Scattering artifact image correction method, device, equipment and storage medium

Abstract

The present invention provides a scattering artifact image correction method, device, equipment and storage medium, which can be applied to the field of medical imaging technology. The method includes: obtaining a projection signal related to a target detection object, wherein the projection signal is obtained by scanning the target detection object based on m projection angles using a radiation source, and m is an integer greater than 1; determining the target sampling angle from the m projection angles using a gradient sampling algorithm; obtaining a sparse scattering signal corresponding to the target sampling angle, wherein a blocking plate is set between the radiation source and the target detection object; processing the sparse scattering signal corresponding to the target sampling angle based on an interpolation algorithm to obtain a target scattering signal corresponding to each of the m projection angles; performing image reconstruction based on the projection signal corresponding to each of the m projection angles and the target scattering signal to generate a scattering artifact correction image.

Description

Technical Field

[0001] The present invention relates to the field of medical imaging technology, and in particular to a scattering artifact image correction method, device, equipment and storage medium. Background Art

[0002] The cone beam computed tomography (CBCT) system is mainly composed of an X-ray tube, a flat-panel detector, a motion system, and an image processing system. The use of a flat-panel detector with a large imaging area in cone beam CT leads to a large increase in scattered signals, which ultimately leads to reduced contrast in the reconstructed image, CT value offset, and scattering artifacts, which greatly reduces the image quality. In clinical practice, the existing methods for correcting image artifacts have a technical problem that the more angles the scattered signal is measured, the higher the X-ray dose received by the scanned object, and the method is easily limited by the shape of the scanned object, resulting in low accuracy in estimating the scattered signal. Summary of the invention

[0003] In view of the above problems, the present invention provides a scattering artifact image correction method, device, equipment and storage medium.

[0004] According to a first aspect of the present invention, a scattering artifact image correction method is provided, comprising: acquiring a projection signal related to a target detection object, wherein the projection signal is obtained by scanning the target detection object based on m projection angles using a radiation source, and m is an integer greater than 1; determining a target sampling angle from the m projection angles using a gradient sampling algorithm; acquiring a sparse scattering signal corresponding to the target sampling angle, wherein the sparse scattering signal is obtained by scanning the target detection object based on the target sampling angle and a blocking plate using a radiation source, and the blocking plate is arranged between the radiation source and the target detection object; processing the sparse scattering signal corresponding to the target sampling angle based on an interpolation algorithm to obtain a target scattering signal corresponding to each of the m projection angles; performing image reconstruction according to the projection signal and the target scattering signal corresponding to each of the m projection angles to generate a scattering artifact corrected image.

[0005] Optionally, determining the target sampling angle from m projection angles using a gradient sampling algorithm includes: determining the i-1th gradient value of the i-1th projection angle based on a difference between an average value of a projection signal corresponding to the i-1th projection angle and an average value of a projection signal corresponding to the i-1th projection angle, wherein m≥i>1 and i is an integer; when i>2 and the first gradient value is greater than a preset sampling gradient threshold, determining the second projection angle as the target sampling angle; when i>2 and the first gradient value is less than or equal to the preset sampling gradient threshold, determining the cumulative sum of the first gradient value and the second gradient value to obtain a second gradient cumulative value; when the second gradient cumulative value is greater than the preset sampling gradient threshold, determining the third projection angle as the target sampling angle; when the second gradient cumulative value is less than or equal to the preset sampling gradient threshold, determining the cumulative sum of the first gradient value to the third gradient value to obtain a third gradient cumulative value; when the third gradient cumulative value is greater than the preset sampling gradient threshold, determining the fourth projection angle as the target sampling angle.

[0006] Optionally, determining the target sampling angle from m projection angles using a gradient sampling algorithm also includes: when i>2 and when the i-1th gradient value is greater than a preset sampling gradient threshold, determining the i-th projection angle as the target sampling angle, wherein the i-1th projection angle is the target sampling angle; when the i-1th gradient value is less than or equal to the preset sampling gradient threshold, determining the i-th gradient cumulative value based on the i-1th gradient value and the i-th gradient value; when the i-th gradient cumulative value is greater than the preset sampling gradient threshold, determining the i+1th projection angle as the target sampling angle.

[0007] Optionally, the preset sampling gradient threshold is obtained based on the following operations: determining a total gradient value according to the sum of the gradient values ​​corresponding to the m projection angles; and determining the preset sampling gradient threshold according to a ratio between the total gradient value and the preset number of sampling angles.

[0008] Optionally, image reconstruction is performed according to the projection signals and target scattering signals corresponding to each of the m projection angles to generate a corrected scattering artifact image, including: subtracting the target scattering signal corresponding to the projection angle from the projection signal corresponding to the projection angle to obtain an original signal corresponding to the projection angle; using a denoising algorithm to process the original signal corresponding to each of the m projection angles to obtain a denoised signal; and processing the denoised signal according to the image reconstruction algorithm to generate a scattering artifact corrected image.

[0009] Optionally, the image reconstruction algorithm includes at least one of the following: a filtered back projection algorithm, an iterative algorithm, and a deep learning algorithm.

