provides a timing parameter value determination device, which is applied to a host computer of a flat panel detector, and the device includes:

[0012] A generating module, used for generating an initial plurality of timing parameter groups to obtain a parameter group to be tested; wherein each timing parameter group includes timing parameter values ​​of each timing type to be parameter-determined for the flat panel detector, and the timing parameter value of each timing type satisfies a predetermined value constraint condition;

[0013] A configuration module, for configuring each timing parameter group in the parameter group to be tested to the flat panel detector, and controlling the flat panel detector to perform image acquisition, obtaining a target image acquired by the flat panel detector, and generating a quality evaluation value under each specified image quality index based on the target image, and obtaining a judgment value of the timing parameter group for each optimization target, wherein each optimization target is an optimization for a specified image quality index;

[0014] An iterative module, for iteratively generating a plurality of optimized timing parameter groups as new parameter groups to be tested, based on the evaluation values ​​of each timing parameter group for each optimization target obtained, and in accordance with a predetermined multi-objective optimization iteration method on the basis of the parameter group to be tested, and returning the step of configuring each timing parameter group in the parameter group to be tested to the flat panel detector;

[0015] The selection module is used to select a timing parameter group from the current parameter group to be tested in response to satisfying a predetermined optimization end condition, and obtain the timing parameter values ​​of each timing type of the flat panel detector.

[0016] In a third aspect, an embodiment of the present application provides an electronic device, including:

[0017] Memory, used to store computer programs;

[0018] The processor is used to implement any of the above-mentioned timing parameter value determination methods when executing the program stored in the memory.

[0019] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the computer program implements any of the above-mentioned methods for determining a timing parameter value.

[0020] Beneficial effects of the embodiments of the present application:

[0021] The timing parameter value determination method provided in the present application can generate an initial plurality of timing parameter groups to obtain a parameter group to be tested, configure each timing parameter group in the parameter group to be tested into a flat-panel detector, control the flat-panel detector to perform image acquisition, obtain a target image acquired by the flat-panel detector, generate a quality assessment value under each specified image quality index based on the target image, obtain a judgment value for each timing parameter group for each optimization target, iteratively generate a plurality of optimized timing parameter groups as new parameter groups to be tested based on the judgment value in accordance with a predetermined multi-objective optimization iteration method, and return to the step of configuring each timing parameter group in the parameter group to be tested into the flat-panel detector, and in response to satisfying a predetermined optimization end condition, select a timing parameter group from the current parameter group to be tested to obtain the timing parameter values ​​of each timing type of the flat-panel detector. It can be seen that the solution provided by the present application takes each specified image quality indicator as the optimization target, and continuously iterates on the basis of the parameter group to be tested in accordance with the predetermined multi-objective optimization iteration method, so as to obtain a new parameter group to be tested, and finally, in response to the optimization end condition, the timing parameter values ​​of each timing type of the flat-panel detector can be selected from the new parameter group to be tested; thus, compared with the prior art, the solution provided by the embodiment of the present application does not require the tester to manually adjust the timing parameter values ​​of the flat-panel detector, so the efficiency of determining the timing parameter values ​​can be greatly improved.

[0022] Furthermore, the timing parameter value determined in the embodiment of the present application is determined through continuous iterative optimization, and can also be considered to be the timing parameter value that best meets the flat-panel detector under the current conditions of use. The image quality of the image data generated by the flat-panel detector after X-ray exposure based on the timing parameter value is better. In addition, in the process of determining the timing parameter value, the timing parameter value of each timing type is required to meet the predetermined value constraint conditions, so a part of the timing parameter values ​​that do not meet the value constraint conditions can be excluded, thereby reducing computing power and improving the efficiency of determining the timing parameter value.

[0023] Of course, implementing any product or method of the present application does not necessarily require achieving all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application, and for ordinary technicians in this field, other embodiments can also be obtained based on these drawings.

[0025] Figure 1 A schematic diagram of the working principle of a flat panel detector provided in an embodiment of the present application;

[0026] Figure 2 A flowchart of a method for determining a timing parameter value provided in an embodiment of the present application;

[0027] Figure 3 A schematic diagram of a multi-objective optimization process provided in an embodiment of the present application;

[0028] FIG4 (a) is a schematic diagram of various types of timing signals provided in an embodiment of the present application;

[0029] FIG4 (b) is a schematic diagram showing the principle of a method for determining a timing parameter value provided in an embodiment of the present application;

[0030] Figure 5 A schematic diagram of the structure of a timing parameter value determination device provided in an embodiment of the present application;

[0031] Figure 6 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field based on the present application belong to the scope of protection of the present application.

[0033] First, some professional terms in the embodiments of the present application are briefly introduced:

[0034] Multi-objective optimization problem: It is necessary to consider multiple objective functions simultaneously during the optimization process. Usually, multiple objective functions are contradictory, that is, achieving a better result (goal) on one objective function may lead to worse results (goals) of other objective functions. Therefore, the multi-objective optimization problem is to find a balance between these contradictory goals; and, usually, the ultimate optimization goal is to find a set of non-dominated solutions (such as Pareto optimal solutions). In order to solve multi-objective optimization problems, multi-objective optimization algorithms can usually be used.

[0035] Multi-objective optimization algorithm: A type of algorithm specifically used to solve multi-objective optimization problems, involving the simultaneous optimization of multiple objective functions, which are often conflicting. The purpose of optimization is to find a set of Pareto optimal solutions. Common multi-objective optimization algorithms include the following:

[0036] (1) NSGA-II (Non-dominated Sorting Genetic Algorithm II): The algorithm selects individuals in the next generation population through non-dominated sorting and crowding distance to maintain the diversity and non-dominance of solutions. This algorithm can effectively find non-dominated solution sets on the Pareto frontier and is suitable for solving complex multi-objective optimization problems.

[0037] (2) MOEA / D (Multi-Objective Evolutionary Algorithm based on Decomposition): MOEA / D solves multi-objective optimization problems by decomposing them into multiple single-objective optimization sub-problems. It uses decomposition techniques to transform multi-objective optimization problems into multiple single-objective optimization problems, and then optimizes these sub-problems separately. The algorithm can efficiently handle large-scale multi-objective optimization problems and maintain the diversity of the solution set.

[0038] (3) SPEA2 (Strength Pareto Evolutionary Algorithm 2): SPEA2 maintains the diversity of the non-dominated solution set through selection and survival strategies. It uses an external archive to store non-dominated solutions and evaluates individuals through a fitness function. The algorithm is able to find high-quality Pareto frontier solutions and is suitable for solving medium to large-scale multi-objective optimization problems.

[0039] Among them, Pareto front: a curve composed of Pareto optimal solutions. Pareto optimal solution refers to a solution that cannot improve the value of one objective function without damaging the values ​​of other objective functions in the process of multi-objective optimization. In other words, Pareto optimal solution is a set of solutions that cannot be improved. For example, customer service a hopes to work as short a day as possible, but the shorter the working time, the more complaints he will receive. Therefore, customer service a wants to find a balance point. Pareto front can be a curve, which can be considered as the relationship curve between the time invested and the number of complaints received.

[0040] Dominace Relation: If a solution is not inferior to another solution in all objective functions, and is better than another solution in at least one objective function, then it can be said that this solution dominates the other solution. For example: the objective functions are f1(x) and f2(x), and there are two solutions A and B (i.e. A and B are the values ​​of x respectively), and the smaller the objective value (i.e. function value) of the objective function, the better it is. The objective value of solution A is f1(A)=0.9 and f2(A)=1.1, and the objective value of solution B is f1(B)=0.5 and f2(B)=0.8. Then, comparing the objective value of f1(x), since f1(A)>f1(B), solution A is inferior to solution B. Comparing the value of f2(x), since f2(A)>f2(B), solution A is inferior to solution B. Therefore, solution A is inferior to solution B in both objective functions, and it can be considered that solution B dominates solution A.

[0041] Non-dominated Solution: A solution is not dominated by any other solution on all objective functions. In multi-objective optimization, the set of all non-dominated solutions is called the Pareto front.

[0042] Crowding distance: It measures the degree of crowding of an individual (which can be understood as a solution mentioned above) in the target space, that is, how many other individuals are around the individual. The larger the crowding distance, the fewer individuals are around the individual, that is, the area where the individual is located is relatively uncrowded. When selecting the next generation of population, the larger the crowding distance, the higher the probability that the individual will be selected.

[0043] Flat panel detector: It can also be called X-ray flat panel detector. It can be used as one of the core components of digital X-ray imaging system. It can convert the collected X-ray images into electrical signals and transmit them to the communicating host computer.

[0044] In order to better understand the present solution, before introducing the method for determining the timing parameter value provided in the embodiment of the present application, the working principle of the flat panel detector is introduced. Figure 1 As shown:

[0045] The flat panel detector may include an X-ray source, a scintillator layer, a sensor layer, an acquisition circuit, a driving circuit, a main control circuit and a host computer, wherein the X-ray source is used to emit X-rays (X-rays), the scintillator layer is used to convert X-rays into visible light, the sensor layer is mainly composed of an array of thin film transistors (TFT) and photodiodes (PD), and is used to convert visible light into electrical signals. The driving circuit is used in conjunction with the acquisition circuit. When the driving circuit outputs a high-level signal to the thin film transistor, the energy storage capacitor in the sensor layer will release the electrical signal to the acquisition circuit, so that the acquisition circuit performs image acquisition and outputs it to the main control circuit. The main control circuit uploads the image data output by the acquisition circuit to the host computer for display. The main control circuit may be a ZYNQ (Zynqall-Programmable SoC, programmable system on chip) main control circuit / FPGA (Field Programmable Gate Array, programmable array logic) main control circuit, and the host computer may be composed of a software development kit (SDK) and a user interface (User The host computer can be set on a personal computer PC.

[0046] The following is an introduction to the method for determining the timing parameter value provided in an embodiment of the present application.

[0047] Among them, the timing parameter value determination method provided in the embodiment of the present application can be applied to the host computer of the flat-panel detector. Specifically, the host computer can be set on the PC side, and the embodiment of the present application does not make specific limitations on this. In one implementation, the timing parameter value determination method provided in the embodiment of the present application can be applied to the functional software built into the host computer, and the functional software integrates the logic of multi-objective optimization and the logic of controlling and analyzing images to obtain image indicators, etc. Specifically, the functional software can be divided into an algorithm module, an image indicator module, etc., and the timing parameter value is determined based on the interaction of each module. The embodiment of the present application does not make specific limitations on this.

