Scattering artifact image correction method and apparatus, device, and storage medium
By processing the sparse scattering signal of the cone-beam CT system using gradient sampling and interpolation algorithms, scattering artifact-corrected images are generated, solving the problems of scattering artifacts and dose increase in the cone-beam CT system, improving image quality and reducing scan time.
Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- UNIV OF SCI & TECH OF CHINA
- Filing Date
- 2024-12-13
- Publication Date
- 2026-06-11
AI Technical Summary
In cone-beam computed tomography (CBCT) systems, the large imaging area of the flat panel detector increases the scattered signal, leading to reduced contrast and scattering artifacts in the reconstructed image. Existing correction methods increase the X-ray dose to the scanned object and have low accuracy in estimating the scattered signal.
The target sampling angle is determined from multiple projection angles using a gradient sampling algorithm, sparse scattering signals are obtained using a blocking plate, and the sparse scattering signals are processed by an interpolation algorithm. Finally, an image with scattering artifact correction is generated by combining the image reconstruction algorithm.
It effectively reduces local errors caused by sparse sampling of non-uniform objects, reduces additional scanning time and patient dose, and improves image quality.
Smart Images
Figure CN2024136514_11062026_PF_FP_ABST
Abstract
Description
Methods, apparatus, equipment and storage media for correcting scattering artifacts in images Technical Field
[0001] This invention relates to the field of medical imaging technology, and more specifically to a method, apparatus, device, and storage medium for correcting scattering artifact images. Background Technology
[0002] Cone-beam computed tomography (CBCT) systems mainly consist of an X-ray tube, a flat panel detector, a motion system, and an image processing system. Due to the use of a large imaging area flat panel detector, CBCT significantly increases the amount of scattered signal, ultimately leading to reduced contrast, CT value shifts, and scattering artifacts in the reconstructed images, greatly degrading image quality. In clinical practice, existing methods for correcting image artifacts involve measuring more angles of scattered signal, resulting in a higher X-ray dose to the scanned object. Furthermore, these methods are easily limited by the shape of the scanned object, leading to technical problems such as low accuracy in estimating scattered signal. Summary of the Invention
[0003] In view of the above problems, the present invention provides a method, apparatus, device and storage medium for correcting scattering artifacts in images.
[0004] According to a first aspect of the present invention, a method for correcting scattering artifacts in an image 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 using a radiation source based on m projection angles, where 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 using a radiation source based on the target sampling angle and a baffle plate, the baffle plate being disposed between the radiation source and the target detection object; processing the sparse scattering signal corresponding to the target sampling angle using an interpolation algorithm to obtain a target scattering signal corresponding to each of the m projection angles; and reconstructing an image based on the projection signals corresponding to each of the m projection angles and the target scattering signal 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-1)th gradient value of the (i-1)th projection angle based on 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-1)th projection angle, where m ≥ i > 1 and i is an integer; determining 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; determining the cumulative sum of the first and second gradient values when i > 2 and the first gradient value is less than or equal to the preset sampling gradient threshold, to obtain the second gradient cumulative value; determining the third projection angle as the target sampling angle when the second gradient cumulative value is greater than the preset sampling gradient threshold; determining the cumulative sum of the first to third gradient values when the second gradient cumulative value is less than or equal to the preset sampling gradient threshold, to obtain the third gradient cumulative value; and determining the fourth projection angle as the target sampling angle when the third gradient cumulative value is greater than the preset sampling gradient threshold.
[0006] Optionally, determining the target sampling angle from m projection angles using the gradient sampling algorithm further includes: when i > 2 and the (i-1)th gradient value is greater than a preset sampling gradient threshold, determining the i-th projection angle as the target sampling angle, where the (i-1)th projection angle is the target sampling angle; when the (i-1)th gradient value is less than or equal to the preset sampling gradient threshold, determining the i-th gradient cumulative value based on the (i-1)th 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+1)th projection angle as the target sampling angle.
[0007] Optionally, the preset sampling gradient threshold is obtained based on the following operations: the total gradient value is determined by the sum of the gradient values corresponding to each of the m projection angles; the preset sampling gradient threshold is determined based on the ratio between the total gradient value and the preset number of sampling angles.
[0008] Optionally, image reconstruction based on the projection signals and target scattering signals corresponding to each of the m projection angles to generate a corrected scattering artifact image includes: subtracting the target scattering 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; processing the original projection signals corresponding to each of the m projection angles using a denoising algorithm to obtain a denoised signal; and processing the denoised signal using an 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, or a deep learning algorithm.
