X-ray image acquisition method, system, x-ray machine and storage medium

Abstract

The embodiment of the present application discloses an X-ray image acquisition method, system, X-ray machine and storage medium. The method comprises: acquiring a target image of a target region; when it is determined that at least one optimization region exists in the target image, calculating the average value of the pixels in the optimization region in the target image and determining the received dose corresponding to the average value of the pixels in the optimization region for each optimization region; adjusting the X-ray emission dose of the X-ray source according to the principle that the received dose of the optimization region reaches the X-ray reference received dose, and acquiring an optimized image of the target region based on the adjusted X-ray emission dose that meets the requirements; and adding each optimized image or adding each optimized image and the target image to obtain an X-ray image of the target region. The technical scheme in the embodiment of the present application can obtain an X-ray image that meets the imaging quality requirements.

Description

Technical Field

[0001] This invention relates to the medical field, and in particular to a method, system, X-ray machine, and computer-readable storage medium for acquiring X-ray images. Background Technology

[0002] In X-ray machines such as medical angiography, the X-ray source and the X-ray receiver (e.g., a flat panel detector) are mounted opposite each other, so that the X-rays generated by the X-ray source penetrate the object and are incident on the X-ray receiver and detected by it.

[0003] However, in practical applications, localized image overexposure due to significant density differences in human tissue within the target area of ​​interest is a common image quality problem. This means that low-density tissues or thinner body parts are overexposed, while high-density tissues or thicker body parts are underexposed. In such cases, it's difficult to see all the details simultaneously. For example, during interventional procedures, low-density areas often become overexposed, such as the lungs or air, resulting in high clinical image contrast. This is especially true in cardiac interventional surgeries, where significant overexposure of the lungs can affect stent visibility, making it impossible to pinpoint the stent's precise location in overexposed areas. Similarly, when scanning leg images, the area between the legs may become overexposed. Furthermore, when scanning the cervical spine, the sides of the neck are prone to overexposure.

[0004] Figure 1 An X-ray image of a patient's thoracic and lumbar spine is shown, such as... Figure 1 As shown, the image of the thoracic spine is overexposed, while the image of the lumbar spine is too dark, making it difficult for doctors to see both the thoracic and lumbar spine clearly in one image, whereas in reality, it is usually necessary to obtain information about both the thoracic and lumbar spine at the same time.

[0005] To address this issue and meet different filtration requirements, the current approach mainly involves placing filters of varying thicknesses between the X-ray source and the X-ray receiver to filter out different amounts of X-rays. By switching between different filters, the desired image quality can be achieved.

[0006] In addition, those skilled in the art are working to find other solutions. Summary of the Invention

[0007] In view of this, this invention provides an X-ray image acquisition method, an X-ray image acquisition system, an X-ray machine, and a computer-readable storage medium to acquire high-quality images of human tissues with large density differences.

[0008] An X-ray image acquisition method proposed in this embodiment of the invention includes: acquiring a target image of a target region; when it is determined that there is at least one region to be optimized in the target image, calculating the average pixel value of the region to be optimized in the target image for each region to be optimized; determining the receiving dose of the region to be optimized corresponding to the average pixel value of the region to be optimized based on a predetermined relationship between the average pixel value and the X-ray receiving dose of the X-ray receiver; adjusting the X-ray emission dose of the X-ray source according to the principle of making the receiving dose of the region to be optimized reach a predetermined X-ray reference receiving dose, and acquiring an optimized image of the target region acquired based on the adjusted X-ray emission dose that meets the requirements; the at least one region to be optimized includes an overexposed bright area and / or an underexposed dark area; adding and synthesizing at least one optimized image corresponding to the at least one region to be optimized, or adding and synthesizing at least one optimized image corresponding to the at least one region to be optimized with the target image to obtain an X-ray image of the target region.

[0009] In one embodiment, the at least one region to be optimized includes overexposed bright areas and underexposed dark areas; for each region to be optimized, calculating the average pixel value of the region to be optimized in the target image includes: calculating the histogram of the target image; finding a global threshold of the histogram using a threshold segmentation method; based on the global threshold, calculating the average value of pixels in the histogram that are below the global threshold to obtain the average pixel value of the dark areas; and calculating the average value of pixels in the histogram that are above the global threshold to obtain the average pixel value of the bright areas.

[0010] In one embodiment, the step of adding and synthesizing at least one optimized image corresponding to at least one region to be optimized, or adding and synthesizing at least one optimized image corresponding to at least one region to be optimized with the target image, includes: superimposing at least one optimized image corresponding to at least one region to be optimized into a whole image, or synthesizing the image portions corresponding to their respective regions of optimization in the optimized images corresponding to different regions to be optimized.

[0011] In one embodiment, the at least one region to be optimized includes overexposed bright areas and / or underexposed dark areas; the step of calculating the average pixel value of the region to be optimized in the target image for each region to be optimized includes: calculating the average value of pixels in the target image whose brightness value is greater than a first brightness threshold to obtain the average pixel value of bright areas; and / or, calculating the average value of pixels in the target image whose brightness value is less than a second brightness threshold to obtain the average pixel value of dark areas; wherein the second brightness threshold is less than or equal to the first brightness threshold.

[0012] In one embodiment, the at least one region to be optimized includes overexposed bright areas and underexposed dark areas, and the second brightness threshold is equal to the first brightness threshold; the step of adding and synthesizing at least one optimized image corresponding to at least one region to be optimized, or adding and synthesizing at least one optimized image corresponding to at least one region to be optimized with the target image, includes: superimposing the at least one optimized image corresponding to at least one region to be optimized into a whole image, or synthesizing the image portions corresponding to each region to be optimized from the optimized images corresponding to different regions to be optimized; or, the at least one region to be optimized includes overexposed bright areas and underexposed dark areas, and the second brightness threshold is less than The first brightness threshold; or the at least one area to be optimized includes an overexposed bright area or an underexposed dark area, and the bright area or the dark area is part of the target image; the step of adding and synthesizing at least one optimized image corresponding to at least one area to be optimized, or adding and synthesizing at least one optimized image corresponding to at least one area to be optimized with the target image, includes: superimposing at least one optimized image corresponding to at least one area to be optimized and the target image into a whole image, or synthesizing the image portions corresponding to their respective areas to be optimized in the optimized images corresponding to different areas to be optimized and the image portions of the target image excluding the at least one area to be optimized.