[0048] Furthermore, the flat panel detector can acquire image data of one row in one row scanning cycle. The image data scanned in one row scanning cycle can be jointly determined by multiple timing signals. The timing signal can include a rising edge and a falling edge. For example, a flat panel detector with an effective pixel array of 1536×2048, that is, the flat panel detector has a total of 1536 rows and 2048 columns, and the row scanning time is 12.8us. Then, the total time required to scan and acquire this image is 12.8us×1536, that is, the acquisition of each row of data requires a row scanning time. After the timing signals of various types are determined, the current timing combination is determined, thereby determining the image quality presented by the flat panel detector. The content of the timing signal will be specifically introduced in subsequent embodiments and will not be elaborated on here.

[0049] The following is a brief introduction to the application scenarios of the timing parameter value determination method provided in the embodiment of the present application:

[0050] The embodiments of the present application are applicable to any scenario using a flat-panel detector, such as medical imaging scenarios, calibration object imaging scenarios, etc., and the embodiments of the present application do not specifically limit this.

[0051] Among them, a method for determining a timing parameter value is applied to a host computer of a flat panel detector, and the method comprises:

[0052] Generate an initial plurality of timing parameter groups to obtain parameter groups to be tested; wherein each timing parameter group includes timing parameter values ​​of various timing types for which parameter determination is to be performed on the flat panel detector, and the timing parameter values ​​of each timing type satisfy a predetermined value constraint condition;

[0053] For each timing parameter group in the parameter group to be tested, the timing parameter group is configured to a flat panel detector, and the flat panel detector is controlled to perform image acquisition, a target image acquired by the flat panel detector is obtained, and based on the target image, a quality evaluation value under each specified image quality index is generated, and a judgment value of the timing parameter group for each optimization target is obtained, where each optimization target is an optimization for a specified image quality index;

[0054] Based on the obtained evaluation values ​​of each timing parameter group for each optimization target, on the basis of the parameter group to be tested, according to a predetermined multi-objective optimization iteration method, iteratively generate multiple optimized timing parameter groups as new parameter groups to be tested, and return the step of configuring each timing parameter group in the parameter group to be tested to the flat panel detector;

[0055] In response to the predetermined optimization end condition being met, a timing parameter group is selected from the current parameter group to be tested to obtain timing parameter values ​​of each timing type of the flat panel detector.

[0056] It can be seen that the scheme provided by the present application takes each designated image quality index as the optimization target, and continuously iterates on the basis of the parameter group to be tested according to the predetermined multi-objective optimization iteration method, so that a new parameter group to be tested can be obtained, and finally, in response to the optimization end condition, the timing parameter values ​​of each timing type of the flat panel detector can be selected from the new parameter group to be tested; thus, compared with the prior art, the scheme provided by the embodiment of the present application does not require the tester to manually adjust the timing parameter value of the flat panel detector, so the efficiency of determining the timing parameter value can be greatly improved. In addition, the timing parameter value determined by the embodiment of the present application is determined through continuous iterative optimization, and can also be considered as the timing parameter value of the flat panel detector that best meets the current conditions of use, and the image quality of the image data generated by the flat panel detector after X-ray exposure based on the timing parameter value is better; in addition, in the process of determining the timing parameter value, the timing parameter value of each timing type is required to meet the predetermined value constraint condition, so a part of the timing parameter value that does not meet the value constraint condition can be excluded, thereby reducing the computing power and improving the efficiency of determining the timing parameter value.

[0057] A method for determining a timing parameter value provided by an embodiment of the present application is described below in conjunction with the accompanying drawings.

[0058] like Figure 2 As shown, a method for determining a timing parameter value provided in an embodiment of the present application is applied to a host computer of a flat panel detector, and the method includes:

[0059] S201, generating a plurality of initial timing parameter groups to obtain a parameter group to be tested;

[0060] Wherein, each timing parameter group includes timing parameter values ​​of each timing type for which parameter determination is to be performed on the flat panel detector, and the timing parameter value of each timing type satisfies a predetermined value constraint condition;

[0061] It is understandable that when the host computer detects the start of the process of determining the timing parameter value, it can generate initial multiple timing parameter groups to obtain the parameter group to be tested. This process can also be considered as generating an initial population. Each individual (i.e., each solution) in the initial population can be considered as a timing parameter group. Each timing parameter group includes timing parameter values ​​of various timing types for which parameters of the flat panel detector are to be determined. Exemplarily, in one implementation, each timing type can include at least four types: SHR (reset sample), SHS (signal sample), LPF1 (LowPass Filter1), and LPF2 (Low Pass Filter2). The embodiment of the present application does not specifically limit this; in other implementations, each timing type can also include only some of the above four types, which is also reasonable. It is understandable that different types of flat panel detectors may require different timing types for parameter determination. The same flat panel detector may require different timing types for parameter determination in different scenarios. In specific applications, the timing types to be determined can be set according to actual needs. It should be emphasized that before generating the initial multiple timing parameter groups, the value constraint condition can also be obtained in advance, wherein the value constraint condition can be used to ensure that the value of the timing parameter value of the flat-panel detector meets the value requirement, that is, the value constraint condition is a condition for constraining the timing parameter value so that it meets the value requirement. Of course, it is also possible not to obtain the value constraint condition. The value constraint condition has been embedded in the logic of the multi-objective optimization of the host computer, and the embodiment of the present application does not make specific limitations on this; and, the value constraint condition may also be affected by the frame rate and exposure time of the flat-panel detector, so before generating the initial multiple timing parameter groups, the frame rate and exposure time of the flat-panel detector can also be obtained first. The frame rate and exposure time can be pre-set by the tester, and the embodiment of the present application does not make specific limitations on this; then, the value constraint condition can be: the time of the rising edge of the timing signal of each timing type is earlier than the time of the falling edge. Of course, the value constraint condition can also include other conditions, and the embodiment of the present application does not make specific limitations on this. In addition, it should be noted that the value constraint condition can be a value constraint for the timing parameters of each timing type, or can be a value constraint for each timing type and value constraints for different timing types at the same time, which is also reasonable.

[0062] Exemplarily, in one implementation, the timing parameter value of each timing type is a two-dimensional array, data of one dimension in the two-dimensional array represents the time of the rising edge of the timing signal of the timing type, and data of another dimension represents the time of the falling edge of the timing signal of the timing type;

[0063] The value constraint condition includes that the time of the rising edge of the timing signal of each timing type is earlier than the time of the falling edge, and a target value range, which is a range of time values ​​for the rising edge and the falling edge.

[0064] It can be understood that any timing signal can include a rising edge and a falling edge, and the timing parameter value of each timing type can be represented in the form of a two-dimensional array, which can be obtained by encoding the timing parameter group using integers, and the two-dimensional array can also be considered to contain two elements; wherein, one dimension of data represents the time of the rising edge of the timing signal of the timing type, and the other dimension of data represents the time of the falling edge of the timing signal of the timing type. The rising edge can be considered as a turn-on signal for the device controlled by the timing signal, and the falling edge can be considered as a turn-off signal for the device controlled by the timing signal. Specifically, the device controlled by the timing signal can be a low-pass filter, an amorphous silicon thin-film transistor, etc., and the embodiments of the present application do not make specific limitations on this. In addition, in the process of encoding the timing signal of each timing type into a two-dimensional array, the value constraints can be taken into account. It should be emphasized that the embodiments of the present application are scalable, and the edges of the timing signals can be represented by arrays. Therefore, it can also be expanded to more complex timing signals, and the size of the array can be consistent with the number of edges of the timing signal. The embodiments of the present application do not make specific limitations on this; for example, the timing parameter value of a timing signal with four edges can be a two-dimensional array with four elements.

[0065] Correspondingly, the value constraint conditions may include that the time of the rising edge of the timing signal of each timing type is earlier than the time of the falling edge, and the waveform of the timing signal of each timing type rises first and then falls, that is, the timing of turning on any element of the flat-panel detector must be before the timing of turning off; and the value constraint conditions may also include a target value range, and the target value range may be a range for time values ​​of the rising edge and the falling edge; wherein, each time in the target value range can be used for time assignment for the rising edge and for time assignment for the falling edge. The present application does not limit the method for determining the target value range, and any implementation method that can determine the target value range can be applied to the embodiments of the present application.

[0066] It can be seen that the embodiments of the present application can take into account the value constraints when encoding the timing signal, thereby reducing the number of invalid solutions and improving the efficiency of determining the timing parameter values; and the timing parameter values ​​introduced in the embodiments of the present application are scalable and can be applied to more complex timing signals, thereby improving the flexibility and scalability of determining the timing parameter values.

[0067] Exemplarily, in one implementation, the target value range is determined by methods A1-A2:

[0068] Mode A1, determining the period length of the row scanning period of the timing signals of the various timing types based on the frame rate and exposure time of the flat panel detector;

[0069] Mode A2, based on the number of specified unit durations contained in the determined cycle duration, is used as the target value range.

[0070] It can be understood that for step A1, the tester can pre-configure the frame rate and exposure time of the flat panel detector, or pre-configure the mapping relationship between the frame rate and exposure time of the flat panel detector and the period duration of the line scan period of the timing signals of various timing types. Therefore, after obtaining the frame rate and exposure time of the flat panel detector configured by the tester, the period duration of the line scan period of the timing signals of various timing types can be directly determined based on the above mapping relationship. Exemplarily, the frame rate is 30fps, the exposure time is 0.01s, and based on the mapping relationship, the period duration of the line scan period of the timing signal 1 can be determined to be 12.8us; when the frame rate is adjusted to 4fps and the exposure time remains unchanged, based on the mapping relationship, the period duration of the line scan period of the timing signal 1 can be determined to be 51.2us. It can be seen that the frame rate affects the period duration of the line scan period.