[0010] Optionally, the m projection angles include target sampling angles and non-target sampling angles; wherein, processing the sparse scattering signal corresponding to the target sampling angle based on the interpolation algorithm to obtain the target scattering signal corresponding to each of the m projection angles includes: processing the sparse scattering signal corresponding to the target sampling angle based on the interpolation algorithm to obtain the interpolated scattering signal corresponding to the non-target sampling angle; and processing the sparse scattering 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 apparatus, comprising:
[0012] The first acquisition module is used to acquire projection signals related to the target detection object. The projection signals are obtained by scanning the target detection object with a radiation source based on m projection angles, where m is an integer greater than 1.
[0013] The sampling module is used to determine the target sampling angle from m projection angles using a gradient sampling algorithm;
[0014] The second acquisition module is used to acquire the sparse scattering signal corresponding to the target sampling angle. The sparse scattering signal is obtained by scanning the target detection object with a radiation source based on the target sampling angle and a baffle plate. The baffle plate is set between the radiation source and the target detection object.
[0015] The processing module is used to process the sparse scattering signal corresponding to the target sampling angle based on the interpolation algorithm to obtain the target scattering signal corresponding to each of the m projection angles.
[0016] The reconstruction module is used to reconstruct the image based on the projection signals corresponding to each of the m projection angles and the target scattering signal, and generate a scattering artifact corrected image.
[0017] A third aspect of the present invention provides an electronic device comprising: one or more processors; and 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 perform the above-described scattering artifact image correction method.
[0018] A fourth aspect of the present invention also provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, cause the processor to perform the above-described scattering artifact image correction method.
[0019] The scattering artifact image correction method, apparatus, device, and storage medium provided by the present invention determine the target sampling angle from m projection angles using a gradient sampling algorithm; then, a baffle is placed between the radiation source and the target object to acquire the scattering signal corresponding to the target sampling angle, thereby performing interpolation and image reconstruction processing to obtain a scattering artifact corrected image. Because the gradient sampling algorithm guides sampling based on the degree of change in the projection signal of the target object, it effectively reduces local errors caused by sparse sampling of non-uniform objects; furthermore, by acquiring only sparse scattering signals from a few target sampling angles and then obtaining the target scattering signals for each of the projection angles through an interpolation algorithm, it effectively reduces the additional time and patient dose caused by additional scanning. Attached Figure Description
[0020] Figure 1 shows a flowchart of a scattering artifact image correction method according to an embodiment of the present invention.
[0021] Figure 2 shows an example schematic diagram of the placement position of the barrier plate according to an embodiment of the present invention.
[0022] Figure 3 shows an example schematic diagram of a barrier plate according to an embodiment of the present invention.
[0023] Figure 4A shows an example schematic diagram of the correction effect of generating a scattering artifact correction image based on a human head phantom according to an embodiment of the present invention.
[0024] Figure 4B shows an example schematic diagram of the correction effect of generating a scattering artifact correction image based on a human pelvic phantom according to an embodiment of the present invention.
[0025] Figure 5 shows a structural block diagram of a scattering artifact image correction device according to an embodiment of the present invention.
[0026] Figure 6 shows a block diagram of an electronic device suitable for implementing a scattering artifact image correction method according to an embodiment of the present invention. Detailed Implementation
[0027] Hereinafter, 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 invention. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the invention for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concept of the invention.
[0028] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the invention. The terms “comprising,” “including,” etc., as used herein indicate the presence of features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.
[0029] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.
[0030] When using expressions such as "at least one of A, B, and C", they should generally be interpreted in accordance with the meaning that is commonly understood by a person skilled in the art (e.g., "a system having at least one of A, B, and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B, and C, etc.).
[0031] In the process of developing this invention, it was discovered that cone-beam computed tomography (CBCT) systems mainly consist of an X-ray tube, a flat panel detector, a motion system, and an image processing system. CBCT, due to the use of a large imaging area flat panel detector, leads to a significant increase in scattered signals, ultimately resulting in reduced contrast, CT value shifts, and scattering artifacts in the reconstructed images, which greatly degrades image quality. In clinical practice, existing methods for correcting image artifacts, the more angles of the scattering signal measured, the higher the X-ray dose received by the scanned object. Furthermore, these methods are easily limited by the shape of the scanned object, leading to low accuracy in estimating the scattering signal.
[0032] In view of this, embodiments of the present invention provide a method, apparatus, device, and storage medium for correcting scattering artifact images. The method includes: acquiring a projection signal related to a target detection object, wherein the projection signal is obtained by scanning the target detection object using a radiation source based on m projection angles, where 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 using a radiation source based on the target sampling angle and a baffle plate, the baffle plate being disposed between the radiation source and the target detection object; processing the sparse scattering signal corresponding to the target sampling angle using an interpolation algorithm to obtain target scattering signals corresponding to each of the m projection angles; and reconstructing an image based on the projection signals corresponding to each of the m projection angles and the target scattering signals to generate a scattering artifact corrected image.
[0033] In the technical solution of this invention, the user information (including but not limited to user personal information, user image information, user device information, such as location information) and data (including but not limited to data used for analysis, stored data, and displayed data) involved are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of related data all comply with relevant laws, regulations, and standards, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entry points for users to choose to authorize or refuse.