[0013] In one embodiment, the method further includes: detecting pixels in the target image whose brightness values ​​are greater than a preset first brightness threshold to obtain overexposed pixels; and determining that there are overexposed bright areas in the target image when the number of overexposed pixels reaches a preset first quantity threshold; and / or detecting pixels in the target image whose brightness values ​​are less than a preset second brightness threshold to obtain underexposed pixels; and determining that there are underexposed dark areas in the target image when the number of underexposed pixels reaches a preset second quantity threshold; wherein the second brightness threshold is less than or equal to the first brightness threshold.

[0014] An X-ray image acquisition system proposed in this embodiment of the invention includes: a first unit for acquiring a target image of a target region; a second unit for, when it is determined that there is at least one region to be optimized in the target image, calculating the average pixel value of the region to be optimized in the target image for each region to be optimized; determining the receiving dose of the region to be optimized corresponding to the average pixel value of the region to be optimized based on a predetermined relationship between the average pixel value and the X-ray receiving dose of the X-ray receiver; adjusting the X-ray emission dose of the X-ray source according to the principle of making the receiving dose of the region to be optimized reach a predetermined X-ray reference receiving dose, and acquiring an optimized image of the target region acquired based on the adjusted X-ray emission dose that meets the requirements; the at least one region to be optimized includes an overexposed bright area and / or an underexposed dark area; and a third unit for adding and synthesizing at least one optimized image corresponding to the at least one region to be optimized, or adding and synthesizing at least one optimized image corresponding to the at least one region to be optimized with the target image to obtain an X-ray image of the target region.

[0015] In one embodiment, the at least one region to be optimized includes overexposed bright areas and underexposed dark areas; the second unit calculates the histogram of the target image; a global threshold of the histogram is found using a threshold segmentation method; based on the global threshold, the average value of pixels in the histogram below the global threshold is calculated to obtain the average value of dark area pixels; the average value of pixels in the histogram above the global threshold is calculated to obtain the average value of bright area pixels.

[0016] In one embodiment, the third unit superimposes at least one optimized image corresponding to the at least one region to be optimized into a whole image, or synthesizes the image portions corresponding to their respective regions in the optimized images corresponding to different regions to be optimized, to obtain an X-ray image of the target region.

[0017] In one embodiment, the at least one area to be optimized includes overexposed bright areas and / or underexposed dark areas; the second unit calculates the average value of pixels in the target image whose brightness value is greater than a first brightness threshold to obtain the average value of bright area pixels; and / or calculates the average value of pixels in the target image whose brightness value is less than a second brightness threshold to obtain the average value of dark area pixels.

[0018] In one embodiment, the at least one region to be optimized includes an overexposed bright area and an underexposed dark area, and the second brightness threshold is equal to the first brightness threshold; the third unit superimposes at least one optimized image corresponding to the at least one region to be optimized into a whole image, or synthesizes the image portions corresponding to their respective regions in the optimized images corresponding to different regions to be optimized, to obtain an X-ray image of the target region; or, the at least one region to be optimized includes an overexposed bright area and an underexposed dark area, and the second brightness threshold is less than the first brightness threshold; or the at least one region to be optimized includes an overexposed bright area or an underexposed dark area, and the bright area or the dark area is part of the target image; the third unit superimposes at least one optimized image corresponding to the at least one region to be optimized and the target image into a whole image, or synthesizes the image portions corresponding to their respective regions in the optimized images corresponding to different regions to be optimized and the image portions of the target image excluding the at least one region to be optimized.

[0019] In one embodiment, the method further includes: a fourth unit, configured to detect pixels in the target image whose brightness values ​​are greater than a preset first brightness threshold, thereby obtaining overexposed pixels; and when the number of overexposed pixels reaches a preset first quantity threshold, to determine that there is an overexposed bright area in the target image; and / or, to detect pixels in the target image whose brightness values ​​are less than a preset second brightness threshold, thereby obtaining underexposed pixels; and when the number of underexposed pixels reaches a preset second quantity threshold, to determine that there is an underexposed dark area in the target image; wherein the second brightness threshold is less than or equal to the first brightness threshold.

[0020] Another X-ray image acquisition system proposed in this embodiment of the invention includes: at least one memory and at least one processor, wherein: the at least one memory is used to store a computer program; the at least one processor is used to call the computer program stored in the at least one memory to execute the X-ray image acquisition method as described in any of the above embodiments.

[0021] An X-ray machine proposed in this embodiment of the invention includes: an X-ray image acquisition system as described in any of the above embodiments.

[0022] The computer-readable storage medium proposed in this embodiment of the invention stores a computer program thereon; the computer program can be executed by a processor to implement the X-ray image acquisition method as described in any of the above embodiments.

[0023] As can be seen from the above scheme, in the embodiments of the present invention, when determining the areas to be optimized in the target image that have overexposed bright areas and / or underexposed dark areas, the X-ray emission dose is adjusted for each area to be optimized according to the X-ray receiving dose that meets the imaging quality requirements, and the optimized image is obtained based on the adjusted X-ray emission dose that meets the requirements. After the optimized images are added together, an X-ray image that meets the overall imaging quality requirements can be obtained.

[0024] Furthermore, by automatically detecting whether there are areas to be optimized in the target image, the intelligence and flexibility of the system application can be improved. Attached Figure Description

[0025] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which will make the above and other features and advantages of the present invention more apparent to those skilled in the art. In the drawings:

[0026] Figure 1 This is an X-ray image of a patient's thoracic and lumbar spine.