[0071] It can be understood that for step A2, the number of specified unit durations contained in the determined cycle duration is multiple. Based on the number of specified unit durations contained in the determined cycle duration, the range of time values ​​for the rising edge and the falling edge can be determined. Usually, the range of time values ​​for the rising edge cannot include the maximum value of the target value range, and the range of time values ​​for the falling edge cannot include the minimum value of the target value range, thereby ensuring that the timing signal is a complete signal with a rising edge and a falling edge. For example, the number of specified unit durations contained in the cycle duration selected by the timing signal 1 is 256, so it can be determined that the target value range can be [1, 256], or, without considering the last unit duration, the target value range can be [1, 255].

[0072] In another implementation, the tester may also pre-configure the frame rate and exposure time of the flat-panel detector and the mapping relationship with the target value range. Based on the frame rate and exposure time of the flat-panel detector configured by the tester, the target value range can be directly determined. Of course, this implementation is only introduced as an example and is not specifically limited in the embodiments of the present application.

[0073] It should be emphasized that the above-mentioned rising edge time and falling edge time are two types of triggering times that have a sequential relationship within the row scanning cycle.

[0074] It can be seen that the embodiments of the present application can select the period duration of the row scanning period of the timing signal of various timing types based on the frame rate and exposure time of the flat-panel detector, and determine the target value range based on the number of specified unit durations contained in the determined period duration. The tester can adjust the target value range by configuring the frame rate and exposure time of the flat-panel detector, thereby improving the user experience, and can also make the determined target value range more in line with the needs of the tester, thereby improving the tester's experience.

[0075] S202, for each timing parameter group in the parameter group to be tested, configure the timing parameter group to a flat panel detector, control the flat panel detector to perform image acquisition, obtain a target image acquired by the flat panel detector, generate a quality evaluation value under each specified image quality index based on the target image, and obtain a judgment value of the timing parameter group for each optimization target, where each optimization target is an optimization for a specified image quality index;

[0076] It can be understood that the host computer can configure each timing parameter group in the parameter group to be tested to the flat-panel detector. Specifically, the timing parameter group can be configured to the flat-panel detector by configuring the register corresponding to each type of timing. Exemplarily, the register has 16 bits, wherein the first eight bits can store the timing parameter value of the rising edge, and the last eight bits can store the timing parameter value of the falling edge, wherein different values ​​of the register corresponding to each type of timing are used to represent different timing parameter values. Of course, the register can also be other bit numbers, which is not specifically limited in the embodiments of the present application; and any method of configuring the timing parameter group to the flat-panel detector is applicable to the embodiments of the present application, which is not specifically limited in the embodiments of the present application.

[0077] It can be understood that after configuring any timing parameter group to the flat-panel detector, the host computer can control the flat-panel detector to perform image acquisition, thereby obtaining the target image acquired by the flat-panel detector, wherein the target image can include bright field image data and dark field image data, the bright field image data is the image data acquired by the flat-panel detector when the X-ray source is turned on, and the dark field image data is the image data acquired by the flat-panel detector when the X-ray source is turned off; then, based on the target image, the quality evaluation value under each specified image quality index can be generated, thereby obtaining the judgment value of the timing parameter group for each optimization target. It should be emphasized that in one implementation, after generating the quality evaluation value under each specified image quality index, the quality evaluation value under each specified image quality index can be evaluated to obtain the judgment value of the timing parameter group for each optimization target. Of course, the quality evaluation value generated under each specified image quality index can also be directly used as the judgment value of the timing parameter group for each optimization target, and the embodiment of the present application does not make specific limitations on this.

[0078] In one implementation, each designated image quality index includes at least a quality index characterizing grayscale information of dark field image data, a quality index characterizing noise information of dark field image data, and a quality index characterizing sensitivity of the flat panel detector;

[0079] Among them, the quality index characterizing the grayscale information of the dark field image data can also be called the dark field background, and the quality index characterizing the noise information of the dark field image data can also be called the dark field pixel noise, which is not specifically limited in the embodiments of the present application.

[0080] In addition, each designated image quality indicator may also include dark field horizontal stripes and dark field vertical stripes. Of course, in some other implementations, any at least two of them may be selected as the above-mentioned designated image quality indicators. The embodiments of the present application do not make specific limitations on this.

[0081] The dark field horizontal stripes represent the horizontal noise mean in the dark field image data, and the dark field vertical stripes represent the vertical noise mean in the dark field image data. In addition, the multi-objectives mentioned in the multi-objective optimization algorithm can be considered as quality evaluation values ​​under each specified image quality index.

[0082] It can be understood that the quality assessment value under each specified image quality index can be calculated based on the target image. For example, the calculation process for the dark field background can include: determining the gray value of each pixel in the dark field image data, and calculating the ratio of the sum of the gray values ​​of each pixel in the dark field image data to the number of pixels in the dark field image data, thereby obtaining the dark field background; for dark field pixel noise, the random fluctuation of the pixel output of the flat panel detector in the absence of X-ray irradiation can be determined, and the standard deviation of the gray value of each pixel after the dark field image bias correction is calculated to obtain the dark field image. Pixel noise can be calculated based on dark field image data; for dark field horizontal stripes, the inconsistency between rows in the dark field image data without X-ray irradiation can be determined, reflecting the inconsistency and noise level of the row readout circuit, and the standard deviation of the mean of each row after the dark field image bias correction is calculated to obtain the dark field horizontal stripes; for dark field vertical stripes, the inconsistency between columns in the dark field image data without X-ray irradiation can be determined, reflecting the inconsistency and noise level of the column readout circuit, and the standard deviation of the mean of each column after the dark field image bias correction is calculated to obtain the dark field vertical stripes.

[0083] It can be understood that under the same radiation source voltage (kV), as the X-ray exposure dose (dose) increases, the detector image grayscale (LSB) increases linearly. The sensitivity is defined as the response value (LSB) of the image grayscale under unit dose (uGy). The radiation source introduced here can be an X-ray source.

[0084] The following is an example of the sensitivity calculation process:

[0085] (1) Usually at 70 kV, change mAs (milliampere-seconds) and take 5 sets of bright-field image data at different doses;

[0086] It is understandable that the radiation source dose can be calibrated to obtain the radiation source dose corresponding to different radiation source currents under the same radiation source voltage under the test environment, as shown in Table 1:

[0087]

[0088] Table 1

[0089] It can be understood that in a specific test environment, when the ray source voltage is 70kv, the ray source current is 20uA, and the dose rate is 17.25uGy / s, if the detector acquisition frame rate is 10fps / s, then the dose per frame is 1.725 uGy, the ray source current is 40uA, the dose rate is 33.58uGy / s, the ray source current is 60uA, the dose rate is 49.88uGy / s, the ray source current is 80uA, the dose rate is 66.10uGy / s, and the ray source current is 100uA, and the dose rate is 82.28uGy / s. And, the process can be calibrated once, and there is no need to repeat the calibration.

[0090] (2) To obtain the grayscale value of the detector under different doses, please refer to Table 2:

[0091]

[0092] Table 2

[0093] It can be understood that when the X-ray source voltage is 70kv, the X-ray source current is 20uA, the dose rate is 17.25uGy / s, and the grayscale value is 932.80; the X-ray source current is 40uA, the dose rate is 33.58uGy / s, and the grayscale value is 1802.32; the X-ray source current is 60uA, the dose rate is 49.88uGy / s, and the grayscale value is 2644.76; the X-ray source current is 80uA, the dose rate is 66.10uGy / s, and the grayscale value is 3469.98; the X-ray source current is 100uA, the dose rate is 82.28uGy / s, and the grayscale value is 4398.58.

[0094] (3) Calculate sensitivity;

[0095] According to the calibration results, a scatter plot of grayscale and dose can be obtained, with the horizontal axis being dose (dose) and the vertical axis being image grayscale (LSB). The scatter plot is fitted into a linear equation, and the slope of the linear equation is calculated. The slope is the sensitivity, and thus the sensitivity can be determined to be 533.00 LSB / uGy. In addition, since the X-ray dose is proportional to the current when the source voltage remains unchanged, if no calibration is performed, the sensitivity can also be expressed as 43.32 LSB / uA-70kV.

[0096] Of course, the above-described method of determining the quality evaluation value under each specified image quality index is only an exemplary introduction. Any method of calculating the quality evaluation value under each specified image quality index in the related art can be applied to the embodiment of the present application, and the embodiment of the present application does not make specific limitations on this. In addition, the above-described bias correction belongs to a correction algorithm that can eliminate the inconsistency of the dark field background, and the embodiment of the present application does not make specific limitations on this.

[0097] It can be seen that the various specified image quality indicators set in the embodiments of the present application are indicators related to the noise of the target image, which can intuitively reflect the situation in which the target image is affected by noise, thereby facilitating the adjustment of the quality assessment value under each specified image quality indicator and providing a basis for determining the timing parameter value.

[0098] For a clear layout, the process of controlling the flat panel detector to collect images will be introduced in other embodiments and will not be described in detail here.

[0099] S203, based on the obtained evaluation values ​​of each timing parameter group for each optimization target, on the basis of the parameter group to be tested, in accordance with a predetermined multi-objective optimization iteration method, iteratively generate multiple optimized timing parameter groups as new parameter groups to be tested;

[0100] And, returning to the step of configuring each timing parameter group in the parameter group to be tested to the flat panel detector;

[0101] It can be understood that, based on the evaluation values ​​of each timing parameter group for each optimization target obtained, the parameter group to be tested can be iterated, and the specific method of iteration can be a predetermined multi-objective optimization iteration method. The multi-objective optimization iteration method used in the present application can be an improved NSGA-II. Of course, other multi-objective optimization algorithms can also be used. The embodiment of the present application does not specifically limit this. Then, multiple optimized timing parameter groups can be iteratively generated as new parameter groups to be tested, and return to step S202, thereby realizing cyclic iteration until the predetermined optimization end condition is met.

[0102] For the sake of clear layout, based on the evaluation values ​​of each timing parameter group for each optimization target, on the basis of the parameter group to be tested, according to the predetermined iterative method of multi-objective optimization, multiple optimized timing parameter groups are iteratively generated as new parameter groups to be tested. The specific method will be introduced in other embodiments and will not be elaborated here.

[0103] S204, in response to satisfying a predetermined optimization end condition, selecting a timing parameter group from the current parameter group to be tested, and obtaining timing parameter values ​​of each timing type of the flat panel detector.

