Image calibration method and device, image correction method and device and electronic equipment

Abstract

The invention discloses an image calibration method and device, an image correction method and device and electronic equipment, and belongs to the technical field of image processing. The image calibration method comprises the following steps: scanning a plastic mold body by adopting CT scanning equipment to obtain first projection data; performing correction calculation on the first projection data to obtain a pixel-level correction coefficient; scanning at least two water models by adopting the CT scanning equipment to obtain second projection data; correcting the second projection data by using the pixel-level correction coefficient, and further performing reconstruction to obtain a water model CT image; and performing correction calculation on the water model CT image to obtain an image domain correction coefficient. According to the image calibration method, orthographic projection calculation does not need to be carried out, specific water model optimization does not need to be carried out, correction can be completed by collecting less data corresponding to a water model, the calculation speed is increased, and the efficiency is high.

Description

Technical Field

[0001] The present application belongs to the field of image processing technology, and in particular relates to an image calibration method and device, an image correction method and device, and an electronic device. Background Art

[0002] CT scanners are widely used in the diagnosis of various diseases. Because the radiation emitted by the CT tube is multi-energy, low-energy radiation is absorbed when passing through objects, leaving the detector primarily with high-energy radiation. This can cause a "hardening" phenomenon, resulting in a decrease in scanned image quality. Related technologies include methods for water hardening correction using water phantoms. However, due to the large calibration range, a large number of water phantoms of varying sizes and shapes are required, requiring a large amount of data collection. Furthermore, the calibration process requires orthographic projection, resulting in a time-consuming and inefficient calculation process. Summary of the Invention

[0003] This application aims to solve at least one of the technical problems existing in the related art. To this end, this application proposes an image calibration method and device, an image correction method and device, and an electronic device, which do not require orthographic projection calculations or specific water model optimization, and can complete the correction by collecting less data corresponding to the water model, thereby improving calculation speed and efficiency.

[0004] In a first aspect, the present application provides an image calibration method, the method comprising:

[0005] Scanning the plastic phantom using a CT scanning device to obtain first projection data;

[0006] performing correction calculation on the first projection data to obtain a pixel-level correction coefficient;

[0007] Scanning at least two water phantoms using the CT scanning device to obtain second projection data;

[0008] Correcting the second projection data using the pixel-level correction coefficient, and then reconstructing to obtain a water phantom CT image;

[0009] Correction calculation is performed on the water phantom CT image to obtain an image domain correction coefficient.

[0010] According to the image calibration method provided in the embodiment of the present application, by collecting projection data of the plastic phantom and calculating preliminary pixel-level correction coefficients based on the projection data, it is possible to correct the energy spectrum differences between detection units in the CT scanning device. Then, the projection data of the water phantom can be corrected based on the pixel-level correction coefficients to reconstruct the water phantom CT image, and then the image domain correction coefficients for secondary correction are calculated based on the water phantom CT image. The image domain correction coefficients can be used to obtain images without water hardening artifacts without performing positive projection calculations or specific water phantom optimization. The correction can be completed by collecting less data corresponding to the water phantom, thereby improving the calculation speed and efficiency.

[0011] In an image calibration method according to an embodiment of the present application, performing correction calculation on the water phantom CT image to obtain image domain correction coefficients includes:

[0012] performing binarization processing on each of the water phantom CT images to obtain a target binarized image corresponding to each of the water phantoms; wherein the pixel values corresponding to the water region in the target binarized image are different from the pixel values corresponding to the plastic region;

[0013] The image domain correction coefficient is obtained based on the target binarized image and the water phantom CT image.

[0014] In an image calibration method according to an embodiment of the present application, the binarization processing of each water phantom CT image to obtain a target binarized image corresponding to each water phantom includes:

[0015] performing binarization processing on the water phantom CT image to obtain an initial binarized image;

[0016] Obtaining a first attenuation coefficient of a water material under a target scanning condition and a second attenuation coefficient of a plastic material under the target scanning condition; the target scanning condition is determined based on a current average energy corresponding to the CT scanning device;

[0017] The pixel values of the water area in the initial binary image are processed based on the first attenuation coefficient, and the pixel values of the plastic area in the initial binary image are processed based on the second attenuation coefficient to obtain the target binary image.

[0018] In an image calibration method according to an embodiment of the present application, performing correction calculation on the first projection data to obtain pixel-level correction coefficients includes:

[0019] Determining projection data corresponding to different thicknesses of the plastic phantom from the first projection data; and determining, based on the relative scanning position of the CT scanning device and the plastic phantom, corresponding penetration lengths of the plastic phantom at different thicknesses; the penetration length being the length of the plastic phantom that a ray emitted from a radiation source passes through to reach each detection unit in the CT scanning device;

[0020] The projection data and the penetration length corresponding to each thickness of the plastic phantom are processed by the least square method to obtain the pixel-level correction coefficient.

[0021] In an image calibration method according to an embodiment of the present application, the at least two water phantoms include a first water phantom and a second water phantom having different diameters; the second projection data includes first central projection data, first eccentric projection data, second central projection data, and second eccentric projection data;

[0022] Scanning at least two water phantoms using the CT scanning device to obtain second projection data includes:

[0023] When the first water phantom is located at a central position of a scanning space formed by the CT scanning device, determining projection data acquired by each detection unit in the CT scanning device at multiple acquisition angles as the first central projection data;

[0024] When the first water phantom is at an eccentric position in the scanning space, determining the projection data collected by each detection unit at multiple collection angles as the first eccentric projection data;

[0025] When the second water phantom is at the center of the scanning space, the projection data collected by each detection unit at multiple collection angles are determined as the second center projection data;

[0026] When the second water phantom is located at an eccentric position in the scanning space, the projection data collected by each detection unit at multiple collection angles is determined as the second eccentric projection data.