[0027] Figure 2 This is an exemplary flowchart of an X-ray image acquisition method in an embodiment of the present invention.

[0028] Figure 3 This is a schematic diagram of a body model to be scanned in an example of the present invention.

[0029] Figure 4A This is a schematic diagram of a target image in one example of the present invention.

[0030] Figure 4B for Figure 4A The diagram shows a histogram of the target image and a global threshold TS found based on the histogram.

[0031] Figure 4C and Figure 4D Based on Figure 3 The diagram shows the first and second optimized images obtained after local image optimization of the body model shown.

[0032] Figure 4E To be Figure 4C The first optimized image shown and Figure 4D A schematic diagram of the X-ray image obtained by adding the second optimized image shown.

[0033] Figure 5 This is an exemplary structural diagram of an X-ray image acquisition system according to an embodiment of the present invention.

[0034] Figure 6 This is an exemplary structural diagram of another X-ray image acquisition system in an embodiment of the present invention.

[0035] The reference numerals in the attached figures are as follows:

[0036]

[0037] Detailed Implementation

[0038] Considering the limited dynamic range of X-ray receivers, it is difficult to record all signals with a high signal-to-noise ratio. For the high-absorption portions of X-rays in human tissue, the image may contain noisy dark areas (hereinafter referred to as dark areas), i.e., underexposure; while for the low-absorption portions, the image may contain bright areas (hereinafter referred to as bright areas), i.e., overexposure. Therefore, in this embodiment of the invention, a method of combining multiple images is considered to obtain the final image. These images can be optimized for different image portions. For example, when both bright and dark areas exist in an image, one image can focus on the darker portion, and another image can focus on the brighter portion. These images are then added together to obtain a final image with good image quality, which clearly presents information from both the darker and brighter areas.

[0039] To provide a clearer understanding of the objectives, technical solutions, and effects of this invention, specific embodiments of the invention are now described with reference to the accompanying drawings. In the drawings, the same reference numerals indicate components with the same or similar structures but the same function.

[0040] In this document, “exemplary” and “illustrative” mean “serving as an example, illustration or description”, and any illustration or implementation described herein as “exemplary” or “illustrative” should not be construed as a more preferred or more advantageous technical solution.

[0041] To keep the drawings simple, each drawing only schematically shows the parts related to the present invention, and they do not represent the actual structure of the product.

[0042] In this article, "one" can mean not only "only one" but also "more than one". In this article, "first", "second", etc., are used only to distinguish them from each other, not to indicate their importance or order.

[0043] Figure 2 This is an exemplary flowchart of an X-ray image acquisition method in an embodiment of the present invention. Figure 2 As shown, the method may include the following steps:

[0044] Step S21: Obtain the target image of the target area.

[0045] In this step, the target area can be an area of ​​interest to the user during clinical operations. Furthermore, this target area can be changed according to the actual application, and the image acquired in step S21 will change accordingly when the target area changes.

[0046] In specific implementation, the scheme in this embodiment can be executed in real time, and correspondingly, step S21 is also executed in real time; it can also be executed periodically, and correspondingly, step S21 is also executed periodically; or it can be executed conditionally, and correspondingly, step S21 can be triggered when the target area is initially determined and when the target area changes.

[0047] like Figure 3 As shown, the pelvic model 31 and the elbow model 32 are placed together to simulate bodies of different thicknesses, thus obtaining the following... Figure 4A The image shown is a schematic diagram of a target. The pelvis is a region of high X-ray absorption, while the elbow is a region of low X-ray absorption.

[0048] Step S22: When it is determined that there is at least one area to be optimized in the target image, such as an overexposed bright area and / or an underexposed dark area, the average pixel value of the area to be optimized in the target image, such as the average pixel value of the bright area and / or the average pixel value of the dark area, is calculated.

[0049] In this step, there are multiple methods to determine whether there are overexposed bright areas and / or underexposed dark areas in the target image. For example, if the user can directly judge from experience that there may be bright areas and / or dark areas to be optimized in the target area image, the system can directly determine this, for example, based on the user's instructions or settings. Accordingly, in this embodiment, the average pixel value of the area to be optimized in the target image, such as the average pixel value of bright areas and / or the average pixel value of dark areas, can be directly calculated. If it is for an application scenario where the target area is constantly changing, or to facilitate the use of users with less experience, or to improve the application flexibility of the method, the system can also automatically determine this. That is, in this embodiment, before calculating the average pixel value of the area to be optimized in the target image, such as the average pixel value of bright areas and / or the average pixel value of dark areas, it can further include: detecting whether there are areas to be optimized in the target image, such as overexposed bright areas and / or underexposed dark areas. For example, in a specific implementation, histogram technology can be used to detect pixels in the target image whose brightness values ​​are greater than a preset first brightness threshold, thus identifying overexposed pixels. When the number of overexposed pixels reaches a preset first quantity threshold, it is determined that there are overexposed bright areas in the target image that need optimization; otherwise, it can be determined that there are no overexposed bright areas in the target image that need optimization. And / or, based on histogram technology, pixels in the target image whose brightness values ​​are less than a preset second brightness threshold can be detected, thus identifying underexposed pixels. When the number of underexposed pixels reaches a preset second quantity threshold, it is determined that there are underexposed dark areas in the target image that need optimization; otherwise, it can be determined that there are no underexposed dark areas in the target image that need optimization. The second brightness threshold is less than or equal to the first brightness threshold. Furthermore, in other embodiments, an image gradient calculation algorithm can be used to determine the grayscale gradient distribution of the bright and / or dark areas, thereby detecting the edges of the bright and / or dark areas, and then fitting an edge curve to obtain a bright boundary line and / or a dark boundary line.

[0050] There are various methods for calculating the average pixel value of the area to be optimized in the target image, such as the average pixel value of the bright area and / or the average pixel value of the dark area.

