A digital grid method and terminal

Abstract

The present invention discloses a digital grid method and a terminal. The method comprises the following steps: determining a simulated boundary diffusion function curve based on a preset scattering simulation model, fitting the simulated boundary diffusion function curve to obtain a scattering model; receiving a scattering correction request of a medical image to be corrected; calculating a scattering boundary diffusion function curve corresponding to the medical image to be corrected based on the scattering model and the medical image to be corrected according to the scattering correction request, and determining a scattering kernel according to the scattering boundary diffusion function curve; performing scattering correction on the medical image to be corrected based on the scattering kernel to obtain a corrected medical image, realizing a digital grid, analyzing a physical simulation model of scattered rays, determining a simulated ESF curve, and the scattering model can better reflect the physical effect of scattering, is more in line with the actual scattering situation, and suppresses the scattering influence in the medical image more effectively and thoroughly, thereby effectively eliminating the influence of scattering in the medical image.

Description

Technical Field

[0001] The present invention relates to the technical field of medical image processing, and in particular to a digital grid method and terminal. Background Art

[0002] For X-ray images, the thicker and denser the object being imaged, the higher the radiation energy required to penetrate and achieve effective image contrast. However, when the radiation energy is higher and the density of the object being imaged is also higher, the radiation is more likely to scatter. When the scattered X-rays hit the detector, they are superimposed on the original direct radiation and form an image, resulting in a nonlinear increase in image grayscale and the formation of localized gray haze, which affects the true image contrast. Therefore, it is crucial to eliminate the effects of image scattering.

[0003] Currently, the suppression of X-ray scattered rays mainly adopts the physical grid method. This method uses a metal plate made of special materials. The special structure of the ray attenuation material can filter out the scattered rays that change direction after penetrating the human body, preventing the scattered rays from reaching the detector for further imaging, thereby achieving the purpose of eliminating scattered rays.

[0004] Physical grids are optional accessories and require a de-gridding image processing program with appropriate specifications and parameters. Although physical grids can suppress most scattered rays, they also absorb some original direct rays. Therefore, to achieve the same image grayscale level, the imaging dose must be increased, which increases the patient's radiation level. On the other hand, for some imaging areas that are not greatly affected by scattering, grids are not required, which requires frequent installation and removal of the grid. Therefore, in the development of X-ray equipment, it is often necessary to consider the ease of use and maintenance. Relevant sensors are needed to detect the loading status of the grid so that doctors can observe the usage status of the grid and avoid misoperation. These factors will increase the development and maintenance costs of the equipment. At the same time, when using physical grids, attention should be paid to specifications such as focal length, front and back sides, and center line, which increases the operation intensity of the doctor.

[0005] Compared to physical grids, digital grids can more easily eliminate the effects of image scattering. Currently, there are related image processing methods for digital grids, but most of them only infer relevant information based on the captured image and cannot completely eliminate scattered rays. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to provide a digital grid method and terminal, which can effectively eliminate the influence of scattering in medical images.

[0007] In order to solve the above technical problems, a technical solution adopted by the present invention is:

[0008] A digital grid method, comprising:

[0009] Determining a simulated boundary diffusion function curve based on a preset scattering simulation model, and fitting the simulated boundary diffusion function curve to obtain a scattering model;

[0010] receiving a scatter correction request for a medical image to be corrected;

[0011] calculating, according to the scatter correction request, a scattering boundary spread function curve corresponding to the medical image to be corrected based on the scattering model and the medical image to be corrected, and determining a scattering kernel according to the scattering boundary spread function curve;

[0012] Scatter correction is performed on the medical image to be corrected based on the scatter kernel to obtain a corrected medical image.

[0013] In order to solve the above technical problems, another technical solution adopted by the present invention is:

[0014] A digital grid terminal includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the following steps are implemented:

[0015] Determining a simulated boundary diffusion function curve based on a preset scattering simulation model, and fitting the simulated boundary diffusion function curve to obtain a scattering model;

[0016] receiving a scatter correction request for a medical image to be corrected;

[0017] calculating, according to the scatter correction request, a scattering boundary spread function curve corresponding to the medical image to be corrected based on the scattering model and the medical image to be corrected, and determining a scattering kernel according to the scattering boundary spread function curve;

[0018] Scatter correction is performed on the medical image to be corrected based on the scatter kernel to obtain a corrected medical image.