[0027] In an image calibration method according to an embodiment of the present application, the method of correcting the second projection data using the pixel-level correction coefficient and then reconstructing the water phantom CT image includes:

[0028] Using the pixel-level correction coefficient, respectively correcting the first central projection data, the first eccentric projection data, the second central projection data, and the second eccentric projection data to obtain corrected first central projection data, corrected first eccentric projection data, corrected second central projection data, and corrected second eccentric projection data;

[0029] The corrected first central projection data is reconstructed to obtain a first water phantom CT image corresponding to the first water phantom; the corrected first eccentric projection data is reconstructed to obtain a second water phantom CT image corresponding to the first water phantom; the corrected second central projection data is reconstructed to obtain a third water phantom CT image corresponding to the second water phantom; the corrected second eccentric projection data is reconstructed to obtain a fourth water phantom CT image corresponding to the second water phantom.

[0030] In a second aspect, the present application provides an image calibration device, comprising:

[0031] A first processing module is configured to scan the plastic phantom using a CT scanning device to obtain first projection data;

[0032] A second processing module is used to perform correction calculation on the first projection data to obtain a pixel-level correction coefficient;

[0033] a third processing module, configured to scan at least two water phantoms using the CT scanning device to obtain second projection data;

[0034] a fourth processing module, configured to correct the second projection data using the pixel-level correction coefficient, and then reconstruct the data to obtain a water phantom CT image;

[0035] The fifth processing module is used to perform correction calculation on the water phantom CT image to obtain an image domain correction coefficient.

[0036] According to the image calibration device provided in the embodiment of the present application, by collecting projection data of a plastic phantom and calculating a preliminary pixel-level correction coefficient based on the projection data, it is possible to correct the energy spectrum differences between detection units in a CT scanning device. Then, the projection data of the water phantom can be corrected based on the pixel-level correction coefficient to reconstruct a water phantom CT image, and then the image domain correction coefficient for secondary correction is calculated based on the water phantom CT image. The image domain correction coefficient can be used to obtain an image without water hardening artifacts without performing a forward projection calculation or specific water phantom optimization. The correction can be completed by collecting less data corresponding to the water phantom, thereby improving the calculation speed and efficiency.

[0037] In a third aspect, the present application provides an image correction method, comprising:

[0038] Use CT scanning equipment to scan the projection data of the object being photographed;

[0039] Correcting the projection data of the photographed object using pixel-level correction coefficients, and then reconstructing a CT image of the photographed object; the pixel-level correction coefficients are obtained based on the image calibration method according to any one of claims 1 to 6;

[0040] The CT image of the photographed object is corrected using an image domain correction coefficient to obtain a water-hardening corrected CT image, wherein the image domain correction coefficient is obtained based on the image calibration method according to any one of claims 1 to 6.

[0041] According to the image correction method provided in the embodiment of the present application, the projection data corresponding to the photographed object is preliminarily corrected by using pixel-level correction coefficients, which can eliminate the ring artifacts caused by detector inconsistency and preliminarily eliminate the water hardening artifacts caused by the energy spectrum differences of the detection units. The projection data after the preliminary correction is then reconstructed to obtain a CT image of the photographed object. The CT image is then corrected for the second time using the image domain correction coefficients to obtain a CT image after water hardening correction. This can eliminate the cup-shaped artifacts caused by the hardening effect, and the calculation time is short, with better correction effect.

[0042] In a fourth aspect, the present application provides an image correction device, comprising:

[0043] a sixth processing module, configured to scan projection data of the object using a CT scanning device;

[0044] a seventh processing module, configured to correct the projection data of the photographed object using pixel-level correction coefficients, and then reconstruct a CT image of the photographed object; the pixel-level correction coefficients are obtained based on the image calibration method according to any one of claims 1 to 6;

[0045] An eighth processing module is used to correct the CT image of the photographed object using an image domain correction coefficient to obtain a water-hardening corrected CT image, wherein the image domain correction coefficient is obtained based on the image calibration method according to any one of claims 1 to 6.

[0046] According to the image correction device provided in the embodiment of the present application, the projection data corresponding to the photographed object is preliminarily corrected through pixel-level correction coefficients, which can eliminate the ring artifacts caused by detector inconsistency and preliminarily eliminate the water hardening artifacts caused by the energy spectrum differences of the detection units. The projection data after the preliminary correction is then reconstructed to obtain a CT image of the photographed object. The CT image is then corrected for the second time through the image domain correction coefficient to obtain a CT image after water hardening correction. This can eliminate the cup-shaped artifacts caused by the hardening effect, the calculation time is short, and the correction effect is better.

[0047] In a fifth aspect, the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the image calibration method described in the first aspect and the image correction method described in the third aspect are implemented.

[0048] In a sixth aspect, the present application provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the image calibration method described in the first aspect and the image correction method described in the third aspect.

[0049] In a seventh aspect, the present application provides a computer program product, comprising a computer program, which, when executed by a processor, implements the image calibration method described in the first aspect and the image correction method described in the third aspect.

