CN111192217A - Digital X-ray image repairing method and system - Google Patents
Digital X-ray image repairing method and system Download PDFInfo
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- CN111192217A CN111192217A CN201911401896.3A CN201911401896A CN111192217A CN 111192217 A CN111192217 A CN 111192217A CN 201911401896 A CN201911401896 A CN 201911401896A CN 111192217 A CN111192217 A CN 111192217A
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- 238000012935 Averaging Methods 0.000 claims description 6
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/77—Retouching; Inpainting; Scratch removal
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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- G06T2207/10116—X-ray image
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Abstract
The embodiment of the invention provides a digital X-ray image repairing method and a system, wherein the digital X-ray image repairing method comprises the following steps: respectively solving difference absolute values of normal pixel points around a pixel point in the medical image in given T directions; setting a direction weight coefficient according to the sorting of the absolute difference values; and after adopting the reference direction weight coefficient of the surrounding normal pixel points, repairing the bad pixel points to obtain updated pixel points. By adding the direction weight coefficient to carry out pixel restoration, the directionality of the edge information can be fully considered, the weight coefficient of the gray level in the direction is determined according to the direction characteristic, the detail information of the image can be restored to the maximum extent, the occurrence of the restoration trace is avoided, and the image quality is effectively improved.
Description
Technical Field
The invention relates to the technical field of medical imaging, in particular to a digital X-ray image repairing method and a digital X-ray image repairing system.
Background
During the process of acquiring images, a detector configured in the digital radiography system sometimes has fixed-position abnormally bright or abnormally dark points, which are called as bad pixel points. The presence of bad pixel points can affect the accuracy of the diagnosis.
Due to the factors of the processing technology level of the detector, the bad pixel points are independently and discretely distributed, and sometimes a plurality of bad pixel points are connected together to form a bad pixel cluster. The detector manufacturer will repair the bad pixel, and the existing repair method is basically to repair the bad pixel by interpolation according to the gray value of the normal pixel in the neighborhood of the bad pixel.
The existing repairing method can restore the details of the image to a certain extent, but the details of the edge class can cause blur, obvious repairing marks can appear in the image, the image quality is reduced, and the film reading and diagnosis of doctors are influenced.
Disclosure of Invention
In view of the above problems, embodiments of the present invention are proposed to provide a digital X-ray image inpainting method and a corresponding digital X-ray image inpainting system that overcome or at least partially solve the above problems.
In order to solve the above problem, an embodiment of the present invention discloses a method for repairing a digital X-ray image, including:
respectively solving difference absolute values of normal pixel points around a pixel point in the medical image in given T directions;
setting a direction weight coefficient according to the sorting of the absolute difference values;
and after adopting the reference direction weight coefficient of the surrounding normal pixel points, repairing the bad pixel points to obtain updated pixel points.
Further, after the reference direction weight coefficients of the surrounding normal pixel points are adopted, the step of repairing the bad pixel points to obtain updated pixel points further includes:
and taking the updated pixel point as a normal pixel point to participate in the repair calculation of the next adjacent bad pixel point.
Further, the step of respectively obtaining the difference absolute values of normal pixel points around a pixel point in the medical image in the given T directions includes:
and respectively solving difference absolute values of normal pixel points around a pixel point in the medical image in the horizontal direction, the vertical direction, the 45-degree direction and the 135-degree direction.
Further, the step of setting the direction weight coefficients in the order of the absolute difference values includes:
judging whether the absolute difference values have the same value or not;
and if so, averaging the direction weight coefficients of the difference absolute values of the same numerical value.
The embodiment of the invention discloses a digital X-ray image repairing system, which comprises:
the difference absolute value calculation module is used for respectively obtaining the difference absolute values of normal pixel points around one pixel point in the medical image in the given T directions;
the weight arrangement module is used for setting a direction weight coefficient according to the sorting of the absolute difference values;
and the bad pixel point repairing module is used for repairing the bad pixel points to obtain updated pixel points after adopting the reference direction weight coefficients of the surrounding normal pixel points.
Further, the bad pixel repairing module includes:
and the bad pixel point repairing unit is used for taking the updated pixel point as a normal pixel point to participate in the repairing calculation of the next adjacent bad pixel point.
