Cross-scattering correction method, device and computer equipment

Abstract

The application relates to a cross-scattering correction method, device and computer equipment, and relates to the technical field of medical imaging, and can improve the accuracy of cross-scattering correction results. The method is applied to a dual-source or multi-source CT imaging system, the dual-source or multi-source CT imaging system comprises at least two detectors, and the method comprises the following steps: acquiring a plurality of detection signal curves of the detectors respectively, the detection signal curves are determined based on detection signals collected by each detector for a scanning object; for each detector, a first convolution region corresponding to the detection signal curve of the detector is determined according to the boundary position characteristics of the detection signal curve of the detector, and scattering estimation information corresponding to the detector is determined according to the convolution result of the first convolution region and a preset convolution kernel; and cross-scattering correction results of each detector are determined according to the scattering estimation information corresponding to each detector.

Description

Technical Field

[0001] This application relates to the field of medical imaging technology, and in particular to a cross-scattering correction method, apparatus, and computer equipment. Background Technology

[0002] With the development of medical technology, dual-source CT imaging systems can now be used to acquire CT images. A dual-source CT imaging system consists of two X-ray tubes and detectors. The two X-ray tubes can scan the object from different angles, and the corresponding scan data is obtained through the two detectors. In dual-source CT imaging systems, cross-scattering is a physical factor that significantly affects image quality. Cross-scattering refers to the phenomenon where photons, after being scattered by the object, are transmitted to the lateral detectors.

[0003] In related technologies, when estimating and correcting the scattering signal in cross scattering, preset phantoms of different sizes and located at different eccentric positions are scanned in advance to obtain scattering signals under different conditions. During actual imaging, the size and position of the actual phantom are approximated with the size and position of various preset phantoms that have been recorded to determine the closest preset phantom and select its corresponding scattering signal. Then, scattering estimation is performed based on the scattering signal.

[0004] However, the above methods have high roughness and are difficult to obtain accurate cross-scattering correction results. Summary of the Invention

[0005] Therefore, it is necessary to provide a cross-scattering correction method, apparatus, computer equipment, computer-readable storage medium, and computer program product to address the aforementioned technical problems.

[0006] In a first aspect, this application provides a cross-scattering correction method applied to a dual-source or multi-source CT imaging system, the dual-source or multi-source CT imaging system comprising at least two detectors, the method comprising:

[0007] The detection signal curves of each of the multiple detectors are obtained, and the detection signal curves are determined based on the detection signals collected by each detector for the scanned object.

[0008] For each detector, based on the boundary position characteristics of the detector's detection signal curve, a first convolution region corresponding to the detection signal curve is determined, and based on the convolution result of the first convolution region and a preset convolution kernel, the scattering estimation information corresponding to the detector is determined.

[0009] Based on the scattering estimation information corresponding to each detector, the cross-scattering correction result of each detector is determined.

[0010] In one embodiment, determining the first convolution region corresponding to the detection signal curve based on the boundary position characteristics of the detector's detection signal curve includes:

[0011] Based on the boundary position characteristics of the detector's detection signal curve, a first start position and a first end position are determined in the detector channel direction of the detection signal curve, and a first edge is determined based on the first start position and the first end position;

[0012] A second edge with a length less than a preset curve amplitude threshold is determined in the signal intensity direction of the detection signal curve;

[0013] Based on the first edge and the second edge, the first convolution region corresponding to the detection signal curve is determined.

[0014] In one embodiment, determining the first convolution region corresponding to the detection signal curve based on the first edge and the second edge includes:

[0015] A rectangular region is determined based on the first edge and the second edge;

[0016] The first convolution region corresponding to the detection signal curve is obtained from the rectangular region.

[0017] In one embodiment, before determining the first convolution region corresponding to the detection signal curve based on the boundary position characteristics of the detector's detection signal curve, the method further includes:

[0018] Obtain a preset curve amplitude threshold; the curve amplitude threshold is less than the maximum amplitude of the detection signal curve;

[0019] From the detection signal curve, determine the curve points whose amplitude matches the curve amplitude threshold;

[0020] The boundary position characteristics of the detection signal curve are obtained based on the abscissa of the curve points.

[0021] In one embodiment, the preset convolutional kernel is determined through the following steps:

[0022] The main ray signal and cross-scattering signal collected by the target detector on the phantom are acquired; the target detector is any one of the plurality of detectors.

[0023] Based on the boundary position characteristics of the main ray signal curve corresponding to the main ray signal, the second convolution region corresponding to the main ray signal curve is determined; and based on the cross-scattering signal and the known phantom scattering parameters of the phantom, the scattering estimation information corresponding to the target detector is determined.

[0024] The scattering estimation information corresponding to the target detector is deconvolved based on the second convolution region to obtain a preset convolution kernel.

[0025] In one embodiment, determining the second convolution region corresponding to the main ray signal curve based on the boundary position features of the main ray signal curve corresponding to the main ray signal includes:

[0026] Based on the boundary position characteristics of the main ray signal curve corresponding to the main ray signal, a second starting position and a second ending position are determined in the detector channel direction of the main ray signal curve, and a third edge is determined based on the second starting position and the second ending position;

[0027] A fourth edge with a length less than a preset curve amplitude threshold is determined in the direction of the signal intensity of the main ray signal curve;

[0028] The second convolution region corresponding to the main ray signal curve is determined based on the third edge and the fourth edge.

[0029] In one embodiment, the first convolutional region includes the signal strength of each of the plurality of detector channels in the detector;

[0030] The step of determining the scattering estimation information corresponding to the detector based on the convolution result of the first convolution region and the preset convolution kernel includes:

[0031] For each detector channel in the first convolution region, the signal strength deviation of the detector channel is obtained based on the product of the signal strength of the detector channel and the preset convolution kernel.

[0032] The scattering estimation information corresponding to the detector is determined based on the summation of the signal strength deviations of the multiple detector channels.

[0033] In one embodiment, determining the cross-scattering correction result for each detector based on the scattering estimation information corresponding to each detector includes:

[0034] Obtain the signal strength of the detection signal acquired by each of the detectors;

[0035] For each detector, the signal strength is adjusted based on the scattering estimation information corresponding to the detector to obtain the adjusted signal strength;

[0036] Based on the adjusted signal strength of each detector, the cross-scattering correction result of each detector is obtained.