[0104] It can be understood that the predetermined optimization end condition can be that the number of iterations reaches the maximum number of iterations. Of course, it can also be other conditions, for example: the difference between the optimal solution corresponding to the current parameter group to be tested and the optimal solution corresponding to the last parameter group to be tested is less than a predetermined threshold. At this time, it can also be considered that the predetermined optimization end condition is met; of course, the above exemplary introduction can be used as an optimization end condition, wherein the number of iterations reaching the maximum number of iterations can also be considered as the optimization condition of the multi-objective optimization itself, and the embodiment of the present application does not make specific limitations on this. And, in response to meeting the predetermined optimization end condition, a timing parameter group can be selected from the current parameter group to be tested as the timing parameter value of each timing type of the flat panel detector, and the selected timing parameter group can be considered as a Pareto optimal solution; and, selecting a timing parameter group from the current parameter group to be tested can be selecting a non-dominated solution in the parameter group to be tested, and of course, it can also be randomly selected, and the embodiment of the present application does not make specific limitations on this. Exemplarily, the parameter groups to be tested include timing parameter group 1, timing parameter group 2 and timing parameter group 3. At this time, timing parameter group 2 can be selected, and the timing parameter values ​​of timing parameter group 2 can be used as the timing parameter values ​​of each timing type of the flat panel detector.

[0105] In addition, the process of selecting a timing parameter group from the current parameter group to be tested does not necessarily have to be executed immediately in response to satisfying the predetermined optimization condition. There may also be a certain delay, which is not specifically limited in the embodiments of the present application.

[0106] It can be seen that the scheme provided by the present application takes each designated image quality index as the optimization target, and continuously iterates on the basis of the parameter group to be tested according to the predetermined multi-objective optimization iteration method, so that a new parameter group to be tested can be obtained, and finally, in response to the optimization end condition, the timing parameter values ​​of each timing type of the flat panel detector can be selected from the new parameter group to be tested; thus, compared with the prior art, the scheme provided by the embodiment of the present application does not require the tester to manually adjust the timing parameter value of the flat panel detector, so the efficiency of determining the timing parameter value can be greatly improved. In addition, the timing parameter value determined by the embodiment of the present application is determined through continuous iterative optimization, and can also be considered as the timing parameter value of the flat panel detector that best meets the current conditions of use, and the image quality of the image data generated by the flat panel detector after X-ray exposure based on the timing parameter value is better; in addition, in the process of determining the timing parameter value, the timing parameter value of each timing type is required to meet the predetermined value constraint condition, so a part of the timing parameter value that does not meet the value constraint condition can be excluded, thereby reducing the computing power and improving the efficiency of determining the timing parameter value.

[0107] Optionally, in another embodiment, the step of iteratively generating a plurality of optimized timing parameter groups based on the obtained evaluation values ​​for each optimization target of each timing parameter group on the basis of the parameter group to be tested in accordance with a predetermined iterative method of multi-objective optimization as a new parameter group to be tested includes steps B1-B3:

[0108] Step B1, based on the obtained evaluation values ​​of each timing parameter group for each optimization target, analyzing the reference information for multi-target optimization of each timing parameter group in the parameter group to be tested; wherein the reference information includes a non-dominated level and a crowding distance; wherein the non-dominated level of each timing parameter group represents: the degree of superiority or inferiority of the evaluation values ​​of the timing parameter group for each optimization target compared with the evaluation values ​​of other timing parameter groups, and the crowding distance of each timing parameter group represents: when each timing parameter group in the parameter group to be tested is represented as an individual, it is used to represent the crowding degree of the individual of the timing parameter group in the target space; wherein the target space is a space with each specified image quality index as different dimensions;

[0109] Step B2, selecting a timing parameter group from the parameter groups to be tested according to the obtained reference information of each timing parameter group;

[0110] Step B3, based on the selected timing parameter group, generating multiple optimized timing parameter groups as new parameter groups to be tested;

[0111] Correspondingly, the method of selecting a timing parameter group from the current parameter group to be tested to obtain the timing parameter values ​​of each timing type of the flat panel detector includes step C1:

[0112] Step C1, select a timing parameter group from the timing parameter groups belonging to the non-dominated solutions of the current parameter group to be tested, and obtain the timing parameter values ​​of each timing type of the flat-panel detector; wherein the timing parameter group belonging to the non-dominated solution is: the evaluation value of this timing parameter group for each optimization target is not inferior to the evaluation value of another timing parameter group for each optimization target.

[0113] It can be understood that, for step B1, the non-dominated level and crowding distance of each timing parameter group in the reference group to be tested can be calculated based on the quality evaluation values ​​under each specified image quality index. The non-dominated level can be determined according to the dominance relationship between the quality evaluation values ​​of each timing parameter group under each specified image quality index. The non-dominated level of each timing parameter group represents: the degree of superiority or inferiority of the evaluation value of the timing parameter group for each optimization target compared with the evaluation values ​​of other timing parameter groups. The timing parameter group with a lower non-dominated level indicates that the solution of the timing parameter group (the evaluation value for each optimization target) performs well under each specified image quality index, that is, the quality evaluation value of the solution of the timing parameter group under each specified image quality index can dominate the solutions of other timing parameter groups. For example, f1(x) is the objective function for dark field horizontal stripes, and f2(x) is the objective function for dark field vertical stripes. The timing parameter group A is substituted into the two objective functions. By using the target function, we can get f1(A)=1 and f2(A)=1. Substituting the timing parameter group A into the two target functions, we can get f1(B)=0.5 and f2(B)=0.8. The smaller the value of the target function, the better it is. Then, it can be determined that the non-dominated level of the timing parameter group A is 1, and the non-dominated level of the timing parameter group B is 2. It should be emphasized that the calculation of the crowding distance can be used to maintain the diversity of the population. The crowding distance of each timing parameter group is characterized by: when each timing parameter group in the parameter group to be tested is represented as an individual, it is used to represent the degree of crowding of the individuals of the timing parameter group in the target space. Among them, the target space is a space with each specified image quality indicator as a different dimension. The crowding distance of any timing parameter group can be intuitively reflected through the target space. In addition, the larger the crowding distance, the fewer other timing parameter groups around the timing parameter group, the fewer other timing parameter groups close to the timing parameter group, and the more unique the timing parameter group. Of course, the reference information is not limited to the non-dominated level and crowding distance described above, but may also include other reference information, which is not specifically limited in the embodiments of the present application. It should be emphasized that any implementation method of calculating the non-dominated level and crowding distance in the related art can be applied to the embodiments of the present application, which is not specifically limited in the embodiments of the present application.

[0114] It can be understood that, for step B2, based on the reference information of each timing parameter group obtained, a timing parameter group with a lower non-dominance level and a larger crowding distance can be selected from the parameter group to be tested. When selecting the timing parameter group, the timing parameter group (individual) with a lower non-dominance level can be preferentially selected. If the non-dominance levels are the same, the timing parameter group with a larger crowding distance is preferentially selected. In this way, the selected timing parameter group can ensure the diversity of the population and avoid premature convergence. Of course, other methods can also be used to select the timing parameter group. The above is only an exemplary introduction and does not limit the embodiments of the present application.

[0115] It can be understood that, for step B3, after selecting the timing parameter group, multiple optimized timing parameter groups can be generated, and the generated multiple optimized timing parameter groups can be used as new parameter groups to be tested. The optimization process can also be based on a multi-objective optimization algorithm. For the sake of clear layout, multiple optimized timing parameter groups are generated based on the selected timing parameter group as the specific content of the new parameter group to be tested. It will be introduced in other embodiments, so no further details will be given here.

[0116] It can be understood that, for step C1, a timing parameter group can be selected from the various timing parameter groups belonging to the non-dominated solutions of the current parameter group to be tested, and the timing parameter values ​​of the timing parameter group can be used as the timing parameter values ​​of each timing type of the flat-panel detector, that is, the evaluation value of the timing parameter group for each optimization target is not inferior to the evaluation value of another timing parameter group for each optimization target, then, there will be no other timing parameter group whose evaluation value for each optimization target is better than the evaluation value of this timing parameter group for each optimization target.

[0117] It can be seen that the embodiment of the present application can generate multiple optimized timing parameter groups based on the selected timing parameter group according to the reference information of each timing parameter group obtained as a new parameter group to be tested. Subsequently, a timing parameter group can be selected from the various timing parameter groups belonging to the non-dominated solution of the current parameter group to be tested to obtain the timing parameter values ​​of each timing type of the flat-panel detector. The determined timing parameter values ​​belong to the timing parameter values ​​of each timing parameter group of the non-dominated solution, which are determined through continuous iterative optimization and can also be considered as the timing parameter values ​​of the flat-panel detector that best meet the current conditions of use. The image quality of the image data generated by the flat-panel detector after X-ray exposure based on the timing parameter value is better. In addition, the timing reference group selected based on the reference information is unique, so that the iterative process can be guaranteed not to end prematurely.

[0118] Optionally, in another embodiment, step B3, generating multiple optimized timing parameter groups based on the selected timing parameter groups as new parameter groups to be tested, includes steps B31-B32:

[0119] Step B31, performing a predetermined adjustment process on the selected timing parameter group; wherein the predetermined adjustment process includes an exchange process of some parameter values ​​between two timing parameter groups, and / or an adjustment process of some parameter values ​​of any timing parameter group;

[0120] Step B32, constructing a plurality of optimized timing parameter groups from the parameter group to be tested and the selected timing parameter group after the predetermined adjustment process as new parameters to be tested.

[0121] It can be understood that, for step B31, the selected timing parameter group is subjected to a predetermined adjustment process. Specifically, the predetermined adjustment process may include exchanging some parameter values ​​of the two timing parameter groups, and / or adjusting some parameter values ​​of any timing parameter group. Therefore, the predetermined adjustment process may only perform the exchange process of some parameter values ​​between the two timing parameter groups, or only perform the adjustment process of some parameter values ​​of any timing parameter group, or may perform the above processes simultaneously, and the embodiments of the present application do not make specific limitations on this. Of course, the two predetermined adjustment processes introduced above are only exemplary introductions, and the embodiments of the present application do not make specific limitations on this.

