CN106413236A - Exposure parameter adjusting method and device - Google Patents
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Abstract
The invention provides an exposure parameter adjusting method and device, wherein the method comprises the following steps of: obtaining a gray parameter of an interesting area in a pre-exposure image, wherein the pre-exposure image is obtained by pre-exposure of a detected body; according to the gray parameter and an exposure parameter when pre-exposure is carried out, obtaining the equivalent thickness of the detected body; and, according to the equivalent thickness and an expected gray parameter of the interesting area, determining an exposure parameter when formal exposure is carried out, wherein the exposure parameter comprises the tube voltage kv and the exposure dose mAs, so that the tube voltage kv and the exposure dose mAs are used in the formal exposure. By means of the exposure parameter adjusting method and device provided by the invention, the image quality when exposure is controlled by AEC can be improved.
Description
Technical Field
The present application relates to medical device technologies, and in particular, to a method and an apparatus for adjusting exposure parameters.
Background
Digital Radiography (DR) equipment is widely used due to its advantages of small radiation dose, high image quality, and the like, and in order to obtain an ideal image quality, it is necessary to set appropriate exposure parameters for the DR equipment, and the parameters may include: tube voltage (kv) and exposure dose (ma ms) for the radiation generating bulb. In a traditional mode, a doctor can determine the value of the exposure parameter according to the characteristics of the patient, such as the height and the weight of the patient, and the subjective experience of the doctor is combined, but the mode of manually setting the exposure parameter completely depends on the subjective experience of the doctor, and the stability of image quality is poor due to the lack of scientific theoretical basis. To overcome the above-mentioned drawbacks of manual Exposure Control, AEC (Automatic Exposure Control) technology is currently beginning to be applied to DR apparatuses, which can automatically adjust Exposure parameters.
One of the AEC parameter adjustment modes is a secondary exposure method, the method comprises two stages of pre-exposure and formal exposure, one exposure parameter can be preset according to experience during pre-exposure, the preset exposure parameter is adjusted according to an exposure image obtained by pre-exposure, and the adjusted parameter is more accurate to be used in the formal exposure. For example, an average gray scale of an exposure image obtained by pre-exposure may be calculated, and an adjustment coefficient by which an exposure dose (mAs) in the exposure parameter is adjusted may be obtained from the average gray scale and a desired gray scale. However, in practical application, it is found that the exposure parameters adjusted by the secondary exposure method still cannot obtain ideal image quality when the exposure is used in the main exposure.
Disclosure of Invention
In view of the above, the present application provides an exposure parameter adjustment method and apparatus to improve image quality when AEC is used to control exposure.
Specifically, the method is realized through the following technical scheme:
in a first aspect, an exposure parameter adjustment method is provided, where the method includes:
acquiring gray parameters of a region of interest in a pre-exposure image, wherein the pre-exposure image is obtained by pre-exposing a detected object;
obtaining the equivalent thickness of the detected body according to the gray-scale parameters and the exposure parameters during pre-exposure;
and determining exposure parameters during formal exposure according to the equivalent thickness and the expected gray scale parameters of the region of interest, wherein the exposure parameters comprise a tube voltage kv and an exposure dose mAs, so that the tube voltage kv and the exposure dose mAs are used in the formal exposure.
In a second aspect, an exposure parameter adjusting apparatus is provided, the apparatus comprising:
the parameter acquisition module is used for acquiring gray parameters of an interested area in a pre-exposure image, and the pre-exposure image is obtained by pre-exposing a detected object;
the thickness determining module is used for obtaining the equivalent thickness of the detected body according to the gray-scale parameter and the exposure parameter during pre-exposure;
and the adjusting processing module is used for determining exposure parameters during formal exposure according to the equivalent thickness and the expected gray scale parameters of the region of interest, wherein the exposure parameters comprise a tube voltage kv and an exposure dose mAs, so that the tube voltage kv and the exposure dose mAs are used in the formal exposure.
According to the exposure parameter adjusting method and device, the parameter relation between the exposure parameters and the gray scale parameters of the exposure image is established by using the unchanged parameter equivalent thickness in pre-exposure and formal exposure, so that the quantitative relation between parameter adjustment and gray scale change is more accurate, two exposure parameters of tube voltage kv and exposure dose mAs can be adjusted according to the quantitative relation, and compared with the traditional method that one exposure parameter mAs can be adjusted only according to a simple gray scale ratio method, the parameter adjustment of the scheme can more accurately adjust the gray scale of the image, and the image quality when AEC is adopted to control exposure is improved.