[0037] Secondly, this application also provides a cross-scattering correction device for use in a dual-source or multi-source CT imaging system, wherein the dual-source or multi-source CT imaging system includes at least two detectors, and the device includes:

[0038] The curve acquisition module is used to acquire the detection signal curves of each of the multiple detectors, and the detection signal curves are determined based on the detection signals collected by each detector for the scanned object.

[0039] The convolution module is used to determine, for each detector, a first convolution region corresponding to the detection signal curve based on the boundary position characteristics of the detector's detection signal curve, and to determine the scattering estimation information corresponding to the detector based on the convolution result of the first convolution region and the preset convolution kernel.

[0040] The correction result acquisition module is used to determine the cross-scattering correction result of each detector based on the scattering estimation information corresponding to each detector.

[0041] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the cross-scattering correction method as described in any of the preceding claims.

[0042] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the cross-scattering correction method as described in any of the preceding claims.

[0043] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the cross-scattering correction method as described in any of the preceding claims.

[0044] The aforementioned cross-scattering correction method, apparatus, computer equipment, computer-readable storage medium, and computer program product are applied to a dual-source or multi-source CT imaging system, which includes at least two detectors. In this method, the detection signal curves of multiple detectors can be acquired, and the detection signal curves are determined based on the detection signals acquired by each detector for the scanned object. Then, for each detector, a first convolution region corresponding to the detection signal curve is determined according to the boundary position characteristics of the detector's detection signal curve, and the scattering estimation information corresponding to the detector is determined according to the convolution result of the first convolution region and a preset convolution kernel. Furthermore, the cross-scattering correction result of each detector can be determined based on the scattering estimation information corresponding to each detector. In this application, on the one hand, the scattering estimation information corresponding to the detector is determined based on the convolution result of the first convolution region and the preset convolution kernel. This makes it unnecessary to approximate the actual phantom situation with a limited preset phantom situation during the estimation of cross scattering. Instead, scattering estimation can be performed directly according to the detection signal image corresponding to the scanned object and the determined first convolution region, ensuring that the scattering estimation information accurately matches the actual situation of the scanned object. On the other hand, this embodiment determines the first convolution region corresponding to the detection signal curve based on the boundary position characteristics of the detection signal curve, which can reduce the interference of the intensity change amplitude of the detection signal curve on the scattering estimation. Thus, the accuracy of cross scattering estimation can be effectively improved. Attached Figure Description

[0045] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1 This is a flowchart illustrating a cross-scattering correction method in one embodiment;

[0047] Figure 2a This is a schematic diagram of cross-scattering in a dual-source CT imaging system according to one embodiment;

[0048] Figure 2b This is a schematic diagram of cross-scattering in another dual-source CT imaging system in one embodiment;

[0049] Figure 3 This is a comparative schematic diagram of a detection signal curve in one embodiment;

[0050] Figure 4 This is a flowchart illustrating one step in determining a first convolutional region in one embodiment;

[0051] Figure 5a This is a schematic diagram of a first convolution region in one embodiment;

[0052] Figure 5b This is a schematic diagram of another first convolution region in one embodiment;

[0053] Figure 6 This is a schematic diagram of a shoulder structure in one embodiment;

[0054] Figure 7a This is a schematic diagram of a convolution process in one embodiment;

[0055] Figure 7b This is a schematic diagram of another convolution process in one embodiment;

[0056] Figure 8 This is a flowchart illustrating another cross-scattering correction method in one embodiment;

[0057] Figure 9 This is a structural block diagram of a cross-scattering correction device in one embodiment;

[0058] Figure 10 This is an internal structural diagram of a computer device in one embodiment;

[0059] Figure 11 This is an internal structural diagram of another computer device in one embodiment. Detailed Implementation

[0060] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0061] In one embodiment, such as Figure 1 As shown, a cross-scattering correction method is provided. This embodiment illustrates the application of this method to a dual-source or multi-source CT imaging system, wherein the dual-source or multi-source CT imaging system includes at least two detectors. It is understood that this method can also be applied to a server, and further to a system including both a dual-source or multi-source CT imaging system and a server, and is implemented through the interaction between the CT imaging system and the server. In this embodiment, the method includes the following steps:

[0062] S101, acquire the detection signal curves of multiple detectors respectively, the detection signal curves are determined based on the detection signals acquired by each detector for the scanned object.

[0063] In practice, the object can be scanned using a dual-source or multi-source CT imaging system.

[0064] The dual-source or multi-source CT imaging system can be a medical imaging device integrating two or more X-ray tube detectors. The scanned object can be any object for which CT images need to be acquired; for example, the scanned object can be one or more of the following: a living organism, tissue, or organ.

[0065] During the scanning process using a dual-source or multi-source CT imaging system, multiple detectors within the system can acquire signals, with each detector receiving a corresponding detection signal. The received signal can simultaneously contain both the primary X-ray signal and cross-scattered signals; alternatively, it can contain only the primary X-ray signal or only the cross-scattered signal. For example, by identifying the type of the received signal, the primary X-ray signal can be determined and used as the detection signal for subsequent analysis. Similarly, by appropriately closing and opening the matching and non-matching X-ray tubes, the detector can receive only the primary X-ray signal or only the cross-scattered signal.

[0066] Among them, the main X-ray signal refers to the signal sourced from the matched, opposite X-ray tube, while the cross-scattered signal refers to the signal scattered from the non-matched, side X-ray tube. For example, such as Figure 2a In the dual-source CT imaging system shown, X-ray tube 1 is paired with detector 1 on the opposite side, and X-ray tube 2 is paired with detector 2 on the opposite side. When detectors 1 and 2 are turned on simultaneously, if X-rays are emitted from X-ray tube 2, a portion of the rays can be received by detector 2; this portion of the signal is called the main X-ray signal. The other portion is cross-scattered and received by detector 1; this signal is called the cross-scattered signal. For example, ... Figure 2b In the dual-source CT imaging system shown, if X-rays are emitted from the X-ray tube 1, the detector 2 can receive the cross-scattered signal from the X-ray tube 1.