[0122] The following describes the exchange of some parameter values ​​between two timing parameter groups and the adjustment of some parameter values ​​of any timing parameter group:

[0123] Exemplarily, in one implementation, the process of exchanging some parameter values ​​between the two timing parameter groups includes steps D1-D4:

[0124] Step D1, swapping the parameter values ​​of the first designated parameter positions in the two timing parameter groups to obtain the current two timing parameter groups;

[0125] Step D2, analyzing whether the two current timing parameter groups satisfy the auxiliary constraint conditions respectively; wherein the auxiliary constraint conditions are used to characterize the constraint of the parameter values ​​between the various timing types;

[0126] Step D3, if satisfied, complete the swap process;

[0127] Step D4: if not satisfied, then the parameter values ​​of the second designated parameter positions of the two current timing parameter groups are interchanged to obtain the two current timing parameter groups, and then return to the step of analyzing whether the two current timing parameter groups satisfy the auxiliary constraint conditions respectively.

[0128] The exchange process of some parameter values ​​between two timing parameter groups may also be referred to as cross processing of some parameter values ​​between two timing parameter groups, which is not specifically limited in the embodiment of the present application.

[0129] It can be understood that, for step D1, the two timing parameter groups are both among the selected timing parameter groups. When selecting the two timing parameter groups, it can also be based on the first probability. The first probability can be pre-set by the tester, and is used to select two timing parameter groups from the selected timing parameter groups to exchange some parameter values. The first probability can be a higher probability. Exemplarily, the first probability can be 80%. Of course, the two timing parameter groups for performing the interchange processing can also be directly selected by the tester. The embodiment of the present application does not make specific limitations on this. It should be emphasized that the first designated parameter position can also be pre-set by the tester. After selecting two timing parameter groups, the parameter values ​​of the first designated parameter positions in the two timing parameter groups can be interchanged to obtain the current two timing parameter groups. For example, the binary code of timing parameter group 1 is 00010, and the binary code of timing parameter group 2 is 10101. The first designated parameter position is the position after the second bit. Therefore, by interchangeably processing timing parameter group 1 and timing parameter group 2, the binary code of timing parameter group 1 is 00101, and the binary code of timing parameter group 2 is 10010.

[0130] It can be understood that, for step D2, after the parameter values ​​of the two timing parameter groups are interchanged, it is possible to analyze whether the two current timing parameter groups respectively meet the auxiliary constraint conditions, which are used to characterize the constraints of the parameter values ​​between the various timing types, that is, the constraints on the rising and falling edges of the timing signals corresponding to the parameter values ​​of the various timing types. For example: the auxiliary constraint condition indicates that the falling edge of the timing parameter value of the SHR type is earlier than the rising edge of the timing parameter value of the SHS type, the timing parameter group 1 is the timing parameter value of the SHR type, and the timing parameter group 2 is the timing parameter value of the SHS type. After the parameter values ​​of the two timing parameter groups are interchanged, it is possible to analyze whether the falling edge of the timing parameter value of the interchanged timing parameter group 1 is earlier than the timing parameter value of the timing parameter group 2. If so, the task meets the auxiliary constraint condition. Of course, the auxiliary constraint conditions introduced above are only used as an exemplary introduction, and the embodiments of the present application do not specifically limit this. In addition, the two timing parameter groups after the interchange process must not only meet the auxiliary constraint conditions, but also meet the value constraint conditions. This process can also be called a repair mechanism.

[0131] It can be understood that, for step D3, if the auxiliary constraint condition is met, it is determined that the interchange process is completed, that is, the interchange process of some parameter values ​​between the two timing parameter groups in the predetermined adjustment process is completed.

[0132] It is understandable that, for step D4, if it is not satisfied, the parameter values ​​of the second specified parameter positions of the current two timing parameter groups are interchanged, and the second specified parameter position can be a position related to the first specified parameter position, for example: a position after the first specified parameter position; the second specified parameter position can also be set by the tester, and the embodiment of the present application does not specifically limit this. And, after the parameter values ​​of the second specified parameter positions of the current two timing parameter groups are interchanged to obtain the current two timing parameter groups, step D2 can be returned until the auxiliary constraint condition is satisfied and the interchange process is completed.

[0133] It can be seen that in the process of exchanging some parameter values ​​between two timing parameter groups in the embodiment of the present application, the value constraints and auxiliary constraints must also be met. The timing parameter groups that are not met can be exchanged again until the value constraints and auxiliary constraints are met, thereby improving the accuracy of determining the timing parameter values, and also improving the efficiency of determining the timing parameter values.

[0134] Exemplarily, in one implementation, the adjustment process of some parameter values ​​of any timing parameter group includes steps E1-E2:

[0135] Step E1, adjusting some parameter values ​​of the timing parameter group according to a predetermined value adjustment range;

[0136] Step E2: if the adjusted timing parameter group meets the value constraint condition, the adjustment of some parameter values ​​is completed; otherwise, the adjusted timing parameter group is adjusted again to meet the value constraint condition.

[0137] Among them, the adjustment process of some parameter values ​​can also be called variation processing of local disturbances, and the embodiments of the present application do not make specific limitations on this.

[0138] It can be understood that, for step E1, the selected timing parameter group for performing the adjustment processing of some parameter values ​​can be selected based on the second probability, and the second probability can be pre-set by the tester, and is used to select any timing parameter group from the selected timing parameter group to perform the adjustment processing of some parameter values. The second probability can be a lower probability. For example, the second probability can be 10%. Of course, the timing parameter group for performing the adjustment processing of some parameter values ​​can also be directly selected by the tester, and the embodiment of the present application does not make specific restrictions on this. It should be emphasized that some parameter values ​​of the timing parameter group can be adjusted according to the predetermined value adjustment range; specifically, ai is the value of the rising edge before adjustment, and the rising edge is adjusted within the range of [1, bi], so as to obtain the value of the rising edge after adjustment ai', bi is the value of the falling edge before adjustment, and the falling edge is adjusted within the range of [ai', n], so as to obtain the value of the falling edge after adjustment bi', and n is the maximum range of the time value of the falling edge. Of course, the adjustment process can also be bit reversal variation, Gaussian variation, etc., and the embodiment of the present application does not make specific restrictions on this.

[0139] It can be understood that, for step E2, if the adjusted timing parameter group meets the value constraint condition, it can be determined that the adjustment of some parameter values ​​is completed. For example, the value adjustment range of the rising edge is (0-100), and the adjusted value of the rising edge is 96, so it can be considered that the adjustment of some parameter values ​​is completed. And, if it is not satisfied, it is necessary to adjust the adjusted timing parameter group again. The process of re-adjustment can be considered as adjusting the parameter value outside the value adjustment range to within the value adjustment range so that it meets the value constraint condition and completes the adjustment of some parameter values. For example, the value adjustment range of the rising edge is (0-100), and the adjusted value of the rising edge is 120, so the value of the rising edge can be adjusted again so that the value of the rising edge is within the value adjustment range, and the adjusted value of the rising edge is 98. Among them, the process of re-adjusting the adjusted timing parameter group can also be considered as the process of repairing the adjusted timing parameter group.

[0140] It can be seen that in the process of adjusting the partial parameter values ​​of any timing parameter group, the present application also needs to meet the value constraint conditions. The timing parameter values ​​that do not meet the value constraint conditions can be adjusted to meet the value constraint conditions, thereby improving the accuracy of determining the timing parameter values, and also improving the efficiency of determining the timing parameter values.

[0141] It can be understood that, for step B32, after the selected timing parameter group is subjected to a predetermined adjustment process, the parameter group to be tested and the selected timing parameter group after the predetermined adjustment process can be merged, wherein the parameter group to be tested can be considered as the parent population, and the selected timing parameter group after the predetermined adjustment process can be considered as the child population, and the parent population and the child population are merged to construct a new population, that is, the merged timing parameter group; and the non-dominated level and crowding distance of the merged timing parameter group can be recalculated, and this process has been introduced in the above embodiment, and will not be repeated here, and the non-dominated level and crowding distance calculated are used to screen out half of the number of timing parameter groups from the merged timing parameter group, and the screening mechanism is to select the timing parameter group with a low non-dominated level and a large crowding distance, so as to obtain a new parameter to be tested. Exemplarily, from the merged timing parameter group R t Select 50 timing parameter groups from the total 100 timing parameter groups to form the next generation timing parameter group P {t+1} , as the new parameter to be tested, where the selection method is to first select the individuals with the lowest non-dominated level. If the number is less than 50, then select the timing parameter group with the largest crowding distance from the timing parameter groups with the same non-dominated level.

[0142] In order to better understand the above process, the following will be introduced with reference to the accompanying drawings. Figure 3 As shown:

[0143] S301, input frame rate / exposure time and value constraints;

[0144] It can be understood that the frame rate, exposure time and value constraints can be input into the host computer, and the frame rate and exposure time can also be set according to the actual working state of the flat panel detector;

[0145] S302, customized coding;

[0146] It can be understood that, according to the characteristics of the timing signal of the flat panel detector, a two-dimensional array is used to encode the timing signal parameters.

[0147] S303, initializing the population;

[0148] It can be understood that the population size and the initial value of the timing signal can be set. The population can also be considered as multiple timing parameter groups. For example, a flat-panel detector has m timing parameter groups that need to be adjusted, and a scanning cycle is divided into n parts. Since the value constraints are considered during encoding, the first element ai (rising edge) of the two-dimensional array represented by each timing parameter group is generated from the interval (0, n), and the second element bi (falling edge) is randomly generated from the interval (ai, n]. This ensures that the rising edge and falling edge of each timing parameter group meet the basic constraints, and finally an m×2 matrix can be obtained.

[0149] S304, obtaining the fitness function value of each target;

[0150] It can be understood that this process can also be considered as generating quality evaluation values ​​under various specified image quality indicators based on the target image, and obtaining the evaluation values ​​of the timing parameter group for various optimization targets.

[0151] S305, fast non-dominated sorting and crowding distance calculation;

[0152] It can be understood that the non-dominated sorting can be considered as sorting based on the non-dominated level.

[0153] S306, the number of iterations is 1;

[0154] It can be understood that the number of iterations may also be referred to as GEN, and GEN may also be considered as a mark used to mark the number of iterations.

[0155] S307, selecting a timing parameter group;

[0156] It can be understood that this process can be considered as selecting a timing parameter group from the parameter groups to be tested according to the obtained non-dominated level and congestion degree of each timing parameter group.