[0019] The present invention has the beneficial effects of eliminating the need for a physical grid method. Instead, a simulated boundary spread function (ESF) curve is determined based on a preset scattering simulation model, and the simulated ESF curve is fitted to obtain a scattering model. A corresponding scattering boundary spread function (ESF) curve is calculated based on the scattering model and the medical image to be corrected according to a received scatter correction request for the medical image to be corrected. A scattering kernel is determined based on the scattering ESF curve, and finally, scatter correction is performed on the medical image to be corrected based on the scattering kernel. This implements a digital grid. Scatter correction is no longer performed solely based on the captured image. Instead, the physical simulation model of the scattered rays is analyzed to determine the simulated ESF curve, and the ESF curve is fitted to obtain the scattering model. The scattering model better reflects the physical effects of scattering. Scatter correction is performed using the scattering model in combination with the captured medical image and the scattering kernel, thereby more accurately matching actual scattering conditions and more effectively and thoroughly suppressing the effects of scattering in the medical image, thereby effectively eliminating the effects of scattering in the medical image. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 This is a flowchart of a digital grid method according to an embodiment of the present invention;

[0021] Figure 2 This is a structural diagram of a digital grid terminal according to an embodiment of the present invention;

[0022] Figure 3 Schematic diagram of a preset scattering simulation model in a digital grid method according to an embodiment of the present invention;

[0023] Figure 4 Schematic diagram of a penumbra curve in a digital grid method according to an embodiment of the present invention;

[0024] Figure 5 Schematic diagram of a simulated boundary diffusion function curve in a digital grid method according to an embodiment of the present invention;

[0025] Figure 6 Schematic diagram of the process of scatter correction in the digital grid method according to an embodiment of the present invention;

[0026] Figure 7 Schematic diagram of an S-curve in a digital grid method according to an embodiment of the present invention;

[0027] Figure 8 (a) is a schematic diagram of a medical image to be corrected in a digital grid method according to an embodiment of the present invention;

[0028] Figure 8 (b) is a schematic diagram of a corrected medical image in the digital grid method according to an embodiment of the present invention;

[0029] Description of labels:

[0030] 1. Radiation source; 2. Lead plate; 3. Flat-panel detector; 4. Phantom; 5. X-ray. DETAILED DESCRIPTION

[0031] To illustrate the technical content, achieved objectives and effects of the present invention in detail, the following description is given in conjunction with the embodiments and accompanying drawings.

[0032] Please refer to Figure 1 , an embodiment of the present invention provides a digital grid method, comprising:

[0033] Determining a simulated boundary diffusion function curve based on a preset scattering simulation model, and fitting the simulated boundary diffusion function curve to obtain a scattering model;

[0034] receiving a scatter correction request for a medical image to be corrected;

[0035] calculating, according to the scatter correction request, a scattering boundary spread function curve corresponding to the medical image to be corrected based on the scattering model and the medical image to be corrected, and determining a scattering kernel according to the scattering boundary spread function curve;

[0036] Scatter correction is performed on the medical image to be corrected based on the scatter kernel to obtain a corrected medical image.

[0037] As can be seen from the above description, the present invention has the beneficial effects of eliminating the need for a physical grid method. Instead, a simulated boundary spread function (ESF) curve is determined based on a preset scattering simulation model, and the simulated ESF curve is fitted to obtain a scattering model. A corresponding scattering boundary spread function (ESF) curve is calculated based on the scattering model and the medical image to be corrected according to a received scatter correction request for the medical image to be corrected. A scattering kernel is determined based on the scattering ESF curve, and finally, scatter correction is performed on the medical image to be corrected based on the scattering kernel. This implements a digital grid. Scatter correction is no longer performed solely based on the captured image. Instead, the physical simulation model of the scattered rays is analyzed to determine the simulated ESF curve, and the ESF curve is fitted to obtain the scattering model. The scattering model better reflects the physical effects of scattering. Scatter correction is performed using the scattering model in combination with the captured medical image and the scattering kernel, thereby more accurately matching actual scattering conditions. The effects of scattering in the medical image are more effectively and thoroughly suppressed, thereby effectively eliminating the effects of scattering in the medical image.

[0038] Furthermore, determining the simulated boundary diffusion function curve based on the preset scattering simulation model includes:

[0039] Acquire images of a preset scattering simulation model to obtain a penumbra image set;

[0040] downsampling the penumbra image set to obtain a downsampled penumbra image set;

[0041] determining a penumbra boundary direction from the downsampled penumbra image set;

[0042] A simulated boundary diffusion function curve is determined based on the downsampled penumbra image set and the penumbra boundary direction.