[0050] The above one or more technical solutions in the embodiments of the present application have at least one of the following technical effects:

[0051] By collecting projection data of the plastic phantom and calculating preliminary pixel-level correction coefficients based on the projection data, it is possible to correct the energy spectrum differences between detection units in the CT scanning device. Then, the projection data of the water phantom can be corrected based on the pixel-level correction coefficients to reconstruct the water phantom CT image. Furthermore, the image domain correction coefficients for secondary correction are calculated based on the water phantom CT image. The image domain correction coefficients can be used to obtain images without water hardening artifacts without the need for positive projection calculations or specific water phantom optimization. The correction can be completed by collecting less data corresponding to the water phantom, which improves the calculation speed and efficiency.

[0052] Furthermore, after preliminary correction in the projection domain, water phantom CT images of the two large and small water phantoms at different positions can be obtained, and then a binary image can be obtained based on the attenuation coefficients of the water material and the plastic material. The image domain correction coefficient is then calculated based on the binary image. A smaller number of water phantoms can be used to correct the attenuation differences between the plastic material and the water material under different energy spectra, which reduces the amount of collected data and improves the calculation speed and correction efficiency.

[0053] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become obvious from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0055] Figure 1 This is one of the flowcharts of the image calibration method provided in the embodiment of the present application;

[0056] Figure 2 This is the second flow chart of the image calibration method provided in the embodiment of the present application;

[0057] Figure 3This is one of the result diagrams of the image calibration method provided in the embodiment of the present application;

[0058] Figure 4 This is the second schematic diagram of the result of the image calibration method provided in the embodiment of the present application;

[0059] Figure 5 This is the third result diagram of the image calibration method provided in the embodiment of the present application;

[0060] Figure 6 is a structural diagram of an image calibration device provided in an embodiment of the present application;

[0061] Figure 7 1 is a flow chart of an image correction method provided in an embodiment of the present application;

[0062] Figure 8 is a structural diagram of an image correction device provided in an embodiment of the present application;

[0063] Figure 9 It is a structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0064] The following will be combined with the accompanying drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the embodiments described are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of this application.

[0065] The terms "first," "second," and the like in the specification and claims of this application are used to distinguish similar objects, and are not used to describe a specific order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments of this application can be implemented in an order other than that illustrated or described herein, and that the objects distinguished by "first," "second," and the like are generally of the same type, and do not limit the number of objects; for example, the first object can be one or more. In addition, the term "and / or" in the specification and claims refers to at least one of the connected objects, and the character " / " generally indicates that the objects connected are in an "or" relationship.

[0066] The image calibration method, image calibration device, electronic device, and readable storage medium provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings through specific embodiments and their application scenarios.

[0067] The image calibration method may be applied to a terminal, and may be specifically executed by hardware or software in the terminal.

[0068] The terminal includes, but is not limited to, a portable communication device such as a mobile phone or tablet computer having a touch-sensitive surface (e.g., a touch screen display and / or a touch pad). It should also be understood that, in some embodiments, the terminal may not be a portable communication device, but a desktop computer having a touch-sensitive surface (e.g., a touch screen display and / or a touch pad).

[0069] In the following embodiments, a terminal including a display and a touch-sensitive surface is described. However, it should be understood that the terminal may include one or more other physical user interface devices such as a physical keyboard, a mouse, and a joystick.

[0070] The image calibration method provided in the embodiments of the present application may be executed by an electronic device or a functional module or functional entity in the electronic device that can implement the image calibration method. The electronic devices mentioned in the embodiments of the present application include but are not limited to mobile phones, tablet computers, computers, cameras, and wearable devices. The image calibration method provided in the embodiments of the present application is described below using an electronic device as an example of the execution entity.

[0071] like Figure 1 As shown, the image calibration method includes: step S1, step S2, step S3, step S4 and step S5.

[0072] Step S1: Scanning a plastic phantom using a CT scanner to obtain first projection data;

[0073] In this step, a CT (Computed Tomography) device is a medical imaging device that uses X-rays and computer processing technology to generate cross-sectional images of the inside of a human body.

[0074] The plastic phantom may be used to simulate the density and structure of human tissue. For example, the plastic phantom may include a PMMA (polymethyl methacrylate) phantom.

[0075] The plastic phantom can be placed in the scanning space formed by the CT scanning equipment. The scanning space is the area used to place the scanned object.

[0076] The first projection data is a measurement value of the radiation intensity received by the detection unit in the CT scanning device after attenuation by the plastic phantom. The first projection data can be represented in the form of a two-dimensional image, where the value of each pixel represents the radiation intensity at the corresponding position.

[0077] Step S2: performing correction calculation on the first projection data to obtain pixel-level correction coefficients;

[0078] In this step, the pixel-level correction coefficients can be used to correct the projection data collected by the CT scanning device.

[0079] The pixel-level correction coefficients are used to compensate for the errors of the CT scanning equipment in the projection domain.

[0080] Based on the first projection data corresponding to the plastic phantom, a pixel-level correction coefficient can be calculated.

[0081] Step S3: Scanning at least two water phantoms using a CT scanner to obtain second projection data;

[0082] In this step, the water mold can be a cylinder, and the interior of the water mold can contain pure water.

[0083] The shell of the water model can be made of PMMA material, or other materials with an attenuation coefficient close to that of PMMA material, which is not limited in this application.