[0034] It should be noted that the sequence numbers of the operations in the following methods are for descriptive purposes only and should not be considered as indicating the execution order of the operations. Unless explicitly stated otherwise, the method does not need to be executed in the exact order shown.
[0035] Figure 1 shows a flowchart of a scattering artifact image correction method according to an embodiment of the present invention.
[0036] As shown in Figure 1, the method 100 includes operations S110 to S150.
[0037] In operation S110, the projection signal related to the target detection object is acquired.
[0038] Optionally, the target detection object represents the object to be detected, such as a human head phantom or a human pelvic phantom.
[0039] Optionally, during imaging using a cone beam computed tomography (CBCT) system, the radiation source scans the target object based on m projection angles to obtain projection signals corresponding to each of the m projection angles, where m is an integer greater than 1.
[0040] For example, the projection angle of the radiation source can be adjusted every 1° to obtain the projection signals corresponding to 0° to 600°.
[0041] In operation S120, the target sampling angle is determined from m projection angles using a gradient sampling algorithm.
[0042] Optionally, determining one or more target sampling angles from m projection angles using a gradient sampling algorithm may include: determining whether the next projection angle is a target sampling angle based on the intensity gradient changes of the projection signals of the current projection angle and the next projection angle.
[0043] For example, when the intensity gradient changes significantly, the subsequent projection angle can be determined as the target sampling angle; when the intensity gradient changes slightly, the subsequent projection angle can be determined as the non-target sampling angle.
[0044] Optionally, a uniform sampling algorithm or a non-uniform sampling algorithm can be used to determine the target sampling angle. For example, if m is 600, the projection angle of the radiation source is adjusted every 10°, and 60 target sampling angles are determined from 600 projection angles.
[0045] Optionally, the number of target sampling angles is much smaller than the number of projection angles.
[0046] In operation S130, the sparse scattering signal corresponding to the target sampling angle is acquired.
[0047] Optionally, a baffle is placed between the radiation source and the target object. During the imaging process using a cone-beam computed tomography system, the radiation source scans the target object based on the target sampling angle and the baffle to obtain a sparse scattering signal corresponding to the target sampling angle.
[0048] Optionally, the rays include emitted rays and scattered rays. Emitted rays irradiate the target object, generating a primary emission signal, while scattered rays irradiate the target object, generating a scattered signal that produces noise or image artifacts. Rays irradiating the target object generate a projection signal that forms an image. The projection signal includes both primary and scattered signals, with sparse scattered signals characterizing the scattered signal.
[0049] Optionally, the beam deflector should be able to block at least 99.9% of the emitted rays. The beam deflector can be a full beam deflector, and there are no restrictions on its specific shape.
[0050] Figure 2 shows an example schematic diagram of the placement position of the barrier plate according to an embodiment of the present invention.
[0051] As shown in Figure 2, the radiation source can be an X-ray source, the baffle can be a beam baffle, the target detection object is the scanning object, the beam baffle 220 is installed between the X-ray source 210 and the scanning object 230, the X-ray source 210 emits X-rays based on the target sampling angle, the X-rays pass through the beam baffle 220 to irradiate the scanning object 230, and the flat panel detector 240 collects the sparse scattering signal.
[0052] Figure 3 shows an example schematic diagram of a barrier plate according to an embodiment of the present invention.
[0053] As shown in Figure 3, X-rays pass through a beam blocking plate to irradiate the scanned object. The blocking plate includes a hollow area 310 and a blocking area 320. The sparse scattering signal collected by the flat panel detector includes the scattering signal generated by the scattered rays passing through the hollow area 310 to irradiate the target object and then being deflected before reaching the flat panel detector.
[0054] In operation S140, the sparse scattering signal corresponding to the target sampling angle is processed based on the interpolation algorithm to obtain the target scattering signal corresponding to each of the m projection angles.
[0055] Optionally, the remaining angles among the m projection angles, excluding the target sampling angle, are determined as the angles to be interpolated. For example, if the target sampling angles are determined to be 0°, 2°, and 5° from the projection angles of 0°, 1°, 2°, 3°, 4°, and 5°, then the angles to be interpolated are 1°, 3°, and 4°.
[0056] Optionally, an interpolation algorithm is used to process the sparse scattering signal corresponding to the target sampling angle to obtain the sparse scattering signal corresponding to the angle to be interpolated. Based on the sparse scattering signals corresponding to the target sampling angle and the angle to be interpolated, the target scattering signals corresponding to each of the m projection angles are obtained.
[0057] Optionally, target scattering signals have higher integrity, accuracy, and smoothness compared to sparse scattering signals.
[0058] In operation S150, image reconstruction is performed based on the projection signals and target scattering signals corresponding to each of the m projection angles, generating a scattering artifact corrected image.