[0067] For each detector, a corresponding detection signal curve can be generated. In some examples, the detector channel can be used as the horizontal axis and the signal strength of the detection signal can be used as the vertical axis to generate the detection signal curve. The detection signal curve can characterize the signal strength of the detection signals received on multiple channels in the detector.

[0068] S102, for each detector, based on the boundary position characteristics of the detector's detection signal curve, determine the first convolution region corresponding to the detection signal curve, and based on the convolution result of the first convolution region and the preset convolution kernel, determine the scattering estimation information corresponding to the detector.

[0069] In related technologies, there are two main schemes for cross-scattering correction. One is to add an off-field detector to monitor the scattered signal. Simultaneously, the scattered signal within the field of view is considered a linear interpolation of the off-field signal. This scheme is feasible when the collimation is narrow, but as the collimation increases, the scattering distribution exhibits a complex two-dimensional appearance, and linear interpolation, or even higher-order interpolation, is insufficient to provide good scattering estimation results. The other scheme involves pre-scanning phantoms of different sizes and located at different eccentric positions to obtain scattering signals under different conditions. During actual imaging, the size and position of the scanned object are approximated with the sizes and positions of various phantoms with corresponding recorded scattering signals to determine the closest phantom and select its corresponding scattering signal. Then, scattering estimation is performed based on this scattering signal. This scheme has high roughness and poor correction effect.

[0070] In this embodiment, the convolution region corresponding to the detection signal curve can be determined. For ease of distinction, this convolution region is referred to as the first convolution region. After obtaining the first convolution region, a pre-defined convolution kernel can be used to perform a convolution operation on the first convolution region to obtain the corresponding convolution result. Then, the scattering estimation information corresponding to the detector can be determined based on the convolution result. The scattering estimation information can be a scattering distribution, for example, one or more elements such as the energy, spatial distribution, and intensity of the scattered photons received by the detector can be quantified and estimated, thereby using the obtained scattering distribution as the scattering estimation information. The process of performing a convolution operation on the first convolution region using a pre-defined convolution kernel can be understood as modeling the spatial propagation of scattering through a pre-defined convolution kernel, transforming the physical scattering process into operations such as neighborhood weighted summation in signal processing, thereby achieving efficient scattering estimation and correction. Since this embodiment can perform scattering estimation based on convolution operations, the scattering estimation process does not need to approximate the actual situation of the scanned object with the situation of a limited number of phantoms, but directly performs scattering estimation according to the actual projection value of the scanned object (i.e., the first convolution region corresponding to the detection signal curve), thus achieving better correction results.

[0071] In some exemplary embodiments, the convolution region can be determined based on the region enclosed by the signal curve and the horizontal axis in the coordinate system. In this method, the enclosed region is related to the boundaries of the signal curve and the amplitude of signal variation, for example, as... Figure 3The two probe signal curves shown can be acquired during different scanning processes. The amplitudes of change in probe signal curve 1 and probe signal curve 2 differ significantly. When determining the convolution region, the convolution region of probe signal curve 1 is determined based on the region formed by probe signal curve 1 and the X-axis, while the convolution region of probe signal curve 2 is determined based on the region formed by probe signal curve 2 and the X-axis. However, in practice, it has been found that the amplitude of signal variation contributes little to the estimation of cross-scattering. Considering the amplitude variation when determining the convolution region for subsequent processing increases computational load and may also affect the accuracy of cross-scattering estimation.

[0072] Based on this, in the process of determining the first convolution region in this embodiment, boundary analysis can be performed on the detector's signal curve to obtain boundary position features reflecting the boundary position of the signal curve. These boundary position features can be understood as features that characterize the intersection position of the signal curve with the horizontal or vertical axis of the coordinate system. They can accurately or approximately reflect the start and end positions of the signal curve in the signal image. Furthermore, the first convolution region for subsequent convolution operations can be determined based on these boundary position features. The first convolution region in this application can change accordingly with changes in the boundary region features; conversely, the first convolution region can remain unchanged when the boundary region features remain constant. For example, as... Figure 3 Although the variation amplitudes of the two detection signal curves shown are quite different, since the boundary positions of detection signal curves 1 and 2 are the same, the first convolution regions determined for detection signal curves 1 and 2 respectively can be the same or quite similar.

[0073] S103, Based on the scattering estimation information corresponding to each detector, determine the cross-scattering correction result for each detector.

[0074] After obtaining the scattering estimation information corresponding to each detector in step S102, the cross-scattering correction result for each detector can be obtained based on this information. Specifically, for each detector, the signal strength of the detection signal acquired by the detector can be corrected based on the scattering estimation information, and the resulting correction result is used as the cross-scattering correction result for that detector. For example, after obtaining the scattering estimation information of detector 1 based on its detection signal curve, the detection signal acquired by detector 1 is corrected using this information. Similarly, after obtaining the scattering estimation information of detector 2 based on its detection signal curve, the detection signal acquired by detector 2 is corrected using this information.

[0075] The aforementioned cross-scattering correction method can be applied to dual-source or multi-source CT imaging systems, which include at least two detectors. In this method, the detection signal curves of multiple detectors can be acquired, which are determined based on the detection signals acquired by the detectors for the scanned object. Then, for each detector, the first convolution region corresponding to the detection signal curve is determined according to the boundary position characteristics of the detector's detection signal curve, and the scattering estimation information corresponding to the detector is determined according to the convolution result of the first convolution region and the preset convolution kernel. Furthermore, the cross-scattering correction result of each detector can be determined based on the scattering estimation information corresponding to each detector. In this embodiment, on the one hand, the scattering estimation information corresponding to the detector is determined based on the convolution result of the first convolution region and the preset convolution kernel. This eliminates the need to approximate the situation of the scanned object with that of the finite phantom during the estimation of cross scattering. Instead, scattering estimation can be performed directly based on the detection signal image corresponding to the scanned object and the determined first convolution region, ensuring that the scattering estimation information accurately matches the actual situation of the scanned object. On the other hand, this embodiment determines the first convolution region corresponding to the detection signal curve based on the boundary position characteristics of the detection signal curve, which reduces the interference of the intensity change amplitude of the detection signal curve on the scattering estimation. Thus, the accuracy of cross scattering estimation can be effectively improved.

