Motion detection method, system and program product based on cbct projection data

Abstract

The present disclosure provides a motion detection method, system and program product based on CBCT projection data. The method of the present disclosure performs a residual value determination step on a plurality of scan contexts in a CBCT scan, respectively, to obtain a plurality of residual values corresponding to the plurality of scan contexts, and determines a motion of a scanned object in the CBCT scan process through the plurality of residual values. In the residual value determination step, a first projection value change rate between a first angle and a second angle of a target pixel position along a rotation direction of a radiation source in the CBCT scan is determined, a second projection value change rate from a first position to a second position of a detector is determined, and a residual value is calculated through a difference between the first projection value change rate and the second projection value change rate and a third projection value change rate perpendicular to a radiation direction, the third projection value change rate being used to reflect a spatial gradient. The present disclosure can determine whether an observable motion of a scanned object occurs in the CBCT scan process.

Description

Technical Field

[0001] This disclosure relates to the field of image processing technology, and specifically to motion detection methods, motion detection systems, readable storage media, and computer program products based on CBCT projection data. Background Technology

[0002] When performing CBCT (cone-beam computed tomography) on an object, artifacts will appear in the resulting projected image if the object moves during the scan. Therefore, in some scenarios, it is necessary to determine whether the object moved during the scan.

[0003] The common approach is to train a deep neural network to identify whether CBCT imaging results contain artifacts caused by the motion of the scanned object, thereby determining whether the scanned object has moved. However, this method is highly dependent on the maturity of the neural network model's training, and the accuracy of the identification is difficult to guarantee. Summary of the Invention

[0004] This disclosure provides a motion detection method, motion detection system, readable storage medium, and computer program product based on CBCT projection data.

[0005] The first aspect of this disclosure proposes a motion detection method based on CBCT projection data, comprising: performing a residual value determination step on multiple scanning contexts in a CBCT scan to obtain multiple residual values ​​corresponding to the multiple scanning contexts, wherein the values ​​of at least one data item are different in different scanning contexts, the data item including the scanning angle and the target pixel position on the detector, and the residual value being used to represent the degree of motion of the scanned object undergoing the CBCT scan under the corresponding scanning context; and determining the motion of the scanned object during the CBCT scan process using the multiple residual values; wherein the residual value determination step includes: based on the current scan context... The method defines a first projection value change rate between a first angle and a second angle on the target pixel position along the rotation direction of the source in the CBCT scan, and a second projection value change rate from a first position on the detector to a second position, wherein the scan angle is between the first angle and the second angle, and the target pixel position is between the first position and the second position; and calculates a residual value using the difference between the first projection value change rate and the second projection value change rate and a third projection value change rate perpendicular to the ray direction, wherein the ray direction is the direction formed by the source and the target pixel position at the scan angle, and the third projection value change rate is used to reflect the spatial gradient.

[0006] According to some embodiments of this disclosure, the projection value of the target pixel position at the first angle comes from the projection image at the prior scan angle, and the projection value of the target pixel position at the second angle comes from the projection image at the subsequent scan angle. In the rotation trajectory of the CBCT scan, the prior scan angle is located before the scan angle in the scan context, and the subsequent scan angle is located after the scan angle in the scan context.

[0007] According to some embodiments of this disclosure, the scanning angle in the scanning context is the intermediate angle between the first angle and the second angle.

[0008] According to some embodiments of this disclosure, the first projection value change rate is calculated as follows: calculate the first projection difference between the projection value of the second angle and the projection value of the first angle, calculate the quotient of the first projection difference and the angle difference and use it as the first projection value change rate, wherein the angle difference is the angle difference between the first angle and the second angle.

[0009] According to some embodiments of this disclosure, the pixel position in the scanning context is the middle position between the first position and the second position, the line connecting the first position and the source position at the scanning angle is parallel to the line connecting the pixel position and the source position at the first angle, and the line connecting the second position and the source position at the scanning angle is parallel to the line connecting the pixel position and the source position at the second angle.

[0010] According to some embodiments of this disclosure, the second projection value change rate is calculated as follows: calculate the second projection difference between the projection value at the second position and the projection value at the first position, calculate the quotient of the second projection difference and the target angle and use it as the second projection value change rate, wherein the target angle is the angle formed by taking the source position under the scanning angle as the intersection of two lines and taking the first position and the second position as the endpoints of the two lines respectively.

[0011] According to some embodiments of this disclosure, the residual value determination step further includes: determining a third projection difference between a fourth projection value from projection data of a subsequent scanning context and a third projection value from projection data of a previous scanning context, wherein the third projection value is obtained by passing through a first ray parallel to the ray direction and passing through a source position at the first angle, and the fourth projection value is obtained by passing through a second ray parallel to the ray direction and passing through a source position at the second angle; and determining the ray spacing between the first ray and the second ray, and using the quotient of the third projection difference and the ray spacing as the rate of change of the third projection value.

