Method and system for calculating shape of light intensity distribution of focus of CT bulb tube

Abstract

The invention discloses a CT bulb tube focus light intensity distribution shape calculation method and system, and relates to the technical field of medical image.The method comprises the steps that a flat die body is scanned, and projection data corresponding to the flat die body are obtained; calculating position data of the flat die body based on the projection data, and calculating size data of the flat die body based on the position data; performing simulation projection on the flat die body based on the projection data, the position data and the size data to obtain a projection result of the flat die body; constructing a focus shape model, inputting a projection result into the focus shape model, and calculating a parameter optimal value of a focus light intensity distribution model by taking projection data as a target based on least square iteration; and the shape of the bulb tube focus light intensity distribution is calculated based on the parameter optimal value, so that the problem that the shape of the CT bulb tube focus light intensity distribution cannot be accurately calculated in the prior art can be solved.

Description

Technical Field

[0001] The present invention relates to the field of medical imaging technology, and in particular to a shape calculation method and system for CT tube focal point light intensity distribution. Background Art

[0002] In CT imaging systems, the intensity distribution of the X-ray source has a significant impact on image quality. Ideally, the X-ray source is assumed to be a point source, with uniform and concentrated intensity distribution. This allows the imaging system to produce clear, distortion-free projection images. However, in practice, the focal point of an X-ray source has a specific size and complex intensity distribution, far from being an ideal point source. This non-ideal intensity distribution can lead to blurring and artifacts during imaging, compromising diagnostic accuracy.

[0003] Therefore, there is an urgent need for a method that can accurately calculate the light intensity distribution shape of the CT tube focus. Summary of the Invention

[0004] In view of this, the present invention proposes a method and system for calculating the shape of the light intensity distribution at the focus of a CT tube, which can accurately calculate the shape of the light intensity distribution at the focus of a CT tube.

[0005] To achieve the above object, the present invention provides the following technical solutions: A method for calculating the shape of the light intensity distribution at the focus of a CT tube comprises: Scanning the flat panel phantom to obtain projection data corresponding to the flat panel phantom; Calculating position data of the flat panel phantom based on the projection data, and calculating size data of the flat panel phantom based on the position data; Performing simulated projection on the flat panel phantom based on the projection data, position data, and size data to obtain a projection result of the flat panel phantom; Inputting the projection result into the pre-constructed focus shape model, and calculating the optimal parameter values ​​of the focus light intensity distribution model based on the least squares method iteration with the projection data as the target; The shape of the light intensity distribution at the focus of the tube is calculated based on the optimal values ​​of the parameters.

[0006] On the basis of the above technical solution, the present invention can also be improved as follows: Optionally, scanning the flat panel phantom to obtain projection data corresponding to the flat panel phantom includes: Scanning the flat panel phantom to obtain intensity data corresponding to the flat panel phantom; performing a first preprocessing on the intensity data to obtain first preprocessed intensity data; performing a second preprocessing on the first preprocessed intensity data to obtain second preprocessed intensity data; Projection data corresponding to the flat panel phantom is obtained based on the second preprocessed intensity data.

[0007] Optionally, calculating the position data of the flat panel phantom based on the projection data includes: The left end position coordinates and the right end position coordinates of the flat panel phantom are calculated based on the least squares method, and the position data of the flat panel phantom is obtained based on the left end position coordinates and the right end position coordinates.

[0008] Optionally, calculating the size data of the flat phantom based on the position data includes: Calculate the size data of the flat phantom using formula (1); Formula (1); Where, is the size data of the flat phantom, is the horizontal coordinate value of the left end position of the flat phantom, is the vertical coordinate value of the left end position of the flat phantom, is the horizontal coordinate value of the right end position of the flat phantom, is the ordinate value of the right end position of the flat phantom.

[0009] Optionally, performing simulated projection on the flat panel phantom based on the projection data, position data, and size data to obtain a projection result of the flat panel phantom includes: The projection result is calculated by formula (2); Formula (2); Where, is the projection result, c is the number of the detector pixel unit, is the exposure angle, is the number of virtual foci on one side, and m is the number of virtual foci is the position coordinate of the virtual focus.

[0010] Optionally, the calculating the shape of the light intensity distribution at the focus of the tube based on the optimal parameter value includes: The shape of the light intensity distribution at the focus of the tube is calculated by formula (3); Formula (3); Where, is the shape of the light intensity distribution at the focus of the tube, is the total number of Gaussian functions, is the sequence number of the Gaussian function in the focal shape model, is the amplitude of the nth Gaussian function, is the offset position relative to the focal center, is the symmetric center position of the nth Gaussian function, is the standard deviation of the nth Gaussian function.