Drawings
FIG. 1 is a schematic diagram of an AEC system shown in an exemplary embodiment of the present application;
FIG. 2 is a flow chart illustrating a calibration process according to an exemplary embodiment of the present application;
FIG. 3 is a schematic view of an exposure environment shown in an exemplary embodiment of the present application;
FIG. 4 is a phantom thickness image generated from a stepped phantom shown in an exemplary embodiment of the present application;
FIG. 5 is a phantom thickness image generated from a wedge-shaped phantom according to an exemplary embodiment of the present application;
FIG. 6 is an exposure image of a step phantom shown in an exemplary embodiment of the present application;
FIG. 7 is an exposure image of a wedge phantom shown in an exemplary embodiment of the present application;
FIG. 8 is a flowchart illustrating an application process according to an exemplary embodiment of the present application;
FIG. 9 is a flow chart illustrating segmentation of a pre-exposed image foreground according to an exemplary embodiment of the present application;
FIG. 10 is a statistical gray-scale histogram of an active image shown in an exemplary embodiment of the present application;
FIG. 11 is a hardware block diagram of a DR device according to an exemplary embodiment of the present application;
fig. 12 is a view showing a structure of an exposure parameter adjusting apparatus according to an exemplary embodiment of the present application;
fig. 13 shows a structure of another exposure parameter adjustment apparatus according to an exemplary embodiment of the present application.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.
AEC is a technology capable of automatically adjusting exposure parameters of DR equipment, and can overcome the defect of low precision of manual exposure control in the traditional mode. Fig. 1 illustrates a schematic diagram of an AEC system in a DR apparatus that can be applied to a double exposure method (double exposure is one of AEC control methods, and AEC control techniques, such as ionization chamber control methods). As shown in fig. 1, the controller 11 may be configured to generate exposure parameters such as a tube voltage (kv) and an exposure dose (mAs), and send the exposure parameters to the high voltage generator 12, and the high voltage generator 12 controls the bulb 13 to emit exposure radiation (e.g., x-ray) according to the exposure parameters. After the exposure radiation passes through the subject 14, the exposure radiation is received by the detector 15, and the controller 11 may generate an exposure image of the subject 14 based on the radiation received by the detector 15, and may be used for medical diagnosis of the subject 14. The appropriateness of the exposure parameters generated by the controller 11 directly affects the quality of the subsequent exposure image, and the effect of adjusting the quality of the exposure image can be achieved by adjusting the exposure parameters such as exposure dose (mAs).
The exposure parameter adjusting method provided in the embodiment of the present application can be applied to the adjustment of the AEC parameters in the architecture shown in fig. 1, and the parameter adjustment is used in the AEC control of the secondary exposure. In the second exposure method, the second exposure method may include two stages, namely, pre-exposure and main exposure, wherein an exposure parameter may be set in advance according to experience during the pre-exposure, the subject is exposed through the preset exposure parameter, and then the preset exposure parameter is adjusted according to an exposure image of the subject obtained by the pre-exposure, the adjusted parameter is more accurate for the main exposure of the subject during the main exposure, and the dosage used in the pre-exposure stage is usually less than that used during the main exposure.
The exposure parameter adjustment method of this embodiment describes how to adjust the exposure parameters set during pre-exposure to obtain the parameters used during formal exposure, and specifically may be to establish parameter conversion from a pre-exposure stage to a formal exposure stage by using the unchanged parameter equivalent thickness in pre-exposure and formal exposure to obtain a parameter relationship between the exposure parameters and the gray scale parameters of the exposure image, so that the quantization relationship between parameter adjustment and gray scale change is more accurate, and two exposure parameters, namely, the tube voltage kv and the exposure dose mAs, can be adjusted according to the quantization relationship, and obtain more accurate parameters through parameter adjustment, so that the quality of the image obtained by formal exposure is improved.