[0084] Water phantom is a homogeneous substance with a known and stable CT value (Hounsfield Unit, HU).

[0085] The sizes of the water models can be different, and the number of the at least two water models can be two or more, which is not limited in this application.

[0086] The water phantom can be placed in the scanning space, and the water phantom can be placed at the center or eccentric position of the scanning space, and the projection data corresponding to the water phantom at different positions can be obtained respectively.

[0087] When collecting the second projection data of the water model, the radiation source and the detection unit can be respectively set on both sides of the water model, and the second projection data needs to be collected at multiple collection angles. The multiple collection angles can be evenly distributed within a 360-degree range. For example, the positional relationship between the radiation source and the detection unit is relatively static, and the radiation source and the detection unit can rotate around the curved surface of the water model to collect the second projection data of the water model within a 360-degree range.

[0088] Step S4: Correcting the second projection data using a pixel-level correction coefficient, and then reconstructing to obtain a water phantom CT image;

[0089] In this step, the pixel-level correction coefficient may be an nth-order polynomial, for example, a cubic polynomial.

[0090] The pixel-level correction coefficient can be used to perform water hardening correction on the second projection data, and then the corrected second projection data can be reconstructed to obtain a water phantom CT image.

[0091] The second projection data can be corrected using pixel-level correction coefficients to remap the projection samples based on the known attenuation characteristics of water to compensate for errors in ray hardening.

[0092] For example, a polynomial fitting method may be used to fit the relationship between the measured projection data of the water phantom and the ideal projection data to obtain the corrected second projection data.

[0093] The water phantom CT image corresponding to the water phantom is reconstructed based on the corrected second projection data. The filtered back projection method, the iterative reconstruction method, or other image reconstruction methods can be used. The selection can be based on user needs and is not limited in this application.

[0094] For example, a CT scanning device can emit X-rays or other types of radiation into a water phantom and receive attenuation signals generated by these radiations after passing through different tissues inside the water phantom. The attenuation signals can then be processed and reconstructed to obtain a water phantom CT image corresponding to the water phantom.

[0095] Step S5: Perform correction calculation on the water phantom CT image to obtain image domain correction coefficients.

[0096] In this step, the water phantom CT image is processed to obtain the image domain correction coefficient.

[0097] During the actual implementation process, the projection data of the object being photographed collected by the CT scanning device can be preliminarily corrected based on the pixel-level correction coefficient to obtain the preliminarily corrected projection data, and then the CT image corresponding to the object being photographed can be reconstructed based on the preliminarily corrected projection data. The CT image can be water-hardening corrected using the image domain correction coefficient to obtain the water-hardening corrected CT image.

[0098] According to the image calibration method provided in the embodiment of the present application, by collecting projection data of the plastic phantom and calculating preliminary pixel-level correction coefficients based on the projection data, it is possible to correct the energy spectrum differences between detection units in the CT scanning device. Then, the projection data of the water phantom can be corrected based on the pixel-level correction coefficients to reconstruct the water phantom CT image, and then the image domain correction coefficients for secondary correction are calculated based on the water phantom CT image. The image domain correction coefficients can be used to obtain images without water hardening artifacts without performing positive projection calculations or specific water phantom optimization. The correction can be completed by collecting less data corresponding to the water phantom, thereby improving the calculation speed and efficiency.

[0099] In some embodiments, step S2 may include:

[0100] Determining projection data corresponding to different thicknesses of the plastic phantom from the first projection data; and determining corresponding penetration lengths of the plastic phantom at different thicknesses based on a relative scanning position of the CT scanning device and the plastic phantom;

[0101] The least square method is used to process the projection data and penetration length corresponding to each thickness of the plastic phantom to obtain the pixel-level correction coefficient.

[0102] In this embodiment, the plastic mold can be a stepped mold, which includes multiple horizontally stacked parts (for example, it can be 5 or other numbers, which is not limited in this application), each part has the same thickness, and each part can be a circular band, that is, the shape of each part is a band area limited by semicircular curves on the left and right sides, and cut off by two parallel lines on the top and bottom.

[0103] The thickness range of the plastic phantom can cover the equivalent attenuation length during actual shooting. For example, the maximum thickness of the plastic phantom can be determined based on the thickness of the human skull during actual shooting. For example, the maximum thickness of the plastic phantom can be set to 20 cm. It can be assumed that the attenuation of the 20 cm plastic phantom is consistent with the maximum attenuation of the human skull.

[0104] When photographing plastic molds of different thicknesses, the radiation source and the detection unit can be respectively arranged directly below and directly above the plastic mold being photographed along the thickness direction.

[0105] A radiation source is a device or component that generates radiation (such as X-rays). In CT scanning, the radiation source can be a high-voltage tube that generates X-rays by accelerating electrons and colliding with a metal target. The X-rays can be emitted in a fan shape or other shapes, which is not limited in this application.

[0106] In CT scanning or other radiation imaging, a detection unit is an independent element in a detector array. The detection unit can be used to receive radiation (such as X-rays) after being attenuated by an object. Each detection unit can independently measure and record the intensity of the received radiation.

[0107] The penetration length is the length of the plastic mold body that the radiation emitted from the radiation source passes through to reach each detection unit.

[0108] Based on the angle between the connecting line between the detection unit and the radiation source and the plastic mold body, as well as the thickness of the plastic mold body, the corresponding penetration length of the plastic mold body can be calculated.

