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

Abstract

The invention provides an imaging data calibration method. The imaging data calibration method comprises the following steps of S100, performing downsampling on original volume data; s200, correcting the X-ray attenuation value of the volume data in the two branches, and respectively projecting to obtain a second projection drawing sequence and a third projection drawing sequence; s300, downsampling the original projection drawing to obtain a first projection drawing sequence; and S400, traversing the first projection drawing sequence, the second projection drawing sequence and the third projection drawing sequence at the same angle, and calculating corresponding scattering artifacts to correct the original volume data. According to the method, the forward projection of the volume data and the secondary reconstruction of the original projection drawing are combined, reasonable X-ray attenuation value correction and truncation correction are designed, the final scattering artifact removal correction effect is good, meanwhile, the design of the whole algorithm is simple, the calculation speed is very high, the practical application value is very high, and the method is suitable for popularization and application. Therefore, a large amount of economic cost and time cost can be saved.

Description

Technical Field

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

[0002] In CT scanning, scatter artifacts are mainly caused by the Compton scattering effect that occurs when X-rays interact with the object being measured. This effect causes X-ray photons to lose some of their energy, thereby changing their original path and energy distribution, and ultimately forming blurred and distorted artifacts on the image. The related technologies for removing scatter artifacts in existing CTs are all very complex. Some make precise and complex improvements in hardware, which requires a large amount of investment, or perform complex post-processing using projection images and reconstructed images, which in turn leads to an increase in post-processing time. Therefore, not only the economic cost is increased, but also the time cost is increased. Summary of the Invention

[0003] To solve the above technical problems, the present invention combines the forward projection of volume data and the original projection Figure 2 with several reconstructions, and designs reasonable X-ray attenuation value correction and truncation correction, so that the scatter artifact correction effect is good. The specific technical solutions are as follows: The first aspect of the present disclosure provides an imaging data calibration method, including the following steps: Downsample the original volume data; In two branches, correct the X-ray attenuation value of the volume data and perform projections respectively to obtain a second projection image sequence and a third projection image sequence; Downsample the original projection image to obtain a first projection image sequence; 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 scatter artifacts to correct the original volume data.

[0004] Preferably, the downsampling process in the downsampling of the original volume data and the original projection image is as follows: The downsampling step size retains the data of the corresponding points at every certain step size.

[0005] Preferably, the X-ray attenuation value correction process in the step of correcting the X-ray attenuation value of the volume data in two branches includes: Correct the X-ray attenuation value of the volume data in two branches; Remove outliers from the volume data after correcting the X-ray attenuation value in the two branches.

[0006] Preferably, the X-ray attenuation value correction in the step of correcting the X-ray attenuation value of the volume data in two branches includes: Data points with X-ray attenuation values within -1000 to -500 are all corrected to -1000; Data points with X-ray attenuation values within -500 to 750 are all corrected to 0; Data points with X-ray attenuation values within 750 to 2000 are all corrected to 2000.

[0007] Preferably, the outlier removal in the step of removing outliers from the two volume data after correcting the X-ray attenuation values in the branches includes: Data points with X-ray attenuation values within -1000 to -500 are all corrected to -1000; Data points with X-ray attenuation values greater than 2000 are all corrected to 2000.

[0008] Preferably, the projection in the step of correcting the X-ray attenuation values of the volume data in the two branches and respectively performing projections 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 re-projected onto each angle at the time of shooting to obtain a projection image sequence.

[0009] 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 the corresponding scatter artifacts to correct the original volume data includes: Cyclically extracting projection images; Calculating scatter artifacts; Back-projection correction.

[0010] Preferably, the step of cyclically extracting projection images includes: Each time, projection images at the same angle are extracted from the first projection image sequence, the second projection image sequence, and the third projection image sequence.

[0011] Preferably, the step of calculating scatter artifacts includes: Calculating truncation correction, and the calculation formula is: ; Calculating scatter artifacts, and the calculation formula is: Wherein, is defined as the first projection sequence, is defined as the second projection sequence, is defined as the third projection sequence.

[0012] Preferably, the step of back-projection correction includes: After obtaining the scatter artifacts corresponding to the projection angle, the scatter artifacts at this angle are back-projected and reconstructed to obtain the scatter artifacts on the corresponding volume data, and then the original volume data is used to subtract it to obtain the CT volume data without scatter artifacts.

[0013] The second aspect of the present disclosure provides an electronic device, including: a memory that stores execution instructions; and a processor that executes the execution instructions stored in the memory, so that the processor executes the imaging data calibration method described in any of the above embodiments.

[0014] The third aspect of the present disclosure provides a readable storage medium, in which execution instructions are stored, 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.