[0157] S308, partial matching crossover;

[0158] It is understandable that this process can be considered as the above-mentioned exchange process of some parameter values ​​between two timing parameter groups, and no further elaboration is given here.

[0159] S309, local perturbation variation;

[0160] It is understandable that this process can be considered as the adjustment process of some parameter values ​​of any timing parameter group introduced above, and will not be elaborated in detail here.

[0161] S310, combined population;

[0162] It is understandable that the initial population can be merged with the population after crossover and mutation to obtain a merged population.

[0163] S311, Fast Non-Dominated Sorting and Crowding Distance Computation;

[0164] It can be understood that the non-dominated level and crowding distance are recalculated for the merged population and sorted.

[0165] S312, generating a new population;

[0166] It can be understood that, from the merged population, half of the timing parameter groups with lower non-dominated levels and higher crowding distances are selected to generate a new population.

[0167] S313, whether the maximum number of iterations has been reached;

[0168] It is understandable that it is possible to detect whether the maximum number of iterations has been reached, and if so, outputting the optimal solution, otherwise, executing step S314.

[0169] S314, the number of iterations increases by 1;

[0170] It is understandable that the number of iterations may be updated, and it may also be considered that GEN=GEN+1.

[0171] It can be seen that the embodiment of the present application can perform predetermined adjustment processing on the selected timing parameter group, and construct the parameter group to be tested and the selected timing parameter group after the predetermined adjustment processing into multiple optimized timing parameter groups as new parameters to be tested. In this process, the value constraints must be continuously met, which improves the accuracy of determining the timing parameter values ​​and also improves the efficiency of determining the timing parameter values.

[0172] Optionally, in another embodiment, steps F1-F2 are further included:

[0173] Step F1, obtaining environmental information of the flat panel detector during the process of controlling the flat panel detector to acquire images; wherein the environmental information includes temperature information and / or humidity information;

[0174] Step F2, in response to obtaining the timing parameter values ​​of each timing type of the flat panel detector, establishing a binding relationship between the timing parameter values ​​of each timing type of the flat panel detector and the environmental information.

[0175] It can be understood that, for step F1, since the environmental information of the flat-panel detector can also affect the quality evaluation value under each specified image quality indicator, the environmental information of the flat-panel detector can be obtained in the process of controlling the flat-panel detector to perform image acquisition. The environmental information may include temperature information and / or humidity information. Of course, the environmental information may also include other information, such as: the light level of the shooting environment, which is not specifically limited in the embodiments of the present application.

[0176] It can be understood that, for step F2, in response to the obtained timing parameter values ​​of each timing type of the flat panel detector, a binding relationship between the timing parameter values ​​of each timing type of the flat panel detector and the environmental information can be established. Based on the binding relationship, when the timing parameter values ​​of the same environmental information need to be determined next time, the timing parameter values ​​of the bound timing parameter group can be directly obtained without re-iteration. Exemplarily, two sets of timing parameter values ​​are stored, and the corresponding frame rates are both 10fps. The temperature of the timing parameter value 1 is 10 degrees, and the temperature of the timing parameter value 2 is 30 degrees. The noise at different temperatures is also different. If the current operating temperature is 29 degrees and the corresponding frame rate is 10fps, the timing parameter value of the temperature of 30 degrees can be directly adapted to achieve rapid determination of the timing parameter value.

[0177] It can be seen that the embodiment of the present application can obtain the timing parameter values ​​of each timing type of the flat panel detector and establish a binding relationship between the timing parameter values ​​and the environmental information. When the timing parameter values ​​of the same environmental information need to be determined next time, no iteration is required, which reduces computing power and improves the efficiency of determining the timing parameter values.

[0178] Optionally, in another embodiment, controlling the flat panel detector to perform image acquisition comprises steps G1-G2:

[0179] Step G1, sending a first image acquisition instruction to the flat panel detector, so that the flat panel detector responds to the first image acquisition instruction and performs image acquisition according to the current timing parameter value when the X-ray source is turned on;

[0180] Step G2, sending a second image acquisition instruction to the flat panel detector, so that the flat panel detector responds to the second image acquisition instruction and performs image acquisition according to the current timing parameter value when the X-ray source is turned off.

[0181] In the embodiment of the present application, the turning on or off of the X-ray source can be controlled by the detector, and can also be controlled by the host computer of the flat-panel detector or other processing terminals. For example, after the detector receives the image acquisition instruction, it synchronously controls the turning on or off of the X-ray source. For another example, when the host computer sends the image acquisition instruction to the detector, it sends the turning on or off instruction to the X-ray source. That is, the embodiment of the present application does not specifically limit the specific control implementation of turning on or off the X-ray source.

[0182] Exemplarily, step G1 is for a scene of shooting bright field image data, and a first image acquisition instruction can be sent to the flat panel detector. The image acquisition instruction can be an external trigger signal, and the flat panel detector can be controlled by the signal. The flat panel detector responds to the first image acquisition instruction and sends an opening instruction to the X-ray source to turn on the X-ray source, and performs image acquisition according to the current timing parameter value. The target image acquired is bright field image data; in one implementation, the X-ray source can also be controlled by a PC, and the PC can configure the tube voltage and tube current to the X-ray source through a port (Communication Module Outlet, COM), and send an opening instruction. Of course, the above two implementations can be applied to the embodiment of the present application, and the embodiment of the present application does not make specific limitations on this; wherein, the acquired bright field image data can be an empty field image, and there is no need to place an object for image acquisition. Of course, image acquisition can also be performed on an object, and the embodiment of the present application does not make specific limitations on this.

[0183] Exemplarily, step G2 is for a scene of shooting dark field image data, a second image acquisition instruction can be sent to the flat panel detector, and the flat panel detector responds to the second image acquisition instruction and sends a shutdown instruction to the X-ray source to turn off the X-ray source, and performs image acquisition according to the current timing parameter value, and the acquired target image is the dark field image data; and, in one implementation, the X-ray source can also be controlled by a PC to turn off the X-ray source. Of course, the above two implementations can be applied to the embodiment of the present application, and the embodiment of the present application does not specifically limit this; wherein, the acquired dark field image data image can be an empty field image, and there is no need to place an object for image acquisition.

[0184] Optionally, in another embodiment, the present application also provides another method for determining a timing parameter value, as shown in FIG. 4( a) and FIG. 4( b):

[0185] FIG4( a ) shows timing signals representing four timing types, namely SHR (reset sampling), LPF1 (low-pass filter 1), SHS (signal sampling) and LPF2 (low-pass filter 2), which are not specifically limited in the embodiments of the present application.

[0186] FIG4 (b) is a schematic diagram of the principle of determining the timing parameter value. The PC can control the X-ray source through the interface, set the frame rate / exposure time of the flat panel detector, and set the detector timing signal constraint. The constraint can also be considered as the value constraint condition introduced above. The frame rate / exposure time and timing signal constraint are input into the multi-objective optimization algorithm. The multi-objective optimization algorithm can generate a set of timing parameter groups, and the generated timing parameter groups are updated to the flat panel detector. This process can also be called updating the timing configuration. The interaction between the PC and the flat panel detector is based on GIGE (Gigabit Ethernet vision, Gigabit Ethernet visual transmission interface). The configuration information of the timing parameter group can be sent to the flat panel detector through GVCP (GigE Vision Control Protocol, Gigabit Ethernet visual control protocol). After receiving the timing parameter group, the flat panel detector can perform register configuration and control the gate integrated circuit and the readout integrated circuit. The English abbreviation of the gate integrated circuit can be GIC (Gate Integrated Circuit), and the English abbreviation of the readout integrated circuit can be ROIC (Readout Integrated Circuit). After the flat-panel detector is successfully configured, the PC can send image acquisition instructions to the flat-panel detector, and the flat-panel detector starts image acquisition and transmits the acquired image data to the PC through GVSP (GigE Vision Streaming Protocol), so that the PC can calculate image indicators based on the acquired image data. In addition, the flat-panel detector can also obtain temperature / humidity information and transmit it to the PC through GVCP, so that the multi-objective optimization algorithm can obtain temperature / humidity information. The multi-objective optimization algorithm can evaluate the timing effect based on the image indicators and determine whether to iterate. If the number of iterations is reached, the iteration is stopped and the optimal solution is output, that is, the determined timing parameter value is output.

[0187] Furthermore, another method for determining a timing parameter value provided by an embodiment of the present application may include:

[0188] Step 1, initializing the timing parameter group;

[0189] Step 1.1: Randomly generate an initial timing parameter group P0, where the number of timing parameter groups in the initial timing parameter group is N.

[0190] Step 1.2: Encode each timing parameter group, usually using binary encoding or real number encoding.

[0191] Exemplarily, the number of initialized timing parameter groups is N=100, the maximum number of iterations is 500, the crossover probability is 0.8, the mutation probability is 0.1, and the minimum pulse width minPulseWidth is 1. Generate the initial population, each timing signal of the flat panel detector is composed of a rising edge and a falling edge, and by default, the falling edge>rising edge should be satisfied. Therefore, the rising edge riseTime of each timing signal is generated between [1, 255-minPulseWidth], and the falling edge fallTime is generated between [riseTime+minPulseWidth, 255]. After the population is initialized, 100 timing parameter groups are randomly generated, and each timing parameter group is represented by a 4×2 matrix.

[0192] Step 2, evaluating the fitness, that is, evaluating the function value of the above fitness function;

[0193] Step 2.1: Calculate multiple objective function values ​​for each timing parameter group.

[0194] Step 2.2: Perform non-dominated sorting on each timing parameter group to determine its non-dominated level.

[0195] Step 2.3: Calculate the crowding distance for each timing parameter group to maintain the diversity of the population.

[0196] Exemplarily, the objective function values ​​corresponding to the 100 timing parameter groups are calculated. The objective function values ​​can also be considered as the quality assessment values ​​under the various specified image quality indicators introduced above. After the objective function values ​​are calculated, the timing parameter groups can be non-dominated sorted, the non-dominated levels can be determined, and the crowding distance of each timing parameter group can be calculated.