[0010] Optionally, the m projection angles include a target sampling angle and a non-target sampling angle; wherein, processing the sparse scattered signal corresponding to the target sampling angle based on an interpolation algorithm to obtain the target scattering signal corresponding to each of the m projection angles includes: processing the sparse scattered signal corresponding to the target sampling angle based on an interpolation algorithm to obtain the interpolated scattering signal corresponding to the non-target sampling angle; processing the sparse scattered signal corresponding to the target sampling angle and the interpolated scattering signal corresponding to the non-target sampling angle using a smoothing algorithm to obtain the target scattering signal corresponding to each of the m projection angles.

[0011] A second aspect of the present invention provides a scattering artifact image correction device, comprising:

[0012] A first acquisition module is used to acquire a projection signal related to the target detection object, wherein the projection signal is obtained by scanning the target detection object based on m projection angles using a radiation source, where m is an integer greater than 1;

[0013] A sampling module, used to determine a target sampling angle from m projection angles using a gradient sampling algorithm;

[0014] A second acquisition module is used to acquire a sparse scattered signal corresponding to a target sampling angle, wherein the sparse scattered signal is obtained by scanning the target detection object using a radiation source based on the target sampling angle and a blocking plate, and the blocking plate is arranged between the radiation source and the target detection object;

[0015] A processing module, used for processing the sparse scattered signal corresponding to the target sampling angle based on an interpolation algorithm to obtain the target scattered signal corresponding to each of the m projection angles;

[0016] The reconstruction module is used to perform image reconstruction according to the projection signals corresponding to the m projection angles and the target scattering signals to generate a scattering artifact corrected image.

[0017] A third aspect of the present invention provides an electronic device, comprising: one or more processors; a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors execute the above-mentioned scattering artifact image correction method.

[0018] A fourth aspect of the present invention further provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, causes the processor to execute the above-mentioned scattering artifact image correction method.

[0019] According to the scattering artifact image correction method, device, equipment and storage medium provided by the present invention, the target sampling angle is determined from m projection angles by using a gradient sampling algorithm; then a blocking plate is placed between the radiation source and the target detection object to obtain the scattering signal corresponding to the target sampling angle, thereby performing interpolation and image reconstruction processing to obtain a scattering artifact correction image. Since the gradient sampling algorithm is used to guide sampling according to the degree of change of the projection signal of the target detection object, the local error caused by sparse sampling of non-uniform objects is effectively reduced; in addition, only the sparse scattering signals of a few target sampling angles are collected, and then the target scattering signals of all projection angles are obtained by the interpolation algorithm, which effectively reduces the extra time and extra patient dose caused by the extra scan. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The above and other objects, features and advantages of the present invention will become more apparent through the following description of the embodiments of the present invention with reference to the accompanying drawings.

[0021] Figure 1 A flow chart of a scattering artifact image correction method according to an embodiment of the present invention is shown.

[0022] Figure 2 An exemplary schematic diagram showing the placement of a blocking plate according to an embodiment of the present invention is shown.

[0023] Figure 3 An exemplary schematic diagram of a blocking plate according to an embodiment of the present invention is shown.

[0024] Figure 4A An example schematic diagram showing the correction effect of generating a scattering artifact corrected image based on a human head phantom according to an embodiment of the present invention is shown.

[0025] Figure 4B An exemplary schematic diagram showing the correction effect of generating a scattering artifact corrected image based on a human pelvic phantom according to an embodiment of the present invention is shown.

[0026] Figure 5 A structural block diagram of a scattering artifact image correction device according to an embodiment of the present invention is shown.

[0027] Figure 6 A block diagram of an electronic device suitable for implementing a scattering artifact image correction method according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0028] Below, embodiments of the present invention will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present invention. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of embodiments of the present invention. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of concepts of the present invention.

[0029] The terms used herein are only for describing specific embodiments and are not intended to limit the present invention. The terms "comprise", "include", etc. used herein indicate the existence of features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0030] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0031] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0032] In the process of implementing the present invention, it is found that the cone beam computed tomography (CBCT) system is mainly composed of an X-ray tube, a flat panel detector, a motion system, and an image processing system. The cone beam CT uses a flat panel detector with a large imaging area, which leads to a large increase in scattered signals, which ultimately leads to reduced contrast in the reconstructed image, CT value offset and scattering artifacts, which greatly reduces the image quality. In clinical practice, the more angles the existing method for correcting image artifacts measures for scattered signals, the higher the X-ray dose received by the scanned object, and it is easily limited by the shape of the scanned object, resulting in a technical problem of low accuracy in estimating scattered signals.

[0033] In view of this, an embodiment of the present invention provides a method, device, equipment and storage medium for scattering artifact image correction. The method includes: obtaining a projection signal related to a target detection object, wherein the projection signal is obtained by scanning the target detection object based on m projection angles using a radiation source, and m is an integer greater than 1; determining a target sampling angle from the m projection angles using a gradient sampling algorithm; obtaining a sparse scattering signal corresponding to the target sampling angle, wherein the sparse scattering signal is obtained by scanning the target detection object based on the target sampling angle and a blocking plate using a radiation source, and the blocking plate is set between the radiation source and the target detection object; processing the sparse scattering signal corresponding to the target sampling angle based on an interpolation algorithm to obtain a target scattering signal corresponding to each of the m projection angles; performing image reconstruction based on the projection signal and the target scattering signal corresponding to each of the m projection angles to generate a scattering artifact corrected image.

