Imaging data calibration method, electronic device, storage medium and program product

Abstract

The present invention provides an imaging data calibration method, comprising the following steps: S100: downsampling the original volume data; S200: correcting the X-ray attenuation values ​​of the volume data in two branches and projecting them separately to obtain a second projection image sequence and a third projection image sequence; S300: downsampling the original projection image to obtain a first projection image sequence; S400: traversing the first projection image sequence, the second projection image sequence, and the third projection image sequence at the same angle and calculating the corresponding scattering artifacts to correct the original volume data. The present application combines forward projection of the volume data with secondary reconstruction of the original projection image, designs reasonable X-ray attenuation value correction and truncation correction, and achieves a good final de-scattering artifact correction effect. The entire algorithm is concise in design, has a very fast calculation speed, and has high practical application value, thereby saving a large amount of economic and time costs.

Description

Technical Field

[0001] The present invention relates to the technical field, and in particular to an imaging data calibration method, an electronic device, a storage medium, and a program product. Background Art

[0002] In CT scans, scatter artifacts are primarily caused by the Compton scattering effect, which occurs when X-rays interact with the object being scanned. This effect causes X-ray photons to lose some of their energy, altering their original path and energy distribution, ultimately resulting in blurred and distorted images. Existing technologies for removing scatter artifacts from CT are extremely complex, requiring either sophisticated and costly hardware improvements or complex post-processing using projections and reconstructed images, which increases post-processing time, increasing both financial and time costs. Summary of the Invention

[0003] In order to solve the above technical problems, the present invention combines the forward projection and original projection of volume data Figure 2 For the reconstruction, a reasonable X-ray attenuation correction and truncation correction are designed to achieve good de-scattering artifact correction effect. The specific technical solution is as follows:

[0004] A first aspect of the present disclosure provides an imaging data calibration method, comprising the following steps:

[0005] Downsampling the original volume data;

[0006] In the two branches, the X-ray attenuation values ​​of the volume data are corrected and projected respectively to obtain a second projection image sequence and a third projection image sequence;

[0007] Downsampling the original projection image to obtain a first projection image sequence;

[0008] The first projection image sequence, the second projection image sequence and the third projection image sequence at the same angle are traversed and corresponding scattering artifacts are calculated to correct the original volume data.

[0009] Preferably, the downsampling process in downsampling the original volume data and the original projection image is as follows:

[0010] The downsampling step size is used to retain the data of corresponding points at a certain step size.

[0011] Preferably, the X-ray attenuation value correction processing in the step of correcting the X-ray attenuation values ​​of the volume data in the two branches includes:

[0012] The volume data are corrected for X-ray attenuation values ​​in two branches;

[0013] Outliers are removed from the two volume data after X-ray attenuation correction is completed in the branches.

[0014] Preferably, the X-ray attenuation value correction in the step of performing X-ray attenuation value correction on volume data in the two branches includes:

[0015] All data points with X-ray attenuation values ​​between -1000 and -500 are corrected to -1000;

[0016] All data points with X-ray attenuation values ​​between -500 and 750 are corrected to 0;

[0017] All data points with X-ray attenuation values ​​between 750 and 2000 were corrected to 2000.

[0018] Preferably, the step of removing outliers from the volume data after the X-ray attenuation value correction is completed in the two branches includes:

[0019] All data points with X-ray attenuation values ​​between -1000 and -500 are corrected to -1000;

[0020] All data points with X-ray attenuation values ​​greater than 2000 were corrected to 2000.

[0021] Preferably, the projection in the steps of correcting the X-ray attenuation values ​​of the volume data in the two branches and respectively projecting to obtain the second projection image sequence and the third projection image sequence is forward projection, and the projection step includes:

[0022] Using the geometric information of the imaging system, the volume data is reprojected to various angles at the time of shooting to obtain a sequence of projection images.

[0023] Preferably, the step of traversing the first projection image sequence, the second projection image sequence, and the third projection image sequence at the same angle and calculating corresponding scattering artifacts to correct the original volume data includes:

[0024] Loop extraction of projection graph;

[0025] Calculate scattering artifacts;

[0026] Backprojection correction.