[0076] Furthermore, the cross-scattering correction method provided in this embodiment can directly perform scattering estimation and correction on the original data (i.e., the detection signal curve determined based on the detection signal), without the need to reconstruct the image before scattering estimation. This saves computing resources and significantly improves the correction speed, making the cross-scattering correction faster.

[0077] In one exemplary embodiment, such as Figure 4 As shown, in step S102, determining the first convolution region corresponding to the detector signal curve based on the boundary position characteristics of the detector's detection signal curve may include the following steps:

[0078] S401, based on the boundary position characteristics of the detector's detection signal curve, determine the first starting position and the first ending position in the detector channel direction of the detection signal curve, and determine the first edge based on the first starting position and the first ending position.

[0079] Specifically, the detection signal curve can be recorded in a two-dimensional coordinate system, which can be composed of mutually perpendicular detector channel directions and signal intensity directions. This coordinate system can be used to describe the intensity changes of the detection signals received by different channels in the detector.

[0080] Meanwhile, the boundary position characteristics of the detection signal curve may include the start position and / or end position of the detection signal curve, or other positions that differ from the start position and / or end position of the curve by a preset distance.

[0081] Accordingly, in this step, the start and end positions can be determined in the detector channel direction based on the boundary position characteristics of the detection signal curve. For ease of distinction, these start and end positions are referred to as the first start position and the first end position. Then, the corresponding region edges are determined based on the first start position and the first end position. For ease of distinction, the region edges determined based on the first start position and the first end position are referred to as the first edges. The first edges can limit the span of the first convolution region in the detector channel direction.

[0082] S402, determine a second edge with a length less than a preset curve amplitude threshold in the signal intensity direction of the detection signal curve.

[0083] As mentioned earlier, cross-scattering estimation and correction primarily relate to the boundaries (or span) of the probe signal curve, and are insensitive to the amplitude of changes in the probe signal curve along the signal intensity direction. Directly determining the convolution region based on the amplitude of changes in the probe signal curve along the signal intensity direction may introduce redundant resource consumption and affect the accuracy of the cross-scattering results. Therefore, in this embodiment, a curve amplitude threshold can be predetermined, allowing for the removal of regions above the threshold or a reduction in the weight of regions above the threshold. Simultaneously, the first convolution region is determined based on the regions below the curve amplitude threshold.

[0084] In some exemplary embodiments, the curve amplitude threshold can be an empirical value, which can be determined based on multiple test results or experimental results. For example, given a preset convolution kernel and target scattering estimation information as a reference, multiple curve amplitude thresholds can be set, and the corresponding scattering estimation information can be calculated based on each curve amplitude threshold. By determining the difference between each scattering estimation information and the target scattering estimation information, the curve amplitude threshold corresponding to the smallest difference can be determined.

[0085] Furthermore, after obtaining the detection signal curve, the edge of the detection signal curve in the signal intensity direction can be determined according to a preset curve amplitude threshold. For ease of distinction, the edge determined according to the curve amplitude threshold is called the second edge, and the length of the second edge is less than the curve amplitude threshold. For example, the distance corresponding to the curve amplitude threshold in the signal intensity direction can be determined as the second edge.

[0086] S403, determine the first convolution region corresponding to the detection signal curve based on the first edge and the second edge.

[0087] After obtaining the first edge and the second edge, since the first edge defines the span of the first convolution region in the detector channel direction and the second edge defines the amplitude of the first convolution region in the signal intensity direction, the first convolution region can be determined based on the first edge and the second edge.

[0088] In this embodiment, a first edge is determined in the detector channel direction based on a first starting position and a first ending position, and a second edge with a length less than a preset curve amplitude threshold is determined in the signal intensity direction. Then, a first convolution region is determined based on the first and second edges. On the one hand, this can accurately define the horizontal range matching the boundary of the detection signal curve in the detector channel direction, which is convenient for subsequent signal analysis focusing on specific spatial locations (such as specific detector channels). On the other hand, it can focus only on the signal portion with amplitude changes within a certain range, eliminate irrelevant signal interference, and reduce the impact of the change amplitude of the detection signal curve on cross-scattering estimation. Compared with convolving the entire detection signal curve and the range enclosed by the horizontal coordinate, determining the first convolution region in this embodiment can reduce the amount of computation, while highlighting the features of the signal of interest, making the convolution result more reflective of the key information of the signal, which helps in the subsequent understanding, analysis and processing of the signal, and improves the accuracy and efficiency of subsequent analysis.

[0089] In an exemplary embodiment, in step S403, determining the first convolution region corresponding to the detection signal curve based on the first edge and the second edge may include the following steps:

[0090] Based on the first edge and the second edge, a rectangular region is determined; based on the rectangular region, the first convolution region corresponding to the detection signal curve is obtained.

[0091] Specifically, the first edge is the range defined by the first start position and the first end position in the direction of the detector channel, which can limit the range of the detector channel. Meanwhile, the second edge is the range determined in the direction of signal strength according to the curve amplitude threshold, which can limit the range of signal strength amplitude. By combining the first edge and the second edge, a rectangular region can be formed.

[0092] Furthermore, the first convolution region corresponding to the probe signal curve can be determined based on this rectangular region. In some examples, the region enclosed by the probe signal curve and the horizontal axis in the coordinate system can be determined, and the first convolution region can be determined based on the intersection of this enclosed region and the rectangular region. For example, as shown... Figure 5a and Figure 5b As shown, the first convolution region 501 and the first convolution region 502 can be obtained in this way.

[0093] In this embodiment, by determining the first convolution region based on the rectangular area defined by the first edge and the second edge, irrelevant background or unimportant amplitude variation parts that may exist in the signal can be quickly removed, so that subsequent convolution operations can focus more on detecting the core information of the signal. Moreover, this method is simple and convenient, and can quickly obtain the first convolution region, thereby improving the processing efficiency of cross scattering correction.

[0094] In an exemplary embodiment, before determining the first convolution region corresponding to the detector signal curve based on the boundary position characteristics of the detector's detector signal curve, the following steps may be included:

[0095] Obtain a preset curve amplitude threshold; the curve amplitude threshold is less than the maximum amplitude of the detection signal curve; from the detection signal curve, determine the curve points whose amplitude matches the curve amplitude threshold; based on the abscissa of the curve points, obtain the boundary position characteristics of the detection signal curve.