[0015] The fourth aspect of the present disclosure provides a computer program product, including a computer program / instructions, characterized in that when the computer program / instructions are executed by a processor, they are used to implement the imaging data calibration method described in any of the above embodiments.

[0016] From the above technical solutions, it can be seen that the present invention has the following beneficial effects: First, downsample the original volume data, then perform X-ray attenuation value correction and outlier removal processing in two branches respectively, and perform projections respectively to obtain a second projection image sequence and a third projection image sequence. Then, directly downsample the original projection images to obtain a first projection image sequence; then traverse the first projection image sequence, the second projection image sequence, and the third projection image sequence at the same angle, calculate the corresponding scatter artifacts, and then use the obtained scatter artifacts to correct the original volume data. This solution combines the forward projection of the volume data and the original projection Figure 2 For the second reconstruction, reasonable X-ray attenuation value correction and truncation correction are designed, so that the scatter artifact removal correction effect is good, and the design of the entire algorithm is simple, the calculation speed is very fast, and it has high practical application value. It solves the problem in the prior art that a large amount of economic and time costs are wasted by making precise and complex improvements on the hardware or performing complex post-processing on the projection images and reconstructed images to achieve CT scatter artifact removal. Description of the Drawings

[0017] Figure 1 It is a flowchart of step M10 of the present invention; Figure 2 It is a flowchart of step S200 of the present invention; Figure 3 It is a flowchart of step S400 of the present invention; Figure 4 It is a flowchart of downsampling the original volume data and the original projection images of the present invention; Figure 5 It is a flowchart of traversing the projection image sequences at the same angle and calculating the corresponding scatter artifacts to correct the original volume data of the present invention. Detailed Embodiment

[0018] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. Before describing the technical solutions of the embodiments of the present invention in detail, the nouns and terms involved will be explained. In this specification, components with the same name or the same reference numeral represent similar or identical structures, and are for illustrative purposes only.

[0019] Refer to 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.

[0020] Specifically, S100: Downsample the original volume data; First, perform downsampling on the original CT volume data. Downsampling will generate two branches.

[0021] Among them, downsampling the original volume data (such as CT or CBCT projection data) is a key step to balance computational efficiency and scattering estimation accuracy. The role of downsampling in scatter correction is as follows: Accelerate scatter field estimation: Scatter calculation (such as based on Monte Carlo or convolution superposition method) has a large computational amount, and downsampling can significantly reduce the iteration time. Noise suppression: The influence of high-frequency noise (such as quantum noise) is reduced at low resolution, and the scatter estimation is more stable. Multi-scale processing: First estimate the scatter field at low resolution, and then upsample to high resolution to correct the original data. When downsampling the original projection data, parameters need to be set, such as the angular direction and the detector pixel direction. The angular direction usually maintains the original number of angles (to avoid information loss), and the detector pixel direction: scale down proportionally (such as 2×2 mean pooling). Downsampling the initially reconstructed volume data for low-resolution scatter simulation requires isotropic downsampling (to avoid geometric distortion).

[0022] Continue to the next step, S200: Correct the X-ray attenuation values of the volume data in the two branches and perform projections respectively to obtain a second projection map sequence and a third projection map sequence; In CT image processing, correcting the X-ray attenuation value of the volume data is a key step to optimize image quality, enhance contrast of specific tissues, or correct artifacts. After correcting the X-ray attenuation values of the volume data in the two branches, continue with the projection operation to obtain a second projection map sequence and a third projection map sequence.

[0023] Furthermore, the X-ray attenuation value correction process in S200 includes the following steps: S210: Correct the X-ray attenuation values of the volume data in the two branches; 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: ① Correct all data points with X-ray attenuation values in the range of -1000 to -500 to -1000; ② Correct all data points with X-ray attenuation values in the range of -500 to 750 to 0; ③ Correct all data points with X-ray attenuation values in the range of 750 to 2000 to 2000.

[0024] S220: Remove outliers from the two volume data after X-ray attenuation value correction in the branches; The method for removing outliers from the volume data is as follows: ① Correct all data points with X-ray attenuation values in the range of -1000 to -500 to -1000; ② Correct all data points with X-ray attenuation values greater than 2000 to 2000.

[0025] Through the above operations, after downsampling the original volume data, X-ray attenuation value correction and outlier removal can be performed in the two branches.

[0026] 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 attenuation degree of tissues in CT (Computed Tomography) images to X-rays and is the standardized unit of pixel values in CT images.

[0027] In addition, the projection method in S200 is forward projection, and the projection steps are: using the geometric information of the imaging system, re-project the volume data to each angle during shooting, so that a sequence of projection images can be obtained, such as the second projection image sequence and the third projection image sequence mentioned above.