[0012] According to some embodiments of this disclosure, calculating a residual value using the difference between the first projection value change rate and the second projection value change rate and a third projection value change rate perpendicular to the ray direction includes: determining a target difference between the first projection value change rate and the second projection value change rate; calculating the quotient of the target difference with the distance between the source and the target pixel position at the scanning angle to obtain a target quotient value; and determining the difference between the target quotient value and the third projection value change rate perpendicular to the ray direction to obtain a residual value.

[0013] According to some embodiments of this disclosure, determining the motion of the scanned object during the CBCT scanning process using the plurality of residual values ​​includes: summing the residual values ​​of the plurality of target pixel positions belonging to the same scanning angle to obtain the total residual value of the scanning angle; and if the total residual value exceeds a residual threshold, determining that the scanned object moves at the corresponding scanning angle during the CBCT scanning process.

[0014] According to some embodiments of this disclosure, the multiple pixel positions corresponding to the multiple scanning contexts are uniformly arranged on the detector.

[0015] According to some embodiments of this disclosure, the multiple scanning angles corresponding to the multiple scanning contexts are evenly distributed within the CBCT scanning angle range.

[0016] According to some embodiments of this disclosure, the rotation angle of the CBCT scan of the object being scanned is less than 360°.

[0017] A second aspect of this disclosure provides a motion detection system based on CBCT projection data, comprising: a scanning device for scanning an object, including a radiation source and a detector; a memory storing execution instructions; and a processor that executes the execution instructions stored in the memory, causing the processor to perform motion detection as described in any of the above embodiments.

[0018] A third aspect of this disclosure provides a readable storage medium storing a computer program that, when executed by a processor, is used to implement the motion detection method described in any of the above embodiments.

[0019] This disclosure provides a fourth aspect of a computer program product, the computer program product comprising a computer program, which, when executed by a processor, is used to implement the motion detection method described in any of the above embodiments. Attached Figure Description

[0020] The accompanying drawings illustrate exemplary embodiments of the present disclosure and, together with the description thereof, serve to explain the principles of the present disclosure. These drawings are included to provide a further understanding of the present disclosure and are incorporated in and constitute a part of this specification.

[0021] Figure 1 A schematic diagram of the overall process of motion detection M10 based on CBCT projection data according to some embodiments of this disclosure is shown.

[0022] Figure 2 A schematic diagram of the overall process for determining residual values ​​in some embodiments of this disclosure is shown.

[0023] Figure 3 A schematic diagram illustrating the positional relationship between the source and pixel positions under different scanning angles according to some embodiments of this disclosure is shown.

[0024] Figures 4-5 A schematic diagram of the overall process for performing the residual value determination step in some other embodiments of this disclosure is shown.

[0025] Figure 6 A schematic diagram of the overall process of motion detection M10 based on CBCT projection data according to some other embodiments of this disclosure is shown.

[0026] Figure 7 The LCE residual plot shows that there is significant motion at a certain scanning angle.

[0027] Figure 8 The LCE residual plot shows that there is no obvious motion at a certain scanning angle.

[0028] Figure 9 A graph showing the total residual value at different scanning angles is presented.

[0029] Figure 10 This is a schematic block diagram of a motion detection device based on CBCT projection data according to one embodiment of the present disclosure.

[0030] Figure 11 This is a schematic block diagram of a motion detection system 1000 based on CBCT projection data according to one embodiment of the present disclosure. Detailed Implementation

[0031] The present disclosure will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the disclosure. Furthermore, it should be noted that, for ease of description, only the parts relevant to the present disclosure are shown in the accompanying drawings.

[0032] It should be noted that, where there is no conflict, the embodiments and features described in this disclosure can be combined with each other. The technical solutions of this disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0033] Unless otherwise stated, the exemplary implementations / embodiments shown are to be understood as providing exemplary features of various details that provide ways in which the technical concepts of this disclosure can be implemented in practice. Therefore, unless otherwise stated, the features of various implementations / embodiments may be additionally combined, separated, interchanged and / or rearranged without departing from the technical concepts of this disclosure.

[0034] The terminology used herein is for the purpose of describing particular embodiments and is not restrictive. As used herein, unless the context clearly indicates otherwise, the singular forms “a” and “the” are intended to include the plural forms as well. Furthermore, when the terms “comprising” and / or “including” and variations thereof are used in this specification, it indicates the presence of the stated features, integrals, steps, operations, parts, components, and / or groups thereof, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, parts, components, and / or groups thereof. It should also be noted that, as used herein, the terms “substantially,” “about,” and other similar terms are used as approximate terms rather than as terms of degree, thus explaining the inherent biases in measurements, calculated values, and / or provided values ​​that would be recognized by one of ordinary skill in the art.

