CN112102355A - Low-contrast resolution identification method, equipment, storage medium and system for flat panel detector - Google Patents
Low-contrast resolution identification method, equipment, storage medium and system for flat panel detector Download PDFInfo
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Abstract
The invention provides a method, equipment, a storage medium and a system for identifying low-contrast resolution of a flat panel detector, wherein the method comprises the following steps: acquiring an original gray image generated by a flat panel detector; extracting a test card image; acquiring the circle center position of the test card; identifying a circular through hole from the test card image and acquiring the circle center position of the circular through hole; calculating the circle center positions of the circular counter bores on the inner ring and the outer ring based on the circle center of the test card and the circle center of the circular through hole; positioning each circular counter bore from the test card image based on the circle center of each circular counter bore and the diameter of each circular counter bore; based on the circle center position of the test card and the positions of the circular counter bores, the average gray value of the area where the circle center of the test card is located and the average gray value of the area where the circular counter bores are located in the original gray image are calculated, and the low contrast value of the area where the circular counter bores are located relative to the area where the circle center is located is calculated on the basis. The invention improves the identification accuracy of the low-contrast resolution of the flat panel detector.
Description
Technical Field
The invention relates to the field of medical imaging, in particular to a method, equipment, a storage medium and a system for identifying low-contrast resolution of a flat panel detector.
Background
The method for measuring the low-contrast resolution of the flat panel detector by adopting the aluminum test card is a conventional flat panel detector performance test method. In the prior art, the operation is generally carried out manually. Specifically, an aluminum test card with a circular counter bore is placed in a window of a flat panel detector to be tested, X-rays generated by an X-ray bulb tube penetrate through the aluminum test card and are captured by the flat panel detector, and the flat panel detector generates a gray image containing an image of the test card. A tester observes the definition of the circular counter bore on the gray level image and determines the low-contrast resolution of the flat panel detector based on a pre-configured test card contrast comparison table.
The measurement of low contrast resolution of a flat panel detector is performed manually, which is not only inefficient, but also affected by subjective assumptions of individuals, and it is difficult to achieve high measurement accuracy.
Disclosure of Invention
In order to solve the above technical problems, a first aspect of the present invention provides a method for identifying a low contrast resolution of a flat panel detector, which has the following specific technical scheme:
a method for identifying low contrast resolution of a flat panel detector, which is executed in an electronic device, comprises the following steps:
acquiring an original gray image of an image containing a test card generated by a flat panel detector, wherein: the test card is a circular aluminum plate, the surface of the test card is provided with an inner ring formed by a plurality of circular counter bores and an outer ring formed by a plurality of circular counter bores, the inner ring and the outer ring are concentric with the test card, the diameter of each circular counter bore is the same, the depth of each circular counter bore is different, the test card is also provided with a circular through hole penetrating through the test card, the diameter of the circular through hole is different from that of the circular counter bores, and the circle center of the circular through hole is staggered with that of the test card;
extracting a test card image with the background removed from the original gray level image;
acquiring the circle center position of the test card;
identifying the circular through hole from the test card image and acquiring the circle center position of the circular through hole;
calculating the circle center positions of the circular counter bores on the inner ring and the outer ring based on the circle center position of the test card and the circle center position of the circular through hole;
positioning each circular counter bore from the test card image based on the circle center position of each circular counter bore and the diameter of the circular counter bore;
calculating the average gray value of the area where the circle center of the test card is located and the average gray value of the area where the circular counter bores are located in the original gray image based on the circle center position of the test card and the positions of the circular counter bores;
and calculating the low contrast value of the area of each circular counter bore relative to the area of the center of the test card based on the average gray value of the area of the center of the test card and the average gray value of the area of each circular counter bore.
In some embodiments, the extracting the background-removed test card image from the original grayscale image includes: performing negation processing on the obtained original gray level image; calculating a segmentation gray threshold of the inverted original gray image by adopting a maximum inter-class variance method; performing binarization processing on the original gray level image based on the segmentation gray level threshold value to obtain a binary gray level image; and extracting the binary gray level image of the test card from the binary gray level image by adopting a connected domain search method.
In some embodiments, said identifying said circular through holes from said test card image comprises: performing negation processing on the extracted binary gray level image of the test card; and identifying the circular through hole from the inverted binary gray level image of the test card by adopting a connected domain searching method.
In some embodiments, the calculating the circle center position of each circular counter bore on the inner ring and the outer ring based on the circle center position of the test card and the circle center position of the circular through hole includes: calculating the central angle between the circle center of the circular through hole and the circle center of each circular counter bore according to the geometric position relation between the circle center of the test card and the circle centers of the circular through holes and the distribution rule of each circular counter bore on the inner ring and the outer ring; and acquiring the circle center of each circular counter bore based on the central angle and the distribution rule of each circular counter bore.