[0051] For example, if it is determined that the target image contains both overexposed bright areas and underexposed dark areas that need optimization, in the first example, the histogram of the target image can be calculated first, and a threshold segmentation method such as the Otsu method (Maximum Inter-Class Difference) can be used to find the global threshold of the histogram. Figure 4B It shows Figure 4AThe diagram shows a histogram of the target image and a global threshold TS found based on the histogram. Then, based on the global threshold, the average value of pixels IH in the histogram above the global threshold can be calculated to obtain the average value of pixels in the bright area, and the average value of pixels IL in the histogram below the global threshold can be calculated to obtain the average value of pixels in the dark area.

[0052] In the second example, histogram technology can be used to calculate the average value of pixels in the target image whose brightness value is greater than a first brightness threshold, thus obtaining the average value of pixels in the bright area. Simultaneously, the average value of pixels in the target image whose brightness value is less than a second brightness threshold can be calculated, thus obtaining the average value of pixels in the dark area. The second brightness threshold is less than or equal to the first brightness threshold.

[0053] If an overexposed bright area in the target image is identified as needing optimization, but there is no underexposed dark area, or even if there is a dark area but optimization is not considered, then the average value of the pixels in the target image with a brightness value greater than a first brightness threshold can be calculated based on histogram technology to obtain the average value of the bright area pixels.

[0054] If it is determined that there are underexposed dark areas in the target image that need to be optimized, but there are no overexposed bright areas, or even if there are bright areas but optimization of the bright areas is not considered, then the average value of the pixels in the target image with brightness values ​​less than the second brightness threshold can be calculated based on histogram technology to obtain the average value of the dark area pixels.

[0055] Of course, if it is determined that there are no overexposed bright areas or underexposed dark areas to be optimized in the target image, then the target image can be directly used as the X-ray image of the target region.

[0056] Step S23: Based on the predetermined relationship between the pixel average value and the X-ray receiving dose of the X-ray receiver, determine the receiving dose of the region to be optimized corresponding to the pixel average value of the region to be optimized. For example, determine the receiving dose of the bright region corresponding to the pixel average value of the bright region and / or the receiving dose of the dark region corresponding to the pixel average value of the dark region.

[0057] In this step, if the target image contains both overexposed bright areas and underexposed dark areas that need to be optimized, the bright area receiving dose corresponding to the average pixel value of the bright area and the dark area receiving dose corresponding to the average pixel value of the dark area are determined according to the pre-determined relationship between the average pixel value of the bright area and the X-ray receiving dose of the X-ray receiver.

[0058] If there are overexposed bright areas in the target image that need to be optimized, but there are no underexposed dark areas, or even if there are dark areas but optimization of the dark areas is not considered, then the bright area receiving dose corresponding to the average pixel value of the bright area is determined according to the relationship between the pre-determined average pixel value and the X-ray receiving dose of the X-ray receiver.

[0059] If there are underexposed dark areas in the target image that need optimization, but there are no overexposed bright areas, or even if there are bright areas but optimization is not considered for the bright areas, then the dark area receiving dose corresponding to the average pixel value of the dark area is determined according to the relationship between the pre-determined average pixel value and the X-ray receiving dose of the X-ray receiver.

[0060] Step S24: Compare the received dose of the area to be optimized with a predetermined X-ray reference received dose that meets imaging requirements. Adjust the X-ray emission dose of the X-ray source according to the principle of making the received dose of the area to be optimized reach the X-ray reference received dose, and acquire an optimized image of the target area based on the adjusted X-ray emission dose that meets the requirements. For example, compare the received dose of the bright area with a predetermined X-ray reference received dose that meets imaging requirements. Adjust the X-ray emission dose of the X-ray source according to the principle of making the received dose of the bright area reach or approach the X-ray reference received dose by a predetermined degree, and acquire a first optimized image of the target area based on the adjusted X-ray emission dose that meets the requirements; and / or compare the received dose of the dark area with the X-ray reference received dose. Adjust the X-ray emission dose of the X-ray source according to the principle of making the received dose of the dark area reach or approach the X-ray reference received dose by a predetermined degree, and acquire a second optimized image of the target area based on the adjusted X-ray emission dose that meets the requirements.

[0061] In this embodiment, the X-ray reference receiving dose can be a range of values, such as A±10%, A±5%, etc., where A is a predetermined X-ray receiving dose that meets the imaging requirements, such as 100, etc.

[0062] The process of adjusting the X-ray emission dose of the X-ray source according to the principle of ensuring that the received dose of the region to be optimized reaches the X-ray reference received dose can be a cyclical process. This is because a single adjustment may not guarantee that the corresponding X-ray received dose will reach the X-ray reference received dose. Therefore, after one adjustment, a current adjusted image of the target region based on the adjusted X-ray emission dose can be acquired. Then, the average pixel value of the region to be optimized in the current adjusted image is calculated. Based on the relationship between the average pixel value and the X-ray received dose of the X-ray receiver, the received dose of the region to be optimized corresponding to the average pixel value is determined. It is then determined whether the received dose of the region to be optimized reaches the X-ray reference received dose. If it does, the current adjusted image is used as the optimized image for the corresponding region to be optimized; otherwise, the X-ray emission dose of the X-ray source continues to be adjusted, and the process returns to the step of acquiring the current adjusted image of the target region based on the adjusted X-ray emission dose. The adjustment of the X-ray emission dose of the X-ray source can be achieved by adjusting parameters of the X-ray source, such as voltage and current.

[0063] In this step, if the target image contains both overexposed bright areas to be optimized and underexposed dark areas, then the first optimized image and the second optimized image are obtained. Figure 4C and Figure 4D The figures respectively show the basis Figure 3 The diagram shows the first and second optimized images obtained after local image optimization of the body model shown.

[0064] If there are overexposed bright areas in the target image that need to be optimized, but there are no underexposed dark areas, or even if there are dark areas but optimization is not considered for the dark areas, then only the first optimized image is obtained.

[0065] If the target image contains underexposed dark areas that need optimization, but does not contain overexposed bright areas, or even if bright areas exist but optimization of the bright areas is not considered, then only the second optimized image is obtained.