[0011] Optionally, the optimal value of the parameter is 、 and .

[0012] A shape calculation system for CT tube focus light intensity distribution, comprising: A projection data acquisition module, configured to scan the flat panel phantom and obtain projection data corresponding to the flat panel phantom; a position calculation module, configured to calculate position data of the flat panel phantom based on the projection data; a size calculation module, configured to calculate size data of the flat phantom based on the position data; a projection result acquisition module, configured to simulate projection of the flat panel phantom based on the projection data, position data, and size data to obtain a projection result of the flat panel phantom; a parameter calculation module, configured to input the projection result into the pre-constructed focus shape model, and calculate optimal parameter values ​​of the focus light intensity distribution model based on the least squares method iteration with the projection data as the target; The shape calculation module is used to calculate the shape of the light intensity distribution at the focus of the tube based on the optimal value of the parameter.

[0013] An electronic device comprises a memory, a processor and a computer program stored in the memory and running on the processor, wherein the steps of the method are implemented when the processor executes the computer program.

[0014] A non-transitory computer-readable storage medium stores a computer program, which implements the steps of the method when executed by a processor.

[0015] The present invention has the following advantages: The proposed method for calculating the shape of the CT tube's focal light intensity distribution obtains projection data by scanning a flat-panel phantom. Simulating projections based on position and size data constructs a focal shape model and iteratively optimizes parameters using the least-squares method. This method achieves precise calculation of the CT tube's focal light intensity distribution shape. Compared to traditional methods, this method effectively eliminates the effects of scanning system errors and phantom positioning deviations, improving the accuracy of focal shape calculation. This method provides a reliable basis for tube performance evaluation, image quality optimization, and equipment maintenance, reduces image artifacts caused by focal shape errors, and enhances CT system imaging stability and diagnostic accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] For purposes of illustration and not limitation, the present invention will now be described with reference to embodiments thereof and the accompanying drawings, in which: Figure 1 Schematic diagram of a flow chart of a method for calculating the shape of the light intensity distribution at the focus of a CT tube in an embodiment of the present invention; Figure 2 Schematic diagram of the main components of the shape calculation system for the CT tube focal point light intensity distribution in an embodiment of the present invention; Figure 3 This is a schematic diagram of the physical structure of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0017] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work should fall within the scope of protection of the present invention.

[0018] It should be noted that the terms "first," "second," and the like in the description of the present invention and the accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a particular order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate for the embodiments of the present invention described herein. In addition, the terms "including," "having," and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to these processes, methods, products, or apparatuses.

[0019] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features thereof can be combined with each other. The embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0020] Figure 1 FIG. 1 is a flow chart of a method for calculating the shape of the CT tube focus light intensity distribution in an embodiment of the present invention. Figure 1 As shown, the method for calculating the shape of the CT tube focus light intensity distribution provided by the embodiment of the present invention includes the following steps S101 to S105.

[0021] S101 , scanning a flat panel phantom to obtain projection data corresponding to the flat panel phantom.

[0022] Scan the flat phantom made of high attenuation material using the same preset conditions, scan the flat phantom, and obtain the intensity data corresponding to the flat phantom During scanning, place the flat-panel phantom as far away from the center of rotation as possible to ensure that the flat-panel phantom projection covers all channels. The flat-panel phantom can be made of high-attenuation materials such as tungsten and molybdenum.

[0023] Perform a first preprocessing on the intensity data to obtain first preprocessed intensity data The preprocessing is mainly to interpolate the bad channel data and perform air correction and correction for the difference in exposure at each angle. The first preprocessing intensity data If it is less than a certain threshold, it is set to 0.

[0024] The first preprocessed intensity data is preprocessed for the second time to obtain the second preprocessed intensity data. ; ; Where c is the detector pixel unit number, v is the vth exposure angle, and T is the threshold value for distinguishing the boundary between air and the flat phantom.

[0025] Projection data corresponding to the flat panel phantom is obtained based on the second preprocessed intensity data.

[0026] S102 , calculating position data of the flat panel phantom based on the projection data, and calculating size data of the flat panel phantom based on the position data.

[0027] The left end position coordinates and the right end position coordinates of the flat panel phantom are calculated based on the least squares method, and the position data of the flat panel phantom is obtained based on the left end position coordinates and the right end position coordinates.