[0043] As can be seen from the above description, images captured by a preset scattering simulation model are obtained to obtain a penumbra image set, which is downsampled, and the penumbra boundary direction is determined from the downsampled penumbra image set. A simulated boundary diffusion function curve is determined based on the downsampled penumbra image set and the penumbra boundary direction. The simulated ESF curve reflects the changing relationship between the scattering intensity and the scattering range under different shooting tube voltages and phantom thicknesses, so that the actual scattering boundary diffusion function curve of the medical image to be corrected can be obtained by subsequent calculation.

[0044] Furthermore, the preset scattering simulation model includes a first parameter and a second parameter, and the simulated boundary diffusion function curve is a simulated boundary diffusion function curve obtained under a preset number of different first tube voltages and different first body thicknesses;

[0045] The fitting of the simulated boundary diffusion function curve to obtain a scattering model comprises:

[0046] determining corresponding first and second parameters based on the first tube voltage and the first body thickness;

[0047] The simulated boundary diffusion function curve is fitted based on the first parameter and the second parameter to obtain a scattering model.

[0048] Furthermore, the simulated boundary diffusion function curve includes scattering intensity and scattering range;

[0049] The fitting of the simulated boundary diffusion function curve based on the first parameter and the second parameter to obtain a scattering model includes:

[0050] The scattering model is:

[0051] y=A*e B*x ;

[0052] In the formula, y represents the scattering intensity, x represents the scattering range, A represents the first parameter, and B represents the second parameter.

[0053] As can be seen from the above description, the corresponding first and second parameters are determined based on the first tube voltage and the first body thickness, and the simulated boundary spread function curve is fitted based on the first and second parameters to obtain a scattering model. Subsequently, the actual scattering boundary spread function curve can be calculated using the scattering model and the tube voltage and body thickness actually captured.

[0054] Furthermore, the calculating, according to the scatter correction request, based on the scatter model and the medical image to be corrected, a scattering boundary diffusion function curve corresponding to the medical image to be corrected includes:

[0055] acquiring a second tube voltage and a second body thickness corresponding to the medical image to be corrected according to the scatter correction request;

[0056] A scattering boundary diffusion function curve corresponding to the medical image to be corrected is calculated based on the scattering model, the second tube voltage, and the second body thickness.

[0057] As can be seen from the above description, a second tube voltage and a second body thickness corresponding to the medical image to be corrected are obtained according to a scatter correction request, and a scattering boundary spread function curve corresponding to the medical image to be corrected is calculated based on the scattering model, the second tube voltage, and the second body thickness. The tube voltage and body thickness actually captured based on the scattering model can better fit the actual shooting conditions of the medical image to be corrected, thereby making the scattering boundary spread function curve more accurate and reliable.

[0058] Furthermore, determining the scattering kernel according to the scattering boundary spread function curve includes:

[0059] Derivative the scattering boundary spread function curve to obtain a line spread function curve;

[0060] determining a scattering core radius based on the scattering boundary diffusion function curve and the medical image to be corrected;

[0061] A scattering core is determined according to the scattering core radius and the line spread function curve.

[0062] From the above description, it can be seen that by taking the derivative of the scattering boundary diffusion function curve to obtain the line spread function curve, the scattering kernel radius is determined based on the scattering boundary diffusion function curve and the medical image to be corrected, and the scattering kernel is determined according to the scattering kernel radius and the line spread function curve. This can improve the accuracy of the scattering kernel calculation, and subsequently use the scattering kernel for scattering correction, thereby improving the effect of suppressing the scattering effect in the medical image.

[0063] Furthermore, determining the scattering core radius based on the scattering boundary diffusion function curve and the medical image to be corrected includes:

[0064] Acquiring a photographed part corresponding to the medical image to be corrected, and determining a first preset threshold value according to the photographed part and the second body thickness;

[0065] Determining a maximum value corresponding to the scattering boundary diffusion function curve, and calculating a product of the maximum value and the first preset threshold;

[0066] determining a target scattering range from the scattering boundary spread function curve according to the product;

[0067] A scattering core radius is determined according to the target scattering range, the second tube voltage, and the product.

[0068] As can be seen from the above description, the calculation of the scattering kernel radius takes into account the imaging site, body thickness, and tube voltage. For thicker imaging sites, such as the waist and abdomen, the first preset threshold is set lower, resulting in a larger scattering kernel radius. For other sites with higher first preset thresholds, the scattering kernel radius is smaller. At the same time, the higher the imaging tube voltage, the larger the scattering kernel radius. This allows for processing of scattering over a wider range. The scattering kernel is determined based on the scattering kernel radius and the line spread function curve. The scattering kernel can change with changes in the imaging site, body thickness, and tube voltage, thereby achieving self-adaptation of the scattering kernel and ensuring that the scattering effect in medical images can be accurately and thoroughly eliminated in the future.