[0035] There are several reasons why artifacts may appear in the projection images (i.e., scanned images) obtained by CBCT scans. In addition to artifacts caused by the movement of the scanned object, they may also be caused by the presence of metal objects or other reasons in the scanned object. Therefore, if artifacts appear in the image, it is necessary to investigate the cause and determine whether the artifacts are caused by the movement of the scanned object.

[0036] If a neural network model is used to identify motion artifacts in CBCT imaging results, the accuracy of the neural network model is difficult to meet the requirements, and the training of the neural network model requires a large number of samples and time.

[0037] If the comparison is made by increasing the shooting angle (above 360°) and making differences, additional doses are required, which will produce more radiation to the scanned object and is not applicable to scenarios with shooting angles below 360°.

[0038] Therefore, a technology that is highly accurate, low-cost, and applicable to various shooting angles and scenarios is needed to detect whether the scanned object is moving during the scanning process.

[0039] Therefore, this disclosure proposes a motion detection method based on CBCT projection data.

[0040] Figure 1 A schematic diagram illustrating the overall process of motion detection M10 based on CBCT projection data according to some embodiments of this disclosure is shown. Figure 1 The method shown includes steps S100 and S200.

[0041] S100: A residual value determination step is performed on multiple scanning contexts in the CBCT scan to obtain multiple residual values ​​corresponding to the multiple scanning contexts. The values ​​of at least one data item differ in different scanning contexts. Data items include the scanning angle and the pixel position on the detector. The residual values ​​are used to represent the degree of motion of the scanned object in the corresponding scanning context.

[0042] S200 determines the motion of the scanned object through multiple residual values.

[0043] By performing CBCT (cone-beam computed tomography) scans on the object being scanned, multiple frames of projection data (i.e., scan data) at various scanning angles can be obtained, with each frame corresponding to a scanning angle. During the CBCT scan, the radiation source and detector rotate around a center of rotation. The positions of the radiation source and detector will also be different at different scanning angles.

[0044] In this paper, 'scan context' refers to a computational unit determined by a specific scan angle and a specific detector pixel position. A scan context includes a scan angle and a pixel position; different scan angles, different pixel positions, or both result in different scan contexts.

[0045] The detector can be a planar detector, with multiple pixel positions set on its detection surface, each pixel position corresponding to a detection unit. Each frame in the multiple projection frames corresponds to multiple scanning contexts. In different scanning contexts corresponding to the same frame, the scanning angle is the same, but the pixel positions are different. Assuming that a total of N projection images are captured in the CBCT scan of the scanned object, and the detector has a total of M detection units, then the number of scanning contexts used for motion detection of the scanned object can be N×M.

[0046] Each scan context involved in the motion detection calculation can generate a corresponding residual value through the residual value determination step. A residual value represents the degree of motion of the scanned object in the corresponding scan context. By using multiple residual values ​​corresponding to multiple scan contexts, the motion of the scanned object during the CBCT scan process can be determined.

[0047] Figure 2 A schematic diagram of the overall flow of the residual value determination step S100 in some embodiments of this disclosure is shown. (See also...) Figure 2The residual value determination steps include steps S110 and S130.

[0048] S110, based on the current scanning context, determines a first rate of change of projection value between a first angle and a second angle of the target pixel position along the rotation direction of the source in the CBCT scan, and determines a second rate of change of projection value from a first position to a second position on the detector. Here, the scanning angle is located between the first angle and the second angle, and the target pixel position is located between the first position and the second position. It can be understood that the target pixel position refers to the pixel position in the current scanning context.

[0049] S130: The residual value is calculated using the difference between the first and second projection value change rates and the third projection value change rate perpendicular to the ray direction. Here, the ray direction is the direction formed by the source and target pixel positions at the scanning angle. The third projection value change rate reflects the spatial gradient. Specifically, the third projection value change rate is equivalent to the partial derivative (non-angular partial derivative) of the Radon transform in spatial direction.

[0050] Figure 3 A schematic diagram illustrating the positional relationship between the source and pixel positions at different scanning angles according to some embodiments of this disclosure is shown. See also... Figure 3 Let A be the rotation center of the source and detector, and C be the circle containing the rotation trajectories of the source and detector. D and S1 represent the positions of the detector and source, respectively, at scan angle r1 (current frame projection, r1 not shown in the figure). Sa represents the position of the source at the previous scan angle (previous frame projection), and Sb represents the position of the source at the next scan angle (next frame projection). The previous scan angle is the first angle, which can be derived from the previous scan context. The next scan angle is the second angle, which can also be derived from the next scan context.

[0051] It is understandable that the absolute spatial position of the target pixel will change with different scanning angles, but the position of the target pixel on the detector remains unchanged, that is, the relative positional relationship between the target pixel and the radiation source remains unchanged.

[0052] Taking the target pixel position p1 on detector D as an example, during the process of the radiation source rotating from Sa to Sb, position p1 will receive rays at different times, such as the ray emitted from the radiation source at Sa that passes through position p1, and the ray emitted from the radiation source at Sb that passes through position p1. These rays form corresponding projection values ​​respectively.