[0197] Step 3, select an operation;

[0198] It can be understood that from the current timing parameter group P t Select the timing parameter group in the Q t , where the selection method usually uses tournament selection or crowding distance-based selection, and can also combine non-dominated sorting and crowding distance to select the timing parameter group.

[0199] Step 4, cross processing;

[0200] It is understandable that from Q t In the example, two timing parameter groups are randomly selected for cross processing to generate a new timing parameter group. The cross processing can be considered as the above-mentioned exchange processing of some parameter values ​​between the two timing parameter groups. The cross method can be single-point cross, multi-point cross or uniform cross, which is not specifically limited in the embodiment of the present application.

[0201] Exemplarily, there are two timing parameter groups of the parent generation, each of which has four parameter values, timing parameter group 1 is {199, 227; 41, 235; 220, 252; 147, 198}, and timing parameter group 2 is {138, 207; 177, 213; 60, 195; 10, 111}, and the intersection points are 3 and 4, that is, the parameter values ​​of the third and fourth positions can be exchanged. After the crossover processing, timing parameter group 1 is {199, 227; 41, 235; 60, 195; 10, 111}, and timing parameter group 2 is {138, 207; 177, 213; 220, 252; 147, 198}.

[0202] Step 5, mutation operation;

[0203] It is understandable that the mutation operation is performed on the newly generated timing parameter group, and the mutation operation can be considered as the adjustment process of some parameter values ​​of any timing parameter group introduced above to increase the diversity of the population. The mutation method can be bit flip mutation, Gaussian mutation, etc.

[0204] Step 6, merging populations;

[0205] Step 6.1: Set the current timing parameter group P t and the newly generated timing parameter group Q t Merge to generate the merged timing parameter group R t , the number of timing parameter groups is 2N.

[0206] Step 7, determine the non-dominated sorting and calculate the crowding distance;

[0207] Step 7.1: Calculate the combined population R t The non-dominated levels of each timing parameter group are sorted according to the non-dominated level of each timing parameter group.

[0208] Step 7.2: Calculate the crowding distance for each timing parameter group to maintain the diversity of the population.

[0209] Step 8, select the next generation population;

[0210] It can be understood that according to the calculated crowding distance and the sorting of the non-dominated level, the combined timing parameter group R t Select N timing parameter groups from among them to form the next generation timing parameter group P {t+1} The selection principle used in the process of selecting N timing parameter groups is: the ones with lower non-dominated levels are given priority over the ones with higher non-dominated levels, and the ones with larger crowding distances are given priority over the ones with smaller crowding distances for the same non-dominated levels.

[0211] Step 9, loop iteration until termination;

[0212] Step 9.1: Check whether the termination condition is met. If the maximum number of iterations is reached or the population converges, it is determined that the termination condition is met.

[0213] Step 9.2: If the termination condition is met, output the optimal solution set; otherwise, return to step 3 to continue iterating.

[0214] It is understandable that when the number of iterations reaches 100, it will stop automatically, and a non-dominated solution set will be obtained. According to actual needs, an optimal signal-to-noise ratio or optimal sensitivity or a compromise solution is selected as the optimal solution under the current frame rate / exposure time and temperature.

[0215] Exemplarily, the results of the first iteration are: SHR Rise (rising edge time) = 10, SHR Fall (falling edge time) = 50, SHS Rise = 60, SHS Fall = 150, LPF1 Rise = 30, LPF1 Fall = 50, LPF2Rise = 100, LPF2 Fall = 155; dark field pixel noise: 20, dark field horizontal stripes: 1.9, dark field vertical stripes: 2.0, sensitivity: 400LSB / uGy, signal-to-noise ratio: 32dB.

[0216] The results of the second iteration are: SHR Rise = 10, SHR Fall = 50, SHS Rise = 60, SHS Fall = 150, LPF1 Rise = 20, LPF1 Fall = 50, LPF2 Rise = 80, LPF2 Fall = 155; dark field pixel noise: 18, dark field horizontal stripes: 1.8, dark field vertical stripes 3.4, sensitivity: 300LSB / uGy, signal-to-noise ratio: 33dB.

[0217] The above-mentioned result of the first iteration and the result of the second iteration are used to characterize the difference between iteration results in different iteration processes.

[0218] It can be seen that the scheme provided by the present application takes each designated image quality index as the optimization target, and continuously iterates on the basis of the parameter group to be tested according to the predetermined multi-objective optimization iteration method, so that a new parameter group to be tested can be obtained, and finally, in response to the optimization end condition, the timing parameter values ​​of each timing type of the flat panel detector can be selected from the new parameter group to be tested; thus, compared with the prior art, the scheme provided by the embodiment of the present application does not require the tester to manually adjust the timing parameter value of the flat panel detector, so the efficiency of determining the timing parameter value can be greatly improved. In addition, the timing parameter value determined by the embodiment of the present application is determined through continuous iterative optimization, and can also be considered as the timing parameter value of the flat panel detector that best meets the current conditions of use, and the image quality of the image data generated by the flat panel detector after X-ray exposure based on the timing parameter value is better; in addition, in the process of determining the timing parameter value, the timing parameter value of each timing type is required to meet the predetermined value constraint condition, so a part of the timing parameter value that does not meet the value constraint condition can be excluded, thereby reducing the computing power and improving the efficiency of determining the timing parameter value.

[0219] Based on the above method embodiment, the present application embodiment also provides a timing parameter value determination device, such as Figure 5 As shown: a host computer applied to a flat panel detector, the device comprises:

[0220] A generating module 510 is used to generate an initial plurality of timing parameter groups to obtain a parameter group to be tested; wherein each timing parameter group includes timing parameter values ​​of each timing type to be parameter-determined for the flat panel detector, and the timing parameter value of each timing type satisfies a predetermined value constraint condition;

[0221] The configuration module 520 is used to configure each timing parameter group in the parameter group to be tested to the flat panel detector, control the flat panel detector to perform image acquisition, obtain the target image acquired by the flat panel detector, generate the quality evaluation value under each specified image quality index based on the target image, and obtain the judgment value of each optimization target of the timing parameter group, each optimization target is the optimization of a specified image quality index;

[0222] Iterative module 530, for iteratively generating a plurality of optimized timing parameter groups as new parameter groups to be tested based on the evaluation values ​​of each optimization target obtained for each timing parameter group and in accordance with a predetermined multi-objective optimization iteration method on the basis of the parameter group to be tested, and returning the step of configuring each timing parameter group in the parameter group to be tested to the flat panel detector;

[0223] The selection module 540 is used to select a timing parameter group from the current parameter group to be tested in response to satisfying a predetermined optimization end condition, and obtain the timing parameter values ​​of each timing type of the flat panel detector.

[0224] Optionally, the timing parameter value of each timing type is a two-dimensional array, data of one dimension in the two-dimensional array represents the time of the rising edge of the timing signal of the timing type, and data of another dimension represents the time of the falling edge of the timing signal of the timing type;

[0225] The value constraint condition includes that the time of the rising edge of the timing signal of each timing type is earlier than the time of the falling edge, and a target value range, which is a range of time values ​​for the rising edge and the falling edge.

[0226] Optionally, the target value range is determined by:

[0227] Determining the period length of the row scanning period of the timing signals of the various timing types based on the frame rate and exposure time of the flat panel detector;

[0228] The target value range is determined based on the number of specified unit durations contained in the determined cycle duration.

[0229] Optionally, an iteration module, including:

[0230] An analysis submodule, for analyzing reference information for multi-objective optimization of each timing parameter group in the parameter group to be tested based on the obtained evaluation value of each timing parameter group for each optimization target; wherein the reference information includes a non-dominated level and a crowding distance; wherein the non-dominated level of each timing parameter group represents: the degree of superiority or inferiority of the evaluation value of the timing parameter group for each optimization target compared with the evaluation values ​​of other timing parameter groups; and the crowding distance of each timing parameter group represents: when each timing parameter group in the parameter group to be tested is represented as an individual, it is used to represent the crowding degree of the individual of the timing parameter group in the target space; wherein the target space is a space with each specified image quality index as different dimensions;

[0231] A selection submodule, used for selecting a timing parameter group from the parameter groups to be tested according to the obtained reference information of each timing parameter group;

[0232] A generation submodule, used to generate multiple optimized timing parameter groups based on the selected timing parameter groups as new parameter groups to be tested;

[0233] The selection module is specifically used for:

[0234] A timing parameter group is selected from the timing parameter groups belonging to the non-dominated solutions of the current parameter group to be tested to obtain the timing parameter values ​​of each timing type of the flat-panel detector; wherein the timing parameter group belonging to the non-dominated solution is: the evaluation value of this timing parameter group for each optimization target is not inferior to the evaluation value of another timing parameter group for each optimization target.

[0235] Optionally, generate submodules, specifically for:

[0236] Performing a predetermined adjustment process on the selected timing parameter group; wherein the predetermined adjustment process includes an exchange process of some parameter values ​​between two timing parameter groups, and / or an adjustment process of some parameter values ​​of any timing parameter group;

[0237] The parameter group to be tested and the selected timing parameter group after the predetermined adjustment process are constructed into a plurality of optimized timing parameter groups as new parameters to be tested.

[0238] Optionally, the exchange process of some parameter values ​​between the two timing parameter groups includes:

[0239] Interchange the parameter values ​​of the first designated parameter positions in the two timing parameter groups to obtain the current two timing parameter groups;

[0240] Analyze whether the two current timing parameter groups satisfy the auxiliary constraint conditions respectively; wherein the auxiliary constraint conditions are used to characterize the constraint of the parameter values ​​between the various timing types;

[0241] If satisfied, the swap process is completed;

[0242] If not, the parameter values ​​of the first designated parameter positions of the two current timing parameter groups are interchanged to obtain the two current timing parameter groups, and the process returns to the step of analyzing whether the two current timing parameter groups respectively satisfy the auxiliary constraint conditions.

[0243] Optionally, the adjustment process of some parameter values ​​of any timing parameter group includes:

[0244] According to a predetermined value adjustment range, adjusting some parameter values ​​of the timing parameter group;

[0245] If the adjusted timing parameter group meets the value constraint condition, the adjustment of some parameter values ​​is completed; otherwise, the adjusted timing parameter group is adjusted again to meet the value constraint condition.