[0069] Furthermore, performing scatter correction on the medical image to be corrected based on the scatter kernel to obtain a corrected medical image includes:

[0070] Normalizing the scattering kernel to obtain a normalized scattering kernel;

[0071] Downsampling the medical image to be corrected to obtain a downsampled medical image to be corrected;

[0072] performing a convolution operation on the downsampled medical image to be corrected and the normalized scattering kernel to obtain a scattering component;

[0073] Determine a scattering ratio weight matrix according to a preset curve;

[0074] Performing scattering ratio weighting on the scattering components using the scattering ratio weight matrix to obtain weighted scattering components;

[0075] Scatter correction is performed on the downsampled medical image to be corrected according to the weighted scatter component, and upsampling is performed on the corrected downsampled medical image to be corrected to obtain a corrected medical image.

[0076] Furthermore, the scattered component S is:

[0077] S = PSF**I;

[0078] Wherein, PSF represents the normalized scattering kernel, I represents the downsampled medical image to be corrected, and ** represents the convolution operation;

[0079] The scattering ratio weight matrix R is:

[0080]

[0081] Wherein, M represents the first variation range parameter of the preset curve, N represents the second variation range parameter of the preset curve, Q represents the gain coefficient of the preset curve, and P represents the inflection point of the preset curve;

[0082] The weighted scattered component S' is:

[0083] S′=S*R;

[0084] The corrected and downsampled medical image to be corrected I p for:

[0085] I p =IS′.

[0086] From the above description, it can be seen that the scattering kernel is normalized, the medical image to be corrected is downsampled, and the downsampled medical image to be corrected is convolved with the normalized scattering kernel to obtain the scattering component, thereby realizing scattering estimation. The scattering ratio weight matrix is ​​determined according to a preset curve, and the scattering component is weighted by the scattering ratio weight matrix to obtain the weighted scattering component. The downsampled medical image to be corrected is scatter corrected according to the weighted scattering component, and upsampled after correction to obtain the corrected medical image. The normalization of the scattering kernel ensures that the image grayscale will not be changed when processing the flat grayscale value area of ​​the image. level, thereby ensuring the image quality of the medical image after scatter correction. The corrected medical image is downsampled to obtain a low-resolution downsampled medical image, which can improve the subsequent calculation efficiency. The scattering component obtained by scatter estimation is then weighted by the scattering ratio, mainly applying different scattering weights to different tissue densities in the imaging part, so as to improve the accuracy of the digital filter grid. The final upsampling operation restores the image to the same resolution as the original medical image, and finally obtains a medical image in which the scattering component is eliminated while only the direct ray effect is retained, thereby effectively eliminating the influence of scattering in the medical image.

[0087] Please refer to Figure 2 Another embodiment of the present invention provides a digital grid terminal, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, each step in the above-mentioned digital grid method is implemented.

[0088] The digital grid method and terminal described above in the present invention are applicable to medical images affected by scattering, and are primarily used in conventional digital X-ray imaging products. The program can be directly integrated into the imaging system software as an alternative to the physical grid function. It is also applicable to other X-ray imaging systems that use flat-panel detectors for imaging. The following describes a specific embodiment of the method:

[0089] Example 1

[0090] Please refer to Figure 1 、 2 -8. A digital grid method according to this embodiment includes:

[0091] S1. determining a simulated boundary diffusion function curve based on a preset scattering simulation model, and fitting the simulated boundary diffusion function curve to obtain a scattering model;

[0092] Wherein, the preset scattering simulation model is a physical model, such as Figure 3 As shown, the preset scattering simulation model includes a ray source 1, a lead plate 2, a flat panel detector 3, a phantom 4, and X-rays 5. The ray source 1 and the flat panel detector 3 form a shooting environment, and the source-image distance SID is set to 1.5 meters. The phantom 4 can be made of a material with radiation attenuation characteristics similar to that of the human body to simulate the human body. In this embodiment, PMMA (polymethyl methacrylate) is used as the phantom 4 to simulate the human body, and the distance between the phantom 4 and the flat panel detector 3 is set to 2 cm. At the same time, a lead plate 2 of a certain thickness is prepared to completely absorb the X-rays 5 in image acquisition and is placed on the PMMA phantom 4 so that it can cover half of the irradiation field to form a penumbra image. The commonly used high-voltage dose conditions are used, that is, the first tube voltage kV is 70, 80, 90, 100, and 110, and the PMMA phantoms with first body thicknesses of 10 cm, 12 cm, 14 cm, 16 cm, 18 cm, and 20 cm are photographed to obtain penumbra images under different scattering intensities and different phantom thicknesses.