[0053] The first projection value change rate is the change in the projection value at position p1 during the process of the source moving from Sa to Sb. The projection value is obtained through Radon transform, and the first projection value change rate is equivalent to the partial derivative of the Radon transform with respect to angle when rotating within a specified angular interval with the target pixel position p1 as the center.

[0054] The first projection value change rate is used to reflect the projection change caused by the movement of the radiation source, that is, the rate of change of the Radon transform caused by motion. It is understandable that calculating the first projection value change rate requires projection data from multiple frames before and after the current frame.

[0055] If the scanned object is stationary between Sa and Sb, the rate of change of the first projection value mainly reflects geometric rotation and will therefore resemble the spatial distribution of the internal structure of the scanned object. If the human body being scanned moves during the Sa to Sb period, such as a tissue sliding into or out of the ray path, the rate of change of the first projection value will increase abnormally or have its sign reversed.

[0056] The second projection value change rate is the change (difference) between the projection values ​​of multiple rays emitted from the source S1 and projected onto the vicinity of position p1 when the source S1 is in the same position. It is equivalent to the rate of change of the Radon transform in the direction perpendicular to S1-p1 when the source is fixed at position S1 in the current frame, and it also belongs to the partial derivative of the Radon transform with respect to angle. The projection points of the multiple rays projected onto the vicinity of position p1 can correspond to a first position on one side of the horizontal plane of p1 and a second position on the other side of the horizontal plane of p1.

[0057] The second projection value change rate reflects the rate of change of the projected image in a local spatial direction, and can estimate the expected spatial gradient in the absence of motion as a reference. It is understood that the second projection value change rate can be calculated using only the projection data of the current frame.

[0058] If the object being scanned does not move at time S1, the rate of change of the second projection value can predict how the projection value at position p1 will change as the scanning continues.

[0059] In step S130, the purpose of calculating the rate of change of the third projection value is to compensate for the influence of the structure. The scanned object may contain strong edges or high-contrast structures, such as the boundary between bone and soft tissue. Even if the scanned object is stationary, it may still generate a large gradient in the direction perpendicular to the ray, causing a difference between the rate of change of the first and second projection values. This gradient will increase the LCE residual value even when there is no movement. By calculating the spatial gradient value perpendicular to the ray direction, the pseudo-consistency error caused by the static high-gradient structure of the object can be estimated and eliminated, allowing the LCE to focus more on anomalies caused by motion and avoiding misinterpreting high-contrast edges as motion signals.

[0060] The residual value can be an LCE (Local Consistency Error) residual. The residual value is used to represent the deviation between the actual observed rate of change of the Radon transform with respect to the rotation angle at a point p1 of the detector in the CBCT projection data and the differential geometric consistency relation that point p1 should satisfy under the static object assumption.

[0061] Under ideal conditions (no motion, rigid body, continuous rotation), CBCT projection data satisfies the differential consistency relation of the Radon transform. That is, the change in the projection value of the same point observed from different angles roughly corresponds to the spatial gradient of the object's internal structure. Correspondingly, the rates of change of the first and second projection values ​​will be approximately equal, resulting in a low LCE residual value. If the scanned object moves during the scan, this consistency cannot be achieved, and the LCE residual value will significantly increase (become significantly non-zero).

[0062] Assume the lungs move up and down during the scan due to respiration. At one moment, a ray passes through the air (low attenuation). At the next moment, a ray from the same point p1 passes through soft tissue due to lung movement (high attenuation). The rate of change of the first projection value will be significantly increased, but the rate of change of the second projection value will have a smooth transition and a small predicted change. The difference between the two rates of change will be large, resulting in a high LCE residual value, confirming that motion of the scanned object has been detected.

[0063] The motion detection method based on CBCT projection data proposed according to the embodiments of this disclosure compares the difference between "actually observed time changes" and "should have changed under static assumptions" at the differential geometry level, accurately extracts the inconsistency information caused by motion, and can quickly determine whether the scanned object has moved during the scanning process using only the projection data obtained from the scan, without the need to build a neural network model. It is also applicable to scenes with shooting angles below 360 degrees, and has low cost, high detection efficiency, and detection accuracy that meets the requirements.

[0064] In some implementations, the projection value of the target pixel position at a first angle can be derived from the projection image at a previously scanned angle. The projection value of the target pixel position at a second angle can be derived from the projection image at a subsequently scanned angle. In the rotation trajectory of a CBCT scan, the previously scanned angle is before the scanned angle in the scanning context, i.e., the scanned angle in the previous scanned context. The subsequently scanned angle is after the scanned angle in the scanning context, i.e., the scanned angle in the subsequent scanned context. That is, the calculation of the rate of change of the first projection value requires projection data from multiple frames, including the current frame, the frames before the current frame, and the frames after the current frame. The current frame provides a fixed pixel position, while the frames before and after the current frame provide the projection values ​​of that pixel position at different locations of the source. For example, Figure 3 In this context, Sa represents the source position at the earlier scanning angle, and Sb represents the source position at the later scanning angle.