[0059] Optionally, based on the projection signals and target scattering signals corresponding to each of the m projection angles, the original scattering signals corresponding to each of the m projection angles are obtained, and image reconstruction is performed based on the original scattering signals corresponding to each of the m projection angles to generate a scattering artifact corrected image.
[0060] Optionally, by using a gradient sampling algorithm to guide sampling based on the degree of change in the projection signal of the target object, the local error caused by sparse sampling of non-uniform objects is effectively reduced. In addition, by collecting sparse scattering signals from only a few target sampling angles and then obtaining the target scattering signals for each of the projection angles through an interpolation algorithm, the additional time and additional patient dose caused by additional scanning are effectively reduced.
[0061] Optionally, determining the target sampling angle from m projection angles using a gradient sampling algorithm includes: determining the (i-1)th gradient value of the (i-1)th projection angle based on 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-1)th projection angle, where m ≥ i > 1 and i is an integer; determining 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; determining the cumulative sum of the first and second gradient values when i > 2 and the first gradient value is less than or equal to the preset sampling gradient threshold, to obtain the second gradient cumulative value; determining the third projection angle as the target sampling angle when the second gradient cumulative value is greater than the preset sampling gradient threshold; determining the cumulative sum of the first to third gradient values when the second gradient cumulative value is less than or equal to the preset sampling gradient threshold, to obtain the third gradient cumulative value; and determining the fourth projection angle as the target sampling angle when the third gradient cumulative value is greater than the preset sampling gradient threshold.
[0062] Optionally, a cone-beam computed tomography (CBCT) system is used to generate multiple projection images corresponding to different projection angles. For the projection image corresponding to the i-th projection angle, the average value of the projection signal corresponding to the i-th projection angle is obtained based on the ratio of the projection signal to the number of pixels in the projection image.
[0063] Optionally, the (i-1)th gradient value represents the degree of change of the projection signal between the (i-1)th projection angle and the ith projection angle.
[0064] For example, the second gradient value corresponding to the second projection angle is determined based on 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.
[0065] Optionally, the projection angle 0° is the first projection angle. The first projection angle is used as the target sampling angle for 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.
[0066] Optionally, if the first gradient value is less than or equal to a preset sampling gradient threshold, the second projection angle is skipped and sampling is not performed, and the sum of the first and second gradient values is calculated as the second gradient cumulative value; if the second gradient cumulative value is greater than the preset sampling gradient threshold, the third projection angle is determined as the target sampling angle; if the second gradient cumulative value is less than or equal to the preset sampling gradient threshold, the third projection angle is skipped and sampling is not performed, and the sum of the first to third gradient values is calculated to determine the third gradient cumulative value; if the third gradient cumulative value is greater than the preset sampling gradient threshold, the fourth projection angle is determined as the target sampling angle.
[0067] Optionally, determining the target sampling angle from m projection angles using the gradient sampling algorithm further includes: when i > 2 and the (i-1)th gradient value is greater than a preset sampling gradient threshold, determining the i-th projection angle as the target sampling angle, where the (i-1)th projection angle is the target sampling angle; when the (i-1)th gradient value is less than or equal to the preset sampling gradient threshold, determining the i-th gradient cumulative value based on the (i-1)th 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+1)th projection angle as the target sampling angle.
[0068] Optionally, if the (i-1)th projection angle is the target sampling angle, the (i-1)th projection angle is used as the target sampling angle for the initial iteration, and the magnitude of the (i-1)th gradient value and the preset sampling gradient threshold are determined.
[0069] Optionally, if the (i-1)th gradient value is greater than the preset sampling gradient threshold, the next projection angle (the i-th projection angle) of the (i-1)th projection angle is determined as the target sampling angle; if the (i-1)th 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 magnitude of the i-th gradient cumulative value and the preset sampling gradient threshold is determined.
[0070] Optionally, if the cumulative gradient value of the i-th gradient is greater than the preset sampling gradient threshold, the next projection angle (the (i+1)-th projection angle) of the i-th projection angle is determined as the target sampling angle; if the gradient value of the i-th gradient is less than or equal to the preset sampling gradient threshold, the (i+1)-th projection angle is skipped and sampling is not performed, and the comparison between the (i+1)-th gradient cumulative value and the preset sampling gradient threshold continues. The (i+1)-th gradient cumulative value is determined based on the sum of the gradient values from the (i-1)-th to the (i+1)-th gradient values.
[0071] Optionally, if the angle in the last iteration exceeds the number m of the projected angles, stop iterative sampling and record the distribution of the target sampling angles.
[0072] Optionally, a gradient sampling algorithm can be used to select the target sampling angle based on the gradient value change of the projection signal. The sampling is guided by the change of the projection signal of the scanned object, which effectively reduces the local error caused by sparse sampling of non-uniform objects.