[0093] Said S1 specifically includes:

[0094] S11, acquiring images of a preset scattering simulation model to obtain a penumbra image set;

[0095] S12, downsampling the penumbra image set to obtain a downsampled penumbra image set;

[0096] Specifically, since current radiological images all use large-format flat-panel detectors, in order to improve the overall image processing speed, the penumbra image set is downsampled by a factor of 2 to obtain a downsampled penumbra image set;

[0097] S13, determining a penumbra boundary direction from the downsampled penumbra image set;

[0098] S14, determining a simulated boundary diffusion function curve based on the downsampled penumbra image set and the penumbra boundary direction;

[0099] Specifically, a row (column) of pixel values ​​perpendicular to the penumbra boundary direction and located in the image centerline is extracted from each penumbra image in the downsampled penumbra image set, such as Figure 4 As shown, Figure 4 The penumbra curve captured by each first tube voltage when the first body thickness is 18 cm is obtained. The pixel values ​​corresponding to the shadow part under the lead plate are intercepted again for the extracted pixel values ​​of the row to generate a simulated boundary diffusion function curve, such as Figure 5 As shown in the figure, this part of the pixel values ​​is all formed by the scattering of X-rays when they pass through the other half of the PMMA phantom that is not covered by the lead plate;

[0100] The preset scattering simulation model includes a first parameter and a second parameter, the simulated boundary diffusion function curve is a simulated boundary diffusion function curve obtained under a preset number of different first tube voltages and different first body thicknesses, the simulated boundary diffusion function curve includes a scattering intensity and a scattering range, that is, a changing relationship between the scattering intensity and the scattering range, the scattering intensity is a pixel value, and the unit of the scattering range is a pixel. Then, fitting the simulated boundary diffusion function curve in S1 to obtain a scattering model includes:

[0101] S15. Determine corresponding first and second parameters based on the first tube voltage and the first body thickness;

[0102] S16, fitting the simulated boundary diffusion function curve based on the first parameter and the second parameter to obtain a scattering model;

[0103] Specifically, the scattering model is:

[0104] y=A*e B*x ;

[0105] Wherein, y represents the scattering intensity, x represents the scattering range, A represents the first parameter, and B represents the second parameter;

[0106] Since the first parameter has an obvious linear relationship with both the first tube voltage and the first body thickness, and the second parameter has a linear relationship only with the first body thickness, a first linear function is used to fit the linear relationship between the first parameter and the first tube voltage. The first linear function is:

[0107] A=t A _kV*kV+b A _kV;

[0108] Where, t A _kV represents the slope of the first parameter with the first tube voltage, kV represents the first tube voltage, b A _kV represents the intercept of the first parameter with the first tube voltage;

[0109] The study found that the slope and intercept of the first parameter with the first tube voltage in the fitting results are also linearly related to the first body thickness. Therefore, the second linear function and the third linear function are used to fit the linear relationship between the slope and intercept of the first tube voltage and the first body thickness. The second linear function is:

[0110] t A _kV=t_t A _kV_H*H+b_t A _kV_H;

[0111] Where t_t A _kV_H represents the first fitting parameter, b_t A _kV_H represents the second fitting parameter, and H represents the first body thickness;

[0112] The third linear function is:

[0113] b A _kV=t_b A _kV_H*H+b_b A _kV_H;

[0114] Where t_b A _kV_H represents the third fitting parameter, b_b A _kV_H represents the fourth fitting parameter;

[0115] The first fitting parameter and the second fitting parameter are t A _kV and H linear relationship, the third fitting parameter and the fourth fitting parameter are b A _Linear relationship between kV and H, t A _kV and b A _kV is the linear relationship between the first parameter A and the first tube voltage kV. Therefore, the first parameter A can be calculated based on kV and H.