[0109] Plastic phantoms of different thicknesses each correspond to a set of projection data and penetration lengths. Based on the projection data and penetration lengths corresponding to the plastic phantoms of each thickness, a pixel-level correction coefficient can be calculated.

[0110] In one implementation, during actual implementation, the pixel-level correction coefficient may be calculated using the following formula:

[0111] Among them, μ1 is the attenuation coefficient of the plastic material under the current average energy, L1 is the corresponding penetration length of the plastic phantom under different detection units, C1 is the pixel-level correction coefficient to be calculated, which is obtained by C 1i A set of correction coefficients, C 1iis the i-th coefficient in the pixel-level correction coefficient, P1 is the projection data corresponding to different detection units, and the superscript i of P1 is 0, 1, or 2, which is used to represent the power of the image domain correction coefficient.

[0112] In another embodiment, the pixel-level correction coefficient can be calculated using the following formula:

[0113] when When the value is minimum, the corresponding C1 is the pixel-level correction coefficient to be calculated. w(L1) is the weight coefficient, which reflects the constraint on the thickness distribution range of the ray passing through the phantom. The more rays pass through a specific thickness range, the smaller the weight coefficient; the fewer rays pass through, the larger the weight coefficient. This coefficient can improve the accuracy of the correction coefficient calculation when the length distribution of the ray passing through the phantom is uneven.

[0114] In the actual implementation process, the positions of the radiation source and the detection unit can be fixed, and then the plastic phantom of each thickness can be photographed. The projection data can be taken for more than 2 seconds, and the projection data can be obtained by calculating the average value to reduce data noise.

[0115] According to the position coordinates of the detection unit, the corresponding penetration length of the plastic mold with different thicknesses can be calculated;

[0116] According to the projection data and penetration length corresponding to the plastic phantom at different thicknesses, the pixel-level correction coefficient can be calculated.

[0117] like Figure 2 As shown, in some embodiments, step S3 may include:

[0118] When the first water phantom is located at a central position of a scanning space formed by the CT scanning device, projection data collected by each detection unit in the CT scanning device at multiple collection angles are determined as first central projection data;

[0119] When the first water phantom is at an eccentric position in the scanning space, the projection data collected by each detection unit at multiple collection angles are determined as first eccentric projection data;

[0120] When the second water phantom is at the center of the scanning space, the projection data collected by each detection unit at multiple collection angles are determined as second center projection data;

[0121] When the second water phantom is at an eccentric position in the scanning space, the projection data collected by each detection unit at multiple collection angles is determined as second eccentric projection data.

[0122] In this embodiment, the at least two water molds may include a first water mold and a second water mold having different diameters.

[0123] For example, the first water mold may be a water mold with a larger diameter, and the second water mold may be a water mold with a smaller diameter.

[0124] The second projection data corresponding to the water phantom may include first central projection data, first eccentric projection data, second central projection data, and second eccentric projection data.

[0125] The water phantom can be placed at different positions, and then the projection data of the water phantom at different positions can be collected respectively, so that the collected projection data can cover all the detection units.

[0126] For example, the water phantom can be placed at the center position and the eccentric position of the scanning space, and then the projection data of the water phantom at different positions can be collected, wherein the center position can be the center of the imaging range of the scanner, the imaging range of the scanner is circular, and the size of the imaging range can be determined based on the parameters of the scanner. For example, the diameter of the imaging range of a general CT scanner is about 25 cm; the offset distance between the eccentric position and the center position can be determined based on the diameter of the water phantom. For example, when the diameter of the water phantom is 20 cm, the maximum offset distance between the eccentric position and the center position is 25 mm, so that when the water phantom is in the eccentric position, it does not exceed the imaging range of the scanner.

[0127] The first central projection data is projection data collected by each detection unit at multiple collection angles when the first water phantom is located at the center of the scanning space.

[0128] The first off-center projection data is projection data collected by each detection unit at multiple collection angles when the first water phantom is at an off-center position in the scanning space.

[0129] The second central projection data is projection data collected by each detection unit at multiple collection angles when the second water phantom is located at the center of the scanning space.

[0130] The second off-center projection data is projection data collected by each detection unit at multiple collection angles when the second water phantom is at an off-center position in the scanning space.

[0131] In some embodiments, step S4 may include:

[0132] Using a pixel-level correction coefficient, respectively correcting the first central projection data, the first eccentric projection data, the second central projection data, and the second eccentric projection data to obtain corrected first central projection data, corrected first eccentric projection data, corrected second central projection data, and corrected second eccentric projection data;

[0133] The corrected first central projection data is reconstructed to obtain the first water phantom CT image corresponding to the first water phantom; the corrected first eccentric projection data is reconstructed to obtain the second water phantom CT image corresponding to the first water phantom; the corrected second central projection data is reconstructed to obtain the third water phantom CT image corresponding to the second water phantom; the corrected second eccentric projection data is reconstructed to obtain the fourth water phantom CT image corresponding to the second water phantom.

[0134] In this embodiment, the second projection data may include first central projection data, first eccentric projection data, second central projection data, and second eccentric projection data.

[0135] The first central projection data, the first eccentric projection data, the second central projection data and the second eccentric projection data can be corrected respectively based on the pixel-level correction coefficient to obtain the corrected first central projection data, the corrected first eccentric projection data, the corrected second central projection data and the corrected second eccentric projection data.