[0073] Optionally, the preset sampling gradient threshold is obtained based on the following operations: the total gradient value is determined by the sum of the gradient values corresponding to each of the m projection angles; the preset sampling gradient threshold is determined based on the ratio between the total gradient value and the preset number of sampling angles.
[0074] Optionally, the preset number of sampling angles represents the expected number of target sampling angles.
[0075] Optionally, first determine the m projection angles and the preset number of sampling angles n, and calculate the gradient value of each of the m projection angles; then determine the total gradient value based on the sum of the gradient values of each of the m projection angles; finally, determine the preset sampling gradient threshold based on the ratio between the total gradient value and the preset number of sampling angles.
[0076] Optionally, image reconstruction is performed based on the projection signals corresponding to each of the m projection angles and the target scattering signal to generate a corrected scattering artifact image, including:
[0077] Subtract the target scattering signal corresponding to the projection angle from the projection signal corresponding to the projection angle to obtain the original emission signal corresponding to the projection angle; process the original emission signals corresponding to each of the m projection angles using a denoising algorithm to obtain a denoised signal; process the denoised signal according to the image reconstruction algorithm to generate a scattering artifact corrected image.
[0078] Optionally, for each projection angle, the target scattering signal is subtracted from the projection signal to obtain the original emission signal. The original emission signal represents the projection signal that does not contain scattering information.
[0079] For example, for a projection angle of 1°, the target scattering signal corresponding to 1° is subtracted from the projection signal corresponding to 1° to obtain the original signal corresponding to the projection angle of 1°.
[0080] Optionally, a denoising algorithm can be used to process the original projected signals corresponding to each of the m projection angles to obtain the denoised signals. For example, the denoising algorithm can be penalized weighted least squares, guided filtering, or deep learning algorithms.
[0081] Optionally, an image reconstruction algorithm can be used to process the denoised signal to obtain a scattering artifact-corrected image. The scattering artifact-corrected image represents the cone-beam CBCT image after scattering artifact correction.
[0082] Optionally, the image reconstruction algorithm includes at least one of the following: a filtered back-projection algorithm, an iterative algorithm, or a deep learning algorithm.
[0083] For example, iterative algorithms can include joint algebraic reconstruction algorithms, total variational prior algorithms, etc.
[0084] Optionally, the m projection angles include target sampling angles and non-target sampling angles; wherein, processing the sparse scattering signal corresponding to the target sampling angle based on the interpolation algorithm to obtain the target scattering signal corresponding to each of the m projection angles includes: processing the sparse scattering signal corresponding to the target sampling angle based on the interpolation algorithm to obtain the interpolated scattering signal corresponding to the non-target sampling angle; and processing the sparse scattering 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.
[0085] Optionally, the m projection angles include n target sampling angles and mn non-target sampling angles.
[0086] Optionally, an interpolation algorithm is used to process the sparse scattering signals corresponding to each of the n target sampling angles to obtain the interpolated scattering signals corresponding to each of the mn non-target sampling angles. For example, the interpolation algorithm can be a linear interpolation algorithm, a quadratic interpolation algorithm, a cubic spline interpolation algorithm, etc.
[0087] Optionally, a smoothing algorithm is used to process the sparse scattering signals corresponding to each of the n target sampling angles to obtain the target scattering signals corresponding to each of the n target sampling angles; a smoothing algorithm is used to process the interpolated scattering signals corresponding to each of the mn non-target sampling angles to obtain the target scattering signals corresponding to each of the mn non-target sampling angles.
[0088] For example, smoothing algorithms can include Gaussian filtering, mean filtering, median filtering, etc.
[0089] Optionally, only sparse scattering signals from a few target sampling angles are collected, reducing the number of scattering signals. Then, the target scattering signals for each projection angle are obtained through an interpolation algorithm, effectively reducing the additional time and patient dose caused by additional scanning, thereby solving the technical problems of increased scanning time and scanning dose in traditional dual-scanning modes.
[0090] Figure 4A shows an example schematic diagram of the correction effect of generating a scattering artifact correction image based on a human head phantom according to an embodiment of the present invention.
[0091] As shown in Figure 4A, a human head phantom is irradiated with X-rays. A scattering artifact-corrected image 410 is obtained using a conventional dual-scan mode, and a scattering artifact-corrected image 420 is obtained using the scattering artifact correction method of this embodiment. Subtracting the scattering artifact-corrected image 420 from the scattering artifact-corrected image 410 yields a difference image 430. The conventional dual-scan mode acquires scattering signals from 600 projection angles, while the scattering artifact correction method of this embodiment acquires sparse scattering signals from only 15 projection angles, reducing the additional scan dose and time by 97.5%. As can be seen from the difference image 430, after reducing the additional scan time and dose by 97.5%, the scattering artifact correction method of this embodiment is almost indistinguishable from the scattering artifact-corrected image obtained by the conventional dual-scan mode. The scattering artifact correction method of this embodiment reduces additional scan time and dose, and improves scattering correction efficiency.