[0096] In practical applications, a curve amplitude threshold can be set based on the processed detection signal curve and related prior indications. In some examples, this threshold is less than the maximum amplitude of any detection signal curve. Personnel can determine a suitable threshold through multiple tests, which will not be elaborated here. By ensuring the curve amplitude threshold is less than the maximum amplitude of any detection signal curve, the threshold is kept within a reasonable range. Specifically, if the threshold is greater than or equal to the maximum amplitude of the detection signal curve, it becomes difficult to effectively filter and analyze the signal. Ensuring the threshold is less than the maximum amplitude helps distinguish the effects of different amplitude components in the detection signal.

[0097] Then, points whose amplitudes match the curve amplitude threshold, i.e., curve points, can be determined from the probe signal curve. In some exemplary embodiments, points in the probe signal curve whose signal amplitudes match the curve amplitude threshold can be used as matching curves. For example, if the curve amplitude threshold is h, a straight line with height h and balanced on the horizontal axis of the coordinate system can be drawn, and the intersection of this line and the probe signal curve can be determined as the matching curve point. Of course, in other embodiments, points in the probe signal curve (e.g., all points or some points) can be compared with a preset curve amplitude threshold. When the amplitude of a certain point is equal to or close to (e.g., the difference between the two is less than the threshold) the curve amplitude threshold, it can be determined as a matching curve point.

[0098] Furthermore, the boundary position features of the detection signal curve can be obtained based on the abscissa of the curve points. In some embodiments, if there are two matching curve points, these two points can be determined as boundary position features; if there are more than two matching curve points, the first and last curve points can be determined based on their abscissas, and these two points can then be determined as boundary position features.

[0099] In this embodiment, by setting a curve amplitude threshold that is less than the maximum amplitude of the detection signal curve, the corresponding curve points are determined accordingly. This allows focusing on points in the detection signal whose amplitude is below the curve amplitude threshold, thereby reducing the interference of the detection signal curve amplitude on cross-scattering estimation and correction, and accurately identifying boundary position features that reflect the boundary position of the detection signal curve.

[0100] In one exemplary embodiment, the detection signal curve may include sub-signal curves corresponding to at least two tissue structures of the scanned object, for example in Figure 6 The schematic diagram of the shoulder structure shown may include sub-signal curves corresponding to the neck and both arms; multiple sub-signal curves are separated from each other. Accordingly, in step S102, determining the first convolution region corresponding to the detector signal curve based on the boundary position characteristics of the detector's detection signal curve may include:

[0101] For each sub-signal curve, the first convolution region corresponding to the sub-signal curve is determined based on the boundary position characteristics of the sub-signal curve.

[0102] In practical applications, the detection signal curve may include sub-signal curves corresponding to at least two tissue structures of the scanned object. For example, Figure 6 A schematic diagram of a shoulder structure is shown, in which the central structure is the neck, the structures on the left and right sides are the raised arms, and the lower arc-shaped structure is the headrest. Figure 2a In a cross-scattering scenario, with both X-ray tube 1 and X-ray tube 2 turned on simultaneously, such as Figure 7a As shown, the detection signal curves corresponding to the detection signals received by detector 1 can be used to obtain three sub-signal curves 701 corresponding to the arm, neck, and arm in sequence.

[0103] Furthermore, for each of the three sub-signal curves, the boundary position features of the sub-signal curve can be determined, and the first convolution region corresponding to the sub-signal curve can be determined based on these boundary position features. The method for determining the boundary position features of the sub-signal curve and the method for determining the first convolution region can be found in the description of determining the boundary position features and the first convolution region of the probe signal curve in the previous embodiment, and will not be repeated here. For example, as... Figure 7a As shown, the first convolution region of each of the three sub-signal curves can be obtained, which is the rectangular region enclosed by the dashed line and the X-axis in the figure. The scattering distribution signal shown in 702 is obtained through the convolution operation.

[0104] On the other hand, combining Figure 2b In the cross-scattering scenario, with both X-ray tube 1 and X-ray tube 2 turned on simultaneously, the curve of the detection signal received by detector 2 is as follows: Figure 7bAs shown in 703, since detector 2 is in the same direction as the arm, neck and X-ray tube, a detection signal curve is obtained at this time. The processing is as described above. After determining the first convolution region and performing the convolution operation, the scattering distribution signal shown in 704 can be obtained.

[0105] In this embodiment, by determining the boundary position features of each sub-signal curve and determining the first convolution region corresponding to each sub-signal curve based on the boundary position features of each sub-signal curve, targeted analysis can be performed on the detection signal curve corresponding to each segment of soft tissue, thereby improving the recognition accuracy of the first convolution region.

[0106] Convolution operations involve the use of a preset convolution kernel, which can be determined by measurement or simulation. In an exemplary embodiment, the preset convolution kernel is determined through the following steps:

[0107] S1, acquire the main ray signal and cross-scattering signal collected by the target detector on the phantom; the target detector is any one of multiple detectors.

[0108] In practice, a multi-source CT imaging system can be used to scan the phantom. The phantom can be any phantom with known scattering parameters. In some examples, the phantom can be a water film. During scanning, a water film with known dimensions and relevant phantom scattering parameters can be placed at the center of rotation, or it can be placed at other locations. During the scanning process, the target detector in the multi-source CT imaging system can acquire signals, obtaining the main ray signal and cross-scattering signal acquired for the preset phantom.

[0109] Taking a dual-source CT imaging system as an example, X-ray tube 1 is paired with detector 1, and X-ray tube 2 is paired with detector 2. On one hand, X-ray tube 1 can be turned on and the signal of detector 2 can be measured. At this time, since X-ray tube 2 is not turned on, detector 2 only receives cross-scattered signals. On the other hand, X-ray tube 2 can be turned on and X-ray tube 1 can be turned off, and the signal of detector 2 can be measured. At this time, only the main X-ray signal is received.

[0110] S2, based on the boundary position characteristics of the main ray signal curve corresponding to the main ray signal, determine the second convolution region corresponding to the main ray signal curve, and based on the cross-scattering signal and the known phantom scattering parameters of the phantom, determine the scattering estimation information corresponding to the target detector.