[0065] The scanning angle in the scanning context can be the intermediate angle between the first angle and the second angle. That is, the difference between the first angle and the scanning angle is equal to the difference between the scanning angle and the second angle. The projection ray of position p1 under Sa and Sb is differentiated by the projection ray of position p1 under S1. In addition, the rays emanating from S1 and distributed on both sides of position p1 can also be differentiated by the projection ray of position p1 under S1.

[0066] The first projection value change rate can be calculated as follows: calculate the first projection difference between the projection value of the second angle and the projection value of the first angle, and calculate the quotient of the first projection difference and the angle difference as the first projection value change rate. Here, the angle difference is the difference between the first angle and the second angle.

[0067] With R1 as the projection value of the first angle, R2 as the projection value of the second angle, and Δθ as the projection angle interval between the current frame and the adjacent frame (e.g., rotating 0.2° per frame), the rate of change of the first projection value = (R2-R1) / 2Δθ.

[0068] In some implementations, the pixel position in the scanning context is the midpoint between the first position and the second position. That is, the difference between the first position and position p1 is equal to the difference between position p1 and the second position. Figure 3Let the previous scanning angle before the current scanning angle be the first angle, and the next scanning angle after the current scanning angle be the second angle. Then Sa and Sb are the source positions under the first angle and the second angle, respectively. The line S1Ea connecting the first position Ea and the source position S1 under the current scanning angle can be parallel to the line DSa (i.e., p1Sa) connecting the pixel position p1 on the detector D and the source position Sa under the first angle. The line S1Eb connecting the second position Eb and the source position S1 under the current scanning angle can be parallel to the line DSb (i.e., p1Sb) connecting the pixel position p1 on the detector D and the source position Sb under the second angle.

[0069] It is understandable that the detector can be an arc-shaped detector, and Ea and Eb can be two location points on the arc-shaped detector. Figure 3 The image shows the positions of the rays when using an ideal curved detector, with positions Ea and Eb both located on the circular trajectory C. An ideal curved detector means that the detector surface coincides with the circular trajectory C. In actual CBCT operations, due to geometric equivalence, the scene can be converted to data under an ideal curved detector by performing equivalent operations on data from non-ideal curved detector scenarios.

[0070] The second projection value change rate can be calculated as follows: calculate the second projection difference between the projection value at the second position and the projection value at the first position, and calculate the quotient of the second projection difference and the target angle as the second projection value change rate. The target angle is the angle formed by taking the source position at the scanning angle as the intersection of two lines, and taking the first position and the second position as the endpoints of the two lines respectively. Figure 3 The target angle is the angle between lines S1Ea and S1Eb, where S1 is the intersection of the lines. There are multiple adjacent pixels near position p1 on the detector, such as the first position Ea and the second position Eb. The two rays from S1 to Ea and Eb have corresponding projection values ​​R3 and R4. The rate of change of the second projection value = (R4 - R3) / 2Δu, where Δu is the target angle.

[0071] Figure 4 A schematic flowchart illustrating the residual value determination steps of some other embodiments of this disclosure is shown. (See also...) Figure 4 The residual value determination step may also include steps S121 and S122.

[0072] S121, determine a third projection difference between a fourth projection value from the projection data of the subsequent scanning context and a third projection value from the projection data of the previous scanning context, wherein the third projection value can be obtained by a first ray parallel to the ray direction and passing through the source position at a first angle. The fourth projection value can be obtained by a second ray parallel to the ray direction and passing through the source position at a second angle.

[0073] S122, determine the ray spacing between the first ray and the second ray, and use the quotient of the third projection difference and the ray spacing as the rate of change of the third projection value.

[0074] Figure 3 In the diagram, dashed line B1 represents the first ray, dashed line B2 represents the second ray, and DS1 represents the ray direction. The first ray, the ray direction, and the second ray are parallel to each other.

[0075] It should be noted that the projection value of the first angle in step S110 is different from the third projection value in step S121 because the projection value of the first angle comes from ray Dsa, while the third projection value comes from ray B1. Similarly, the projection value of the second angle in step S110 is different from the fourth projection value in step S121 because the projection value of the second angle comes from ray Dsb, while the third projection value comes from ray B2.

[0076] Figure 5 A schematic flowchart illustrating the residual value determination steps of some other embodiments of this disclosure is shown. (See also...) Figure 5 In step S130, the residual value is calculated by the difference between the rate of change of the first projection value and the rate of change of the second projection value, as well as the rate of change of the third projection value perpendicular to the ray direction. Specifically, this may include steps S131, S132, and S133.