[0028] First, assume that the left end position coordinates and the right end position coordinates of the flat phantom are and ; Then, the coordinates of the tube focal center at each exposure angle According to the rotation angle, the angle between the two vectors formed by the focus position and the left and right ends of the flat phantom at each exposure angle is known; The data at each exposure angle constitutes the coordinates of the flat panel phantom position and A series of equations are used to calculate the position coordinates of the left and right ends of the flat phantom using the least squares method. and and the dimensions of the flat panel phantom.

[0029] Calculate the size data of the flat phantom using formula (1); Formula (1); Where, is the size data of the flat phantom, is the horizontal coordinate value of the left end position of the flat phantom, is the vertical coordinate value of the left end position of the flat phantom, is the horizontal coordinate value of the right end position of the flat phantom, is the ordinate value of the right end position of the flat phantom.

[0030] S103 , performing simulated projection on the flat panel phantom based on the projection data, the position data, and the size data to obtain a projection result of the flat panel phantom.

[0031] The constructed tube focus light intensity distribution model can calculate the focus light intensity at any point on the focus plane. There are 2M+1 virtual focal points in total, that is, the light intensity of 2M+1 virtual focal points can be obtained ; in, .

[0032] The projection of the simulated flat phantom under the focal light intensity distribution model constructed using a Gaussian function is first calculated. The line connecting the position of the mth virtual focus and the cth detector pixel at each projection angle v is checked to see whether it intersects with the flat phantom. If so, it means that the ray passes through the flat phantom, that is, the light intensity of the focus is attenuated by the high-density flat phantom and does not contribute to the detector pixel. Otherwise, if it does not intersect, it means that the light intensity of the virtual focus shines on the detector and the detector receives the light intensity of this virtual focus.

[0033] ; The projection result is calculated by formula (2); Formula (2); Where, is the projection result, c is the number of the detector pixel unit, is the exposure angle, is the number of virtual foci on one side, and m is the number of virtual foci is the position coordinate of the virtual focus.

[0034] S104: Input the projection result into a pre-built focus shape model, and calculate the optimal parameter values ​​of the focus light intensity distribution model based on the least squares method iteration with the projection data as the target.

[0035] The optimal value of the parameter is 、 and .

[0036] S105, calculating the shape of the light intensity distribution at the focus of the tube based on the optimal parameter values.

[0037] The shape of the light intensity distribution at the focus of the tube is calculated by formula (3); Formula (3); Where, is the shape of the light intensity distribution at the focus of the tube, is the total number of Gaussian functions, is the sequence number of the Gaussian function in the focal shape model, is the amplitude of the nth Gaussian function, is the offset position relative to the focal center, is the symmetric center position of the nth Gaussian function, is the standard deviation of the nth Gaussian function.

[0038] This method for calculating the shape of the focal light intensity distribution of a CT tube supports selecting some detector pixels to test the focal light intensity distribution shape model. It can detect the focal light intensity distribution shape from some detector channels and analyze the differences in focal light intensity distribution observed by different detector channels, providing a basis for more accurate correction of these differences.

[0039] Figure 2 Schematic diagram of the main components of the shape calculation system of the CT tube focus light intensity distribution in the embodiment of the present invention. Figure 2 As shown, the shape calculation system 1 for the CT tube focal light intensity distribution provided by the embodiment of the present invention includes a projection data acquisition module 10, a position calculation module 20, a size calculation module 30, a projection result acquisition module 40, a parameter calculation module 50 and a shape calculation module 60.

[0040] The projection data acquisition module 10 is used to scan the flat panel phantom to obtain projection data corresponding to the flat panel phantom; a position calculation module 20, configured to calculate position data of the flat panel phantom based on the projection data; a size calculation module 30, configured to calculate size data of the flat phantom based on the position data; a projection result acquisition module 40, configured to simulate projection of the flat panel phantom based on the projection data, position data, and size data to obtain a projection result of the flat panel phantom; A parameter calculation module 50 is configured to input the projection result into the pre-built focus shape model, and calculate optimal parameter values ​​of the focus light intensity distribution model based on the least squares method iteration with the projection data as the target; The shape calculation module 60 is used to calculate the shape of the light intensity distribution at the focus of the tube based on the optimal parameter values.

[0041] Figure 3A schematic diagram of the physical structure of an electronic device provided in an embodiment of the present invention, such as Figure 3 As shown, the electronic device 70 includes: a processor 701 (processor), a memory 702 (memory) and a bus 703; The processor 701 and the memory 702 communicate with each other via the bus 703. The processor 701 is used to call the program instructions in the memory 702 to execute the methods provided by the above-mentioned method embodiments, so as to execute the methods provided by the implementation methods of the present invention.