[0028] Specifically, S300: Downsample the original projection images to obtain the first projection image sequence; After directly downsampling the original projection images, the first projection image sequence can be directly obtained.

[0029] Downsampling the original projection image sequence is a common operation to accelerate processing or reduce data volume. When performing projection image downsampling, the selection of downsampling dimension and the relationship between key parameters need to be considered. The selection of downsampling dimension includes the detector pixel direction: usually can be downsampled (less high-frequency information), the angular direction: generally remains unchanged (to avoid reconstruction artifacts caused by angular undersampling), and the energy channel (spectral CT): the original number of channels needs to be maintained. The influence of parameters on downsampling is as follows: detector pixel size, the equivalent pixel size increases after downsampling (geometric calibration needs to be adjusted), reconstructed FOV, the maximum FOV may shrink after downsampling, and noise characteristics, the standard deviation of quantum noise is reduced by N times (N is the downsampling factor).

[0030] It should be noted that the downsampling process in the S100 and S300 steps is as follows: the above-mentioned downsampling step size is 2, and data of corresponding points are retained at regular intervals.

[0031] Refer to 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 scatter artifacts to correct the original volume data; By traversing the first projection image sequence, the second projection image sequence, and the third projection image sequence at the same angle, then calculating the scatter artifacts corresponding to the first projection image sequence, the second projection image sequence, and the third projection image sequence, and finally using the obtained scatter artifacts to correct the original volume data.

[0032] Further, the S400 includes: S410: Cyclically extract projection images; Among them, the number of cycles is N: equal to the number of projection images in the projection image sequence. If the number of projection images in the projection image sequence is 0, this step ends. If the number of projection images in the projection image sequence is greater than 0, this operation is implemented as follows: Each time, projection images at the same angle are extracted from the first projection image sequence, the second projection image sequence, and the third projection image sequence.

[0033] S420: Generate scatter artifacts; Among them, generating scatter artifacts includes: S421: Calculate truncation correction; The specific calculation method is as follows: It should be noted that truncation correction is an important coefficient proposed by this algorithm, and the influence brought by truncation during secondary projection is eliminated through the ratio of the original projection image and the secondary projection.

[0034] S422: Calculate scatter artifacts; The specific calculation method is as follows: 。

[0035] S430: Back-projection correction; After obtaining the scatter artifacts corresponding to the projection angle, perform back-projection reconstruction on the scatter artifacts at this angle, so that the scatter artifacts on the corresponding volume data can be obtained. Finally, subtract it from the original volume data to obtain the CT volume data without scatter artifacts.

[0036] In addition, can be defined as the first projection sequence, and can be defined as the second projection sequence, and can be defined as the third projection sequence.

[0037] It should be noted that back-projection correction is also called BP correction. During the training process of the neural network, BP is the abbreviation of BackPropagation (backward propagation). BP correction refers to the process of calculating the gradient of the loss function with respect to the network parameters through the backward propagation algorithm and adjusting the weights and biases (i.e., parameter update) using the gradient descent method (or other optimization algorithms).

[0038] Backward propagation is an efficient algorithm for calculating the gradients of a neural network. The core is the chain rule. Starting from the output layer, calculate the gradients of the loss function with respect to the parameters of each layer backward layer by layer (i.e., how the error is distributed to the weights and biases of each layer).

[0039] In summary: When it is necessary to remove scatter artifacts from CT images, first downsample the original CT volume data and the original projection images. After downsampling the original CT volume data, continue to perform X-ray attenuation value correction and outlier removal processing in two branches respectively, and perform projections respectively to obtain the second projection image sequence and the third projection image sequence. After downsampling the original projection images, the first projection image sequence can be directly obtained; then traverse the first projection image sequence, the second projection image sequence, and the third projection image sequence at the same angle, calculate the corresponding scatter artifacts, and then use the obtained scatter artifacts to correct the original volume data. This solution combines the forward projection of the volume data and the original projection Figure 2 times of reconstruction, designs reasonable X-ray attenuation value correction and truncation correction, so that the final scatter artifact removal correction effect is good, and the design of the entire algorithm is simple, so the calculation speed is very fast and it has high practical application value. Compared with the existing CT scatter artifact removal technology, the scatter artifact removal technology of this application can save a large amount of economic cost and time cost.

[0040] This application also discloses an electronic device, including: a memory that stores execution instructions; and A processor that executes the execution instructions stored in the memory, such that the processor executes the imaging data calibration method according to any of the above embodiments.

[0041] The present application also discloses a readable storage medium storing execution instructions, which are used to implement the imaging data calibration method according to any of the above embodiments when being executed by a processor.

[0042] The present application also discloses a computer program product including a computer program / instructions, which are used to implement the imaging data calibration method according to any of the above embodiments when being executed by a processor.