In some embodiments, the test card 1 is a circular aluminum plate with a thickness of 20mm, the inner ring is composed of 9 circular counter bores arranged at equal intervals, and the outer ring is composed of 10 circular counter bores arranged at equal intervals.
In some embodiments, the hole depths of the 9 circular counter bores on the inner ring decrease sequentially in a clockwise direction, the hole depths of the 10 circular counter bores on the outer ring decrease sequentially in a clockwise direction, and the maximum hole depth of the circular counter bore on the inner ring is smaller than the minimum hole depth of the circular counter bore on the outer ring.
In some embodiments, the circular through holes are located in the inner ring, the diameter of each circular counter bore is 1cm, and the diameter of each circular through hole is 2 mm.
A second aspect of the present invention provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the identification method according to any one of the above descriptions when executing the computer program.
A third aspect of the invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the identification method of any one of the above.
The fourth aspect of the present invention provides an automatic low-contrast resolution recognition system for a flat panel detector, comprising: an imaging module comprising an X-ray tube, a flat panel detector, and a test card disposed on the flat panel detector, the test card employing the test card of claim 1, the X-ray tube for generating X-rays, the flat panel detector detecting X-rays to generate an original grayscale image including an image of the test card; the image acquisition module is used for transmitting the original gray level image to electronic equipment; electronic equipment for executing the identification method of any one of the above.
According to the invention, the automatic identification of the low-contrast resolution of the flat panel detector is completed through an image processing technology, so that the identification accuracy is obviously improved, and the identification efficiency is improved.
Drawings
FIG. 1 is a schematic diagram of a low contrast resolution identification system for a flat panel detector according to an embodiment of the present invention;
FIG. 2 is a diagram illustrating a structure of a test card according to an embodiment of the present invention;
FIG. 3 is a flowchart illustrating a method for identifying low contrast resolution of a flat panel detector according to an embodiment of the present invention;
FIG. 4 is a flowchart illustrating a method for identifying low contrast resolution of a flat panel detector according to an embodiment of the present invention;
FIG. 5 is a flowchart illustrating a method for identifying low contrast resolution of a flat panel detector according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of an electronic device in an embodiment of the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
Identification System embodiments
As shown in fig. 1, the present embodiment provides an automatic low-contrast resolution recognition system for a flat panel detector, which includes an imaging module, an image acquisition module (not shown), and an electronic device (not shown). The imaging module includes an X-ray tube 10, a flat panel detector 20, and a test card 30 disposed on the flat panel detector 20.
The test card 30 is a circular aluminum plate with a predetermined thickness (e.g. 20mm), and as shown in fig. 2, the surface of the test card 30 is provided with an inner ring 32 formed by a plurality of circular counter bores and an outer ring 33 formed by a plurality of circular counter bores, the inner ring 32 and the outer ring 33 are concentric with the test card 30, that is: the centers of the inner ring 32, the outer ring 33 and the test card 30 are coincident. The diameters of all the circular counterbores on the inner ring 32 and the outer ring 33 are the same (for example, 1cm), and the hole depths of the circular counterbores are different. In addition, the test card 30 is further provided with a circular through hole 31 penetrating through the test card 30, a diameter of the circular through hole 31 is different from a diameter of the circular counter bore (for example, 2mm), and a center of the circular through hole 31 is staggered from a center of the test card 30.
It should be noted that the circular counter bore mentioned in the present invention refers to a circular hole disposed on the surface of the test card 30 and not penetrating through the test card 30.
The X-ray generated by the X-ray bulb 10 irradiates the flat panel detector 20, and the flat panel detector 20 generates an original gray image after being subjected to light sensing. Because the aluminum test card 30 is placed on the flat panel detector 20, and the X-rays are transparent to aluminum, the original gray scale image includes an image of the test card. Since the test card 30 is provided with the circular counter bores with different depths, the average gray scales of the imaging areas corresponding to the circular counter bores are different.
The determination of the low contrast value of the flat panel detector 20 can be accomplished by calculating the ratio of the average gray level of each circular counter bore to the average gray level of other non-porous regions of the test card image (typically, the center region of the test card image is selected).