[0027] Preferably, the step of cyclically extracting projection images includes: extracting projection images of the same angle from the first projection image sequence, the second projection image sequence and the third projection image sequence each time.

[0028] Preferably, the step of calculating scattering artifacts includes:

[0029] Calculate the truncation correction, and the calculation formula is: ;

[0030] Calculate the scattering artifacts, and the calculation formula is:

[0031] in, Defined as the first projection sequence, Defined as the second projection sequence, Defined as the third projection sequence.

[0032] Preferably, the back-projection correction step includes:

[0033] After obtaining the scattering artifacts at the corresponding projection angle, the scattering artifacts at the angle are back-projected and reconstructed to obtain the scattering artifacts on the corresponding volume data, which are then subtracted from the original volume data to obtain the CT volume data without scattering artifacts.

[0034] A second aspect of the present disclosure provides an electronic device, including:

[0035] a memory storing execution instructions; and

[0036] A processor executes the execution instruction stored in the memory, so that the processor executes the imaging data calibration method described in any one of the above embodiments.

[0037] A third aspect of the present disclosure provides a readable storage medium, wherein the readable storage medium stores execution instructions, and when the execution instructions are executed by a processor, they are used to implement the imaging data calibration method described in any of the above embodiments.

[0038] A fourth aspect of the present disclosure provides a computer program product, comprising a computer program / instruction, wherein the computer program / instruction is used to implement the imaging data calibration method described in any of the above embodiments when executed by a processor.

[0039] It can be seen from the above technical solutions that the present invention has the following beneficial effects:

[0040] First, the original volume data is downsampled, and then the X-ray attenuation value correction and outlier removal processing are performed in two branches respectively, and the second projection image sequence and the third projection image sequence are obtained respectively. Then, the original projection image is directly downsampled to obtain the first projection image sequence; then the first projection image sequence, the second projection image sequence and the third projection image sequence at the same angle are traversed, and the corresponding scattering artifacts are calculated. Then, the obtained scattering artifacts are used to correct the original volume data. This scheme combines the forward projection of the volume data and the original projection Figure 2The proposed algorithm is simple in design and has a very fast calculation speed, which has high practical application value. It solves the problem in existing technologies that CT descattering artifacts is achieved by making sophisticated hardware improvements or performing complex post-processing of projection images and reconstructed images, which wastes a lot of economic and time costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is a flow chart of step M10 of the present invention;

[0042] Figure 2 This is a flow chart of step S200 of the present invention;

[0043] Figure 3 This is a flow chart of step S400 of the present invention;

[0044] Figure 4 This is a flow chart of downsampling the original volume data and the original projection image according to the present invention;

[0045] Figure 5 The flowchart of the present invention is to traverse a sequence of projection images at the same angle and calculate corresponding scattering artifacts to correct the original volume data. DETAILED DESCRIPTION

[0046] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. Before describing in detail the technical solutions of each embodiment of the present invention, the nouns and terms involved are explained. In this specification, components with the same name or the same number represent similar or identical structures and are for illustrative purposes only.

[0047] Reference Figure 1 、 Figure 2 and Figure 4 As shown, the present invention provides an imaging data calibration method M10. The imaging data calibration method M10 of this embodiment includes the following steps: S100, S200, 300 and S400.

[0048] Specifically, S100: downsampling the original volume data;

[0049] First, the original CT volume data is downsampled, and downsampling will produce two branches.

[0050] Downsampling the raw volumetric data (such as CT or CBCT projection data) is a key step, aiming to balance computational efficiency and scatter estimation accuracy. Downsampling plays the following roles in scatter correction: Accelerating scatter field estimation: Scattering calculations (e.g., based on Monte Carlo or convolution-superposition methods) are computationally intensive, and downsampling can significantly reduce iteration time. Noise suppression: The impact of high-frequency noise (e.g., quantum noise) at low resolution is reduced, resulting in more stable scatter estimation. Multi-scale processing: The scattering field is first estimated at low resolution, and then upsampled to high resolution to correct the raw data. When downsampling the raw projection data, parameters such as the angular direction and detector pixel direction must be set. The angular direction typically maintains the original angle (to avoid information loss), while the detector pixel direction is scaled down (e.g., using 2×2 mean pooling). When downsampling the initially reconstructed volumetric data for low-resolution scatter simulation, isotropic downsampling is required to avoid geometric distortion.