[0116] The second parameter has only a linear relationship with the first body thickness, so the relationship with the first body thickness can be fitted using a fourth linear function. The fourth linear function is:

[0117] B=t B _H*H+b B _H;

[0118] Where, t B_H represents the fifth fitting parameter, b B _H represents the sixth fitting parameter;

[0119] Therefore, the second parameter B can be calculated based on H;

[0120] In summary, according to t B _H, b B _H, t_t A _kV_H, b_t A _kV_H, t_b A _kV_H and b_b A _kV_H can be used to calculate the first and second parameters through the actual tube voltage and body thickness, and the above fitting order is not important;

[0121] S2. receiving a scatter correction request for a medical image to be corrected;

[0122] S3, according to the scatter correction request, based on the scatter model and the medical image to be corrected, calculate a scattering boundary diffusion function curve corresponding to the medical image to be corrected, and determine a scattering kernel according to the scattering boundary diffusion function curve, such as Figure 6 As shown, specifically including:

[0123] S31. Acquire a second tube voltage and a second body thickness corresponding to the medical image to be corrected according to the scatter correction request;

[0124] The second tube voltage and the second body thickness are the tube voltage and body thickness corresponding to the actual shooting;

[0125] Since the specific thickness of the human body cannot be known in each actual photograph, a mapping relationship between the actual photographed human body thickness and the PMMA thickness in the scattering model is established by setting a preset body shape thickness comparison table. The preset body shape thickness comparison table sets the equivalent thickness of different PMMA phantoms according to different body shapes as the second body thickness for the actual photograph. The preset body shape thickness comparison table can be set according to actual conditions. In an optional embodiment, the preset body shape thickness comparison table includes PMMA equivalent thicknesses for different body shapes, such as obese, slightly obese, medium, slightly thin, and thin. For example, if the body shape of the patient corresponding to the medical image to be corrected is obese, the second body thickness corresponding to the "obese" body shape can be determined according to the preset body shape thickness comparison table.

[0126] S32. Calculate a scattering boundary diffusion function curve corresponding to the medical image to be corrected based on the scattering model, the second tube voltage, and the second body thickness;

[0127] S33, deriving the scattering boundary spread function curve to obtain a line spread function curve;

[0128] Specifically, the line spread function curve is as follows:

[0129] y = A * B * e B*x ;

[0130] S34. Determining the scatter kernel radius based on the scatter boundary diffusion function curve and the to-be-corrected medical image specifically includes:

[0131] S341. Obtaining the imaging part corresponding to the to-be-corrected medical image, and determining a first preset threshold according to the imaging part and the second body thickness;

[0132] S342. Determining the highest value corresponding to the scatter boundary diffusion function curve, and calculating the product of the highest value and the first preset threshold;

[0133] S343. Determining the target scatter range from the scatter boundary diffusion function curve according to the product;

[0134] Specifically, taking the x values in the scatter boundary diffusion function curve that are less than the product as the target scatter range;

[0135] S344. Determining the scatter kernel radius according to the target scatter range, the second tube voltage, and the product;

[0136] Specifically, taking the second preset threshold as a reference, dividing the second tube voltage by the second preset threshold as the weight of the second tube voltage, and then multiplying the weight by the target scatter range to obtain the scatter kernel radius;

[0137] In this embodiment, the second preset threshold is 100 kV;

[0138] S35. Determining the scatter kernel according to the scatter kernel radius and the line spread function curve;

[0139] Specifically, rotating the line spread function curve around a preset axis by a preset angle according to the scatter kernel radius r to form a scatter kernel;

[0140] In this embodiment, the preset axis is the y-axis, and the preset angle is 360°, that is, the part of the line spread function curve where 0 < x ≤ r rotates 360° around the y-axis to form a data matrix with a size of (2 * r + 1) * (2 * r + 1), that is, the scatter kernel;

[0141] In actual engineering implementation, circular correction also needs to be performed on the data matrix, that is, setting the values at the four corners of the matrix to 0, and only retaining the data within the inscribed circular range;

[0142] S4. Performing scatter correction on the to-be-corrected medical image based on the scatter kernel to obtain the corrected medical image, specifically including:

[0143] S41, normalizing the scattering kernel to obtain a normalized scattering kernel;

[0144] Specifically, all element values ​​in the scattering kernel are summed to obtain a total value, and each element value is divided by the total value to obtain a normalized scattering kernel;

[0145] S42, downsampling the medical image to be corrected to obtain a downsampled medical image to be corrected;

[0146] S43, performing a convolution operation on the downsampled medical image to be corrected and the normalized scattering kernel to obtain a scattering component;

[0147] Specifically, the scattered component S is:

[0148] S = PSF**I;

[0149] Wherein, PSF represents the normalized scattering kernel, I represents the downsampled medical image to be corrected, and ** represents the convolution operation;

[0150] S44, determining a scattering ratio weight matrix according to a preset curve;

[0151] Specifically, the scattering ratio weight matrix R is:

[0152]

[0153] Wherein, M represents the first variation range parameter of the preset curve, N represents the second variation range parameter of the preset curve, Q represents the gain coefficient of the preset curve, and P represents the inflection point of the preset curve;

[0154] In an optional embodiment, the preset curve is an S-curve. The prototype of the S-curve is the logistic curve in mathematics. By slightly modifying it, an S-curve function with a specified range is obtained. That is, the range of the original S-curve is (0, 1), and the range of the modified S-curve is (N, M+N). Q can control the speed of change of the curve, and the positive or negative value of Q will change the direction of the S-curve.