[0136] Then, reconstruction can be performed based on the corrected projection data to obtain a water phantom CT image corresponding to the water phantom.

[0137] By reconstructing each corrected projection data, a CT image corresponding to each corrected projection data can be obtained. That is, two water phantoms of different diameters can be set. For each water phantom, its corresponding central projection data and eccentric projection data can be collected. For each projection data, it can be reconstructed based on the pixel-level correction coefficient to obtain a water phantom CT image, thereby obtaining four different water phantom CT images (i.e., the first water phantom CT image, the second water phantom CT image, the third water phantom CT image and the fourth water phantom CT image).

[0138] In some embodiments, step S5 may include:

[0139] Binarization processing is performed on each corrected water phantom CT image to obtain a target binary image corresponding to each water phantom;

[0140] Based on the target binarized image and the rectified water phantom CT image, the image domain correction coefficients are obtained.

[0141] In this embodiment, the corrected water phantom CT image is binarized to obtain a target binarized image. The pixel values corresponding to the water area in the target binarized image are different from the pixel values corresponding to the plastic area (such as the PMMA area).

[0142] For example, a threshold can be selected and pixel values below the threshold are set to 0 (black) and pixel values above the threshold are set to 255 (white). For example, the pixels in the corrected water phantom CT image can be divided into two categories: one representing water areas (set to 1 or white) and the other representing other areas (such as plastic edges, set to 0 or black).

[0143] For each water phantom, the pixel values of the water area and the plastic area can be extracted from its corrected water phantom CT image, and the average pixel value or other statistics of these areas can be calculated. Then, the correction error can be calculated based on these statistics and known ideal values (such as the ideal CT value of water and the ideal CT value of plastic, which can be obtained based on the binarized image). Then, the optimization algorithm can be used to adjust the correction coefficient to minimize the correction error. When a set of optimal correction coefficients is found, it can be determined as the image domain correction coefficient.

[0144] In some embodiments, performing binarization processing on each corrected water phantom CT image to obtain a target binarized image corresponding to each water phantom may include:

[0145] Binarization is performed on the corrected water phantom CT image to obtain an initial binary image;

[0146] obtaining a first attenuation coefficient of a water material under a target scanning condition and a second attenuation coefficient of a plastic material under the target scanning condition;

[0147] The pixel values of the water area in the initial binary image are processed based on the first attenuation coefficient, and the pixel values of the plastic area in the initial binary image are processed based on the second attenuation coefficient to obtain a target binary image.

[0148] In this embodiment, the target scanning condition is determined based on the current average energy corresponding to the CT scanning device, and the target scanning condition matches the scanning condition used to acquire the projection data corresponding to the plastic phantom and the water phantom.

[0149] Scanning conditions may also include X-ray energy and scanning time.

[0150] The attenuation coefficient is used to characterize the material's ability to attenuate X-rays under target scanning conditions.

[0151] The attenuation coefficient of the water material under the target scanning condition and the attenuation coefficient of the PMMA material under the target scanning condition can be obtained respectively.

[0152] The water area in the initial binary image can be assigned the attenuation coefficient of the water material under the target scanning condition, i.e., the first attenuation coefficient; and the plastic area in the initial binary image can be assigned the attenuation coefficient of the plastic material under the target scanning condition, i.e., the second attenuation coefficient.

[0153] In some embodiments, performing binarization processing on each corrected water phantom CT image to obtain a target binarized image corresponding to each water phantom may include:

[0154] Binarization is performed on the corrected water phantom CT image to obtain an initial binary image;

[0155] Obtaining a first attenuation coefficient corresponding to the water material and a second attenuation coefficient corresponding to the plastic material;

[0156] The pixel values of the water area in the initial binary image are processed based on the first attenuation coefficient, and the pixel values of the plastic area in the initial binary image are processed based on the second attenuation coefficient to obtain a target binary image.

[0157] In this embodiment, the corrected water phantom CT image I1 can be binarized to obtain an initial binarized image. Then, the water area in the initial binarized image is assigned a water material attenuation coefficient μ2 (a first attenuation coefficient), and the PMMA area at the edge of the water phantom in the initial binarized image is assigned a PMMA material attenuation coefficient μ1 (a second attenuation coefficient) to obtain a target binarized image I corresponding to the water phantom. b ;

[0158] Among them, μ1 is the attenuation coefficient of PMMA material at the current average energy, and μ2 is the attenuation coefficient of water material at the current average energy.

[0159] The least squares method can be used to binarize the target image I b The water phantom CT image I1 obtained after preliminary correction is processed to obtain the image domain water hardening correction coefficient C2 (image domain correction coefficient):

[0160]

[0161] Among them, I b is the target binary image (ideal water phantom CT image after threshold segmentation), C2 is the image domain correction coefficient to be calculated, and C 2i is the i-th coefficient in the image domain correction coefficient, I1 is the water phantom CT image obtained after preliminary correction, and the superscript i of I1 is 0, 1, or 2, which is used to represent the power of the image domain correction coefficient.

[0162] like Figure 4 The water phantom CT image after preliminary correction is shown as an example. The water hardening artifacts in the water phantom CT image after preliminary correction are not completely eliminated. The image domain correction coefficient can be calculated based on the corrected water phantom CT image; Figure 5An example is given of an image obtained by performing secondary correction on a water phantom CT image obtained after primary correction based on an image domain correction coefficient. The image domain correction coefficient can eliminate image artifacts in the water phantom CT image.