In order to make parameter adjustment more accurate, the exposure parameter adjustment method provided in the embodiment of the present application includes two parts, namely "correction" and "application", where the "correction" stage is mainly to establish a parameter relationship model that is needed in exposure parameter adjustment through sampling data, for example, the model may include a relationship between an exposure parameter and an image gray scale of an exposure image, the model may be applied to the "application" stage, and the "application" stage is to begin to formally perform exposure scanning on a subject (e.g., a patient). In both "correction" and "application", pre-exposure and main exposure are respectively included, for example, the model is built by secondary exposure, or scanning and image building of the object are completed by secondary exposure. The "correction" and "application" processes will be described separately as follows.
Correction procedure
The correction process is mainly used for establishing parameter relationships used in the subsequent application process. In this example, a phantom is used in the calibration process, the phantom is subjected to secondary exposure, and during pre-exposure and final exposure, corresponding exposure parameters, a thickness of the phantom, and gray-scale parameters of an image are respectively obtained, and a relationship model between the three parameters under pre-exposure and final exposure conditions is respectively established.
It should be noted that the relationship model during pre-exposure and the relationship model during main exposure are related by "equivalent thickness", because the equivalent thickness is a constant factor during both pre-exposure and main exposure. The 'equivalent thickness' is the thickness of the die body when the die body made of a specific material is used for simulating a human body with a specific composition, and the die body and the human body with the same equivalent thickness can realize the approximate function of energy spectrum attenuation. The actual body thickness can be converted to an equivalent thickness for the corresponding phantom.
Fig. 2 illustrates a flowchart of the correction process, and the present example does not limit the execution order of the steps. The method comprises the following steps:
in step 201, an exposure environment is determined, the exposure environment including a phantom, a bulb and a detector.
In the step, the spatial position relationship among the bulb, the die body and the detector can be determined, and the sampling exposure of the die body is carried out under the condition that the relative spatial position is not changed. Fig. 3 illustrates an exposure environment.
In step 202, an equivalent thickness of the phantom is calculated based on a phantom thickness model established in an exposure environment.
In this example, a mold thickness model (or simply a thickness model) formed by the exposure radiation emitted by the bulb passing through the mold body may be established, and the mold thickness model is used to determine the length of the exposure radiation within the range of the mold body when the exposure radiation passes through the mold body. Taking the exposure environment illustrated in fig. 3 as an example, the thickness model is established as follows:
let the position of the radiation source be Ps＝(xs,ys,zs) The position of the ray reaching the flat panel detector after passing through the die body is Pd＝(xd,yd,zd) The unit direction of the ray is(Pd≠Ps) Then PsAnd PdL (P) of the straight line betweens,Pd) The equation can be expressed as the following spatial straight-line parameter equation, where t in the following equation represents a step coefficient, and (x, y, z) in the equation represents a three-directional coordinate corresponding to any point on the straight line:
the length T (P) of the straight line in the range of the die bodys,Pd) Comprises the following steps:
wherein,
wherein, phantom is a motif.
In addition, in order to more intuitively understand the equivalent thickness result calculated according to the thickness model, a thickness image of the phantom may be generated according to the previously established phantom thickness model. FIG. 4 illustrates a phantom thickness image generated using a stepped phantom, and FIG. 5 illustrates a phantom thickness image generated using a wedge-shaped phantom. For example, as can be seen from fig. 3, different portions of the stepped phantom may have different thicknesses, that is, the equivalent thicknesses of the same phantom at different portions may be different. Equivalent thicknesses for different regions of the phantom can be determined from the thickness image, assuming that the step thickness image shown in FIG. 4 includes six different equivalent thicknesses, namely, radThick-1, radThick-2, and radThick-3 through radThick-6, respectively.
In step 203, the phantom is exposed under different exposure conditions in the pre-exposure and the main exposure, respectively, to obtain an exposure image of the phantom.
In this step, in the pre-exposure or the formal exposure, the exposure parameters may be changed to expose the phantom, for example, the voltage of the tube is set to kv-1, the exposure dose is mAs-1, and the phantom is subjected to a single pre-exposure to obtain a pre-exposure image of the phantom, and then the formal exposure is performed with another set of exposure parameters "kv-2 and mAs-2" (where, of the exposure parameters used for the pre-exposure and the formal exposure, at least the exposure dose mAs is different) to obtain a formal exposure image of the phantom. Then, the tube voltage of the exposure parameters is changed to kv-3 and the exposure dose is mAs-3, another secondary exposure is carried out on the model, namely, the tube voltage is kv-3 and the exposure dose is mAs-3, and the formal exposure is carried out by the eosin parameters of "kv-4 and mAs-4". FIGS. 6 and 7 illustrate exposure images obtained during a final exposure using a stepped and tapered phantom, respectively.