[0034] In the technical solution of the present invention, the user information (including but not limited to user personal information, user image information, user device information, such as location information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved are all information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data comply with relevant laws, regulations and standards, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0035] It should be noted that the sequence numbers of the operations in the following method are only used as representations of the operations for the purpose of description, and should not be regarded as representing the execution order of the operations. Unless explicitly stated, the method does not need to be executed completely in the order shown.

[0036] Figure 1 A flow chart of a scattering artifact image correction method according to an embodiment of the present invention is shown.

[0037] like Figure 1 As shown, the method 100 includes operations S110 to S150.

[0038] In operation S110, a projection signal related to a target detection object is acquired.

[0039] Optionally, the target detection object represents an object to be detected, for example, it may be a human head phantom or a human pelvic phantom.

[0040] Optionally, during imaging using a cone beam computed tomography (CBCT) system, the radiation source scans the target detection object based on m projection angles respectively to obtain projection signals corresponding to the m projection angles, where m is an integer greater than 1.

[0041] For example, the projection angle of the radiation source may be adjusted every 1°, so as to obtain projection signals corresponding to 0° to 600°.

[0042] In operation S120, a target sampling angle is determined from the m projection angles using a gradient sampling algorithm.

[0043] Optionally, determining one or more target sampling angles from the m projection angles using a gradient sampling algorithm may include: determining whether the subsequent projection angle is the target sampling angle according to intensity gradient changes of projection signals of the current projection angle and the subsequent projection angle.

[0044] For example, when the intensity gradient changes greatly, the next projection angle may be determined as the target sampling angle; when the intensity gradient changes slightly, the next projection angle may be determined as the non-target sampling angle.

[0045] Optionally, when determining the target sampling angle, a uniform sampling algorithm or a non-uniform sampling algorithm may also be used. For example, m is set to 600, the projection angle of the radiation source is adjusted every 10°, and 60 target sampling angles are determined from the 600 projection angles.

[0046] Optionally, the number of target sampling angles is much smaller than the number of projection angles.

[0047] In operation S130, a sparse scattered signal corresponding to a target sampling angle is acquired.

[0048] Optionally, a blocking plate is set between the radiation source and the target detection object. During imaging using a cone-beam computed tomography system, the radiation source is used to scan the target detection object based on the target sampling angle and the blocking plate to obtain a sparse scattered signal corresponding to the target sampling angle.

[0049] Optionally, the ray includes an outgoing ray and a scattered ray. The outgoing ray irradiates the target detection object to generate an original signal, and the scattered ray irradiates the target detection object to generate a scattered signal and then generate noise or image artifacts. The ray irradiates the target detection object to generate a projection signal and then form an image. The projection signal includes the original signal and the scattered signal, and the sparse scattered signal represents the scattered signal.

[0050] Optionally, the blocking plate can block at least 99.9% of the outgoing rays, and the beam blocking plate can be a full-beam blocking plate, and the specific shape is not limited.

[0051] Figure 2 An exemplary schematic diagram showing the placement of a blocking plate according to an embodiment of the present invention is shown.

[0052] like Figure 2 As shown, the radiation source can be an x-ray light source, the blocking plate can be a beam blocking plate, the target detection object is a scanned object, the beam blocking plate 220 is installed between the x-ray light source 210 and the scanned object 230, the x-ray light source 210 emits x-rays based on the target sampling angle, the x-rays pass through the beam blocking plate 220 to irradiate the scanned object 230, and the flat panel detector 240 collects sparse scattered signals.

[0053] Figure 3 An exemplary schematic diagram of a blocking plate according to an embodiment of the present invention is shown.

[0054] like Figure 3 As shown, x-rays penetrate the beam blocking plate to irradiate the scanned object, and the blocking plate includes a hollow area 310 and a blocking area 320. The sparse scattered signals collected by the flat panel detector include scattered signals generated by the scattered rays passing through the hollow area 310 to irradiate the target detection object and then being deflected and reaching the flat panel detector.

[0055] In operation S140, the sparse scattered signal corresponding to the target sampling angle is processed based on an interpolation algorithm to obtain a target scattered signal corresponding to each of the m projection angles.

[0056] Optionally, the remaining angles of the m projection angles that do not include the target sampling angle are determined as angles to be interpolated. For example, from the projection angles of 0°, 1°, 2°, 3°, 4°, and 5°, the target sampling angles are determined to be 0°, 2°, and 5°, and the angles to be interpolated are 1°, 3°, and 4°.

[0057] Optionally, the sparse scattered signal corresponding to the target sampling angle is processed by an interpolation algorithm to obtain a sparse scattered signal corresponding to the angle to be interpolated. The target scattered signals corresponding to the m projection angles are obtained according to the sparse scattered signals corresponding to the target sampling angle and the angle to be interpolated.

[0058] Optionally, the target scattered signal has higher integrity, accuracy and smoothness than the sparse scattered signal.

[0059] In operation S150, image reconstruction is performed based on the projection signals corresponding to the m projection angles and the target scattering signal to generate a scattering artifact corrected image.

[0060] Optionally, original projection signals corresponding to the m projection angles are obtained according to the projection signals corresponding to the m projection angles and the target scattering signals, and image reconstruction is performed according to the original projection signals of the m projection angles to generate a scattering artifact corrected image.