[0077] S131, determine the target difference between the rate of change of the first projected value and the rate of change of the second projected value.

[0078] S132, calculate the quotient of the target difference and the distance between the source and the target pixel position at the scanning angle to obtain the target quotient value.

[0079] S133, determine the difference between the target quotient and the rate of change of the third projection value perpendicular to the ray direction, and obtain the residual value.

[0080] exist Figure 3 In this model, the distance between the source and the target pixel is the distance between points p1 and S1 on detector D. This distance is used for geometric normalization. Since the longer the ray, the larger the absolute value of the distance between p1 and S1, and the smaller the change in projection angle caused by the same spatial displacement, the target difference can be divided by the ray length to normalize the error to a scale of unit arc length or unit angle change, making LCE comparable for different detector positions.

[0081] Assuming the rate of change of the first projected value is F1, the rate of change of the second projected value is F2, the distance between point p1 and S1 is L, and the rate of change of the third projected value is F3, then the LCE residual value = (F1-F2) / L-F3.

[0082] Figure 6A schematic diagram illustrating the overall process of motion detection M10 based on CBCT projection data according to other embodiments of this disclosure is shown. See also... Figure 6 In step S200, the motion of the scanned object during the CBCT scanning process is determined by multiple residual values, which may specifically include steps S210 and S220.

[0083] S210: Sum the residual values ​​of multiple target pixel positions belonging to the same scanning angle to obtain the total residual value of the scanning angle.

[0084] S220, if the total residual value exceeds the residual threshold, it is determined that the scanned object moves at the corresponding scanning angle during the CBCT scanning process.

[0085] A single scanning angle corresponds to multiple target pixel positions, such as all pixel positions on the detector. A residual value can be calculated for each pixel position, representing the motion at that position. The residual values ​​of all pixel positions at a given scanning angle represent the motion at that scanning angle; this is the total residual value obtained by summing the aforementioned residual values. A residual threshold can be set based on clinical needs or historical data. If the total residual value exceeds the threshold, it indicates that the scanned object has moved at that scanning angle; otherwise, it is considered that the scanned object has not moved at that scanning angle.

[0086] Figure 7 The LCE residual plot shows that there is significant motion at a certain scanning angle. Figure 7 The image contains a lot of clutter, indicating the presence of significant residual values ​​due to motion. Figure 8 The LCE residual plot shows that there is no obvious motion at a certain scanning angle. Figure 8 The image content is relatively smooth, indicating that there are no obvious residual values ​​caused by motion. Figure 7 and Figure 8 In the diagram, the horizontal and vertical axes represent the width and height of the detector.

[0087] Figure 9 A graph showing the total residual value at different scanning angles is provided. (See also...) Figure 9 The horizontal axis represents the scanning angle, or frame, while the vertical axis represents the sum of the residual values ​​of all pixel positions of the detector in each frame, i.e., the total residual value. The total residual value allows us to determine the time or angle at which motion occurs, making it more practical and providing preliminary information for motion calibration.

[0088] For example, multiple pixel positions corresponding to multiple scan contexts in a CBCT scan can be evenly distributed on the detector. For instance, each pixel in the detector can be used as a pixel position in the scan context, or multiple pixels can be sampled from the detector as pixel positions in the scan context. The sampled pixels can be arranged in a matrix, i.e., in a grid pattern.

[0089] In CBCT scans, multiple scan angles corresponding to multiple scan contexts are evenly distributed within the CBCT scan angle range. For example, each frame of projection data can be used to form a corresponding scan context for motion detection by creating a scan angle. Alternatively, multiple scan angles can be sampled from each frame of projection data to form multiple scan contexts, where the angle difference between adjacent sampled scan angles is the same.

[0090] The residual value determination step can be performed after the CBCT scan of the object is completed. The rotation angle of the CBCT scan of the object can be less than 360°. For example, if the CBCT scan only rotates 180°, complete motion detection can still be performed using the 180° projection data.

[0091] Based on any of the above embodiments, this disclosure also provides a motion detection device based on CBCT projection data. Figure 10 This is a schematic block diagram of a motion detection device based on CBCT projection data according to one embodiment of this disclosure. Figure 10 As shown, the motion detection device includes: a residual value calculation module 100 and a motion condition determination module 200.

[0092] The residual value calculation module 100 performs residual value determination steps on multiple scanning contexts in a CBCT scan to obtain multiple residual values ​​corresponding to the multiple scanning contexts. In each scanning context, the value of at least one data item is different. Data items include the scanning angle and the pixel position on the detector. The residual value represents the degree of motion of the scanned object in the corresponding scanning context.