In step 204, sample data under different exposure conditions are acquired under pre-exposure and main exposure, respectively.
When the phantom is exposed according to a certain exposure parameter in step 203, the gray scale parameter of the exposure image corresponding to the exposure parameter can be determined according to the exposure image obtained by exposure. For example, when the die body is pre-exposed by the tube voltage kv-1 and the exposure dose mAs-1, the image gray scale parameter of the pre-exposed image of the die body can be obtained, and when the die body is formally exposed by the tube voltage kv-2 and the exposure dose mAs-2, the image gray scale parameter of the formally exposed image of the die body can be obtained. In the two exposures, the thickness image of the phantom is not changed, that is, the equivalent thickness of the phantom is not changed, which is equivalent to that for the same phantom with the equivalent thickness, the exposure parameters are changed to perform the exposure to obtain corresponding different images.
Taking the step phantom exposure image shown in fig. 6 as an example, the exposure image of fig. 6 is obtained by exposing the phantom corresponding to the thickness image of fig. 4, and image gray scale parameters respectively corresponding to different equivalent thicknesses of the phantom of fig. 4 can be found in the exposure image, where the gray scale parameters may be average gray scales of a region of interest in the image.
For example, comparing FIGS. 4 and 6, the average intensity of the exposed image after pre-exposure is Gray for the location of the equivalent thickness radThick-1 in the phantompre-1, similarly, the mean Gray level of the pre-exposed image is Gray for the region of equivalent thickness radThick-2 in the phantompreAnd 2, obtaining a plurality of groups of corresponding sample data of the thickness and the gray scale. When the voltage of an exposure parameter tube of pre-exposure is changed to kv-2 and the exposure dose is mAs-2, the model is exposed, and a corresponding exposure image can be obtained, at this time, the average gray scale of the image will change. Table 1 below illustrates sample data collected in a pre-exposure, only some of which are illustrated:
TABLE 1 Pre-exposure sample data Collection
As can be seen from table 1, in the pre-exposure sample data, the equivalent thickness of the phantom is not changed, and the gray scale parameter of the exposure image is changed when the exposure parameter is changed; similarly, when the mold body is subjected to main exposure, sample data similar to those in table 1 can be obtained and are not listed. That is, in this step, a sample of a plurality of sets of exposure parameters, equivalent thicknesses, and gray-scale parameters at the time of pre-exposure is obtained, and a plurality of sets of parameters at the time of main exposure can be obtained in the same manner. These parameters can be used in subsequent steps to build a parametric relational model.
In step 205, a parameter relationship between pre-exposure and main exposure is established according to the sample data.
In this example, a parametric relationship between the equivalent thickness, the tube voltage kv, and the unit gray scale can be established under the pre-exposure, as shown in the following formula (1):
radThick＝f(kv,UnitGraypre)....................(1)
wherein, radThick is the equivalent thickness, UnitGraypreIs the unit gray scale in the pre-exposure.
The unit gray can be calculated according to equation (2):
wherein, GraypreAverage gray scale, mAs, for pre-exposurepreThe exposure parameters at the time of pre-exposure were in mAmp seconds.
The parameter relationship between the unit gradation and the tube voltage kv and the equivalent thickness in the main exposure can be obtained as shown in the following formula (3), in which the unit gradation in the formula (3) is the unit gradation of the exposure image in the main exposure and the tube voltage kv is also the exposure parameter in the main exposure.
UnitGray＝f(kv,radThick)..............(3)
The parameter relationship between the above formula (1) and formula (3) can be obtained by a support vector machine or polynomial fitting.
Through the correction process, the parameter relationship of pre-exposure and the parameter relationship during formal exposure corresponding to the formula (1) and the formula (3) are established, and the equivalent thickness radThick in the two formulas is the same. As can be seen from the above formula, in the pre-exposure, the exposure parameters (e.g., kv, mAs) in the pre-exposure can be determinedpre) And Gray scale parameters of pre-exposed images (e.g., Gray)pre、UnitGraypre) Obtaining an equivalent thickness of the object (e.g., phantom); however, the equivalent thickness is kept constant during the main exposure, and the unit gray scale of the exposure image during the main exposure can be calculated based on the calculated equivalent thickness and the exposure parameter tube voltage kv during the main exposure.