[0061] Optionally, by using a gradient sampling algorithm to guide sampling according to the degree of change of the projection signal of the target detection object, the local error caused by sparse sampling of non-uniform objects is effectively reduced; in addition, only sparse scattering signals of a few target sampling angles are collected, and then the target scattering signals of all projection angles are obtained through an interpolation algorithm, which effectively reduces the extra time and additional patient dose caused by additional scanning.

[0062] Optionally, determining the target sampling angle from m projection angles using a gradient sampling algorithm includes: determining the i-1th gradient value of the i-1th projection angle based on a difference between an average value of a projection signal corresponding to the i-1th projection angle and an average value of a projection signal corresponding to the i-1th projection angle, wherein m≥i>1 and i is an integer; when i>2 and the first gradient value is greater than a preset sampling gradient threshold, determining the second projection angle as the target sampling angle; when i>2 and the first gradient value is less than or equal to the preset sampling gradient threshold, determining the cumulative sum of the first gradient value and the second gradient value to obtain a second gradient cumulative value; when the second gradient cumulative value is greater than the preset sampling gradient threshold, determining the third projection angle as the target sampling angle; when the second gradient cumulative value is less than or equal to the preset sampling gradient threshold, determining the cumulative sum of the first gradient value to the third gradient value to obtain a third gradient cumulative value; when the third gradient cumulative value is greater than the preset sampling gradient threshold, determining the fourth projection angle as the target sampling angle.

[0063] Optionally, a cone beam computed tomography system is used to generate projection images corresponding to multiple projection angles. For the projection image corresponding to the i-th projection angle, an average projection signal corresponding to the i-th projection angle is obtained according to a ratio of the projection signal to the number of pixels of the projection image.

[0064] Optionally, the (i-1)th gradient value represents a degree of change in the projection signal between the (i-1)th projection angle and the (i)th projection angle.

[0065] For example, the second gradient value corresponding to the second projection angle is determined according to the difference between the average value of the projection signal corresponding to the third projection angle and the average value of the projection signal corresponding to the second projection angle.

[0066] Optionally, projection angle 0° is the first projection angle, and the first projection angle is used as the target sampling angle of the initial iteration. The difference between the average value of the projection signal corresponding to the projection angle 0° and the average value of the projection signal corresponding to the projection angle 1° is calculated to obtain the first gradient value of the first projection angle.

[0067] Optionally, when the first gradient value is less than or equal to a preset sampling gradient threshold, the second projection angle is skipped and no sampling is performed, and the cumulative sum of the first gradient value and the second gradient value is calculated as the second gradient cumulative value; when the second gradient cumulative value is greater than the preset sampling gradient threshold, the third projection angle is determined as the target sampling angle; when the second gradient cumulative value is less than or equal to the preset sampling gradient threshold, the third projection angle is skipped and no sampling is performed, and the cumulative sum of the first gradient value to the third gradient value is calculated to determine the third gradient cumulative value; when the third gradient cumulative value is greater than the preset sampling gradient threshold, the fourth projection angle is determined as the target sampling angle.

[0068] Optionally, determining the target sampling angle from m projection angles using a gradient sampling algorithm also includes: when i>2 and when the i-1th gradient value is greater than a preset sampling gradient threshold, determining the i-th projection angle as the target sampling angle, wherein the i-1th projection angle is the target sampling angle; when the i-1th gradient value is less than or equal to the preset sampling gradient threshold, determining the i-th gradient cumulative value based on the i-1th gradient value and the i-th gradient value; when the i-th gradient cumulative value is greater than the preset sampling gradient threshold, determining the i+1th projection angle as the target sampling angle.

[0069] Optionally, when the i-1th projection angle is the target sampling angle, the i-1th projection angle is used again as the target sampling angle for the initial iteration to determine the magnitude between the i-1th gradient value and a preset sampling gradient threshold.

[0070] Optionally, when the i-1th gradient value is greater than a preset sampling gradient threshold, the next projection angle of the i-1th projection angle (the i-th projection angle) is determined as the target sampling angle; when the i-1th gradient value is less than or equal to the preset sampling gradient threshold, the i-th projection angle is skipped and sampling is not performed, and the size of the i-th gradient cumulative value and the preset sampling gradient threshold is determined.

[0071] Optionally, when the i-th gradient accumulation value is greater than a preset sampling gradient threshold, the next projection angle of the i-th projection angle (i+1th projection angle) is determined as the target sampling angle; when the i-th gradient value is less than or equal to the preset sampling gradient threshold, the i+1th projection angle is skipped and sampling is not performed, and the i+1th gradient accumulation value and the preset sampling gradient threshold are continuously determined. The i+1th gradient accumulation value is determined based on the cumulative sum of the i-1th gradient value to the i+1th gradient value.

[0072] Optionally, when the last iteration angle exceeds the number m of projection angles, iterative sampling is stopped and the distribution of target sampling angles is recorded.

[0073] Optionally, a gradient sampling algorithm can be used to select a target sampling angle according to changes in the gradient value of the projection signal, and the sampling is guided by changes in the projection signal of the scanned object, effectively reducing local errors caused by sparse sampling of non-uniform objects.

[0074] Optionally, the preset sampling gradient threshold is obtained based on the following operations: determining a total gradient value according to the sum of the gradient values ​​corresponding to the m projection angles; and determining the preset sampling gradient threshold according to a ratio between the total gradient value and the preset number of sampling angles.