[0092] Figure 4B shows an example schematic diagram of the correction effect of generating a scattering artifact correction image based on a human pelvic phantom according to an embodiment of the present invention.
[0093] As shown in Figure 4B, a human pelvic phantom is irradiated with X-rays. Based on the traditional dual-scan mode, a scattering artifact-corrected image 440 is obtained. Based on the scattering artifact correction method of this embodiment combined with a uniform sampling algorithm, a scattering artifact-corrected image 450 is obtained. Based on the scattering artifact correction method of this embodiment combined with a gradient sampling algorithm, a scattering artifact-corrected image 460 is obtained. Subtracting the scattering artifact-corrected image 440 from the scattering artifact-corrected image 450 yields a difference image 470; subtracting the scattering artifact-corrected image 440 from the scattering artifact-corrected image 460 yields a difference image 480. The traditional dual-scan mode acquires scattering signals from 600 projection angles. The scattering artifact correction method of this embodiment, combining both the uniform sampling algorithm and the gradient sampling algorithm, acquires scattering signals from 60 projection angles each, reducing the additional scan dose and time by 90.00%. As can be seen from difference images 470 and 480, the reconstructed image using uniform sampling for sparse sampling has a large local error in the direction of the object's thickness. This local error is reduced after using the gradient sampling algorithm, proving that it is also applicable to objects with severe scattering interference. Furthermore, sparse sampling guided by the gradient sampling algorithm can effectively reduce the local error caused by sparse sampling of non-uniform objects.
[0094] Based on the above-described scattering artifact image correction method, this invention also provides a scattering artifact image correction device. The device will be described in detail below with reference to Figure 5.
[0095] Figure 5 shows a structural block diagram of a scattering artifact image correction device according to an embodiment of the present invention.
[0096] As shown in Figure 5, 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.
[0097] The first acquisition module 510 is used to acquire projection signals related to the target detection object. The projection signals are obtained by scanning the target detection object using a radiation source based on m projection angles, where 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.
[0098] The sampling module 520 is used to determine the target sampling angle from m projected 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 repeated here.
[0099] The second acquisition module 530 is used to acquire a sparse scattering signal corresponding to the target sampling angle. The sparse scattering signal is obtained by scanning the target object using a radiation source based on the target sampling angle and a blocking plate, with the blocking plate positioned between the radiation source and the target 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.
[0100] The processing module 540 is used to process the sparse scattering signal corresponding to the target sampling angle based on the interpolation algorithm to obtain the target scattering 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 repeated here.
[0101] The reconstruction module 550 is used to reconstruct the image based on the projection signals corresponding to each of the m projection angles and the target scattering signal, generating 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 repeated here.
[0102] 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.
[0103] The first sampling submodule is used to determine the (i-1)th gradient value of the (i-1)th projection angle based on 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-1)th projection angle, where m≥i>1 and i is an integer.
[0104] 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 the preset sampling gradient threshold.
[0105] The third sampling submodule is used to determine the sum of the first gradient value and the second gradient value when i > 2 and the first gradient value is less than or equal to the preset sampling gradient threshold, so as to obtain the second gradient cumulative value.
[0106] 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 the preset sampling gradient threshold.
[0107] The fifth sampling submodule is used to determine the sum of the first to third gradient values and obtain the third gradient cumulative value when the second gradient cumulative value is less than or equal to the preset sampling gradient threshold.
[0108] The sixth sampling submodule is used to determine the fourth projection angle as the target sampling angle when the cumulative value of the third gradient is greater than the preset sampling gradient threshold.
[0109] Optionally, the sampling module 520 may also include a seventh sampling submodule, an eighth sampling submodule, and a ninth sampling submodule.
[0110] 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 the preset sampling gradient threshold, wherein the i-1-th projection angle is the target sampling angle.
[0111] The eighth sampling submodule is used to determine the cumulative value of the i-th gradient based on the (i-1)-th gradient value and the i-th gradient value when the i-th gradient value is less than or equal to the preset sampling gradient threshold.
[0112] The ninth sampling submodule is used to determine the (i+1)th projection angle as the target sampling angle when the cumulative gradient value of the i-th gradient is greater than the preset sampling gradient threshold.
[0113] Optionally, the reconstruction module 550 includes a first reconstruction submodule, a second reconstruction submodule, and a third reconstruction submodule.
[0114] The first reconstruction submodule is used to subtract the target scattering signal corresponding to the projection angle from the projection signal corresponding to the projection angle to obtain the original scattering signal corresponding to the projection angle.
[0115] The second reconstruction submodule is used to process the original projected signals corresponding to each of the m projection angles using a noise reduction algorithm to obtain the noise-reduced signal.