[0111] In this step, on the one hand, the main ray signal curve corresponding to the main ray signal can be determined. Then, boundary analysis can be performed on the main ray signal curve to obtain its boundary position characteristics. Based on these boundary position characteristics, the convolution region of the main ray signal curve can be determined. For ease of distinction, this convolution region is referred to as the second convolution region. On the other hand, since the phantom's scattering parameters are known, the scattering estimation information corresponding to the target detector can be calculated based on the cross-scattering signal obtained by the target detector and the known phantom scattering parameters.

[0112] S3, deconvolve the scattering estimation information corresponding to the target detector based on the second convolution region to obtain the preset convolution kernel.

[0113] Furthermore, the scattering estimation information corresponding to the target detector can be deconvolved based on the second convolution region. The deconvolution process can be understood as the inverse operation of the convolution process. Thus, the preset convolution kernel used for subsequent convolution processing can be determined based on the calculation results obtained from the deconvolution process.

[0114] In this embodiment, by scanning a preset phantom with known scattering parameters, the second convolution region and scattering estimation information are determined based on the obtained main ray signal and cross scattering signal. Then, deconvolution processing is performed to obtain a preset convolution kernel that can accurately describe the actual scattering process, thereby improving the accuracy of subsequent cross scattering correction.

[0115] In one embodiment, step S2 may include the following processing:

[0116] S21, based on the boundary position characteristics of the main ray signal curve corresponding to the main ray signal, determine the second starting position and the second ending position in the detector channel direction of the main ray signal curve, and determine the third edge based on the second starting position and the second ending position.

[0117] In practical applications, the main ray signal curve can be recorded in a two-dimensional coordinate system. The boundary position characteristics of the main ray signal curve can include the curve's start position and / or end position, or other positions differing from the curve's start position and / or end position by a preset distance. In this step, the start position and end position can be determined in the detector channel direction based on the boundary position characteristics of the main ray signal curve. For ease of distinction, these start and end positions are referred to as the second start position and the second end position.

[0118] Then, the corresponding region edges are determined based on the second start position and the second end position. For ease of distinction, the region edges determined based on the second start position and the second end position are called the third edges. The third edges can limit the span of the second convolution region in the detector channel direction.

[0119] S22, determine a fourth edge with a length less than a preset curve amplitude threshold in the signal intensity direction of the main ray signal curve.

[0120] In this step, the edge of the main ray signal curve in the signal intensity direction can be determined based on a preset curve amplitude threshold. This curve amplitude threshold can be the same as the curve amplitude threshold used when determining the first convolution region. For ease of distinction, the edge determined in this step is referred to as the fourth edge, and the length of the fourth edge is less than the curve amplitude threshold. For example, the distance corresponding to the curve amplitude threshold in the signal intensity direction can be determined as the fourth edge.

[0121] S23, based on the third and fourth edges, determine the second convolution region corresponding to the main ray signal curve.

[0122] After obtaining the third and fourth edges, since the third edge defines the span of the second convolution region in the detector channel direction and the fourth edge defines the amplitude of the second convolution region in the signal intensity direction, the second convolution region can be determined based on the third and fourth edges.

[0123] In this embodiment, by determining the second convolution region according to the same convolution region determination method, on the one hand, the interference of the signal curve amplitude on the cross-scattering correction result can be reduced, and the computational resource overhead can be reduced. On the other hand, the matching between the preset convolution kernel obtained by subsequent calculation and the actual correction process and the first convolution region can be improved, thereby improving the accuracy of the obtained scattering estimation information.

[0124] It is understood that the process of determining the second convolution region can be the same as the process of determining the first convolution region. For specific processing, please refer to the aforementioned embodiments, which will not be repeated here.

[0125] In an exemplary embodiment, the first convolution region includes the signal strength of each of the multiple detector channels in the detector. It can be understood that by determining the first convolution region as described above, the signal strength of each detector channel can be controlled within a certain amplitude range. In step S102, determining the scattering estimation information corresponding to the detector based on the convolution result of the first convolution region and the preset convolution kernel may include the following steps:

[0126] For each detector channel in the first convolution region, the signal strength deviation of the detector channel is obtained by multiplying the signal strength of the detector channel with the preset convolution kernel; the scattering estimation information corresponding to the detector is determined by summing the signal strength deviations of multiple detector channels.

[0127] In practical applications, convolution operations can be performed along the detector channel direction for the first convolution region. Specifically, for each detector channel in the first convolution region, the signal strength of that detector channel can be multiplied by a preset convolution kernel, and the result of the multiplication can be used as the signal strength deviation of that detector channel. Furthermore, the signal strength deviations of multiple detector channels can be summed, and the summation result can be used as the scattering estimation information corresponding to the detectors in the multiple detector channels.

[0128] In some examples, scattering estimation information can be determined as follows: :

[0129]

[0130] in, The predefined convolution kernel can be related to the rotation angle. Related functions, To the corresponding rotation angle The signal strength corresponding to the detector channel that needs to be calibrated.

[0131] In this embodiment, on the one hand, the signal strength deviation can be calculated independently for each detector channel, which can accurately capture the signal differences between different channels. Since the effect of scattering on each channel of the detector is random and individual, analyzing each channel separately can pinpoint the signal anomaly of each channel in detail, providing more accurate basic data for subsequent correction. On the other hand, by multiplying the signal strength with a preset convolution kernel, the signal change caused by scattering is transformed into a specific numerical deviation, making the originally abstract scattering effect measurable and analyzable, providing clear numerical basis for subsequent image correction, and ensuring that the correction operation is targeted and conforms to the actual signal change law.

[0132] In an exemplary embodiment, step S103, determining the cross-scattering correction result for each detector based on the scattering estimation information corresponding to each detector, may include the following steps:

[0133] The signal strength of the detection signal acquired by each detector is obtained; for each detector, the signal strength is adjusted according to the scattering estimation information corresponding to the detector to obtain the adjusted signal strength; based on the adjusted signal strength of each detector, the cross-scattering correction result of each detector is obtained.

[0134] In practice, the signal strength of the detection signal acquired by each detector can be determined. This signal strength can be the signal strength of all detection signals actually received by the detector (i.e., including the main ray signal and the cross-scattering signal).