[0075] Optionally, the preset number of sampling angles represents an expected number of target sampling angles.

[0076] Optionally, first determine m projection angles and a preset number of sampling angles n, calculate the gradient values ​​of the m projection angles, and then determine the total gradient value according to the sum of the gradient values ​​corresponding to the m projection angles. ; Finally, according to the ratio between the total gradient value and the preset number of sampling angles, the preset sampling gradient threshold is determined as .

[0077] Optionally, performing image reconstruction according to projection signals and target scattering signals corresponding to each of the m projection angles to generate a scattering artifact-corrected image includes:

[0078] The projection signal corresponding to the projection angle is subtracted from the target scattering signal corresponding to the projection angle to obtain the original signal corresponding to the projection angle; the original signal corresponding to each of the m projection angles is processed by a denoising algorithm to obtain a denoised signal; the denoised signal is processed according to an image reconstruction algorithm to generate a scattering artifact corrected image.

[0079] Optionally, for each projection angle, the target scattered signal is subtracted from the projection signal to obtain the original signal. The original signal represents the projection signal without scattering information.

[0080] For example, for a projection angle of 1°, the target scattered signal corresponding to 1° is subtracted from the projection signal corresponding to 1° to obtain the original projection signal corresponding to the projection angle 1°.

[0081] Optionally, the original signals corresponding to the m projection angles are processed respectively using a denoising algorithm to obtain a denoised signal. For example, the denoising algorithm may be a penalty weighted least squares method, a guided filtering algorithm or a deep learning algorithm.

[0082] Optionally, the noise reduction signal is processed using an image reconstruction algorithm to obtain a scattering artifact corrected image. The scattering artifact corrected image represents the cone beam CBCT image after the scattering artifact is corrected.

[0083] Optionally, the image reconstruction algorithm includes at least one of the following: a filtered back projection algorithm, an iterative algorithm, and a deep learning algorithm.

[0084] For example, the iterative algorithm may be a joint algebraic reconstruction algorithm, a total variation prior algorithm, and the like.

[0085] Optionally, the m projection angles include a target sampling angle and a non-target sampling angle; wherein, processing the sparse scattered signal corresponding to the target sampling angle based on an interpolation algorithm to obtain the target scattering signal corresponding to each of the m projection angles includes: processing the sparse scattered signal corresponding to the target sampling angle based on an interpolation algorithm to obtain the interpolated scattering signal corresponding to the non-target sampling angle; processing the sparse scattered signal corresponding to the target sampling angle and the interpolated scattering signal corresponding to the non-target sampling angle using a smoothing algorithm to obtain the target scattering signal corresponding to each of the m projection angles.

[0086] Optionally, the m projection angles include n target sampling angles and mn non-target sampling angles.

[0087] Optionally, an interpolation algorithm is used to process the sparse scattered signals corresponding to the n target sampling angles to obtain interpolated scattered signals corresponding to the mn non-target sampling angles. For example, the interpolation algorithm may be a linear interpolation algorithm, a quadratic interpolation algorithm, a cubic spline interpolation algorithm, or the like.

[0088] Optionally, a smoothing algorithm is used to process the sparse scattered signals corresponding to each of the n target sampling angles to obtain a target scattered signal corresponding to each of the n target sampling angles; a smoothing algorithm is used to process the interpolated scattered signals corresponding to each of the mn non-target sampling angles to obtain a target scattered signal corresponding to each of the mn non-target sampling angles.

[0089] For example, the smoothing algorithm may be a Gaussian filter algorithm, a mean filter algorithm, a median filter algorithm, or the like.

[0090] Optionally, only sparse scattered signals from a few target sampling angles are collected to reduce the number of scattered signals, and then the target scattered signals of all projection angles are obtained through an interpolation algorithm, effectively reducing the extra time and extra patient dose caused by additional scanning, thereby solving the technical problems of increased scanning time and scanning dose in the traditional dual scanning mode.

[0091] Figure 4A An example schematic diagram showing the correction effect of generating a scattering artifact corrected image based on a human head phantom according to an embodiment of the present invention is shown.

[0092] like Figure 4AAs shown, a human head phantom is irradiated with x-rays, a scattering artifact correction image 410 is obtained based on the traditional double scanning mode, and a scattering artifact correction image 420 is obtained based on the scattering artifact correction method of the embodiment of the present invention. The scattering artifact correction image 420 is subtracted from the scattering artifact correction image 410 to obtain a difference image 430. The traditional double scanning mode obtains scattering signals of 600 projection angles, and the scattering artifact correction method of the embodiment of the present invention only obtains sparse scattering signals of 15 projection angles, reducing the additional scanning dose and time by 97.5%. It can be seen from the difference image 430 that after reducing the additional scanning time and dose by 97.5%, there is almost no difference between the scattering artifact correction method of the embodiment of the present invention and the scattering artifact correction image obtained by the traditional double scanning mode. The scattering artifact correction method of the embodiment of the present invention reduces the additional scanning time and additional dose, and improves the scattering correction efficiency.

[0093] Figure 4B An exemplary schematic diagram showing the correction effect of generating a scattering artifact corrected image based on a human pelvic phantom according to an embodiment of the present invention is shown.