[0042] This embodiment provides a non-transitory computer-readable storage medium, which stores computer instructions. The computer instructions enable a computer to execute the method provided by the embodiment of the present invention.

[0043] Those skilled in the art will understand that all or part of the steps of implementing the above-mentioned method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above-mentioned method embodiment; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk, etc. Various storage media that can store program codes.

[0044] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A method for calculating the shape of the light intensity distribution at the focus of a CT tube, characterized in that: include: Scanning the flat panel phantom to obtain projection data corresponding to the flat panel phantom; Calculating position data of the flat panel phantom based on the projection data, and calculating size data of the flat panel phantom based on the position data; Performing simulated projection on the flat panel phantom based on the projection data, position data, and size data to obtain a projection result of the flat panel phantom; Inputting the projection result into the pre-constructed focus shape model, and calculating the optimal parameter values ​​of the focus light intensity distribution model based on the least squares method iteration with the projection data as the target; The shape of the light intensity distribution at the focus of the tube is calculated based on the optimal values ​​of the parameters.

2. The shape calculation method of the CT tube focus light intensity distribution according to claim 1, characterized in that: Scanning the flat panel phantom to obtain projection data corresponding to the flat panel phantom includes: Scanning the flat panel phantom to obtain intensity data corresponding to the flat panel phantom; performing a first preprocessing on the intensity data to obtain first preprocessed intensity data; performing a second preprocessing on the first preprocessed intensity data to obtain second preprocessed intensity data; Projection data corresponding to the flat panel phantom is obtained based on the second preprocessed intensity data.

3. The shape calculation method of the CT tube focus light intensity distribution according to claim 1, characterized in that: The calculating the position data of the flat panel phantom based on the projection data includes: The left end position coordinates and the right end position coordinates of the flat panel phantom are calculated based on the least squares method, and the position data of the flat panel phantom is obtained based on the left end position coordinates and the right end position coordinates.

4. The shape calculation method of the CT tube focus light intensity distribution according to claim 3, characterized in that: The calculating the size data of the flat phantom based on the position data includes: Calculate the size data of the flat phantom using formula (1); Formula (1); Where, is the size data of the flat phantom, is the horizontal coordinate value of the left end position of the flat phantom, is the vertical coordinate value of the left end position of the flat phantom, is the horizontal coordinate value of the right end position of the flat phantom, is the ordinate value of the right end position of the flat phantom.

5. The method for calculating the shape of the CT tube focus light intensity distribution according to claim 4, characterized in that: The performing simulated projection on the flat panel phantom based on the projection data, the position data, and the size data to obtain a projection result of the flat panel phantom includes: The projection result is calculated by formula (2); Formula (2); Where, is the projection result, c is the number of the detector pixel unit, is the exposure angle, is the number of virtual foci on one side, m is the number of virtual foci, is the position coordinate of the virtual focus.

6. The shape calculation method of the CT tube focus light intensity distribution according to claim 5, characterized in that: The calculating of the shape of the light intensity distribution at the focus of the tube based on the optimal parameter value comprises: The shape of the light intensity distribution at the focus of the tube is calculated by formula (3); Formula (3); Where, is the shape of the light intensity distribution at the focus of the tube, is the total number of Gaussian functions, is the sequence number of the Gaussian function in the focal shape model, is the amplitude of the nth Gaussian function, is the offset position relative to the focal center, is the symmetric center position of the nth Gaussian function, is the standard deviation of the nth Gaussian function.

7. The method for calculating the shape of the CT tube focus light intensity distribution according to claim 6, characterized in that: The optimal value of the parameter is 、 and .

8. A shape calculation system for the light intensity distribution at the focus of a CT tube, characterized in that: include: A projection data acquisition module, configured to scan the flat panel phantom and obtain projection data corresponding to the flat panel phantom; a position calculation module, configured to calculate position data of the flat panel phantom based on the projection data; a size calculation module, configured to calculate size data of the flat phantom based on the position data; a projection result acquisition module, configured to simulate projection of the flat panel phantom based on the projection data, position data, and size data to obtain a projection result of the flat panel phantom; a parameter calculation module, configured to input the projection result into the pre-constructed focus shape model, and calculate optimal parameter values ​​of the focus light intensity distribution model based on the least squares method iteration with the projection data as the target; The shape calculation module is used to calculate the shape of the light intensity distribution at the focus of the tube based on the optimal value of the parameter.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A non-transitory computer readable medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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