[0135] Since the scattering estimation information for each detector has been obtained, the signal strength of each detector can be adjusted using this scattering estimation information. In some embodiments, the scattering estimation information can be superimposed on the signal strength to obtain the adjusted signal strength. For example, signal superposition can be performed in the following manner:

[0136]

[0137] in, The adjusted signal strength, To adjust the signal strength of the detection signal acquired by the previous detector. This provides information for scattering estimation.

[0138] Furthermore, the adjusted signal strength of each detector can be used as the cross-scattering correction result for each detector. Alternatively, the adjusted signal strength can be converted into corrected projection data, and the corrected projection data can be used as the cross-scattering correction result.

[0139] In this embodiment, the signal strength of each detector can be differentiated and targeted based on the scattering estimation information of each detector obtained in the early stage. Since different detectors are affected by cross scattering to different degrees, this adjustment method can specifically counteract the interference of scattering on the signal, eliminate the interference added to the signal by scattering, and make the signal closer to the true physical attenuation value, thus laying a solid data foundation for high-quality imaging.

[0140] To enable those skilled in the art to better understand the above steps, the following example illustrates the embodiments of this application, but it should be understood that the embodiments of this application are not limited thereto.

[0141] like Figure 8 As shown, this example includes the following steps:

[0142] S801 acquires the main ray signal and cross-scattering signal obtained by the target detector in a dual-source or multi-source CT imaging system from the water film.

[0143] S802, based on the boundary position characteristics of the main ray signal curve corresponding to the main ray signal, determines the second convolution region corresponding to the main ray signal curve, and based on the cross scattering signal and the known phantom scattering parameters of the water film, determines the scattering estimation information corresponding to the target detector.

[0144] S803, deconvolve the scattering estimation information corresponding to the target detector based on the second convolution region to obtain the preset convolution kernel.

[0145] S804, acquire the detection signal curves of multiple detectors respectively. The detection signal curves are determined based on the detection signals acquired by the detectors for the scanned object in a dual-source or multi-source CT imaging system.

[0146] S805, for each detector, based on the boundary position characteristics of the detector's detection signal curve, determine a first start position and a first end position in the detector channel direction, determine a first edge based on the first start position and the first end position, determine a second edge in the signal intensity direction with a length less than a preset curve amplitude threshold, determine a first convolution region corresponding to the detection signal curve based on the first edge and the second edge, and determine scattering estimation information based on the convolution result of the first convolution region and the preset convolution kernel.

[0147] S806 determines the cross-scattering correction result for each detector based on the scattering estimation information corresponding to each detector.

[0148] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0149] Based on the same inventive concept, this application also provides a cross-scattering correction device for implementing the cross-scattering correction method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more cross-scattering correction device embodiments provided below can be found in the limitations of the cross-scattering correction method described above, and will not be repeated here.

[0150] In one exemplary embodiment, such as Figure 9 As shown, a cross-scattering correction device is provided for use in a dual-source or multi-source CT imaging system, the dual-source or multi-source CT imaging system including at least two detectors, the device comprising:

[0151] The curve acquisition module 901 is used to acquire the detection signal curves of each of the multiple detectors, wherein the detection signal curves are determined based on the detection signals collected by each detector for the scanned object.

[0152] The convolution module 902 is used to determine, for each detector, a first convolution region corresponding to the detection signal curve based on the boundary position characteristics of the detector's detection signal curve, and to determine the scattering estimation information corresponding to the detector based on the convolution result of the first convolution region and the preset convolution kernel.

[0153] The correction result acquisition module 903 is used to determine the cross-scattering correction result of each detector based on the scattering estimation information corresponding to each detector.

[0154] In one embodiment, the convolution module 902 is used for:

[0155] Based on the boundary position characteristics of the detector's detection signal curve, a first start position and a first end position are determined in the detector channel direction of the detection signal curve, and a first edge is determined based on the first start position and the first end position;

[0156] A second edge with a length less than a preset curve amplitude threshold is determined in the signal intensity direction of the detection signal curve;

[0157] Based on the first edge and the second edge, the first convolution region corresponding to the detection signal curve is determined.

[0158] In one embodiment, the convolution module 902 is used for:

[0159] A rectangular region is determined based on the first edge and the second edge;

[0160] The first convolution region corresponding to the detection signal curve is obtained from the rectangular region.

[0161] In one embodiment, the convolution module 902 is further configured to:

[0162] Obtain a preset curve amplitude threshold; the curve amplitude threshold is less than the maximum amplitude of the detection signal curve;

[0163] From the detection signal curve, determine the curve points whose amplitude matches the curve amplitude threshold;

[0164] The boundary position characteristics of the detection signal curve are obtained based on the abscissa of the curve points.

[0165] In one embodiment, the detection signal curve includes sub-signal curves corresponding to at least two tissue structures of the scanned object, and the multiple sub-signal curves are separated from each other;

[0166] Determining the first convolution region corresponding to the detection signal curve based on the boundary position characteristics of the detector's detection signal curve includes:

[0167] For each of the sub-signal curves, the first convolution region corresponding to the sub-signal curve is determined based on the boundary position characteristics of the sub-signal curve.

[0168] In one embodiment, the apparatus further includes a kernel determination module, the kernel determination module being configured to:

[0169] The main ray signal and cross-scattering signal collected by the target detector on the phantom are acquired; the target detector is any one of the plurality of detectors.

[0170] Based on the boundary position characteristics of the main ray signal curve corresponding to the main ray signal, the second convolution region corresponding to the main ray signal curve is determined; and based on the cross-scattering signal and the known phantom scattering parameters of the phantom, the scattering estimation information corresponding to the target detector is determined.

[0171] The scattering estimation information corresponding to the target detector is deconvolved based on the second convolution region to obtain a preset convolution kernel.

[0172] In one embodiment, the kernel determination module is used to:

[0173] Based on the boundary position characteristics of the main ray signal curve corresponding to the main ray signal, a second starting position and a second ending position are determined in the detector channel direction of the main ray signal curve, and a third edge is determined based on the second starting position and the second ending position;

[0174] A fourth edge with a length less than a preset curve amplitude threshold is determined in the direction of the signal intensity of the main ray signal curve;

[0175] The second convolution region corresponding to the main ray signal curve is determined based on the third edge and the fourth edge.