[0093] The residual value determination step includes: based on the current scanning context, determining a first projection value change rate between a first angle and a second angle of the target pixel position along the rotation direction of the source in the CBCT scan; and determining a second projection value change rate from a first position to a second position on the detector, wherein the scanning angle is between the first angle and the second angle, and the target pixel position is between the first position and the second position; and calculating the residual value using the difference between the first projection value change rate and the second projection value change rate and a third projection value change rate perpendicular to the ray direction, wherein the ray direction is the direction formed by the source and the target pixel position at the scanning angle. The third projection value change rate is used to reflect the spatial gradient.

[0094] The motion determination module 200 is used to determine the motion of the scanned object through multiple residual values.

[0095] The motion detection device described above can be in the form of computer software, and each module of the motion detection device can be implemented through computer software modules. The specific implementation process of the functions and roles of each module in the above device is detailed in the corresponding steps of the above method, and will not be repeated here.

[0096] The execution subject of the motion detection method based on CBCT projection data in the specific embodiments of this disclosure can be an electronic device such as a computer or server.

[0097] Therefore, based on any of the above embodiments, this disclosure also provides a motion detection system based on CBCT projection data, which can execute the motion detection method based on CBCT projection data of any of the embodiments described above in this disclosure.

[0098] Figure 11 This is a schematic block diagram of a motion detection system 1000 based on CBCT projection data according to one embodiment of the present disclosure.

[0099] The hardware architecture of the motion detection system 1000 can be implemented using a bus architecture. The bus architecture can include any number of interconnect buses and bridges, depending on the specific application and overall design constraints of the hardware. Bus 1100 connects various circuits including one or more processors 1200, memory 1300, and / or hardware modules. Bus 1100 can also connect various other circuits 1400 such as peripheral devices, voltage regulators, power management circuits, external antennas, etc. Bus 1100 may also include a scanning device, which includes a radiation source and a detector.

[0100] Bus 1100 can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Component (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, only one connection line is used in this diagram, but this does not imply that there is only one bus or only one type of bus.

[0101] The processor 1200 can be a central processing unit (CPU). The processor 1200 can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or combinations of the above types of chips.

[0102] The memory 1300 can serve as a non-transitory computer-readable storage medium, used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as program instructions of the computer program in the embodiments of this disclosure. The processor 1200 implements the motion detection method based on CBCT projection data by running the non-transitory software programs, instructions, and modules stored in the memory 1300.

[0103] The memory 1300 may include a program storage area and a data storage area, wherein the program storage area may store the operating system and application programs required for at least one function; the data storage area may store data created by the processor 1200. Furthermore, the memory 1300 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory 1300 may optionally include memory remotely located relative to the processor 1200, and these remote memories may be connected to the processor 1200 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0104] This disclosure also provides a readable storage medium storing a computer program that, when executed by a processor, is used to implement the methods described above. A "readable storage medium" can be any means capable of containing, storing, communicating, propagating, or transmitting a program for use by or in conjunction with an instruction execution system, apparatus, or device. More specific examples of a readable storage medium include: an electrical connection with one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and portable read-only memory (CDROM), etc.

[0105] This disclosure also provides a computer program product, the methods of which can be implemented wholly or partially through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented wholly or partially as a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instructions are loaded and executed, the processes or functions of this disclosure are performed wholly or partially. The computer can be a general-purpose computer, a special-purpose computer, a computer network, network equipment, user equipment, core network equipment, OAM, or other programmable device.

[0106] Computer programs or instructions can be stored in a readable storage medium or transferred from one readable storage medium to another. For example, the computer program or instructions can be transferred from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The readable storage medium can be any available medium capable of access, or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium, such as a floppy disk, hard disk, or magnetic tape; an optical medium, such as a digital video optical disc; or a semiconductor medium, such as a solid-state drive. The computer-readable storage medium can be a volatile or non-volatile storage medium, or it can include both volatile and non-volatile types of storage media.

[0107] Those skilled in the art will understand that embodiments of this disclosure can be provided as methods, systems, or computer program products. Therefore, this disclosure can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this disclosure can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0108] This disclosure is described with reference to flowchart illustrations and / or block diagrams of methods, systems, and computer program products according to this disclosure. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0109] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0110] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0111] In the description of this specification, the references to terms such as "one embodiment / mode," "some embodiments / modes," "example," "specific example," or "some examples," etc., refer to specific features, structures, or characteristics described in connection with that embodiment / mode or example, which are included in at least one embodiment / mode or example of this disclosure. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment / mode or example. Moreover, the specific features, structures, or characteristics described may be combined in any suitable manner in one or more embodiments / modes or examples. Furthermore, without contradiction, those skilled in the art can combine and integrate the different embodiments / modes or examples described in this specification, as well as the features of different embodiments / modes or examples.

[0112] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this disclosure, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0113] Those skilled in the art should understand that the above embodiments are merely for illustrating the present disclosure and are not intended to limit the scope of the disclosure. Those skilled in the art can make other changes or modifications based on the above disclosure, and these changes or modifications still fall within the scope of the present disclosure.