[0094] like Figure 4B As shown, a human pelvic phantom is irradiated with X-rays, and a scattering artifact correction image 440 is obtained based on the traditional double scanning mode, a scattering artifact correction image 450 is obtained based on the scattering artifact correction method according to the embodiment of the present invention combined with a uniform sampling algorithm, and a scattering artifact correction image 460 is obtained based on the scattering artifact correction method according to the embodiment of the present invention combined with a gradient sampling algorithm. The scattering artifact correction image 440 is subtracted from the scattering artifact correction image 450 to obtain a difference image 470; and the scattering artifact correction image 440 is subtracted from the scattering artifact correction image 460 to obtain a difference image 480. The traditional double scanning mode obtains scattering signals at 600 projection angles, and the scattering artifact correction method according to the embodiment of the present invention combined with the uniform sampling algorithm and the gradient sampling algorithm obtains scattering signals at 60 projection angles, reducing the additional scanning dose and time by 90.00%. It can be seen from the difference images 470 and 480 that the reconstructed image using uniform sampling for sparse sampling has a large local error in the direction where the object thickness is greater. This local error is reduced after using the gradient sampling algorithm, proving that it is also applicable to objects with severe scattering interference, and the sparse sampling guided by the gradient sampling algorithm can effectively reduce the local error caused by sparse sampling of non-uniform objects.

[0095] Based on the above scattering artifact image correction method, the present invention also provides a scattering artifact image correction device. Figure 5 The device is described in detail.

[0096] Figure 5A structural block diagram of a scattering artifact image correction device according to an embodiment of the present invention is shown.

[0097] like Figure 5 As shown, the scattering artifact image correction device 500 of this embodiment includes a first acquisition module 510 , a sampling module 520 , a second acquisition module 530 , a processing module 540 and a reconstruction module 550 .

[0098] The first acquisition module 510 is used to acquire a projection signal related to the target detection object, wherein the projection signal is obtained by scanning the target detection object based on m projection angles using a radiation source, and m is an integer greater than 1. In one embodiment, the first acquisition module 510 can be used to perform the operation S110 described above, which will not be repeated here.

[0099] The sampling module 520 is used to determine the target sampling angle from the m projection angles using a gradient sampling algorithm. In one embodiment, the sampling module 520 can be used to perform the operation S120 described above, which will not be described in detail here.

[0100] The second acquisition module 530 is used to acquire a sparse scattered signal corresponding to the target sampling angle, wherein the sparse scattered signal is obtained by scanning the target detection object using a radiation source based on the target sampling angle and a blocking plate, and the blocking plate is arranged between the radiation source and the target detection object. In one embodiment, the second acquisition module 530 can be used to perform the operation S130 described above, which will not be repeated here.

[0101] The processing module 540 is used to process the sparse scattered signal corresponding to the target sampling angle based on the interpolation algorithm to obtain the target scattered signal corresponding to each of the m projection angles. In one embodiment, the processing module 540 can be used to perform the operation S140 described above, which will not be described in detail here.

[0102] The reconstruction module 550 is used to perform image reconstruction according to the projection signals corresponding to the m projection angles and the target scattering signals to generate a scattering artifact corrected image. In one embodiment, the reconstruction module 550 can be used to perform the operation S150 described above, which will not be described in detail here.

[0103] Optionally, the sampling module 520 includes a first sampling submodule, a second sampling submodule, a third sampling submodule, a fourth sampling submodule, a fifth sampling submodule and a sixth sampling submodule.

[0104] The first sampling submodule is used to determine the i-1th gradient value of the i-1th projection angle according to the difference between the average value of the projection signal corresponding to the i-1th projection angle and the average value of the projection signal corresponding to the i-1th projection angle, wherein m≥i>1 and i is an integer.

[0105] The second sampling submodule is used to determine the second projection angle as the target sampling angle when i>2 and the first gradient value is greater than a preset sampling gradient threshold.

[0106] The third sampling submodule is used to determine the cumulative sum of the first gradient value and the second gradient value to obtain a second gradient accumulation value when i>2 and the first gradient value is less than or equal to a preset sampling gradient threshold.

[0107] The fourth sampling submodule is used to determine the third projection angle as the target sampling angle when the second gradient accumulation value is greater than a preset sampling gradient threshold.

[0108] The fifth sampling submodule is used to determine the cumulative sum of the first gradient value to the third gradient value to obtain a third gradient cumulative value when the second gradient cumulative value is less than or equal to a preset sampling gradient threshold.

[0109] The sixth sampling submodule is used to determine the fourth projection angle as the target sampling angle when the third gradient accumulation value is greater than a preset sampling gradient threshold.

[0110] Optionally, the sampling module 520 further includes a seventh sampling submodule, an eighth sampling submodule and a ninth sampling submodule.

[0111] The seventh sampling submodule is used to determine the i-th projection angle as the target sampling angle when i>2 and the i-1-th gradient value is greater than a preset sampling gradient threshold, wherein the i-1-th projection angle is the target sampling angle.

[0112] The eighth sampling submodule is used to determine the i-th gradient accumulation value according to the i-1-th gradient value and the i-th gradient value when the i-1-th gradient value is less than or equal to the preset sampling gradient threshold.

[0113] The ninth sampling submodule is used to determine the (i+1)th projection angle as the target sampling angle when the i-th gradient accumulation value is greater than a preset sampling gradient threshold.