[0116] The third reconstruction submodule is used to process the noise-reducing signal according to the image reconstruction algorithm and generate a scattering artifact-corrected image.
[0117] Optionally, the processing module 540 includes a first processing submodule and a second processing submodule.
[0118] The first processing submodule is used to process the sparse scattering signal corresponding to the target sampling angle based on the interpolation algorithm to obtain the interpolated scattering signal corresponding to the non-target sampling angle.
[0119] The second processing submodule is used to process the sparse scattering signal corresponding to the target sampling angle and the interpolated scattering signal corresponding to the non-target sampling angle using a smoothing algorithm, so as to obtain the target scattering signal corresponding to each of the m projection angles.
[0120] Optionally, any multiple modules among the first acquisition module 510, sampling module 520, second acquisition module 530, processing module 540, and reconstruction module 550 may be combined into one module, or any one of these modules may be split into multiple modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of other modules and implemented in one module. Optionally, at least one of the first acquisition module 510, sampling module 520, second acquisition module 530, processing module 540, and reconstruction module 550 may be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), programmable logic array (PLA), system-on-a-chip, system-on-a-substrate, system-on-package, application-specific integrated circuit (ASIC), or any other reasonable means of integrating or packaging circuitry, or implemented in software, hardware, or firmware, or in any one of the three implementation methods or a suitable combination of any of them. Alternatively, at least one of the first acquisition module 510, sampling module 520, second acquisition module 530, processing module 540, and reconstruction module 550 may be implemented at least partially as a computer program module, which can perform corresponding functions when the computer program module is run.
[0121] Figure 6 shows a block diagram of an electronic device suitable for implementing a scattering artifact image correction method according to an embodiment of the present invention.
[0122] The electronic device shown in Figure 6 is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.
[0123] As shown in FIG6, 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 portion 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 an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 601 may also include 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.
[0124] RAM 603 stores various programs and data required for the operation of electronic device 600. Processor 601, ROM 602, and RAM 603 are interconnected via bus 604. Processor 601 executes various operations of the method flow according to embodiments of the present invention by executing programs in ROM 602 and / or RAM 603. It should be noted that programs may also be stored in one or more memories other than ROM 602 and RAM 603. Processor 601 may also execute various operations of the method flow according to embodiments of the present invention by executing programs stored in one or more memories.
[0125] Optionally, the electronic device 600 may also include an input / output (I / O) interface 605, which is also connected to the bus 604. The electronic device 600 may also include one or more of the following components connected to the input / output (I / O) interface 605: an input section 606 including a keyboard, mouse, etc.; an output section 607 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN card, modem, etc. The communication section 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 disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 610 as needed so that computer programs read from it can be installed into the storage section 608 as needed.
[0126] Optionally, the method flow according to embodiments of the present invention can be implemented as a computer software program. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable storage medium, the computer program containing program code for performing the method shown in the flowchart. In such embodiments, the computer program can be downloaded and installed from a network via communication section 609, and / or installed from removable medium 611. When the computer program is executed by processor 601, it performs the functions defined in the system of embodiments of the present invention. Optionally, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.
[0127] The present invention also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs, which, when executed, implement the scattering artifact image correction method according to embodiments of the present invention.
[0128] Optionally, the computer-readable storage medium can be a non-volatile computer-readable storage medium. Examples include, but are not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this invention, the computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.
[0129] For example, optionally, the computer-readable storage medium may include ROM 602 and / or RAM 603 and / or one or more memories other than ROM 602 and RAM 603 as described above.
[0130] Embodiments of the present invention also include a computer program product comprising a computer program containing program code for performing the methods provided in the embodiments of the present invention. When the computer program product is run on an electronic device, the program code is used to enable the electronic device to implement the scattering artifact image correction method provided in the embodiments of the present invention.
[0131] When the computer program is executed by the processor 601, it performs the functions defined in the system / apparatus of this embodiment of the invention. Optionally, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.
[0132] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and downloaded and installed via the communication section 609, and / or installed from the removable medium 611. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.
[0133] Optionally, program code for executing the computer programs provided in the embodiments of the present invention can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages include, but are not limited to, languages such as Java, C++, Python, "C", or similar programming languages. The program code can be executed entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).
[0134] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions. Those skilled in the art will understand that the features described in the various embodiments of the present invention can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in the present invention. In particular, the features described in the various embodiments of the present invention can be combined and / or combined in various ways without departing from the spirit and teachings of the present invention. All such combinations and / or pairings fall within the scope of this invention.
[0135] The embodiments of the present invention have been described above. However, these embodiments are merely illustrative and not intended to limit the scope of the invention. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of the invention, and all such substitutions and modifications should fall within the scope of the invention.