The acquisition of the exposure parameter tube voltage kv during the formal exposure can be realized by the following method: a mapping relation lookup table between the equivalent thickness and the tube voltage kv can be established in advance according to experience, and the mapping relation between any equivalent thickness and the tube voltage kv of the formal exposure can be determined by an interpolation method according to the mapping relation lookup table. Thus, after the equivalent thickness is obtained in the subsequent application, the tube voltage kv of the formal exposure can be obtained according to the mapping relation. The mapping relation lookup table can be obtained by performing a clinical test or a test on a human body simulation model body, calculating the equivalent thickness according to a large number of tests, observing the image quality, and selecting the tube voltage kv with better image quality for the given equivalent thickness.
In addition, when the unit gradation of the exposure image at the time of the main exposure is obtained, as can be seen from the formula (2), mAs at the time of the main exposure can be obtained from the unit gradation and the desired gradation:
the Target _ Gray is a desired Gray level of an exposure image of the main exposure, and is a desired ideal average Gray level.
Thus, the parameter relationships according to which the exposure parameters are adjusted are obtained, as shown in equations (1) to (4).
Application process
The application process is to carry out formal scanning image building on a detected object, and also carry out secondary exposure, taking the detected object as a patient as an example, the process carries out pre-exposure and formal exposure on the patient, and determines exposure parameters to be used by the formal exposure by utilizing the parameter relationship established in the correction process in the pre-exposure stage.
Fig. 8 illustrates a flowchart of an application process, and the present example does not limit the execution order of the steps. The method comprises the following steps:
in step 801, a patient is pre-exposed, resulting in a pre-exposed image.
In this step, the exposure parameters of the pre-exposure may be set in advance according to experience, for example, a pre-exposure condition table may be established according to the conditions of the height, weight, age, and the like of the patient for searching and using during the pre-exposure. And pre-exposing the patient through the exposure parameters of the pre-exposure to obtain a pre-exposure image.
In step 802, grayscale parameters of a region of interest in a pre-exposure image are acquired.
This step may obtain a gray scale parameter of a Region of Interest (ROI) in the pre-exposure image, where the gray scale parameter may be an average gray scale. Wherein the number of ROIs in the pre-exposed image can be one or more, and when there are more, these ROIs can be integrated to calculate the average gray scale.
In one example, in order to make the gray scale calculation of the pre-exposure image more accurate, the pre-exposure image may be subjected to foreground segmentation to obtain a foreground image portion. The pre-exposure image may generally comprise a foreground image portion and a background image portion, the foreground image portion being a target image region and the background image portion being a region outside the target image, calculating a gray scale from the foreground image portion will more accurately reflect the quality of the image. In this example, the foreground image portion in the pre-exposure image can be extracted, and the gray parameter of the region of interest in the foreground image portion is calculated, and the process of foreground segmentation will be described in fig. 9.
Fig. 9 illustrates a process of foreground segmentation on a pre-exposure image, which may include:
in step 901, the beam limiter detection is performed on the pre-exposure image, and an effective image of the pre-exposure image in the range of the beam limiter is extracted.
The step can carry out beam limiter detection on the pre-exposure image, and extract the effective image in the beam limiter. For example, an appropriate low-pass filter may be selected to smooth the pre-exposed image first, eliminating noise from interfering with the image. Because the beam limiters are all distributed in a straight line, straight line detection methods such as Hough transform, Redon transform or gradient operation can be adopted for detection. And after the beam limiter is detected, extracting effective images in the beam limiter.
In step 902, a gray histogram of the effective image is counted.
The step can count the gray level histogram of the effective image in the range of the pre-exposure image beam limiter, and carry out smooth processing on the histogram to prepare for searching the peaks and the troughs of the histogram. For example, fig. 10 illustrates a histogram in which the horizontal axis represents the gray scale value of an image, that is, the gray scale corresponding to each pixel, and the vertical axis represents the number of pixels of the gray scale value included in a pre-exposure image.
In step 903, the gray scale value of the trough satisfying the threshold condition in the gray scale histogram is used as the separation threshold.