[0176] In one embodiment, the first convolutional region includes the signal strength of each of the plurality of detector channels in the detector;

[0177] The convolution module is used for:

[0178] For each detector channel in the first convolution region, the signal strength deviation of the detector channel is obtained based on the product of the signal strength of the detector channel and the preset convolution kernel.

[0179] The scattering estimation information corresponding to the detector is determined based on the summation of the signal strength deviations of the multiple detector channels.

[0180] In one embodiment, the correction result acquisition module is configured to:

[0181] Obtain the signal strength of the detection signal acquired by each of the detectors;

[0182] For each detector, the signal strength is adjusted based on the scattering estimation information corresponding to the detector to obtain the adjusted signal strength;

[0183] Based on the adjusted signal strength of each detector, the cross-scattering correction result of each detector is obtained.

[0184] Each module in the aforementioned cross-scattering correction device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0185] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 10 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs in the non-volatile storage media to run. The database stores signal data acquired by the detector. The I / O interfaces are used for information exchange between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When executed by the processor, the computer program implements a cross-scattering correction method.

[0186] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 11As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When executed by the processor, the computer program implements a cross-scattering correction method. The display unit is used to form a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0187] Those skilled in the art will understand that Figure 10 and Figure 11 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0188] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0189] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps in the above method embodiments.

[0190] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0191] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0192] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0193] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0194] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A cross-scattering correction method applied to a dual-source or multi-source CT imaging system, wherein the dual-source or multi-source CT imaging system comprises at least two detectors, characterized in that, The method includes: The detection signal curves of each of the multiple detectors are obtained, and the detection signal curves are determined based on the detection signals collected by each detector for the scanned object. For each detector, based on the boundary position characteristics of the detector's detection signal curve, a first start position and a first end position are determined in the detector channel direction of the detection signal curve. A first edge is determined based on the first start position and the first end position. A second edge with a length less than a preset curve amplitude threshold is determined in the signal intensity direction of the detection signal curve. A first convolution region corresponding to the detection signal curve is determined based on the first edge and the second edge. The scattering estimation information corresponding to the detector is determined based on the convolution result of the first convolution region and a preset convolution kernel. The preset convolution kernel is used to characterize the spatial propagation of scattering. Based on the scattering estimation information corresponding to each detector, the cross-scattering correction result of each detector is determined.

2. The method according to claim 1, characterized in that, Determining the first convolution region corresponding to the detection signal curve based on the first edge and the second edge includes: A rectangular region is determined based on the first edge and the second edge; The first convolution region corresponding to the detection signal curve is obtained from the rectangular region.

3. The method according to claim 1, characterized in that, Before determining the first start position and the first end position in the detector channel direction of the detector signal curve based on the boundary position characteristics of the detector's detection signal curve, the method further includes: Obtain a preset curve amplitude threshold; the curve amplitude threshold is less than the maximum amplitude of the detection signal curve; From the detection signal curve, determine the curve points whose amplitude matches the curve amplitude threshold; The boundary position characteristics of the detection signal curve are obtained based on the abscissa of the curve points.

4. The method according to claim 1, characterized in that, The preset convolutional kernel is determined through the following steps: The main ray signal and cross-scattering signal collected by the target detector on the phantom are acquired; the target detector is any one of the plurality of detectors. Based on the boundary position characteristics of the main ray signal curve corresponding to the main ray signal, the second convolution region corresponding to the main ray signal curve is determined; and based on the cross-scattering signal and the known phantom scattering parameters of the phantom, the scattering estimation information corresponding to the target detector is determined. The scattering estimation information corresponding to the target detector is deconvolved based on the second convolution region to obtain a preset convolution kernel.

5. The method according to claim 4, characterized in that, The step of determining the second convolution region corresponding to the main ray signal curve based on the boundary position characteristics of the main ray signal curve corresponding to the main ray signal includes: Based on the boundary position characteristics of the main ray signal curve corresponding to the main ray signal, a second starting position and a second ending position are determined in the detector channel direction of the main ray signal curve, and a third edge is determined based on the second starting position and the second ending position; A fourth edge with a length less than a preset curve amplitude threshold is determined in the direction of the signal intensity of the main ray signal curve; The second convolution region corresponding to the main ray signal curve is determined based on the third edge and the fourth edge.

6. The method according to claim 1, characterized in that, The first convolution region includes the signal strength of each of the multiple detector channels in the detector; The step of determining the scattering estimation information corresponding to the detector based on the convolution result of the first convolution region and the preset convolution kernel includes: For each detector channel in the first convolution region, the signal strength deviation of the detector channel is obtained based on the product of the signal strength of the detector channel and the preset convolution kernel. The scattering estimation information corresponding to the detector is determined based on the summation of the signal strength deviations of the multiple detector channels.

7. The method according to any one of claims 1 to 6, characterized in that, The step of determining the cross-scattering correction result for each detector based on the scattering estimation information corresponding to each detector includes: Obtain the signal strength of the detection signal acquired by each of the detectors; For each detector, the signal strength is adjusted based on the scattering estimation information corresponding to the detector to obtain the adjusted signal strength; Based on the adjusted signal strength of each detector, the cross-scattering correction result of each detector is obtained.

8. A cross-scattering correction device, applied to a dual-source or multi-source CT imaging system, said dual-source or multi-source CT imaging system comprising at least two detectors, characterized in that, The device includes: The curve acquisition module is used to acquire the detection signal curves of each of the multiple detectors, and the detection signal curves are determined based on the detection signals collected by each detector for the scanned object. A convolution module is used, for each detector, to determine a first start position and a first end position in the detector channel direction of the detector signal curve based on the boundary position characteristics of the detector's detection signal curve; to determine a first edge based on the first start position and the first end position; to determine a second edge with a length less than a preset curve amplitude threshold in the signal intensity direction of the detection signal curve; to determine a first convolution region corresponding to the detection signal curve based on the first edge and the second edge; and to determine the scattering estimation information corresponding to the detector based on the convolution result of the first convolution region and a preset convolution kernel; the preset convolution kernel is used to characterize the spatial propagation of scattering. The correction result acquisition module is used to determine the cross-scattering correction result of each detector based on the scattering estimation information corresponding to each detector.

9. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

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