[0051] Continuing to the next step, S200: performing correction processing on the X-ray attenuation values ​​of the volume data in the two branches and respectively projecting them to obtain a second projection image sequence and a third projection image sequence;

[0052] In CT image processing, correcting the X-ray attenuation values ​​of volume data is a key step in optimizing image quality, enhancing specific tissue contrast, or correcting artifacts. After correcting the X-ray attenuation values ​​of the volume data in two branches, the projection operation is continued to obtain the second and third projection image sequences.

[0053] Furthermore, the X-ray attenuation value correction process in S200 includes the following steps:

[0054] S210: performing X-ray attenuation value correction on the volume data in two branches;

[0055] Correct the X-ray attenuation values ​​of different tissues in the volume data. The method for correcting the X-ray attenuation values ​​of the volume data is as follows:

[0056] ① Correct all data points with X-ray attenuation values ​​between -1000 and -500 to -1000;

[0057] ② Correct all data points with X-ray attenuation values ​​between -500 and 750 to 0;

[0058] ③ All data points with X-ray attenuation values ​​between 750 and 2000 were corrected to 2000.

[0059] S220: removing outliers from the volume data after the X-ray attenuation correction is completed in the two branches;

[0060] Among them, the method of removing outliers from volume data is as follows:

[0061] ① Correct all data points with X-ray attenuation values ​​between -1000 and -500 to -1000;

[0062] ② All data points with X-ray attenuation values ​​greater than 2000 were corrected to 2000.

[0063] Through the above operations, after the original volume data is downsampled, X-ray attenuation value correction and outlier removal processing can be performed in two branches.

[0064] It should be noted that the X-ray attenuation value can also be called the HU value, where HU is the abbreviation of Hounsfield Unit, which is used to measure the degree of attenuation of X-rays by tissue in CT (computed tomography) images and is the standardized unit of pixel value in CT images.

[0065] In addition, the projection method in S200 is forward projection, and the projection step is: using the geometric information of the imaging system, reprojecting the volume data to various angles during shooting, so that a projection image sequence can be obtained, such as the second projection image sequence and the third projection image sequence mentioned above.

[0066] Specifically, S300: downsampling the original projection image to obtain a first projection image sequence;

[0067] By directly downsampling the original projection image, the first projection image sequence can be directly obtained.

[0068] Downsampling the original projection image sequence is a common operation to accelerate processing or reduce data volume. Projection image downsampling requires consideration of the downsampling dimension selection and the relationship between key parameters. The downsampling dimension selection includes the detector pixel direction: usually downsampling is allowed (less high-frequency information), the angular direction: generally maintained as is (to avoid angular undersampling leading to reconstruction artifacts), and the energy channel (spectral CT): the original number of channels must be maintained. The parameters that affect downsampling are as follows: detector pixel size: the equivalent pixel size increases after downsampling (geometric calibration needs to be adjusted); reconstruction field of view (FOV): the maximum FOV may decrease after downsampling); and noise characteristics: the quantum noise standard deviation is reduced by a factor of N (N is the downsampling factor).

[0069] It should be noted that the downsampling process in steps S100 and S300 is as follows: the downsampling step size is 2, and the data of the corresponding points are retained at every certain step size.

[0070] Reference Figure 1 、 Figure 3 and Figure 5 ,Specifically, S400: traverse the first projection image sequence, the second projection image sequence, and the third projection image sequence at the same angle and calculate the corresponding scattering artifacts to correct the original volume data;

[0071] By traversing the first projection image sequence, the second projection image sequence and the third projection image sequence at the same angle, and then calculating the scattering artifacts corresponding to the first projection image sequence, the second projection image sequence and the third projection image sequence, the original volume data is finally corrected using the obtained scattering artifacts.