Traversing all wave crests and wave troughs from right to left in the histogram, and determining the gray value of the wave trough meeting the following two conditions as a segmentation threshold when at least one of the two conditions is met:
the first condition is as follows: when the number of gray scales of a certain wave valley value is less than a certain threshold value. For example, in the example of fig. 10, it is assumed that the horizontal axis corresponding to a certain valley has a grayscale value of 1500, and the vertical axis represents the number of pixels having a grayscale value of 1500 included in the pre-exposure image, and the threshold in the first condition is a threshold for the set number of grays, that is, a threshold is set for the value of the vertical axis.
And a second condition: the ratio or difference between the number of the wave crest gray scales at both sides of the wave trough and the number of the wave trough gray scales is larger than a certain threshold. For example, two peaks are usually present on two sides of the valley, a left peak and a right peak, each peak also has a value on the corresponding longitudinal axis, i.e., a gray number, and for any one of the peaks, a ratio and a difference are required to be made between the gray number of the peak and the gray number of the valley. Assuming that "the number of gradations of peak/the number of gradations of valley" is labeled as a ratio B and "the number of gradations of peak-the number of gradations of valley" is labeled as a difference C, a ratio threshold B1 and a difference threshold C1 may be set, respectively, then this condition two requires that B be greater than B1 and C be greater than C1. And two wave crests on two sides of the wave trough can be compared by selecting one wave crest with a larger longitudinal axis value, so that the conditions of the ratio and the difference are met.
When at least one of the above two conditions is satisfied, the gray value of the trough is determined as the segmentation threshold. Fig. 10 shows a histogram of a pre-exposure image and its threshold value, and the broken line indicates a division threshold value.
In step 904, the image portion of the image corresponding to the gray level less than the separation threshold is taken as the foreground image portion.
In step 803, an equivalent thickness of the subject is obtained from the gradation parameter and the exposure parameter at the time of pre-exposure.
For example, the gray scale parameter of the region of interest in the pre-exposure image acquired in step 802 is an average gray scale. The step can be combined with the formula (2) to obtain the unit gray scale of the pre-exposed image according to the average gray scale and the exposure dose mAs during pre-exposure.
And then combining a formula (1) to obtain the equivalent thickness of the exposed part of the patient according to the unit gray scale, the kv during pre-exposure and the parameter relationship between the equivalent thicknesses.
In step 804, according to the equivalent thickness and the expected gray scale parameter of the region of interest, determining an exposure parameter during formal exposure, where the exposure parameter includes a tube voltage kv and an exposure dose mAs.
For example, the tube voltage kv at the time of formal exposure corresponding to the equivalent thickness may be determined from the equivalent thickness obtained in step 803 in combination with a mapping relationship between the equivalent thickness and the tube voltage kv.
Then, the unit gray scale at the time of the main exposure can be obtained by combining the formula (3) according to the parameter relationship between the equivalent thickness, the tube voltage kv at the time of the main exposure, and the unit gray scale at the time of the main exposure.
And finally, combining a formula (4), and obtaining the exposure dose mAs during formal exposure according to the expected gray-scale parameters and unit gray-scale of the region of interest.
In step 805, the subject is subjected to a main exposure using the calculated tube voltage kv and exposure dose mAs.
The exposure parameter adjusting method of the embodiment can be applied to AEC control executed by a secondary exposure method, and establishes a parameter relation between an exposure parameter and a gray parameter of an exposure image through the unchanged parameter equivalent thickness in pre-exposure and formal exposure, so that the quantization relation between parameter adjustment and gray change is more accurate, two exposure parameters of tube voltage kv and exposure dose mAs can be adjusted according to the quantization relation, and compared with the traditional method that only one exposure parameter mAs can be adjusted according to a simple gray scale method, the parameter adjustment of the scheme can more accurately adjust the gray scale of the image, and the image quality when AEC is adopted to control exposure is improved.
Corresponding to the method, the application also provides an exposure parameter adjusting device. According to different application scenarios, the apparatus may be service logic implemented by software, or may be hardware or a device combining software and hardware. The device of the present application is described below by taking a software implementation as an example. The software is a logical means formed by a processor of the device in which it is located reading corresponding computer program instructions in the non-volatile memory into the memory for execution. Fig. 11 is a hardware configuration diagram of a DR device in which the software device of the present application is located, as an example. The device may include other hardware besides the processor 1101, the memory 1102, the IO interface 1103 and the nonvolatile memory 1104, and details thereof are not repeated.