Continuing to refer to fig. 2, in an alternative embodiment, the inner ring 32 is formed by 9 circular counter bores arranged at equal intervals, which are numbered clockwise, the 9 circular counter bores are circular counter bores 321 to 329, respectively, and the bore depths of the 9 circular counter bores decrease progressively in the clockwise direction, that is: the circular counterbore 321 has the deepest hole depth and the circular counterbore 329 has the shallowest hole depth. The outer lane comprises the circular counter bore that 10 equidistance were arranged, according to clockwise label, is circular counter bore 331 ~ 330 respectively, and the hole depth of 10 circular counter bores diminishes in proper order along clockwise, promptly: the circular counterbore 331 has the deepest hole depth and the circular counterbore 330 has the shallowest hole depth. Further, the maximum bore depth of the circular counterbore located on the inner race 32 is less than the minimum bore depth of the circular counterbore located on the outer race 33, i.e., the bore depth of the circular counterbore 321 is less than the bore depth of the circular counterbore 330.
As described in the background, the prior art generally accomplishes the determination of low contrast values by manual observation, manual table lookup. In this embodiment, the original grayscale image is subjected to image recognition and processing by using an image recognition technology, and finally, the automatic determination of the low contrast value is completed.
Specifically, the image acquisition module acquires an original gray image from the flat panel detector 20 and transmits the original gray image to the electronic device, and the electronic device realizes corresponding image recognition and processing processes, thereby completing automatic determination of the low contrast value.
The image acquisition module may be a built-in image acquisition module integrated in the flat panel detector 20, or may be an external image acquisition module connected to the outside of the flat panel detector 20, which is not limited in the present invention.
The electronic equipment has a program execution function, and a corresponding image recognition algorithm program is preset in the electronic equipment, so that the automatic determination of the low contrast value is realized.
The following embodiments will describe in detail the specific method processes of image recognition and processing.
Embodiment of the identification method
As shown in fig. 3, the present embodiment provides an automatic low-contrast resolution recognition method for a flat panel detector, which is implemented in the electronic device in the foregoing. Specifically, the automatic identification method comprises the following steps:
s100: and acquiring an original gray image of the image containing the test card generated by the flat panel detector.
As described in the previous embodiments, the raw grayscale image is generated by a flat panel detector by sensing the X-rays produced by the X-ray tube, which contains an image of the test card and a background image. The test card image includes an inner circle, an outer circle and a circular through hole pattern.
S200: and extracting the test card image with the background removed from the original gray level image.
Referring to fig. 4, optionally, the test card image with the background removed is extracted from the original gray image as follows.
S201, performing inversion processing on the original gray level image.
Inverting the image is to invert the gray level of the original image, i.e., simply to turn black to white and turn white to black. Assuming that the image whose gray scale range is (0, L-1) is negated, that is, (0, L-1) is transformed to (L-1, 0) by the transformation, the transformation formula is as follows: t-L-1-s. Image inversion is particularly useful for enhancing white or gray details embedded in dark areas of an image.
For example, the maximum gray value of the original gray image is 65535. The gray value of each pixel point of the gray image after the inversion processing is equal to 65535 minus the original gray value.
S202, calculating a segmentation gray threshold of the inverted original gray image by adopting a maximum inter-class variance method.
The maximum inter-class variance method is a self-adaptive threshold determination method, also called Otsu method, OTSU for short. Which divides the image into two parts, an object and a background according to the gray level characteristics of the image.
The algorithm idea of the maximum inter-class variance method is as follows: the larger the inter-class variance between the object and the background is, the larger the difference between two parts constituting the image is, and the smaller the difference between the two parts is caused when part of the object is mistaken for the background or part of the background is mistaken for the object. Thus, a segmentation that maximizes the inter-class variance means that the probability of false positives is minimized. For image I (x, y), the segmentation threshold of the target and background is denoted as T, and the proportion of the number of pixels belonging to the target to the whole image is denoted as omega0Average gray level mu of0(ii) a The proportion of the number of background pixels to the whole image is omega1Average gray of μ1. The total mean gray level of the image is denoted as μ and the inter-class variance is denoted as g.
And obtaining a threshold T which enables the inter-class variance to be maximum by adopting a traversal method, namely the obtained segmentation gray threshold.
And S203, carrying out binarization processing on the inverted original gray level image based on the segmentation gray level threshold value to obtain a binary gray level image.
The binarization processing of the image is to adjust the gray value of a point on the image to 0 or 65535, that is, the whole image shows obvious black and white effect. That is, 65536 brightness levels of gray scale image are selected by proper threshold value to obtain binary image which can still reflect the whole and local features of the image.
In this embodiment, the division gray level threshold value is used as the threshold value for the binarization process. The gray value of the pixel point with the gray value smaller than the segmentation gray threshold is adjusted to be 0, and the gray value of the pixel point with the gray value larger than the segmentation gray threshold is adjusted to be 65535.