[0246] Optionally, the device further comprises;

[0247] An acquisition module, used to acquire environmental information of the flat panel detector during the process of controlling the flat panel detector to acquire images; wherein the environmental information includes temperature information and / or humidity information;

[0248] The establishing module is used to establish a binding relationship between the timing parameter values ​​of each timing type of the flat panel detector and the environmental information in response to obtaining the timing parameter values ​​of each timing type of the flat panel detector.

[0249] Optionally, controlling the flat panel detector to acquire images includes:

[0250] Sending a first image acquisition instruction to the flat panel detector, so that the flat panel detector responds to the first image acquisition instruction and performs image acquisition according to the current timing parameter value when the X-ray source is turned on;

[0251] A second image acquisition instruction is sent to the flat panel detector, so that the flat panel detector responds to the second image acquisition instruction and performs image acquisition according to the current timing parameter value when the X-ray source is turned off.

[0252] Optionally, the designated image quality indicators include at least a quality indicator characterizing grayscale information of dark field image data, a quality indicator characterizing noise information of dark field image data, and a quality indicator characterizing sensitivity of the flat panel detector.

[0253] In the technical solution of this application, the operations involved in obtaining, storing, using, processing, transmitting, providing and disclosing user personal information are all carried out with the user's authorization.

[0254] The present application also provides an electronic device, such as Figure 6 As shown, including:

[0255] Memory 601, used for storing computer programs;

[0256] The processor 602 is used to implement any of the above-mentioned timing parameter value determination methods when executing the program stored in the memory 601.

[0257] Furthermore, the electronic device may further include a communication bus and / or a communication interface, and the processor 602, the communication interface, and the memory 601 communicate with each other via the communication bus.

[0258] The communication bus mentioned in the above electronic device can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0259] The communication interface is used for communication between the above electronic device and other devices.

[0260] The memory may include a random access memory (RAM) or a non-volatile memory (NVM), such as at least one disk memory. Optionally, the memory may also be at least one storage device located away from the aforementioned processor.

[0261] The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0262] In another embodiment provided in the present application, a computer-readable storage medium is provided, in which a computer program is stored. When the computer program is executed by a processor, any of the above-mentioned timing parameter value determination methods is implemented.

[0263] In another embodiment provided in the present application, a computer program product including instructions is also provided, which, when executed on a computer, enables the computer to execute any of the timing parameter value determination methods in the above embodiments.

[0264] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from a website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a solid-state hard disk (SSD), etc.

[0265] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0266] Each embodiment in this specification is described in a related manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0267] The above description is only a preferred embodiment of the present application and is not intended to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application are included in the protection scope of the present application.

Claims

1. A method for determining a timing parameter value, characterized in that: The method is applied to a host computer of a flat panel detector and comprises: Generate an initial plurality of timing parameter groups to obtain parameter groups to be tested; wherein each timing parameter group includes timing parameter values ​​of various timing types for which parameter determination is to be performed on the flat panel detector, and the timing parameter values ​​of each timing type satisfy a predetermined value constraint condition; For each timing parameter group in the parameter group to be tested, the timing parameter group is configured to a flat panel detector, and the flat panel detector is controlled to perform image acquisition, a target image acquired by the flat panel detector is obtained, and based on the target image, a quality evaluation value under each specified image quality index is generated, and a judgment value of the timing parameter group for each optimization target is obtained, where each optimization target is an optimization for a specified image quality index; Based on the obtained evaluation values ​​of each timing parameter group for each optimization target, on the basis of the parameter group to be tested, according to a predetermined multi-objective optimization iteration method, iteratively generate multiple optimized timing parameter groups as new parameter groups to be tested, and return the step of configuring each timing parameter group in the parameter group to be tested to the flat panel detector; In response to satisfying a predetermined optimization end condition, a timing parameter group is selected from the current parameter group to be tested to obtain timing parameter values ​​of each timing type of the flat panel detector.

2. The method according to claim 1, characterized in that The timing parameter value of each timing type is a two-dimensional array, in which one-dimensional data represents the time of the rising edge of the timing signal of the timing type, and the other-dimensional data represents the time of the falling edge of the timing signal of the timing type; The value constraint condition includes that the time of the rising edge of the timing signal of each timing type is earlier than the time of the falling edge, and a target value range, which is a range of time values ​​for the rising edge and the falling edge.

3. The method according to claim 2, characterized in that Methods for determining the target value range include: Determining the period length of the row scanning period of the timing signals of the various timing types based on the frame rate and exposure time of the flat panel detector; The target value range is determined based on the number of specified unit durations contained in the determined cycle duration.

4. The method according to any one of claims 1 to 3, characterized in that: The evaluation values ​​for each optimization target of each timing parameter group obtained are used to iteratively generate multiple optimized timing parameter groups as new parameter groups to be tested based on the parameter groups to be tested in a predetermined iterative manner of multi-objective optimization, including: Based on the obtained evaluation values ​​of each timing parameter group for each optimization target, the reference information for multi-target optimization of each timing parameter group in the parameter group to be tested is analyzed; wherein the reference information includes a non-dominated level and a crowding distance; wherein the non-dominated level of each timing parameter group represents: the degree of superiority or inferiority of the evaluation values ​​of the timing parameter group for each optimization target compared with the evaluation values ​​of other timing parameter groups, and the crowding distance of each timing parameter group represents: when each timing parameter group in the parameter group to be tested is represented as an individual, it is used to represent the crowding degree of the individual of the timing parameter group in the target space; wherein the target space is a space with each specified image quality index as different dimensions; According to the obtained reference information of each timing parameter group, a timing parameter group is selected from the parameter groups to be tested; Based on the selected timing parameter group, generating multiple optimized timing parameter groups as new parameter groups to be tested; The step of selecting a timing parameter group from the current parameter group to be tested to obtain the timing parameter values ​​of each timing type of the flat panel detector includes: A timing parameter group is selected from the timing parameter groups belonging to the non-dominated solutions of the current parameter group to be tested to obtain the timing parameter values ​​of each timing type of the flat-panel detector; wherein the timing parameter group belonging to the non-dominated solution is: the evaluation value of this timing parameter group for each optimization target is not inferior to the evaluation value of another timing parameter group for each optimization target.

5. The method according to claim 4, characterized in that The step of generating a plurality of optimized timing parameter groups based on the selected timing parameter groups as new parameter groups to be tested includes: Performing a predetermined adjustment process on the selected timing parameter group; wherein the predetermined adjustment process includes an exchange process of some parameter values ​​between two timing parameter groups, and / or an adjustment process of some parameter values ​​of any timing parameter group; The parameter group to be tested and the selected timing parameter group after the predetermined adjustment process are constructed into a plurality of optimized timing parameter groups as new parameters to be tested.

6. The method according to claim 5, characterized in that The exchange process of some parameter values ​​between the two timing parameter groups includes: Interchange the parameter values ​​of the first designated parameter positions in the two timing parameter groups to obtain the current two timing parameter groups; Analyze whether the two current timing parameter groups satisfy the auxiliary constraint conditions respectively; wherein the auxiliary constraint conditions are used to characterize the constraint of the parameter values ​​between the various timing types; If satisfied, the swap process is completed; If not, the parameter values ​​of the second designated parameter positions of the two current timing parameter groups are interchanged to obtain the two current timing parameter groups, and the process returns to the step of analyzing whether the two current timing parameter groups respectively satisfy the auxiliary constraint conditions.

7. The method according to claim 5, characterized in that The adjustment process of some parameter values ​​of any timing parameter group includes: According to a predetermined value adjustment range, adjusting some parameter values ​​of the timing parameter group; If the adjusted timing parameter group meets the value constraint condition, the adjustment of some parameter values ​​is completed; otherwise, the adjusted timing parameter group is adjusted again to meet the value constraint condition.

8. The method according to any one of claims 1 to 3, characterized in that: Also includes: Acquiring environmental information of the flat panel detector during the process of controlling the flat panel detector to acquire images; wherein the environmental information includes temperature information and / or humidity information; And, in response to obtaining the timing parameter values ​​of each timing type of the flat panel detector, a binding relationship between the timing parameter values ​​of each timing type of the flat panel detector and the environmental information is established.

9. The method according to claim 1, characterized in that: The controlling the flat panel detector to acquire images comprises: Sending a first image acquisition instruction to the flat panel detector, so that the flat panel detector responds to the first image acquisition instruction and performs image acquisition according to the current timing parameter value when the X-ray source is turned on; A second image acquisition instruction is sent to the flat panel detector, so that the flat panel detector responds to the second image acquisition instruction and performs image acquisition according to the current timing parameter value when the X-ray source is turned off.

10. The method according to any one of claims 1 to 3, characterized in that: The designated image quality indicators at least include a quality indicator representing the grayscale information of the dark field image data, a quality indicator representing the noise information of the dark field image data, and a quality indicator representing the sensitivity of the flat panel detector.

11. A timing parameter value determination device, characterized in that: The host computer used for the flat panel detector comprises: A generating module, used for generating an initial plurality of timing parameter groups to obtain a parameter group to be tested; wherein each timing parameter group includes timing parameter values ​​of each timing type to be parameter-determined for the flat panel detector, and the timing parameter value of each timing type satisfies a predetermined value constraint condition; A configuration module, for configuring each timing parameter group in the parameter group to be tested to the flat panel detector, and controlling the flat panel detector to perform image acquisition, obtaining a target image acquired by the flat panel detector, and generating a quality evaluation value under each specified image quality index based on the target image, and obtaining a judgment value of the timing parameter group for each optimization target, wherein each optimization target is an optimization for a specified image quality index; An iterative module, for iteratively generating a plurality of optimized timing parameter groups as new parameter groups to be tested, based on the evaluation values ​​of each timing parameter group for each optimization target obtained, and in accordance with a predetermined multi-objective optimization iteration method on the basis of the parameter group to be tested, and returning the step of configuring each timing parameter group in the parameter group to be tested to the flat panel detector; The selection module is used to select a timing parameter group from the current parameter group to be tested in response to satisfying a predetermined optimization end condition, and obtain the timing parameter values ​​of each timing type of the flat panel detector.

12. An electronic device, characterized in that: include: Memory, used to store computer programs; A processor, for implementing any of the methods described in claims 1-10 when executing a program stored in a memory.

13. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 10 is implemented.

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