Fig. 12 is a schematic structural diagram of an exposure parameter adjusting apparatus according to an embodiment of the present application, and as shown in fig. 12, the apparatus may include: a parameter obtaining module 1201, a thickness determining module 1202 and an adjusting processing module 1203; wherein,
a parameter obtaining module 1201, configured to obtain a gray scale parameter of a region of interest in a pre-exposure image, where the pre-exposure image is obtained by pre-exposing a subject;
a thickness determining module 1202, configured to obtain an equivalent thickness of the object according to the gray-scale parameter and an exposure parameter during pre-exposure;
and an adjusting processing module 1203, configured to determine, according to the equivalent thickness and the desired gray scale parameter of the region of interest, an exposure parameter during the formal exposure, where the exposure parameter includes kv and mAs, so as to use kv and mAs in the formal exposure.
In one example, the gray scale parameter of the region of interest in the pre-exposure image is an average gray scale;
a thickness determining module 1202, configured to obtain a unit gray level according to the average gray level and the mAs during pre-exposure; and obtaining the equivalent thickness of the detected body according to the unit gray scale, the kv during pre-exposure and the parameter relation between the equivalent thicknesses.
In an example, the adjusting module 1203 is specifically configured to determine kv during formal exposure corresponding to the equivalent thickness according to a parameter relationship between the equivalent thickness and kv; obtaining the unit gray scale during formal exposure according to the equivalent thickness, the kv during formal exposure and the parameter relationship between the unit gray scales during formal exposure; and obtaining the mAs during formal exposure according to the expected gray parameter and the unit gray of the region of interest.
In one example, as shown in fig. 13, the apparatus may further include:
the model establishing module 1204 is used for carrying out pre-exposure and formal exposure on the model body and establishing the parameter relationship; the method comprises the following steps: determining the equivalent thickness of the die body corresponding to the exposure parameters according to a pre-established die body thickness model, wherein the die body thickness model is used for determining the length of the exposure ray in the range of the die body when the exposure ray passes through the die body; determining a gray level parameter of the exposure image corresponding to the exposure parameter according to the exposure image obtained by pre-exposing and formal exposing the die body; and establishing the parameter relation among the exposure parameter, the equivalent thickness and the gray scale parameter.
In an example, the parameter obtaining module 1201 is further configured to: before obtaining the gray scale parameters of the region of interest in the pre-exposure image, carrying out beam limiter detection on the pre-exposure image, and extracting an effective image of the pre-exposure image in the range of the beam limiter; counting a gray level histogram of the effective image; taking the gray value of the trough meeting the threshold condition in the gray histogram as a separation threshold, and taking the image part corresponding to the gray value smaller than the separation threshold as a foreground image part; extracting the region of interest in the foreground image portion.
The above description is only exemplary of the present application and should not be taken as limiting the present application, as any modification, equivalent replacement, or improvement made within the spirit and principle of the present application should be included in the scope of protection of the present application.
Claims (10)
1. An exposure parameter adjustment method, comprising:
acquiring gray parameters of a region of interest in a pre-exposure image, wherein the pre-exposure image is obtained by pre-exposing a detected object;
obtaining the equivalent thickness of the detected body according to the gray-scale parameters and the exposure parameters during pre-exposure;
and determining exposure parameters during formal exposure according to the equivalent thickness and the expected gray scale parameters of the region of interest, wherein the exposure parameters comprise a tube voltage kv and an exposure dose mAs, so that the tube voltage kv and the exposure dose mAs are used in the formal exposure.
2. The method according to claim 1, wherein the gray scale parameter of the region of interest in the pre-exposed image is an average gray scale;
obtaining the equivalent thickness of the object according to the gray scale parameter and the exposure parameter during pre-exposure, and the method comprises the following steps:
obtaining unit gray scale according to the average gray scale and the exposure dose mAs during pre-exposure;
and obtaining the equivalent thickness of the detected body according to the unit gray scale, the tube voltage kv during pre-exposure and the parameter relation between the equivalent thicknesses.
3. The method according to claim 1, wherein the determining the exposure parameters during the formal exposure according to the equivalent thickness and the desired gray scale parameters of the region of interest comprises:
determining the tube voltage kv during formal exposure corresponding to the equivalent thickness according to the parameter relationship between the equivalent thickness and the tube voltage kv;
obtaining the unit gray scale during formal exposure according to the equivalent thickness, the tube voltage kv during formal exposure and the parameter relationship between the unit gray scales during formal exposure;
and obtaining the exposure dose mAs during formal exposure according to the expected gray scale parameter and the unit gray scale of the region of interest.