And S204, extracting the binary gray image of the test card from the binary gray image by adopting a connected domain searching method.
An image processing method for extracting a target region having a closed contour from a binary gray image by connected component search. In the invention, the maximum connected domain in the binary gray level image is an imaging area corresponding to the test card.
Therefore, the connected domain with the largest area extracted from the inverted binary gray image by adopting the connected domain search is naturally the binary gray image of the test card.
S300: and acquiring the circle center position of the test card.
Optionally, the circle center position of the test card is determined by traversing the binary gray level image of the test card.
S400: and identifying the circular through hole from the image of the test card and acquiring the circle center position of the circular through hole.
Referring to fig. 5, alternatively, the circular through holes are identified from the test card image as follows.
S401, performing negation processing on the extracted binary gray level image of the test card.
S402, identifying a circular through hole from the inverted binary gray level image of the test card by adopting a connected domain searching method.
As described in the previous embodiments, optionally, the diameter of each circular counter bore is 1cm, and the diameter of each circular through hole is 2 mm. Therefore, the smallest connected domain existing in the binary gray scale image of the test card is the imaging area of the circular through hole. Therefore, the smallest connected domain obtained by searching the connected domains is the circular through hole.
After the area image corresponding to the circular through hole is identified, the circle center position of the circular through hole can be determined by traversing the image area.
S500: and calculating the circle center positions of the circular counter bores on the inner ring and the outer ring based on the circle center position of the test card and the circle center position of the circular through hole.
For the prepared test card, the relative geometric position relationship between the circle centers of the circular counter bores on the inner ring and the outer ring and the circle centers of the test card and the circular through hole is determined. Therefore, it is easy to understand that if the circle center position of the test card and the circle center position of the circular through hole are obtained, the circle center positions of the circular counter bores on the inner ring and the outer ring can be easily calculated.
For example, optionally, a central angle between the center of the circular through hole and the center of each circular counter bore is calculated according to the geometric position relationship between the center of the test card and the center of the circular through hole and the distribution rule of each circular counter bore on the inner ring and the outer ring; and then acquiring the circle center of each circular counter bore based on the central angle and the distribution rule of each circular counter bore.
S600: and positioning each circular counter bore from the test card image based on the circle center position of each circular counter bore and the diameter of each circular counter bore.
S700: and calculating the average gray value of the area where the circle center of the test card is located and the average gray value of the area where each circular counter bore is located on the test card in the original gray image based on the circle center position of the test card and the positions of each circular counter bore.
The positioning of the circle center of the test card and the circular counter bores on the test card is realized by implementing the steps S200 to S600. Namely, the position of the circle center of the test card and the position of each circular counter bore are positioned from the original gray level image.
And calculating the average gray value of a plurality of pixels in the area where the circle center is located based on the circle center position of the test card. For example, a circle with a diameter of 8mm may be drawn with the center of the test card as the center, and then the gray value of each pixel located in the drawn circle is obtained and averaged, that is, the average gray value of the area where the center of the test card is located is obtained.
And averaging after the gray value of each pixel of the region where each circular counter bore is located on the test card is obtained, namely the average gray value of each circular counter bore is obtained.
S800: and calculating the low contrast value of the area where each circular counter bore is located relative to the area where the circle center is located based on the average gray value of the area where the circle center of the test card is located and the average gray value of the area where each circular counter bore is located.
And after the low contrast value of the area where each circular counter bore is located relative to the area where the circle center is located is obtained, the resolution of the flat panel detector can be determined.
Electronic device embodiment
Fig. 6 is a schematic structural diagram of an electronic device 40 provided in this embodiment, and as shown in fig. 6, the electronic device 40 includes a processor 41 and a memory 43, and the processor 41 is connected to the memory 43, for example, through a bus 42.
The processor 41 may be a CPU, general purpose processor, DSP, ASIC, FPGA or other programmable device, transistor logic device, hardware component, or any combination thereof. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. Processor 41 may also be a combination of computing functions, e.g., comprising one or more microprocessors, a combination of a DSP and a microprocessor, or the like.
The memory 43 may be, but is not limited to, a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, an EEPROM, a CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
The memory 43 is used for storing application program codes of the present application scheme, and is controlled to be executed by the processor 21. The processor 41 is configured to execute the application program code stored in the memory 43 to implement the automatic low-contrast resolution recognition method of the flat panel detector in the above embodiment of the present invention.
Finally, an embodiment of the present invention provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the method for automatically identifying a low contrast resolution of a flat panel detector in the above-mentioned embodiments of the present invention is implemented.