Further, the difference absolute value calculation module includes:
and the difference absolute value calculating unit is used for respectively calculating the difference absolute values of normal pixel points around one pixel point in the medical image in the horizontal direction, the vertical direction, the 45-degree direction and the 135-degree direction.
Further, the difference absolute value calculation module includes:
the proximity judgment unit is used for judging whether the absolute difference values have the same value or not;
and if so, averaging the direction weight coefficients of the difference absolute values of the same numerical value.
An embodiment of the invention discloses an electronic device, which comprises a processor, a memory and a computer program stored on the memory and capable of running on the processor, wherein the computer program, when executed by the processor, implements the steps of the method for digital X-ray image patching.
An embodiment of the invention discloses a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the steps of the method of digital X-ray image patching as described above.
The embodiment of the invention has the following advantages: by adding the direction weight coefficient to carry out pixel restoration, the directionality of the edge information can be fully considered, the weight coefficient of the gray level in the direction is determined according to the direction characteristic, the detail information of the image can be restored to the maximum extent, the occurrence of the restoration trace is avoided, and the image quality is effectively improved.
Drawings
FIG. 1 is a flow chart of the steps of an embodiment of a digital X-ray image inpainting method of the present invention;
FIG. 2 is a pixel point diagram before inpainting in an embodiment of a digital X-ray image inpainting method of the present invention;
FIG. 3 is a pixel point map after inpainting in an embodiment of a digital X-ray image inpainting method of the present invention;
FIG. 4 is a flow chart of steps of an embodiment of a digital X-ray image inpainting method of the present invention;
FIG. 5 is a block diagram of a digital X-ray image patching system embodiment of the present invention;
FIG. 6 is a block diagram of a digital X-ray image patching system of 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.
One of the core ideas of the embodiment of the invention is to provide a digital X-ray image repairing method, which comprises the following steps: respectively solving difference absolute values of normal pixel points around a pixel point in the medical image in given T directions; setting a direction weight coefficient according to the sorting of the absolute difference values; and after adopting the reference direction weight coefficient of the surrounding normal pixel points, repairing the bad pixel points to obtain updated pixel points. By adding the direction weight coefficient to carry out pixel restoration, the directionality of the edge information can be fully considered, the weight coefficient of the gray level in the direction is determined according to the direction characteristic, the detail information of the image can be restored to the maximum extent, the occurrence of the restoration trace is avoided, and the image quality is effectively improved.
Referring to fig. 1, a flow chart of steps of an embodiment of the method for repairing a digital X-ray image according to the present invention is shown, which may specifically include the following steps:
s100, respectively obtaining difference absolute values of normal pixel points around a pixel point in the medical image in given T directions;
s200, setting a direction weight coefficient according to the sorting of the absolute difference values;
s300, after the reference direction weight coefficients of the surrounding normal pixel points are adopted, the bad pixel points are repaired to obtain updated pixel points.
As described with reference to the step S100, the difference absolute values of the normal pixel points around one pixel point in the medical image in the given T directions are respectively obtained. In an embodiment, referring to fig. 2, the image includes 5 bad pixels, which are P (1,1), P (1,2), P (2,1), P (2,2) and P (4,4), respectively, where P (1,1), P (1,2), P (2,1) and P (2,2) form a bad pixel cluster. Firstly, repairing a bad pixel point P (1, 1). Calculating difference absolute values of normal pixel points around the P (1,1) in given T directions, specifically giving four directions, specifically calculating absolute values of gradients of the P (1,1) in the four directions. The four directions are specifically a horizontal direction, a vertical direction, a 45 ° direction, and a 135 ° direction. And during calculation, the gray value of the normal pixel point closest to the bad pixel point in the specified direction is obtained.
Absolute of gradient in horizontal directionFor value D0＝|P(1,3)-P(1,0)|＝1；
Absolute value of vertical gradient D90＝|P(3,1)-P(0,1)|＝2；
Absolute value D of 45 DEG directional gradient45＝|P(2,0)-P(0,2)|＝5；
Absolute value D of 135 DEG directional gradient135＝|P(3,3)-P(0,0)|＝3；
As described with reference to step S200 above, the direction weight coefficients are set in the order of the magnitude of the absolute difference values. In the present embodiment, the absolute values of the gradients in the above four directions are sorted.