[0155] The higher the value of the obtained scattering ratio weight matrix R, the higher the scattering weight of the point, and the higher the retained weight of the scattering component S, and vice versa; since the energy of medical rays is not too high, the generated scattered rays and even higher-order scattered rays are difficult to penetrate the denser tissues of the human body and can only penetrate some lower-density tissues. Therefore, the area of ​​the S-curve corresponding to the low gray value of the image is set to a lower weight value, and the area of ​​the high gray value is set to a higher weight value. The S-curve of the scattering ratio weight matrix R is constructed as follows Figure 7As shown in Figure 2, in actual engineering implementation, the appropriate scattering ratio weight matrix R can be generated by adjusting parameters such as M, N, Q, and P to achieve a natural transition weight change that conforms to the grayscale characteristics.

[0156] S45, performing scattering ratio weighting on the scattering component using the scattering ratio weight matrix to obtain a weighted scattering component;

[0157] Specifically, the weighted scattered component S' is:

[0158] S′=S*R;

[0159] S46, performing scatter correction on the downsampled medical image to be corrected according to the weighted scatter component, and upsampling the corrected downsampled medical image to be corrected to obtain a corrected medical image;

[0160] Specifically, the corrected and downsampled medical image to be corrected I p for:

[0161] I p =IS′;

[0162] The upsampling is performed by linear interpolation. p Restore to original Figure 1 The resolution of the sample size is set and the image is output. The medical image to be corrected is as follows Figure 8 As shown in (a), the corrected medical image is as follows Figure 8 As shown in (b), it can be seen that the processed image has better contrast and more comprehensive details, which is more conducive to subsequent post-processing operations such as image enhancement;

[0163] Compared to physical grids, digital grids avoid the process of first capturing images with grid patterns and then performing de-gridding. Therefore, patients do not need to increase their imaging dose. Instead, they can be imaged directly at a standard dose. The program automatically performs scattered radiation suppression processing to remove scattered radiation effects from the image, resulting in a lower radiation dose for patients, which is more beneficial to their health.

[0164] The digital grid of the present invention does not require all the usage characteristics of a physical grid, such as complicated assembly and disassembly operations and usage methods, expensive development and maintenance costs, and related labor costs. The digital grid can be written into a computer as a set of program algorithms and used directly.

[0165] Example 2

[0166] Please refer to Figure 2A digital grid terminal of this embodiment includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, each step of the digital grid method of the first embodiment is implemented.

[0167] In summary, the present invention provides a digital grid method and terminal. The method determines a simulated boundary spread function curve based on a preset scattering simulation model, and fits the simulated boundary spread function curve to obtain a scattering model. The method receives a scattering correction request for a medical image to be corrected. The method obtains a second tube voltage and a second body thickness corresponding to the medical image to be corrected based on the scattering correction request. The method calculates a scattering boundary spread function curve corresponding to the medical image to be corrected based on the scattering model, the second tube voltage, and the second body thickness, and takes a derivative of the scattering boundary spread function curve to obtain a line spread function curve. The method determines a scattering kernel radius based on the scattering boundary spread function curve and the medical image to be corrected. The method determines a scattering kernel radius based on the scattering kernel radius and the line spread function curve. The calculation of the scattering kernel radius introduces a pulse width modulation (PWF) method. The imaging part, body thickness and tube voltage are taken into consideration, and a scattering kernel is determined according to the scattering kernel radius and the line spread function curve. The scattering kernel can change with changes in the imaging part, body thickness and tube voltage, thereby realizing the self-adaptation of the scattering kernel. Scatter correction is performed on the medical image to be corrected based on the scattering kernel to obtain a corrected medical image, thereby realizing a digital grid. Scatter correction is no longer performed solely based on the captured image, but rather a physical simulation model of scattered rays is analyzed to determine a simulated ESF curve, which is then fitted to obtain a scattering model. The scattering model can better reflect the physical effect of scattering. At the same time, scatter correction is performed by combining the scattering model with the captured medical image and the scattering kernel, thereby more closely fitting the actual scattering situation, more effectively and thoroughly suppressing the scattering effect in the medical image, and thus effectively eliminating the scattering effect in the medical image.