[0072] Furthermore, the S400 includes:

[0073] S410: cyclically extracting projection images;

[0074] Among them, the number of loops is N: equal to the number of projection image sequences. If the number of projection image sequences is 0, then this step ends. If the number of projection image sequences is greater than 0, then this operation is implemented, specifically as follows: each time, projection images of the same angle are extracted from the first projection image sequence, the second projection image sequence, and the third projection image sequence.

[0075] S420: generating scattering artifacts;

[0076] Generating scattering artifacts includes:

[0077] S421: Calculate truncation correction;

[0078] The specific calculation method is as follows: It should be noted that truncation correction is an important coefficient proposed by this algorithm, which eliminates the influence of truncation during secondary projection by adjusting the ratio of the original projection image and the secondary projection.

[0079] S422: Calculate scattering artifacts;

[0080] The specific calculation method is as follows: .

[0081] S430: back-projection correction;

[0082] After obtaining the scattering artifacts at the corresponding projection angle, the scattering artifacts at the angle are back-projected and reconstructed, so that the scattering artifacts on the corresponding volume data can be obtained. Finally, the scattering artifacts are subtracted from the original volume data to obtain the CT volume data without scattering artifacts.

[0083] In addition, you can Defined as the first projection sequence, Defined as the second projection sequence, Defined as the third projection sequence.

[0084] It should be noted that back-projection correction is also called BP correction. In the training process of neural networks, BP is the abbreviation of BackPropagation. BP correction refers to the process of calculating the gradient of the loss function with respect to the network parameters through the back-propagation algorithm, and using the gradient descent method (or other optimization algorithms) to adjust the weights and biases (i.e., parameter update).

[0085] Backpropagation is an algorithm for efficiently calculating the gradient of neural networks. Its core is the chain rule. Starting from the output layer, it calculates the gradient of the loss function with respect to the parameters of each layer in reverse, layer by layer (that is, how the error is distributed to the weights and biases of each layer).

[0086] In summary: when it is necessary to remove scattering artifacts from CT images, the original CT volume data and the original projection images are first downsampled. After the original CT volume data is downsampled, the X-ray attenuation value correction and outlier removal processing are continued in two branches respectively, and the second projection image sequence and the third projection image sequence are projected respectively. After the original projection image is downsampled, the first projection image sequence can be directly obtained; then the first projection image sequence, the second projection image sequence and the third projection image sequence at the same angle are traversed, and the corresponding scattering artifacts are calculated. Then, the obtained scattering artifacts can be used to correct the original volume data. This solution combines the forward projection of the volume data and the original projection Figure 2 The proposed algorithm is simple in design and has a very fast calculation speed. It also has a high practical application value. Compared with the existing CT de-scattering artifact technology, the de-scattering artifact technology of this application can save a lot of economic and time costs.

[0087] The present application also discloses an electronic device, comprising:

[0088] a memory storing execution instructions; and

[0089] A processor is configured to execute the execution instructions stored in the memory, so that the processor executes the imaging data calibration method according to any one of the above embodiments.

[0090] The present application also discloses a readable storage medium, in which execution instructions are stored. When the execution instructions are executed by a processor, they are used to implement the imaging data calibration method of any of the above embodiments.

[0091] The present application also discloses a computer program product, including a computer program / instruction, which is used to implement the imaging data calibration method of any of the above embodiments when executed by a processor.

[0092] For the purposes of this specification, a "readable storage medium" can be any device that can contain, store, communicate, propagate or transmit a program for use with or in conjunction with an instruction execution system, device or apparatus. More specific examples (a non-exhaustive list) of readable storage media include the following: an electrical connection having one or more wires (electronic device), a portable computer disk cartridge (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and editable read-only memory (EPROM or flash memory), a fiber optic device, and a portable read-only memory (CDROM). In addition, the readable storage medium can even be paper or other suitable medium on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing it in other suitable ways as necessary, and then storing it in a memory.

[0093] It should be understood that various parts of the present disclosure can be implemented using hardware, software, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented using software stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement the hardware: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0094] Those skilled in the art will understand that all or part of the steps of the above-mentioned implementation method can be accomplished by instructing related hardware through a program, and the program can be stored in a readable storage medium. When the program is executed, it includes one or a combination of the steps of the method implementation method.