The order of the absolute values of the gradients in the four directions after sorting is as follows:
D0＜D90＜D135＜D45
according to the sequence of the absolute values of the gradients, the weight coefficients of four directions when repairing P (1,1) are determined:
V0＝0.4
V90＝0.3
V135＝0.2
V45＝0.1
referring to the step S300, after the reference direction weight coefficients of the surrounding normal pixels are adopted, the bad pixels are repaired to obtain updated pixels.
Repairing the bad pixel P (1,1)
Gray values in the horizontal direction that contribute when repairing P (1, 1):
P0＝V0*(P(1,0)+A1*(P(1,3)-P(1,0)))；
wherein
D11Denotes the distance from P (1,0) to P (1,1), D10Represents the distance from P (1,0) to P (1, 3).
Gray values in the vertical direction that contribute when repairing P (1, 1):
P90＝V90*(P(0,1)+A2*(P(3,1)-P(0,1)))；
wherein
D21Denotes the distance from P (0,1) to P (1,1), D20Represents the distance from P (0,1) to P (3, 1).
Gray value contributing in repairing P (1,1) in the 45 ° direction:
P45＝V45*(P(2,0)+A3*(P(0,2)-P(2,0)))；
wherein
D31Denotes the distance from P (2,0) to P (1,1), D30Represents the distance from P (2,0) to P (0, 2).
Gray values in the 135 ° direction that contribute when repairing P (1, 1):
P135＝V135*(P(0,0)+A4*(P(3,3)-P(0,0)))；
wherein
D41Denotes the distance from P (0,0) to P (1,1), D40Represents the distance from P (0,0) to P (3, 3).
Calculating the gray value of the repaired pixel point P (1,1) by using the following formula:
P(1,1)＝P0+P90+P45+P135
referring to fig. 2-4, in this embodiment, the step S300 of repairing the bad pixel after the reference direction weight coefficient of the surrounding normal pixel is adopted to obtain the updated pixel further includes:
and S310, taking the updated pixel point as a normal pixel point to participate in the repair calculation of the next adjacent bad pixel point.
Referring to the above steps, the repaired pixel points are used as normal pixel points to participate in repairing other bad pixel points, and the steps S100 to S300 are executed in a circulating manner until all the bad pixel points in the image are completely repaired. Specifically, the repaired pixel point P (1,1) may participate in repairing P (1,2), P (2,1), P (2,2), and P (4, 4).
In this embodiment, the step S100 of respectively obtaining the difference absolute values of the normal pixel points around one pixel point in the medical image in the given T directions includes:
and respectively solving difference absolute values of normal pixel points around a pixel point in the medical image in the horizontal direction, the vertical direction, the 45-degree direction and the 135-degree direction.
In this embodiment, the step S200 of setting the direction weight coefficients according to the sorting order of the absolute difference values includes:
judging whether the absolute difference values have the same value or not;
and if so, averaging the direction weight coefficients of the difference absolute values of the same numerical value.
As described with reference to the above steps, when two or more absolute values of the gradients in the four directions are the same, the corresponding weight coefficients are averaged. When the bad pixel point appears at the edge of the image, the average value of the gray values of the normal pixel points in the neighborhood of the bad pixel point is utilized to repair the bad pixel point.
It should be noted that, for simplicity of description, the method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present invention is not limited by the illustrated order of acts, as some steps may occur in other orders or concurrently in accordance with the embodiments of the present invention. Further, those skilled in the art will appreciate that the embodiments described in the specification are presently preferred and that no particular act is required to implement the invention.
Referring to fig. 5, a block diagram of a digital X-ray image inpainting system according to an embodiment of the present invention is shown, which may specifically include the following modules:
a difference absolute value calculation module 100, configured to respectively obtain difference absolute values of normal pixel points around a pixel point in a medical image in given T directions;
a weight arrangement module 200, configured to set directional weight coefficients according to the sorting of the absolute difference values;
and the bad pixel point repairing module 300 is configured to repair the bad pixel points to obtain updated pixel points after the reference direction weight coefficients of the surrounding normal pixel points are adopted.
Referring to fig. 6, in the present embodiment, the bad pixel repairing module 300 includes:
and a bad pixel point repairing unit 310, configured to use the updated pixel point as a normal pixel point to participate in repairing calculation of a next adjacent bad pixel point.