Claims
1. A scatter artifact image correction method, characterized by, The method includes: Acquire projection signals related to the target detection object, wherein the projection signals are obtained by scanning the target detection object based on m projection angles using a radiation source, where m is an integer greater than 1; The target sampling angle is determined from the m projection angles using a gradient sampling algorithm; Acquire a sparse scattering signal corresponding to the target sampling angle, wherein the sparse scattering signal is obtained by scanning the target detection object with the radiation source based on the target sampling angle and the blocking plate, and the blocking plate is disposed between the radiation source and the target detection object; Based on the interpolation algorithm, the sparse scattering signal corresponding to the target sampling angle is processed to obtain the target scattering signal corresponding to each of the m projection angles; Image reconstruction is performed based on the projection signals and target scattering signals corresponding to the m projection angles, respectively, to generate a scattering artifact-corrected image.
2. The method of claim 1, wherein, The step of determining the target sampling angle from the m projection angles using the gradient sampling algorithm includes: The gradient value of the (i-1)th projection angle is determined based on 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-1)th projection angle, where m ≥ i > 1 and i is an integer. If i > 2 and the first gradient value is greater than the preset sampling gradient threshold, the second projection angle is determined as the target sampling angle. If i > 2 and the first gradient value is less than or equal to the preset sampling gradient threshold, the sum of the first gradient value and the second gradient value is determined to obtain the second gradient cumulative value. If the second gradient accumulation value is greater than the preset sampling gradient threshold, the third projection angle is determined as the target sampling angle; If the second gradient cumulative value is less than or equal to the preset sampling gradient threshold, the sum of the first gradient value to the third gradient value is determined to obtain the third gradient cumulative value; If the third gradient cumulative value is greater than the preset sampling gradient threshold, the fourth projection angle is determined as the target sampling angle.
3. The method of claim 2, wherein, The step of determining the target sampling angle from the m projection angles using the gradient sampling algorithm also includes: When i > 2 and the (i-1)th 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-1)th projection angle is the target sampling angle; If the (i-1)th gradient value is less than or equal to the preset sampling gradient threshold, the cumulative value of the i-th gradient is determined based on the (i-1)th gradient value and the i-th gradient value. If the cumulative value of the i-th gradient is greater than the preset sampling gradient threshold, the (i+1)-th projection angle is determined as the target sampling angle.
4. The method of claim 2, wherein, The preset sampling gradient threshold is obtained based on the following operation: The total gradient value is determined by summing the gradient values corresponding to each of the m projection angles. The preset sampling gradient threshold is determined based on the ratio between the total gradient value and the preset number of sampling angles.
5. The method of claim 1, wherein, The step of reconstructing the image based on the projection signals and target scattering signals corresponding to the m projection angles, and generating a corrected scattering artifact image, includes: Subtract the target scattering signal corresponding to the projection angle from the projection signal corresponding to the projection angle to obtain the original scattering signal corresponding to the projection angle; The original projected signals corresponding to the m projection angles are processed using a noise reduction algorithm to obtain the noise-reduced signals; The denoised signal is processed according to an image reconstruction algorithm to generate the scattering artifact corrected image.
6. The method of claim 5, wherein, The image reconstruction algorithm includes at least one of the following: Filtered back projection algorithm, iterative algorithm, deep learning algorithm.
7. The method of claim 1, wherein, The m projection angles include the target sampling angle and non-target sampling angles; The step of processing the sparse scattering signal corresponding to the target sampling angle based on the interpolation algorithm to obtain the target scattering signal corresponding to each of the m projection angles includes: The sparse scattering signal corresponding to the target sampling angle is processed based on the interpolation algorithm to obtain the interpolated scattering signal corresponding to the non-target sampling angle; The sparse scattering signal corresponding to the target sampling angle and the interpolated scattering signal corresponding to the non-target sampling angle are processed by a smoothing algorithm to obtain the target scattering signal corresponding to each of the m projection angles.
8. A scatter artifact image correction apparatus characterized by comprising: The device includes: The first acquisition module is used to acquire projection signals related to the target detection object, wherein the projection signals are 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 is used to determine the target sampling angle from the m projection angles using a gradient sampling algorithm; The second acquisition module is used to acquire a sparse scattering signal corresponding to the target sampling angle, wherein the sparse scattering signal is obtained by scanning the target detection object with the radiation source based on the target sampling angle and the blocking plate, and the blocking plate is disposed between the radiation source and the target detection object; The processing module is used to process the sparse scattering signal corresponding to the target sampling angle based on the interpolation algorithm to obtain the target scattering signal corresponding to each of the m projection angles; The reconstruction module is used to reconstruct the image based on the projection signals and target scattering signals corresponding to the m projection angles, and generate a scattering artifact corrected image.
9. An electronic device, comprising: include: One or more processors; Memory, used to store one or more instructions. When the one or more instructions are executed by the one or more processors, the one or more processors cause the one or more processors to implement the method of any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that, It stores executable instructions that, when executed by a processor, cause the processor to perform the method according to any one of claims 1 to 7.