[0114] Optionally, the reconstruction module 550 includes a first reconstruction submodule, a second reconstruction submodule and a third reconstruction submodule.

[0115] The first reconstruction submodule is used to subtract the target scattered signal corresponding to the projection angle from the projection signal corresponding to the projection angle to obtain the original projection signal corresponding to the projection angle.

[0116] The second reconstruction submodule is used to process the original signals corresponding to the m projection angles respectively by using a noise reduction algorithm to obtain noise reduction signals.

[0117] The third reconstruction submodule is used to process the noise reduction signal according to the image reconstruction algorithm to generate a scattering artifact corrected image.

[0118] Optionally, the processing module 540 includes a first processing submodule and a second processing submodule.

[0119] The first processing submodule is used to process the sparse scattered signal corresponding to the target sampling angle based on an interpolation algorithm to obtain an interpolated scattered signal corresponding to the non-target sampling angle.

[0120] The second processing submodule is used to process the sparse scattered signal corresponding to the target sampling angle and the interpolated scattered signal corresponding to the non-target sampling angle by using a smoothing algorithm to obtain the target scattered signal corresponding to each of the m projection angles.

[0121] Optionally, any multiple modules among the first acquisition module 510, the sampling module 520, the second acquisition module 530, the processing module 540 and the reconstruction module 550 can be combined into one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module. Optionally, at least one of the first acquisition module 510, the sampling module 520, the second acquisition module 530, the processing module 540 and the reconstruction module 550 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation modes of software, hardware and firmware or in a suitable combination of any of them. Alternatively, at least one of the first acquisition module 510, the sampling module 520, the second acquisition module 530, the processing module 540 and the reconstruction module 550 may be at least partially implemented as a computer program module, and when the computer program module is executed, the corresponding function may be performed.

[0122] Figure 6 A block diagram of an electronic device suitable for implementing a scattering artifact image correction method according to an embodiment of the present invention is shown.

[0123] Figure 6 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0124] like Figure 6As shown, a computer electronic device 600 according to an embodiment of the present invention includes a processor 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage part 608 into a random access memory (RAM) 603. The processor 601 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 601 may also include an onboard memory for caching purposes. The processor 601 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present invention.

[0125] In RAM 603, various programs and data required for the operation of electronic device 600 are stored. Processor 601, ROM 602 and RAM 603 are connected to each other via bus 604. Processor 601 performs various operations of the method flow according to the embodiment of the present invention by executing the programs in ROM 602 and / or RAM 603. It should be noted that the program can also be stored in one or more memories other than ROM 602 and RAM 603. Processor 601 can also perform various operations of the method flow according to the embodiment of the present invention by executing the programs stored in one or more memories.

[0126] Optionally, the electronic device 600 may further include an input / output (I / O) interface 605, which is also connected to the bus 604. The electronic device 600 may further include one or more of the following components connected to the input / output (I / O) interface 605: an input portion 606 including a keyboard, a mouse, etc.; an output portion 607 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 608 including a hard disk, etc.; and a communication portion 609 including a network interface card such as a LAN card, a modem, etc. The communication portion 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the input / output (I / O) interface 605 as needed. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 610 as needed, so that a computer program read therefrom is installed into the storage portion 608 as needed.

[0127] Optionally, the method flow according to the embodiment of the present invention can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program contains a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 609, and / or installed from the removable medium 611. When the computer program is executed by the processor 601, the above-mentioned functions defined in the system of the embodiment of the present invention are executed. Optionally, the system, equipment, device, module, unit, etc. described above can be implemented by a computer program module.

[0128] The present invention also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiment; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the scattering artifact image correction method according to the embodiment of the present invention is implemented.

[0129] Optionally, the computer-readable storage medium may be a non-volatile computer-readable storage medium. For example, it may include, but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device.

[0130] For example, optionally, the computer-readable storage medium may include the ROM 602 and / or the RAM 603 described above and / or one or more memories other than the ROM 602 and the RAM 603 .

[0131] An embodiment of the present invention also includes a computer program product, which includes a computer program, and the computer program contains program code for executing the method provided by the embodiment of the present invention. When the computer program product runs on an electronic device, the program code is used to enable the electronic device to implement the scattering artifact image correction method provided by the embodiment of the present invention.

[0132] When the computer program is executed by the processor 601, the above functions defined in the system / device of the embodiment of the present invention are performed. Optionally, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0133] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 609, and / or installed from a removable medium 611. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0134] Optionally, the program code for executing the computer program provided by the embodiment of the present invention can be written in any combination of one or more programming languages, specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, such as Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (e.g., using an Internet service provider to connect through the Internet).

[0135] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. In this regard, each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions. It can be understood by those skilled in the art that the features recorded in the various embodiments of the present invention can be combined and / or combined in various ways, even if such a combination or combination is not explicitly recorded in the present invention. In particular, without departing from the spirit and teachings of the present invention, the features recorded in the various embodiments of the present invention can be combined and / or combined in various ways. All these combinations and / or combinations fall within the scope of the present invention.

[0136] The embodiments of the present invention are described above. However, these embodiments are only for the purpose of illustration, and are not intended to limit the scope of the present invention. Although each embodiment is described above, it does not mean that the measures in each embodiment cannot be used in combination advantageously. Without departing from the scope of the present invention, those skilled in the art may make various substitutions and modifications, which should all fall within the scope of the present invention.