[0095] Furthermore, the functional units in the various embodiments of the present disclosure may be integrated into a single processing module, each unit may exist physically separately, or two or more units may be integrated into a single module. The aforementioned integrated modules may be implemented in the form of hardware or software functional modules. If the integrated modules are implemented as software functional modules and sold or used as independent products, they may also be stored in a readable storage medium. The storage medium may be a read-only memory, a magnetic disk, or an optical disk, etc.

[0096] The above-described embodiments are merely descriptions of preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should fall within the scope of protection determined by the claims of the present invention.

Claims

1. A method for calibrating imaging data, characterized in that: The following steps are involved: Downsampling the original volume data; In the two branches, the X-ray attenuation values ​​of the volume data are corrected and projected respectively to obtain a second projection image sequence and a third projection image sequence; Downsampling the original projection image to obtain a first projection image sequence; Traversing the first projection image sequence, the second projection image sequence, and the third projection image sequence at the same angle and calculating corresponding scattering artifacts to correct the original volume data; The downsampling of the original volume data adopts isotropic downsampling to keep the geometric structure unchanged; The correction processing of the X-ray attenuation value in the two branches includes: In the first branch, the X-ray attenuation value is segmented and mapped to -1000, 0, and 2000; In the second branch, outliers were truncated to −1000 ≤ HU ≤ 2000, where HU is the abbreviation for Hounsfield units; The downsampling process of downsampling the original volume data and the original projection image is as follows: The downsampling step size is used to retain the data of corresponding points at a certain step size; The X-ray attenuation value segmentation mapping steps include: All data points with X-ray attenuation values ​​between -1000 and -500 are corrected to -1000; All data points with X-ray attenuation values ​​between -500 and 750 are corrected to 0; All data points with X-ray attenuation values ​​between 750 and 2000 were corrected to 2000; The steps for truncating abnormal values ​​after X-ray attenuation correction include: All data points with X-ray attenuation values ​​between -1000 and -500 are corrected to -1000; All data points with X-ray attenuation values ​​greater than 2000 were corrected to 2000.

2. The imaging data calibration method according to claim 1, wherein: The projection in the steps of correcting the X-ray attenuation values ​​of the volume data in the two branches and respectively projecting to obtain the second projection image sequence and the third projection image sequence is forward projection, and the projection step includes: Using the geometric information of the imaging system, the volume data is reprojected to various angles at the time of shooting to obtain a sequence of projection images.

3. The imaging data calibration method according to claim 1, wherein: The steps of traversing the first projection image sequence, the second projection image sequence, and the third projection image sequence at the same angle and calculating corresponding scattering artifacts to correct the original volume data include: Loop extraction of projection graph; Calculate scattering artifacts; Backprojection correction.

4. The imaging data calibration method according to claim 3, wherein: The step of cyclically extracting projection images includes: extracting projection images of the same angle from the first projection image sequence, the second projection image sequence and the third projection image sequence each time.

5. The imaging data calibration method according to claim 3, wherein: The step of calculating scattering artifacts comprises: Calculate the truncation correction, and the calculation formula is: ; Calculate the scattering artifacts, and the calculation formula is: in, Defined as the first projection sequence, Defined as the second projection sequence, Defined as the third projection sequence.

6. The imaging data calibration method according to claim 3, wherein: The back projection correction step comprises: After obtaining the scattering artifacts at the corresponding projection angle, the scattering artifacts at the projection angle are back-projected and reconstructed to obtain the scattering artifacts on the corresponding volume data, which are then subtracted from the original volume data to obtain the CT volume data without scattering artifacts.

7. An electronic device, characterized in that: include: a memory storing execution instructions; as well as A processor, wherein the processor executes the execution instruction stored in the memory, so that the processor executes the imaging data calibration method according to any one of claims 1 to 6.

8. A readable storage medium, characterized in that: The readable storage medium stores execution instructions, which are used to implement the imaging data calibration method according to any one of claims 1 to 6 when executed by a processor.

9. A computer program product, characterized in that The method comprises a computer program / instruction, wherein the computer program / instruction is used to implement the imaging data calibration method according to any one of claims 1 to 6 when the computer program / instruction is executed by a processor.

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