[0066] Step S25: At least one optimized image corresponding to the at least one region to be optimized is added together to synthesize the image, or at least one optimized image corresponding to the at least one region to be optimized is added together with the target image to synthesize the image, thereby obtaining an X-ray image of the target region. For example, the first optimized image and the second optimized image are added together to synthesize the image, or the first optimized image and / or the second optimized image are added together with the target image to synthesize the image, thereby obtaining an X-ray image of the target region.

[0067] In this step, if the target image simultaneously contains both overexposed bright areas and underexposed dark areas to be optimized, and step S22 uses the method in the first example to obtain the average pixel value of the bright areas and the average pixel value of the dark areas, then the first optimized image and the second optimized image can be directly added together to obtain the X-ray image of the target region. Specifically, at least one optimized image corresponding to at least one area to be optimized can be superimposed on the entire image, such as... Figure 4E It shows that Figure 4C The first optimized image shown and Figure 4D The X-ray image shown is obtained by superimposing the second optimized image onto the entire image. It can be seen that the optimized and recombined image can present a clear X-ray image of tissues with significant density differences. Of course, in other embodiments, the image portions corresponding to different regions to be optimized in the optimized images can also be synthesized. For example, the image portions corresponding to the regions to be optimized in the optimized image can be segmented based on bright and / or dark boundary lines, and the segmented portions can be synthesized to obtain an X-ray image of the target region.

[0068] If the target image contains both overexposed bright areas and underexposed dark areas to be optimized, and step S22 uses the method in the second example to obtain the average pixel value of the bright areas and the average pixel value of the dark areas, but the second brightness threshold is equal to the first brightness threshold, then the first optimized image and the second optimized image can still be directly added together as described above to obtain the X-ray image of the target region. If step S22 uses the method in the second example to obtain the average pixel value of the bright areas and the average pixel value of the dark areas, but the second brightness threshold is less than the first brightness threshold, then the first optimized image, the second optimized image, and the target image can be added together to obtain the X-ray image of the target region.

[0069] If there are overexposed bright areas in the target image that need to be optimized, but there are no underexposed dark areas, or even if there are dark areas but optimization is not considered for the dark areas, then the first optimized image and the target image can be added together to obtain the X-ray image of the target region.

[0070] If the target image contains underexposed dark areas that need optimization, but does not contain overexposed bright areas, or even if bright areas exist but optimization of the bright areas is not considered, the second optimized image and the target image can be added together to obtain the X-ray image of the target region.

[0071] When combining at least one optimized image corresponding to at least one region to be optimized with a target image, the process can involve superimposing the at least one optimized image corresponding to at least one region to be optimized and the target image into a single image, or combining the image portions corresponding to each region to be optimized in the optimized images corresponding to different regions to be optimized, and the image portions of the target image excluding the at least one region to be optimized. For example, based on bright and / or dark boundary lines, the image portions of the optimized image corresponding to the region to be optimized and the image portions of the target image excluding the at least one region to be optimized can be segmented, and then the segmented portions can be combined to obtain an X-ray image of the target region.

[0072] In this embodiment, steps S21 to S25 are not intended to limit the execution order of the various technical features. For example, if the target image contains both overexposed bright areas and underexposed dark areas to be optimized, the execution order in this embodiment can be as follows: Figure 2In addition to the sequential execution of steps S21 to S25 shown, the following steps can also be performed: Calculate the average pixel value of the bright area in the target image; determine the bright area receiving dose corresponding to the average pixel value of the bright area based on the relationship between the predetermined average pixel value and the X-ray receiving dose of the X-ray receiver; compare the bright area receiving dose with a predetermined X-ray reference receiving dose that meets the imaging requirements, adjust the X-ray emission dose of the X-ray source according to the principle of making the bright area receiving dose reach or approach the X-ray reference receiving dose to a predetermined extent, and obtain a first optimized image of the target area based on the adjusted X-ray emission dose; calculate the average pixel value of the dark area in the target image; determine the dark area receiving dose corresponding to the average pixel value of the dark area based on the relationship between the predetermined average pixel value and the X-ray receiving dose of the X-ray receiver; compare the dark area receiving dose with the X-ray reference receiving dose, adjust the X-ray emission dose of the X-ray source according to the principle of making the dark area receiving dose reach or approach the X-ray reference receiving dose to a predetermined extent, and obtain a second optimized image of the target area based on the adjusted X-ray emission dose. Furthermore, the process can also include: calculating the average pixel value of the dark area in the target image; determining the dark area receiving dose corresponding to the average pixel value based on a predetermined relationship between the average pixel value and the X-ray receiving dose of the X-ray receiver; comparing the dark area receiving dose with the X-ray reference receiving dose, adjusting the X-ray emission dose of the X-ray source according to the principle of making the dark area receiving dose reach or approach the X-ray reference receiving dose to a predetermined extent, and acquiring a second optimized image of the target area based on the adjusted X-ray emission dose; calculating the average pixel value of the bright area in the target image; determining the bright area receiving dose corresponding to the average pixel value of the bright area based on a predetermined relationship between the average pixel value and the X-ray receiving dose of the X-ray receiver; comparing the bright area receiving dose with a predetermined X-ray reference receiving dose that meets the imaging requirements, adjusting the X-ray emission dose of the X-ray source according to the principle of making the bright area receiving dose reach or approach the X-ray reference receiving dose to a predetermined extent, and acquiring a first optimized image of the target area based on the adjusted X-ray emission dose. The specific execution order can be adjusted according to actual needs and is not limited here.

[0073] The X-ray image acquisition method in the embodiments of the present invention has been described in detail above. The X-ray image acquisition system in the embodiments of the present invention will now be described in detail below. The X-ray image acquisition system in the embodiments of the present invention can be used to implement the X-ray image acquisition method in the embodiments of the present invention. Details not disclosed in detail in the system embodiments of the present invention can be found in the corresponding descriptions in the method embodiments of the present invention, and will not be repeated here.