[0163] According to the image calibration method provided in the embodiment of the present application, after preliminary correction in the projection domain, water phantom CT images of two large and small water phantoms at different positions can be obtained, and then a binary image is obtained based on the attenuation coefficients of the water material and the plastic material. The image domain correction coefficient is then calculated based on the binary image. A smaller number of water phantoms can be used to correct the attenuation differences between the plastic material and the water material under different energy spectra, thereby reducing the amount of collected data and improving the calculation speed and correction efficiency.

[0164] The image calibration device provided in the present application is described below. The image calibration device described below and the image calibration method described above can be referenced to each other.

[0165] The image calibration method provided in the embodiment of the present application can be executed by an image calibration device. In the embodiment of the present application, the image calibration device provided in the embodiment of the present application is described by taking the image calibration method performed by the image calibration device as an example.

[0166] An embodiment of the present application also provides an image calibration device.

[0167] like Figure 6 As shown, the image calibration device includes: a first processing module 610 , a second processing module 620 , a third processing module 630 , a fourth processing module 640 and a fifth processing module 650 .

[0168] A first processing module 610 is configured to scan the plastic phantom using a CT scanning device to obtain first projection data;

[0169] A second processing module 620 is configured to perform correction calculation on the first projection data to obtain a pixel-level correction coefficient;

[0170] A third processing module 630 is configured to scan at least two water phantoms using a CT scanning device to obtain second projection data;

[0171] A fourth processing module 640 is configured to correct the second projection data using a pixel-level correction coefficient, and then reconstruct the second projection data to obtain a water phantom CT image.

[0172] The fifth processing module 650 is used to perform correction calculation on the water phantom CT image to obtain image domain correction coefficients.

[0173] According to the image calibration device provided in the embodiment of the present application, by collecting projection data of a plastic phantom and calculating a preliminary pixel-level correction coefficient based on the projection data, it is possible to correct the energy spectrum differences between detection units in a CT scanning device. Then, the projection data of the water phantom can be corrected based on the pixel-level correction coefficient to reconstruct a water phantom CT image, and then the image domain correction coefficient for secondary correction is calculated based on the water phantom CT image. The image domain correction coefficient can be used to obtain an image without water hardening artifacts without performing a forward projection calculation or specific water phantom optimization. The correction can be completed by collecting less data corresponding to the water phantom, thereby improving the calculation speed and efficiency.

[0174] In some embodiments, the fifth processing module 650 may also be configured to:

[0175] Binarization is performed on each water phantom CT image to obtain a target binary image corresponding to each water phantom; the pixel value corresponding to the water area in the target binary image is different from the pixel value corresponding to the plastic area;

[0176] Based on the target binarized image and the water phantom CT image, the image domain correction coefficients are obtained.

[0177] In some embodiments, the fifth processing module 650 may also be configured to:

[0178] Binarize the water phantom CT image to obtain an initial binary image;

[0179] Obtaining a first attenuation coefficient of a water material under a target scanning condition and a second attenuation coefficient of a plastic material under the target scanning condition; the target scanning condition is determined based on a current average energy corresponding to the CT scanning device;

[0180] The pixel values of the water area in the initial binary image are processed based on the first attenuation coefficient, and the pixel values of the plastic area in the initial binary image are processed based on the second attenuation coefficient to obtain a target binary image.

[0181] In some embodiments, the second processing module 620 may also be configured to:

[0182] Determining projection data corresponding to different thicknesses of the plastic phantom from the first projection data; and determining, based on a relative scanning position of the CT scanner and the plastic phantom, corresponding penetration lengths of the plastic phantom at different thicknesses; the penetration length being the length of the plastic phantom that a ray emitted from the radiation source passes through to reach each detection unit in the CT scanner;

[0183] The least square method is used to process the projection data and penetration length corresponding to each thickness of the plastic phantom to obtain the pixel-level correction coefficient.

[0184] In some embodiments, the at least two water phantoms include a first water phantom and a second water phantom of different diameters; the second projection data includes first central projection data, first eccentric projection data, second central projection data, and second eccentric projection data; and the third processing module 630 may further be configured to:

[0185] Scanning at least two water phantoms using a CT scanner to obtain second projection data includes:

[0186] When the first water phantom is located at a central position of a scanning space formed by the CT scanning device, projection data collected by each detection unit in the CT scanning device at multiple collection angles are determined as first central projection data;

[0187] When the first water phantom is at an eccentric position in the scanning space, the projection data collected by each detection unit at multiple collection angles are determined as first eccentric projection data;

[0188] When the second water phantom is at the center of the scanning space, the projection data collected by each detection unit at multiple collection angles are determined as second center projection data;

[0189] When the second water phantom is at an eccentric position in the scanning space, the projection data collected by each detection unit at multiple collection angles is determined as second eccentric projection data.

[0190] In some embodiments, the fourth processing module 640 may also be configured to:

[0191] Using a pixel-level correction coefficient, respectively correcting the first central projection data, the first eccentric projection data, the second central projection data, and the second eccentric projection data to obtain corrected first central projection data, corrected first eccentric projection data, corrected second central projection data, and corrected second eccentric projection data;

[0192] The corrected first central projection data is reconstructed to obtain the first water phantom CT image corresponding to the first water phantom; the corrected first eccentric projection data is reconstructed to obtain the second water phantom CT image corresponding to the first water phantom; the corrected second central projection data is reconstructed to obtain the third water phantom CT image corresponding to the second water phantom; the corrected second eccentric projection data is reconstructed to obtain the fourth water phantom CT image corresponding to the second water phantom.