The invention has been described above with a certain degree of particularity. It will be understood by those of ordinary skill in the art that the description of the embodiments is merely exemplary and that all changes that come within the true spirit and scope of the invention are desired to be protected. The scope of the invention is defined by the appended claims rather than by the foregoing description of the embodiments.
Claims (10)
1. A method for identifying low contrast resolution of a flat panel detector, performed in an electronic device, the automatic identification method comprising:
acquiring an original gray image of an image containing a test card generated by a flat panel detector, wherein: the test card is a circular aluminum plate, the surface of the test card is provided with an inner ring formed by a plurality of circular counter bores and an outer ring formed by a plurality of circular counter bores, the inner ring and the outer ring are concentric with the test card, the diameter of each circular counter bore is the same, the depth of each circular counter bore is different, the test card is also provided with a circular through hole penetrating through the test card, the diameter of the circular through hole is different from that of the circular counter bores, and the circle center of the circular through hole is staggered with that of the test card;
extracting a test card image with the background removed from the original gray level image;
acquiring the circle center position of the test card;
identifying the circular through hole from the test card image and acquiring the circle center position of the circular through hole;
calculating the circle center positions of the circular counter bores on the inner ring and the outer ring based on the circle center position of the test card and the circle center position of the circular through hole;
positioning each circular counter bore from the test card image based on the circle center position of each circular counter bore and the diameter of the circular counter bore;
calculating the average gray value of the area where the circle center of the test card is located and the average gray value of the area where the circular counter bores are located in the original gray image based on the circle center position of the test card and the positions of the circular counter bores;
and calculating the low contrast value of the area of each circular counter bore relative to the area of the circle center of the test card based on the average gray value of the area of the circle center of the test card and the average gray value of the area of each circular counter bore.
2. The identification method of claim 1, wherein the extracting the background-removed test card image from the original grayscale image comprises:
performing negation processing on the obtained original gray level image;
calculating a segmentation gray threshold of the inverted original gray image by adopting a maximum inter-class variance method;
performing binarization processing on the inverted original gray level image based on the segmentation gray level threshold value to obtain a binary gray level image;
and extracting the binary gray level image of the test card from the binary gray level image by adopting a connected domain search method.
3. The identification method of claim 2, wherein said identifying the circular via from the test card image comprises:
performing negation processing on the extracted binary gray level image of the test card;
and identifying the circular through hole from the inverted binary gray level image of the test card by adopting a connected domain searching method.
4. The identification method according to claim 1, wherein the calculating the circle center position of each of the circular counter bores on the inner ring and the outer ring based on the circle center position of the test card and the circle center position of the circular through hole comprises:
calculating the central angle between the circle center of the circular through hole and the circle center of each circular counter bore according to the geometric position relation between the circle center of the test card and the circle centers of the circular through holes and the distribution rule of each circular counter bore on the inner ring and the outer ring;
and acquiring the circle center of each circular counter bore based on the central angle and the distribution rule of each circular counter bore.
5. The identification method according to claim 1, wherein the test card 1 is a circular aluminum plate with a thickness of 20mm, the inner ring is composed of 9 circular counter bores arranged at equal intervals, and the outer ring is composed of 10 circular counter bores arranged at equal intervals.
6. The identification method as claimed in claim 5, wherein the hole depths of the 9 circular counter bores on the inner ring are sequentially decreased in the clockwise direction, the hole depths of the 10 circular counter bores on the outer ring are sequentially decreased in the clockwise direction, and the maximum hole depth of the circular counter bores on the inner ring is smaller than the minimum hole depth of the circular counter bores on the outer ring.
7. The identification method of claim 1, wherein:
the circular through holes are located in the inner ring, the diameter of each circular counter bore is 1cm, and the diameter of each circular through hole is 2 mm.
8. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the identification method of any one of claims 1 to 7 when executing the program.
9. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a computer program which, when being executed by a processor, carries out the identification method of any one of claims 1 to 7.
10. An automatic low contrast resolution identification system for a flat panel detector, comprising:
an imaging module comprising an X-ray tube, a flat panel detector, and a test card disposed on the flat panel detector, the test card employing the test card of claim 1, the X-ray tube for generating X-rays, the flat panel detector detecting X-rays to generate an original grayscale image including an image of the test card;
the image acquisition module is used for transmitting the original gray level image to electronic equipment;
electronic equipment for performing the identification method of any one of claims 1 to 7.
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| CN202011024785.8A CN112102355B (en) | 2020-09-25 | Low-contrast resolution identification method, device, storage medium and system for flat panel detector |
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| CN202011024785.8A CN112102355B (en) | 2020-09-25 | Low-contrast resolution identification method, device, storage medium and system for flat panel detector |
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