[0074] Figure 5 This is an exemplary structural diagram of an X-ray image acquisition system in an embodiment of the present invention. Figure 5 As shown by the solid line portion, the system may include: a first unit 510, a second unit 520, and a third unit 530.

[0075] The first unit 510 is used to acquire the target image of the target area.

[0076] When the second unit 520 determines that there is at least one area to be optimized in the target image, it calculates the average pixel value of the area to be optimized in the target image for each area to be optimized; it determines the receiving dose of the area to be optimized corresponding to the average pixel value of the area to be optimized based on the relationship between the pre-determined average pixel value and the X-ray receiving dose of the X-ray receiver; it adjusts the X-ray emission dose of the X-ray source according to the principle of making the receiving dose of the area to be optimized reach a pre-determined X-ray reference receiving dose, and acquires an optimized image of the target area based on the adjusted X-ray emission dose that meets the requirements; the at least one area to be optimized includes overexposed bright areas and / or underexposed dark areas. For example, when it is determined that there are overexposed bright areas to be optimized in the target image, the average pixel value of the bright area in the target image is calculated; based on the relationship between the pre-determined average pixel value and the X-ray receiving dose of the X-ray receiver, the bright area receiving dose corresponding to the average pixel value of the bright area is determined; the bright area receiving dose is compared with a pre-determined X-ray reference receiving dose that meets the imaging requirements, and the X-ray emission dose of the X-ray source is adjusted according to the principle of making the bright area receiving dose reach the X-ray reference receiving dose, and a first optimized image of the target area is acquired based on the adjusted X-ray emission dose that meets the requirements; and / or, when it is determined that there are underexposed dark areas to be optimized in the target image, the average pixel value of the dark area in the target image is calculated; based on the relationship between the pre-determined average pixel value and the X-ray receiving dose of the X-ray receiver, the dark area receiving dose corresponding to the average pixel value of the dark area is determined; the dark area receiving dose is compared with the X-ray reference receiving dose, and the X-ray emission dose of the X-ray source is adjusted according to the principle of making the dark area receiving dose reach the X-ray reference receiving dose, and a second optimized image of the target area is acquired based on the adjusted X-ray emission dose that meets the requirements.

[0077] and Figure 2Corresponding to the method described, when it is determined that there are overexposed bright areas and underexposed dark areas in the target image that need optimization, the second unit 520 can follow the method in the first example described in step S22: calculate the histogram of the target image; find the global threshold of the histogram using a threshold segmentation method such as the maximum inter-class difference method; based on the global threshold, calculate the average value of pixels in the histogram that are lower than the global threshold to obtain the average value of dark area pixels; calculate the average value of pixels in the histogram that are higher than the global threshold to obtain the average value of bright area pixels. Alternatively, when it is determined that there are overexposed bright areas and / or underexposed dark areas in the target image that need optimization, the second unit 520 can also follow the method in the second example described in step S22: based on histogram technology, calculate the average value of pixels in the target image whose brightness value is greater than a first brightness threshold to obtain the average value of bright area pixels; and / or, based on histogram technology, calculate the average value of pixels in the target image whose brightness value is less than a second brightness threshold to obtain the average value of dark area pixels.

[0078] The third unit 530 is used to add and synthesize at least one optimized image corresponding to the at least one region to be optimized, or to add and synthesize at least one optimized image corresponding to the at least one region to be optimized with the target image to obtain an X-ray image of the target region. For example, the first optimized image and the second optimized image are added together, or the first optimized image and / or the second optimized image are added together with the target image to obtain an X-ray image of the target region.

[0079] and Figure 2Corresponding to the method shown, when it is determined that there are overexposed bright areas and underexposed dark areas in the target image that need to be optimized, and the second unit 520 calculates the average pixel value of the area to be optimized according to the method in the first example in step S22, and then obtains an optimized image; or, when the second unit 520 calculates the average pixel value of the area to be optimized according to the method in the second example in step S22, and then obtains an optimized image, and the second brightness threshold is equal to the first brightness threshold, the third unit 530 can superimpose at least one optimized image corresponding to at least one area to be optimized into a whole image, or synthesize the image portions corresponding to their respective areas to be optimized in the optimized images corresponding to different areas to be optimized, to obtain an X-ray image of the target region. When it is determined that there are overexposed bright areas and underexposed dark areas in the target image that need to be optimized, and the second unit 520 calculates the average pixel value of the area to be optimized according to the method in the second example described in step S22, and then obtains an optimized image, if the second brightness threshold is less than the first brightness threshold, or if it is determined that there are only overexposed bright areas or underexposed dark areas in the target image that need to be optimized, the third unit 530 can superimpose at least one optimized image corresponding to at least one area to be optimized and the target image as a whole image, or synthesize the image portions corresponding to each area to be optimized in the optimized images corresponding to different areas to be optimized and the image portions of the target image other than the at least one area to be optimized, to obtain an X-ray image of the target region.

[0080] and Figure 2 Corresponding to the method shown, the system in this embodiment of the invention can be as follows: Figure 5 As shown by the dashed line portion, it further includes: a fourth unit 540, used to detect pixels in the target image whose brightness values ​​are greater than a preset first brightness threshold based on histogram technology, obtaining overexposed pixels; and when the number of overexposed pixels reaches a preset first quantity threshold, determining that there are overexposed bright areas in the target image that need optimization; and / or, based on histogram technology, to detect pixels in the target image whose brightness values ​​are less than a preset second brightness threshold, obtaining underexposed pixels; and when the number of underexposed pixels reaches a preset second quantity threshold, determining that there are underexposed dark areas in the target image that need optimization. Wherein, the second brightness threshold is less than or equal to the first brightness threshold.

[0081] Figure 6 This is a schematic diagram of the structure of another X-ray image acquisition system according to an embodiment of the present invention, such as... Figure 6 As shown, the system may include at least one memory 61, at least one processor 62, and at least one display 63. Additionally, it may include other components, such as communication ports. These components communicate via a bus 64.