[0168] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent transformations made using the contents of the present invention's description and drawings, or directly or indirectly applied in related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A digital grid method, characterized in that: include: Determine a simulated boundary diffusion function curve based on a preset scattering simulation model, and fit the simulated boundary diffusion function curve to obtain a scattering model; receiving a scatter correction request for a medical image to be corrected; calculating, according to the scatter correction request, a scattering boundary diffusion function curve corresponding to the medical image to be corrected based on the scattering model and the medical image to be corrected, and determining a scattering kernel according to the scattering boundary diffusion function curve; performing scatter correction on the medical image to be corrected based on the scatter kernel to obtain a corrected medical image; Determining a simulated boundary diffusion function curve based on a preset scattering simulation model comprises: Acquire captured images of a preset scattering simulation model to obtain a penumbra image set; Downsampling the penumbra image set to obtain a downsampled penumbra image set; Determining a penumbra boundary direction from the downsampled penumbra image set; Determine a simulated boundary diffusion function curve based on the downsampled penumbra image set and the penumbra boundary direction; The preset scattering simulation model includes a first parameter and a second parameter, and the simulated boundary diffusion function curve is a simulated boundary diffusion function curve obtained under a preset number of different first tube voltages and different first body thicknesses; The fitting of the simulated boundary diffusion function curve to obtain a scattering model comprises: determining corresponding first and second parameters based on the first tube voltage and the first body thickness; Fitting the simulated boundary diffusion function curve based on the first parameter and the second parameter to obtain a scattering model; The step of calculating a scattering boundary diffusion function curve corresponding to the medical image to be corrected based on the scattering model and the medical image to be corrected according to the scattering correction request comprises: Acquire a second tube voltage and a second body thickness corresponding to the medical image to be corrected according to the scatter correction request; A scattering boundary diffusion function curve corresponding to the medical image to be corrected is calculated based on the scattering model, the second tube voltage and the second body thickness.

2. A digital grid method according to claim 1, characterized in that: The simulated boundary diffusion function curve includes scattering intensity and scattering range; The fitting of the simulated boundary diffusion function curve based on the first parameter and the second parameter to obtain a scattering model comprises: The scattering model is: ； In the formula, y represents the scattering intensity, x represents the scattering range, A represents the first parameter, and B represents the second parameter.

3. A digital grid method according to claim 1, characterized in that: Determining the scattering kernel according to the scattering boundary diffusion function curve comprises: Derivative the scattering boundary diffusion function curve to obtain a line diffusion function curve; Determine a scattering core radius based on the scattering boundary diffusion function curve and the medical image to be corrected; A scattering core is determined according to the scattering core radius and the line spread function curve.

4. A digital grid method according to claim 3, characterized in that: The determining of the scattering core radius based on the scattering boundary diffusion function curve and the medical image to be corrected comprises: Acquire a photographed part corresponding to the medical image to be corrected, and determine a first preset threshold value according to the photographed part and the second body thickness; Determine a maximum value corresponding to the scattering boundary diffusion function curve, and calculate a product of the maximum value and the first preset threshold; determining a target scattering range from the scattering boundary spread function curve according to the product; A scattering core radius is determined according to the target scattering range, the second tube voltage and the product.

5. A digital grid method according to claim 1, characterized in that: The performing scatter correction on the to-be-corrected medical image based on the scatter kernel to obtain a corrected medical image comprises: Normalizing the scattering kernel to obtain a normalized scattering kernel; Downsampling the medical image to be corrected to obtain a downsampled medical image to be corrected; Performing a convolution operation on the downsampled medical image to be corrected and the normalized scattering kernel to obtain a scattering component; Determine a scattering ratio weight matrix according to a preset curve; Using the scattering ratio weight matrix to weight the scattering component, so as to obtain a weighted scattering component; Scattering correction is performed on the downsampled medical image to be corrected according to the weighted scattering component, and upsampling is performed on the corrected downsampled medical image to be corrected to obtain a corrected medical image.

6. A digital grid method according to claim 5, characterized in that: The scattered component S is: ； Wherein, PSF represents the normalized scattering kernel, I represents the downsampled medical image to be corrected, and ** represents the convolution operation; The scattering ratio weight matrix R is: ； Wherein, M represents the first variation range parameter of the preset curve, N represents the second variation range parameter of the preset curve, Q represents the gain coefficient of the preset curve, and P represents the inflection point of the preset curve; The weighted scattered component S' is: ； The corrected medical image I p for: 。 7. A digital grid terminal, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, each step of the digital grid method according to any one of claims 1 to 6 is implemented.

Images