4. A method according to claim 2 or 3, characterized in that the method further comprises: pre-exposure and formal exposure are carried out on the die body, and the parameter relation is established; the method comprises the following steps:
determining the equivalent thickness of the die body corresponding to the exposure parameters according to a pre-established die body thickness model, wherein the die body thickness model is used for determining the length of the exposure ray in the range of the die body when the exposure ray passes through the die body;
determining a gray level parameter of the exposure image corresponding to the exposure parameter according to the exposure image obtained by pre-exposing and formal exposing the die body;
and establishing the parameter relation among the exposure parameter, the equivalent thickness and the gray scale parameter.
5. The method of claim 1, wherein the obtaining gray scale parameters for a region of interest in a pre-exposure image further comprises:
carrying out beam limiter detection on the pre-exposure image, and extracting an effective image of the pre-exposure image in the range of the beam limiter;
counting a gray level histogram of the effective image;
taking the gray value of the trough meeting the threshold condition in the gray histogram as a separation threshold, and taking the image part corresponding to the gray value smaller than the separation threshold as a foreground image part;
extracting the region of interest in the foreground image portion.
6. An exposure parameter adjustment apparatus, characterized by comprising:
the parameter acquisition module is used for acquiring gray parameters of an interested area in a pre-exposure image, and the pre-exposure image is obtained by pre-exposing a detected object;
the thickness determining module is used for obtaining the equivalent thickness of the detected body according to the gray-scale parameter and the exposure parameter during pre-exposure;
and the adjusting processing module is used for determining exposure parameters during formal exposure according to the equivalent thickness and the expected gray scale parameters of the region of interest, wherein the exposure parameters comprise a tube voltage kv and an exposure dose mAs, so that the tube voltage kv and the exposure dose mAs are used in the formal exposure.
7. The apparatus according to claim 6, wherein the gray scale parameter of the region of interest in the pre-exposure image is an average gray scale;
the thickness determining module is specifically used for obtaining unit gray scale according to the average gray scale and the exposure dose mAs during pre-exposure; and obtaining the equivalent thickness of the detected body according to the unit gray scale, the tube voltage kv during pre-exposure and the parameter relation between the equivalent thicknesses.
8. The apparatus of claim 6,
the adjustment processing module is specifically used for determining the tube voltage kv during formal exposure corresponding to the equivalent thickness according to the parameter relationship between the equivalent thickness and the tube voltage kv; obtaining the unit gray scale during formal exposure according to the equivalent thickness, the tube voltage kv during formal exposure and the parameter relationship between the unit gray scales during formal exposure; and obtaining the exposure dose mAs during formal exposure according to the expected gray scale parameter and the unit gray scale of the region of interest.
9. The apparatus of claim 7 or 8, further comprising:
the model establishing module is used for carrying out pre-exposure and formal exposure on the die body and establishing the parameter relation; the method comprises the following steps: determining the equivalent thickness of the die body corresponding to the exposure parameters according to a pre-established die body thickness model, wherein the die body thickness model is used for determining the length of the exposure ray in the range of the die body when the exposure ray passes through the die body; determining a gray level parameter of the exposure image corresponding to the exposure parameter according to the exposure image obtained by pre-exposing and formal exposing the die body; and establishing the parameter relation among the exposure parameter, the equivalent thickness and the gray scale parameter.
10. The apparatus of claim 6,
the parameter obtaining module is further configured to: before obtaining the gray scale parameters of the region of interest in the pre-exposure image, carrying out beam limiter detection on the pre-exposure image, and extracting an effective image of the pre-exposure image in the range of the beam limiter; counting a gray level histogram of the effective image; taking the gray value of the trough meeting the threshold condition in the gray histogram as a separation threshold, and taking the image part corresponding to the gray value smaller than the separation threshold as a foreground image part; extracting the region of interest in the foreground image portion.
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Address after: 110167 No. 177-1 Innovation Road, Hunnan District, Shenyang City, Liaoning Province Patentee after: DongSoft Medical System Co., Ltd. Address before: Hunnan New Century Road 110179 Shenyang city of Liaoning Province, No. 16 Patentee before: Dongruan Medical Systems Co., Ltd., Shenyang |