[0082] At least one memory 61 is used to store a computer program. In one embodiment, the computer program can be understood to include... Figure 5 The X-ray image acquisition system shown comprises various modules. In addition, at least one memory 61 may store an operating system, etc. The operating system includes, but is not limited to: Android, Symbian, Windows, Linux, etc.

[0083] At least one display 63 is used to display the acquired target image, the first optimized image and / or the second optimized image, and the final X-ray image, etc.

[0084] At least one processor 62 is used to invoke a computer program stored in at least one memory 61 to execute the X-ray image acquisition method described in this embodiment of the invention. The processor 62 can be a CPU, processing unit / module, ASIC, logic module, or programmable gate array, etc. It can receive and transmit data through the communication port.

[0085] This invention also provides an X-ray machine, which includes the X-ray image acquisition system described in any of the above embodiments.

[0086] It should be noted that not all steps and modules in the above processes and structural diagrams are mandatory; some steps or modules can be omitted as needed. The execution order of the steps is not fixed and can be adjusted as required. The division of modules is merely for the convenience of description and functional division. In actual implementation, a module can be implemented by multiple modules, and the functions of multiple modules can also be implemented by the same module. These modules can be located in the same device or in different devices.

[0087] It is understood that the hardware modules in the above embodiments can be implemented mechanically or electronically. For example, a hardware module may include specially designed permanent circuits or logic devices (such as dedicated processors, such as FPGAs or ASICs) to perform specific operations. A hardware module may also include programmable logic devices or circuits (such as general-purpose processors or other programmable processors) temporarily configured by software to perform specific operations. The specific method used to implement the hardware module—whether it is mechanical, a dedicated permanent circuit, or a temporarily configured circuit (such as one configured by software)—can be determined based on cost and time considerations.

[0088] Furthermore, this embodiment of the invention also provides a computer-readable storage medium storing a computer program that can be executed by a processor to implement the X-ray image acquisition method described in this embodiment. Specifically, a system or apparatus equipped with a storage medium can be provided, on which software program code implementing the functions of any of the above embodiments is stored, and the computer (or CPU or MPU) of the system or apparatus can read and execute the program code stored in the storage medium. Furthermore, the operating system or other devices operating on the computer can perform some or all of the actual operations through instructions based on the program code. The program code read from the storage medium can also be written to a memory located in an expansion board inserted into the computer or to a memory located in an expansion unit connected to the computer. Subsequently, the CPU or other devices installed on the expansion board or expansion unit can execute some or all of the actual operations based on the instructions of the program code, thereby implementing the functions of any of the above embodiments. Storage medium embodiments for providing program code include floppy disks, hard disks, magneto-optical disks, optical disks (such as CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD+RW), magnetic tapes, non-volatile memory cards, and ROMs. Alternatively, program code can be downloaded from a server computer via a communication network.

[0089] As can be seen from the above scheme, in the embodiments of the present invention, when determining the areas to be optimized in the target image that have overexposed bright areas and / or underexposed dark areas, the X-ray emission dose is adjusted for each area to be optimized according to the X-ray receiving dose that meets the imaging quality requirements, and the optimized image is obtained based on the adjusted X-ray emission dose that meets the requirements. After the optimized images are added together, an X-ray image that meets the overall imaging quality requirements can be obtained.

[0090] Furthermore, by automatically detecting whether there are areas to be optimized in the target image, the intelligence and flexibility of the system application can be improved.

[0091] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for acquiring X-ray images, characterized in that, include: Acquire the target image of the target area (S21); When it is determined that there is at least one area to be optimized in the target image, for each area to be optimized, the average pixel value of the area to be optimized in the target image is calculated; according to the relationship between the pre-determined average pixel value and the X-ray receiving dose of the X-ray receiver, the receiving dose of the area to be optimized corresponding to the average pixel value of the area to be optimized is determined; the X-ray emission dose of the X-ray source is adjusted according to the principle of making the receiving dose of the area to be optimized reach a pre-determined X-ray reference receiving dose, and an optimized image of the target area is acquired based on the adjusted X-ray emission dose that meets the requirements (S22~S24); the at least one area to be optimized includes an overexposed bright area and / or an underexposed dark area; The at least one optimized image corresponding to the at least one region to be optimized is added together to synthesize the image, or the at least one optimized image corresponding to the at least one region to be optimized is added together with the target image to synthesize the X-ray image of the target region (S25). The method further includes: Pixels in the target image whose brightness values ​​exceed a preset first brightness threshold are detected to be overexposed pixels. When the number of overexposed pixels reaches a preset first number threshold, it is determined that there are overexposed bright areas in the target image; and / or, Pixels in the target image whose brightness values ​​are less than a preset second brightness threshold are detected to obtain overly dark pixels. When the number of overly dark pixels reaches a preset second quantity threshold, it is determined that there is an underexposed dark area in the target image that needs to be optimized; wherein, the second brightness threshold is less than or equal to the first brightness threshold.

2. The X-ray image acquisition method according to claim 1, characterized in that, The at least one region to be optimized includes overexposed bright areas and underexposed dark areas; the step of calculating the average pixel value of the region to be optimized in the target image for each region to be optimized includes: Calculate the histogram of the target image; The global threshold of the histogram is found using a threshold segmentation method; Based on the global threshold, the average value of pixels in the histogram that are below the global threshold is calculated to obtain the average value of pixels in the dark area; the average value of pixels in the histogram that are above the global threshold is calculated to obtain the average value of pixels in the bright area.

3. The X-ray image acquisition method according to claim 2, characterized in that, The step of adding and synthesizing at least one optimized image corresponding to at least one region to be optimized, or adding and synthesizing at least one optimized image corresponding to at least one region to be optimized with the target image, includes: The at least one optimized image corresponding to the at least one region to be optimized is superimposed on the whole image, or the image portions corresponding to the respective regions to be optimized in the optimized images of different regions to be optimized are synthesized.