Claims

1. A scattering artifact image correction method, characterized in that: The method comprises: Acquire a projection signal related to the target detection object, wherein the projection signal is obtained by scanning the target detection object based on m projection angles using a radiation source, where m is an integer greater than 1; Determine a target sampling angle from the m projection angles using a gradient sampling algorithm; Acquire a sparse scattered signal corresponding to the target sampling angle, wherein the sparse scattered signal is obtained by scanning the target detection object using the radiation source based on the target sampling angle and a blocking plate, and the blocking plate is arranged between the radiation source and the target detection object; Processing the sparse scattered signal corresponding to the target sampling angle based on an interpolation algorithm to obtain a target scattered signal corresponding to each of the m projection angles; Image reconstruction is performed according to the projection signals corresponding to each of the m projection angles and the target scattering signal to generate a scattering artifact corrected image.

2. The method according to claim 1, characterized in that Determining the target sampling angle from the m projection angles using a gradient sampling algorithm includes: Determine the i-1th gradient value of the i-1th projection angle according to the difference between the average value of the projection signal corresponding to the i-th projection angle and the average value of the projection signal corresponding to the i-1th projection angle, where m≥i>1 and i is an integer; When i>2 and the first gradient value is greater than a preset sampling gradient threshold, determining the second projection angle as the target sampling angle; When i>2 and the first gradient value is less than or equal to the preset sampling gradient threshold, determining the cumulative sum of the first gradient value and the second gradient value to obtain a second gradient cumulative value; When the second gradient cumulative value is greater than the preset sampling gradient threshold, determining the third projection angle as the target sampling angle; When the second gradient cumulative value is less than or equal to the preset sampling gradient threshold, determining the cumulative sum of the first gradient value to the third gradient value to obtain a third gradient cumulative value; When the third gradient accumulation value is greater than the preset sampling gradient threshold, the fourth projection angle is determined as the target sampling angle.

3. The method according to claim 2, characterized in that The step of determining the target sampling angle from the m projection angles by using a gradient sampling algorithm further comprises: When i>2 and the i-1th gradient value is greater than the preset sampling gradient threshold, the i-th projection angle is determined as the target sampling angle, wherein the i-1th projection angle is the target sampling angle; When the i-1th gradient value is less than or equal to the preset sampling gradient threshold, determining the i-th gradient cumulative value according to the i-1th gradient value and the i-th gradient value; When the i-th gradient cumulative value is greater than the preset sampling gradient threshold, the (i+1)-th projection angle is determined as the target sampling angle.

4. The method according to claim 2, characterized in that: The preset sampling gradient threshold is obtained based on the following operations: Determine a total gradient value according to the sum of the gradient values ​​corresponding to the m projection angles; The preset sampling gradient threshold is determined according to the ratio between the total gradient value and the preset sampling angle number.

5. The method according to claim 1, characterized in that The performing image reconstruction according to the projection signals and the target scattering signals corresponding to the m projection angles to generate a corrected scattering artifact image comprises: Subtracting a target scattered signal corresponding to the projection angle from a projection signal corresponding to the projection angle to obtain an original signal corresponding to the projection angle; Using a noise reduction algorithm to process the original signals corresponding to the m projection angles to obtain noise reduction signals; The noise reduction signal is processed according to an image reconstruction algorithm to generate the scattering artifact corrected image.

6. The method according to claim 5, characterized in that The image reconstruction algorithm includes at least one of the following: Filtered back projection algorithm, iterative algorithm, deep learning algorithm.

7. The method according to claim 1, characterized in that The m projection angles include the target sampling angle and the non-target sampling angle; The step of processing the sparse scattered signal corresponding to the target sampling angle based on an interpolation algorithm to obtain the target scattered signal corresponding to each of the m projection angles includes: Processing the sparse scattered signal corresponding to the target sampling angle based on the interpolation algorithm to obtain an interpolated scattered signal corresponding to the non-target sampling angle; The sparse scattered signal corresponding to the target sampling angle and the interpolated scattered signal corresponding to the non-target sampling angle are processed by a smoothing algorithm to obtain the target scattered signal corresponding to each of the m projection angles.

8. A scattering artifact image correction device, characterized in that: The device comprises: A first acquisition module is used to acquire a projection signal related to a target detection object, wherein the projection signal is obtained by scanning the target detection object based on m projection angles using a radiation source, where m is an integer greater than 1; A sampling module, used to determine a target sampling angle from the m projection angles using a gradient sampling algorithm; a second acquisition module, configured to acquire a sparse scattered signal corresponding to the target sampling angle, wherein the sparse scattered signal is obtained by scanning the target detection object using the radiation source based on the target sampling angle and a blocking plate, wherein the blocking plate is disposed between the radiation source and the target detection object; A processing module, used for processing the sparse scattered signal corresponding to the target sampling angle based on an interpolation algorithm to obtain a target scattered signal corresponding to each of the m projection angles; The reconstruction module is used to perform image reconstruction according to the projection signals corresponding to the m projection angles and the target scattering signals to generate a scattering artifact corrected image.

9. An electronic device, characterized in that: include: one or more processors; a memory for storing one or more instructions, Wherein, when the one or more instructions are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: Executable instructions are stored thereon, and when the instructions are executed by a processor, the processor is caused to perform the method according to any one of claims 1 to 7.

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