Claims

1. A motion detection method based on CBCT projection data, characterized in that, include: A residual value determination step is performed on multiple scanning contexts in a CBCT scan to obtain multiple residual values ​​corresponding to the multiple scanning contexts. The values ​​of at least one data item are different in different scanning contexts. The data item includes the scanning angle and the pixel position on the detector. The residual value is used to represent the degree of motion of the scanned object in the corresponding scanning context. as well as The motion of the scanned object during the CBCT scan is determined by the multiple residual values. The residual value determination step includes: Based on the current scanning context, a first projection value change rate between a first angle and a second angle of the target pixel position along the rotation direction of the source in the CBCT scan is determined, and a second projection value change rate from a first position to a second position on the detector is determined, wherein the scanning angle is between the first angle and the second angle, and the target pixel position is between the first position and the second position; and The residual value is calculated by the difference between the first projection value change rate and the second projection value change rate and the third projection value change rate perpendicular to the ray direction. The ray direction is the direction formed by the source and the target pixel position at the scanning angle. The third projection value change rate is used to reflect the spatial gradient.

2. The motion detection method according to claim 1, characterized in that, The projection value of the target pixel position at the first angle comes from the projection image at the prior scan angle, and the projection value of the target pixel position at the second angle comes from the projection image at the subsequent scan angle. In the rotation trajectory of the CBCT scan, the prior scan angle is located before the scan angle in the scan context, and the subsequent scan angle is located after the scan angle in the scan context.

3. The motion detection method according to claim 1 or 2, characterized in that, The scanning angle in the scanning context is the midpoint between the first angle and the second angle.

4. The motion detection method according to claim 1 or 2, characterized in that, The first projection value change rate is calculated as follows: calculate the first projection difference between the projection value of the second angle and the projection value of the first angle, calculate the quotient of the first projection difference and the angle difference and use it as the first projection value change rate, where the angle difference is the angle difference between the first angle and the second angle.

5. The motion detection method according to claim 1, characterized in that, The pixel position in the scanning context is the midpoint between the first position and the second position. The line connecting the first position and the source position at the scanning angle is parallel to the line connecting the pixel position and the source position at the first angle. The line connecting the second position and the source position at the scanning angle is parallel to the line connecting the pixel position and the source position at the second angle.

6. The motion detection method according to claim 1 or 5, characterized in that, The second projection value change rate is calculated as follows: calculate the second projection difference between the projection value at the second position and the projection value at the first position, calculate the quotient of the second projection difference and the target angle and use it as the second projection value change rate. The target angle is the angle formed by taking the source position under the scanning angle as the intersection of two lines and taking the first position and the second position as the endpoints of the two lines respectively.

7. The motion detection method according to claim 1, characterized in that, The residual value determination step further includes: A third projection difference is determined between a fourth projection value from projection data of a subsequent scan context and a third projection value from projection data of a previous scan context. The third projection value is obtained by passing a first ray parallel to the ray direction and passing through the source position at the first angle. The fourth projection value is obtained by passing a second ray parallel to the ray direction and passing through the source position at the second angle. The ray spacing between the first ray and the second ray is determined, and the quotient of the third projection difference and the ray spacing is taken as the rate of change of the third projection value.

8. The motion detection method according to claim 1 or 7, characterized in that, The residual value is calculated using the difference between the rate of change of the first projection value and the rate of change of the second projection value, and the rate of change of the third projection value perpendicular to the ray direction. This includes: Determine the target difference between the rate of change of the first projected value and the rate of change of the second projected value; Calculate the quotient of the target difference and the distance between the source and the target pixel position at the scanning angle to obtain the target quotient value; and The residual value is obtained by determining the difference between the target quotient and the rate of change of the third projection value perpendicular to the ray direction.

9. The motion detection method according to claim 1, characterized in that, Determining the motion of the scanned object during the CBCT scan using the multiple residual values ​​includes: The residual values ​​of multiple target pixel positions belonging to the same scanning angle are summed to obtain the total residual value of the scanning angle; and If the total residual value exceeds the residual threshold, it is determined that the scanned object moves at the corresponding scanning angle during the CBCT scanning process.

10. The motion detection method according to claim 1, characterized in that, The multiple pixel positions corresponding to the multiple scanning contexts are evenly distributed on the detector.

11. The motion detection method according to claim 1, characterized in that, The multiple scanning angles corresponding to the multiple scanning contexts are evenly distributed within the CBCT scanning angle range.

12. The motion detection method according to claim 1, characterized in that, The rotation angle of the CBCT scan of the object being scanned is less than 360°.

13. A motion detection system based on CBCT projection data, characterized in that, include: A scanning device used to scan an object, including a source and a detector; The memory stores execution instructions; as well as A processor that executes the execution instructions stored in the memory, causing the processor to perform the motion detection method according to any one of claims 1 to 12.

14. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, is used to implement the motion detection method according to any one of claims 1 to 12.

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