4. The X-ray image acquisition method according to claim 1, characterized in that, The at least one region to be optimized includes overexposed bright areas and / or underexposed dark areas; the calculation of the average pixel value of the region to be optimized in the target image for each region to be optimized includes: Calculate the average value of pixels in the target image whose brightness value is greater than a first brightness threshold to obtain the average value of bright area pixels; and / or, The average value of pixels in the target image whose brightness value is less than the second brightness threshold is calculated to obtain the average value of dark area pixels; wherein the second brightness threshold is less than or equal to the first brightness threshold.

5. The X-ray image acquisition method according to claim 4, characterized in that, The at least one region to be optimized includes overexposed bright areas and underexposed dark areas, and the second brightness threshold is equal to the first brightness threshold; the step of adding and synthesizing at least one optimized image corresponding to at least one region to be optimized, or adding and synthesizing at least one optimized image corresponding to at least one region to be optimized with the target image, includes: superimposing the at least one optimized image corresponding to at least one region to be optimized into a whole image, or synthesizing the image portions corresponding to their respective regions of optimization in the optimized images corresponding to different regions to be optimized; or, The at least one region to be optimized includes an overexposed bright area and an underexposed dark area, and the second brightness threshold is less than the first brightness threshold; or the at least one region to be optimized includes an overexposed bright area or an underexposed dark area, and the bright area or the dark area is part of the target image; the step of adding and synthesizing at least one optimized image corresponding to at least one region to be optimized, or adding and synthesizing at least one optimized image corresponding to at least one region to be optimized with the target image, includes: superimposing at least one optimized image corresponding to at least one region to be optimized and the target image as a whole image, or synthesizing the image portions corresponding to each region to be optimized in the optimized images corresponding to different regions to be optimized and the image portions of the target image other than the at least one region to be optimized.

6. An X-ray image acquisition system, characterized in that, include: The first unit (510) is used to acquire the target image of the target area; The second unit (520) calculates the average pixel value of the target image for each region to be optimized when it is determined that there is at least one region to be optimized in the target image; determines the receiving dose of the region to be optimized corresponding to the average pixel value of the target image based on the relationship between the pre-determined average pixel value and the X-ray receiving dose of the X-ray receiver; adjusts the X-ray emission dose of the X-ray source according to the principle of making the receiving dose of the region to be optimized reach a pre-determined X-ray reference receiving dose, and acquires an optimized image of the target area based on the adjusted X-ray emission dose that meets the requirements. The at least one area to be optimized includes overexposed bright areas and / or underexposed dark areas; The third unit (530) is used to add and synthesize at least one optimized image corresponding to the at least one region to be optimized, or to add and synthesize at least one optimized image corresponding to the at least one region to be optimized with the target image to obtain an X-ray image of the target region; The system further includes a fourth unit (540) for detecting pixels in the target image whose brightness values ​​are greater than a preset first brightness threshold, obtaining overexposed pixels, and determining that there are overexposed bright areas in the target image when the number of overexposed pixels reaches a preset first quantity threshold; and / or, detecting pixels in the target image whose brightness values ​​are less than a preset second brightness threshold, obtaining underexposed pixels, and determining that there are underexposed dark areas in the target image when the number of underexposed pixels reaches a preset second quantity threshold; wherein the second brightness threshold is less than or equal to the first brightness threshold.

7. The X-ray image acquisition system according to claim 6, characterized in that, The at least one region to be optimized includes overexposed bright areas and underexposed dark areas; the second unit (520) calculates the histogram of the target image; finds the global threshold of the histogram using a threshold segmentation method; based on the global threshold, calculates the average value of pixels in the histogram that are below the global threshold to obtain the average value of dark area pixels; calculates the average value of pixels in the histogram that are above the global threshold to obtain the average value of bright area pixels.

8. The X-ray image acquisition system according to claim 7, characterized in that, The third unit (530) superimposes at least one optimized image corresponding to at least one region to be optimized into a whole image, or synthesizes the image portions corresponding to each region to be optimized in the optimized images corresponding to different regions to be optimized, to obtain the X-ray image of the target region.

9. The X-ray image acquisition system according to claim 6, characterized in that, The at least one area to be optimized includes overexposed bright areas and / or underexposed dark areas; the second unit (520) calculates the average value of pixels in the target image whose brightness value is greater than a first brightness threshold to obtain the average value of bright area pixels; and / or calculates the average value of pixels in the target image whose brightness value is less than a second brightness threshold to obtain the average value of dark area pixels.

10. The X-ray image acquisition system according to claim 9, characterized in that, The at least one region to be optimized includes overexposed bright areas and underexposed dark areas, and the second brightness threshold is equal to the first brightness threshold; the third unit (530) superimposes at least one optimized image corresponding to the at least one region to be optimized into a whole image, or synthesizes the image portions corresponding to their respective regions in the optimized images corresponding to different regions to be optimized, to obtain the X-ray image of the target region; or, The at least one region to be optimized includes an overexposed bright area and an underexposed dark area, and the second brightness threshold is less than the first brightness threshold; or the at least one region to be optimized includes an overexposed bright area or an underexposed dark area, and the bright area or the dark area is part of the target image; the third unit (530) superimposes at least one optimized image corresponding to the at least one region to be optimized and the target image as a whole image, or synthesizes the image portions corresponding to their respective regions to be optimized in the optimized images corresponding to different regions to be optimized and the image portions of the target image other than the at least one region to be optimized.

11. An X-ray image acquisition system, characterized in that, include: At least one memory (61) and at least one processor (62), wherein: The at least one memory (61) is used to store computer programs; The at least one processor (62) is used to call a computer program stored in the at least one memory (61) to execute the X-ray image acquisition method as described in any one of claims 1 to 5.

12. An X-ray machine, characterized in that, The X-ray image acquisition system includes any one of claims 6 to 11.

13. A computer-readable storage medium having a computer program stored thereon; characterized in that, The computer program can be executed by a processor to implement the X-ray image acquisition method as described in any one of claims 1 to 5.

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