In this embodiment, the absolute difference value calculating module 100 includes:
and the difference absolute value calculating unit is used for respectively calculating the difference absolute values of normal pixel points around one pixel point in the medical image in the horizontal direction, the vertical direction, the 45-degree direction and the 135-degree direction.
In this embodiment, the absolute difference value calculating module 100 includes:
the proximity judgment unit is used for judging whether the absolute difference values have the same value or not;
and if so, averaging the direction weight coefficients of the difference absolute values of the same numerical value.
For the system embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, refer to the partial description of the method embodiment.
An embodiment of the invention discloses an electronic device, which comprises a processor, a memory and a computer program stored on the memory and capable of running on the processor, wherein the computer program, when executed by the processor, implements the steps of the method for digital X-ray image patching.
An embodiment of the invention discloses a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the steps of the method of digital X-ray image patching as described above.
The embodiments in the present specification are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
Embodiments of the present invention are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing terminal to cause a series of operational steps to be performed on the computer or other programmable terminal to produce a computer implemented process such that the instructions which execute on the computer or other programmable terminal provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications of these embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the embodiments of the invention.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or terminal that comprises the element.
The above detailed description of the digital X-ray image inpainting method and the digital X-ray image inpainting system according to the present invention is provided, and the principles and embodiments of the present invention are explained herein by using specific examples, which are only used to help understanding the method and the core ideas of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (10)
1. A digital X-ray image inpainting method, comprising:
respectively solving difference absolute values of normal pixel points around a pixel point in the medical image in given T directions;
setting a direction weight coefficient according to the sorting of the absolute difference values;
and after adopting the reference direction weight coefficient of the surrounding normal pixel points, repairing the bad pixel points to obtain updated pixel points.
2. The method according to claim 1, wherein the step of repairing the bad pixel after the reference direction weight coefficients of the surrounding normal pixels are adopted to obtain the updated pixel further comprises:
and taking the updated pixel point as a normal pixel point to participate in the repair calculation of the next adjacent bad pixel point.
3. The method according to claim 1, wherein the step of respectively obtaining the difference absolute value of normal pixel points around a pixel point in the medical image in the given T directions comprises:
and respectively solving difference absolute values of normal pixel points around a pixel point in the medical image in the horizontal direction, the vertical direction, the 45-degree direction and the 135-degree direction.
4. The method of claim 1, wherein the step of setting the directional weight coefficients in order of magnitude of absolute difference comprises:
judging whether the absolute difference values have the same value or not;
and if so, averaging the direction weight coefficients of the difference absolute values of the same numerical value.
5. A digital X-ray image inpainting system, comprising:
the difference absolute value calculation module is used for respectively obtaining the difference absolute values of normal pixel points around one pixel point in the medical image in the given T directions;
the weight arrangement module is used for setting a direction weight coefficient according to the sorting of the absolute difference values;
and the bad pixel point repairing module is used for repairing the bad pixel points to obtain updated pixel points after adopting the reference direction weight coefficients of the surrounding normal pixel points.
6. The system of claim 5, wherein the bad pixel patch module comprises:
and the bad pixel point repairing unit is used for taking the updated pixel point as a normal pixel point to participate in the repairing calculation of the next adjacent bad pixel point.
7. The system of claim 5, wherein the absolute difference value calculation module comprises:
and the difference absolute value calculating unit is used for respectively calculating the difference absolute values of normal pixel points around one pixel point in the medical image in the horizontal direction, the vertical direction, the 45-degree direction and the 135-degree direction.
8. The system of claim 5, wherein the absolute difference value calculation module comprises:
the proximity judgment unit is used for judging whether the absolute difference values have the same value or not;
and if so, averaging the direction weight coefficients of the difference absolute values of the same numerical value.
9. Electronic device, characterized in that it comprises a processor, a memory and a computer program stored on the memory and capable of running on the processor, which computer program, when being executed by the processor, carries out the steps of the method of digital X-ray image patching according to any of claims 1 to 4.
10. Computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by a processor, carries out the steps of the method of digital X-ray image patching according to any one of claims 1 to 4.
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Application publication date: 20200522 |