[0043] For the purposes of this specification, a "readable storage medium" may be any device that can contain, store, communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the readable storage medium include the following: an electrical connection portion (electronic device) having one or more wirings, a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable read-only memory (CDROM). Additionally, the readable storage medium can even be paper or other suitable medium on which a program can be printed, as the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or otherwise processing as appropriate, and then storing it in a memory.

[0044] It should be understood that the various parts of the present disclosure can be implemented by hardware, software, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), and the like.

[0045] Those of ordinary skill in the art of this technology can understand that all or part of the steps for implementing the above embodiments of the method can be completed by a program instructing relevant hardware. The program can be stored in a readable storage medium, and when the program is executed, it includes one or a combination of the steps of the method embodiments.

[0046] In addition, each functional unit in various embodiments of the present disclosure may be integrated into one processing module, or each unit may exist physically alone, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. When the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a readable storage medium. The storage medium may be a read-only memory, a magnetic disk, an optical disc, etc.

[0047] The above-described embodiments are merely descriptions of the preferred embodiments of the present invention and do not limit the scope of the present invention. Without departing from the design spirit of the present invention, various deformations and improvements made by those of ordinary skill in the art to the technical solution of the present invention shall fall within the protection scope determined by the claims of the present invention.

Claims

1. An imaging data calibration method, characterized in that, It includes the following steps: Downsample the original volume data; In two branches, correct the X-ray attenuation values of the volume data and perform projections respectively to obtain the second projection image sequence and the third projection image sequence; Downsample the original projection images to obtain the first projection image sequence; 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 scatter artifacts to correct the original volume data.

2. The imaging data calibration method according to claim 1, wherein The downsampling process in the downsampling of the original volume data and the original projection images is as follows: The downsampling step is to retain the data of the corresponding points at a certain interval.

3. The imaging data calibration method according to claim 1, wherein The X-ray attenuation value correction process in the step of correcting the X-ray attenuation values of the volume data in two branches includes: Correct the X-ray attenuation values of the volume data in two branches; Remove outliers from the volume data that have completed X-ray attenuation value correction in the two branches.

4. The imaging data calibration method according to claim 3, wherein The X-ray attenuation value correction in the step of correcting the X-ray attenuation values of the volume data in two branches includes: All data points with X-ray attenuation values in the range of -1000 to -500 are corrected to -1000; All data points with X-ray attenuation values in the range of -500 to 750 are corrected to 0; All data points with X-ray attenuation values in the range of 750 to 2000 are corrected to 2000.

5. The imaging data calibration method according to claim 3, wherein The outlier removal in the step of removing outliers from the volume data that have completed X-ray attenuation value correction in the two branches includes: All data points with X-ray attenuation values in the range of -1000 to -500 are corrected to -1000; All data points with X-ray attenuation values greater than 2000 are corrected to 2000.

6. The imaging data calibration method according to claim 1, characterized in that, The projection in the step of correcting the X-ray attenuation values of the volume data in two branches and performing projections respectively 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, re-project the volume data to each angle during shooting to obtain a projection image sequence.

7. The imaging data calibration method according to claim 1, wherein The steps based on 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 scatter artifacts to correct the original volume data include: Cyclically extract projection images; Calculate scatter artifacts; Back-projection correction.

8. The imaging data calibration method according to claim 7, wherein The step of cyclically extracting projection images includes: Each time, extract projection images at the same angle from the first projection image sequence, the second projection image sequence, and the third projection image sequence.

9. The imaging data calibration method according to claim 7, characterized in that The step of calculating scatter artifacts includes: Calculate the truncation correction, and the calculation formula is: ; Calculate the scattering artifact, and the calculation formula is as follows: Among them, is defined as the first projection sequence, is defined as the second projection sequence, is defined as the third projection sequence.

10. The imaging data calibration method according to claim 7, wherein The step of back-projection correction includes: After obtaining the scatter artifacts at the corresponding projection angle, perform back-projection reconstruction on the scatter artifacts at the projection angle to obtain the scatter artifacts on the corresponding volume data, and then subtract it using the original volume data to obtain the CT volume data without scatter artifacts.

11. An electronic device, characterized in that, It includes: A memory that stores execution instructions; And A processor that executes the execution instructions stored in the memory, so that the processor executes the imaging data calibration method according to any one of claims 1-10.

12. A readable storage medium, characterized in that, The executable instructions are stored in the readable storage medium, and when the executable instructions are executed by the processor, they are used to implement the imaging data calibration method according to any one of claims 1-10.

13. A computer program product, characterized in that, Comprising a computer program / instructions, characterized in that when the computer program / instructions are executed by a processor, they are used to implement the imaging data calibration method according to any one of claims 1-10.

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