[0193] The image calibration device in the embodiment of the present application can be an electronic device or a component in an electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal or a device other than a terminal. For example, the electronic device can be a mobile phone, a tablet computer, a laptop computer, a PDA, a vehicle-mounted electronic device, a mobile Internet device (MID), an augmented reality (AR) / virtual reality (VR) device, a robot, a wearable device, an ultra-mobile personal computer (UMPC), a netbook or a personal digital assistant (PDA), etc. It can also be a server, a network attached storage (NAS), a personal computer (PC), a television (TV), a teller machine or a self-service machine, etc., and the embodiment of the present application does not specifically limit it.

[0194] The image calibration device in the embodiment of the present application may be a device having an operating system. The operating system may be an Android operating system, an iOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0195] The image calibration device provided in the embodiment of the present application can achieve Figures 1 to 5 To avoid repetition, the various processes implemented in the method embodiment are not described here.

[0196] like Figure 7 As shown, the embodiment of the present application further provides an image correction method, including: step S6, step S7 and step S8.

[0197] Step S6: Scan projection data of the object using a CT scanner;

[0198] In this step, the object to be photographed can be a human body. For example, a human head can be scanned by a CT scanning device. The CT scanning device can be controlled to start scanning, and the X-ray tube and detector start to rotate to scan the head. After the X-rays pass through the head, they are received by the detector. The detector can convert the received X-ray intensity into electrical signals. The computer system can process these signals to generate projection data.

[0199] Step S7: Correcting the projection data of the object using the pixel-level correction coefficient, and then reconstructing to obtain a CT image of the object;

[0200] In this step, the projection data of the photographed object may be preliminarily corrected based on the pixel-level correction coefficient.

[0201] The pixel-level correction coefficient is obtained based on the image calibration method described in any of the above embodiments.

[0202] Then, a CT image of the object can be reconstructed based on the projection data after preliminary correction.

[0203] Step S8: Correct the CT image of the photographed object using the image domain correction coefficient to obtain a water-hardened corrected CT image.

[0204] In this step, the CT image of the photographed object may be secondary corrected based on the image domain correction coefficient to obtain a secondary corrected CT image, thereby removing water hardening artifacts in the CT image of the photographed object.

[0205] The image domain correction coefficient is obtained based on the image calibration method described in any of the above embodiments.

[0206] In this application, pixel-level correction coefficients are obtained by using a plastic phantom for calibration. In actual application, the pixel-level correction coefficients are used to perform preliminary correction on the projection data corresponding to the photographed object. This can preliminarily eliminate water hardening artifacts caused by energy spectrum differences in the detection unit. The energy spectrum differences are the uneven energy spectrum caused by rays filtered through different thicknesses.

[0207] It can also eliminate ring artifacts caused by detector inconsistency, where detector inconsistency is caused by differences in the detector pixels themselves;

[0208] By using pixel-level correction coefficients to perform preliminary correction on the projection data corresponding to the photographed object, it is possible to simultaneously correct the energy spectrum differences of the detection units and the inconsistency of the detectors;

[0209] By using image domain correction coefficients to perform image domain water hardening correction on the CT image after preliminary water hardening correction, all water hardening artifacts can be eliminated.

[0210] According to the image correction method provided in the embodiment of the present application, the projection data corresponding to the photographed object is preliminarily corrected by using pixel-level correction coefficients, which can eliminate the ring artifacts caused by detector inconsistency and preliminarily eliminate the water hardening artifacts caused by the energy spectrum differences of the detection units. The projection data after the preliminary correction is then reconstructed to obtain a CT image of the photographed object. The CT image is then corrected for the second time using the image domain correction coefficients to obtain a CT image after water hardening correction. This can eliminate the cup-shaped artifacts caused by the hardening effect, and the calculation time is short, with better correction effect.

[0211] The image correction device provided in the present application is described below. The image correction device described below and the image correction method described above can be referenced to each other.

[0212] The image correction method provided in the embodiment of the present application can be executed by an image correction device. In the embodiment of the present application, the image correction device provided in the embodiment of the present application is described by taking the image correction method executed by the image correction device as an example.

[0213] An embodiment of the present application also provides an image correction device.

[0214] like Figure 8 As shown, the image correction device includes: a sixth processing module 810, a seventh processing module 820 and an eighth processing module 830.

[0215] A sixth processing module 810 is configured to scan projection data of an object using a CT scanning device;

[0216] a seventh processing module 820, configured to correct the projection data of the photographed object using pixel-level correction coefficients, and then reconstruct a CT image of the photographed object; the pixel-level correction coefficients are obtained based on the image calibration method described in any of the above embodiments;

[0217] The eighth processing module 830 is used to correct the CT image of the photographed object using an image domain correction coefficient to obtain a water-hardening corrected CT image, wherein the image domain correction coefficient is obtained based on the image calibration method described in any of the above embodiments.

[0218] According to the image correction device provided in the embodiment of the present application, the projection data corresponding to the photographed object is preliminarily corrected through pixel-level correction coefficients, which can eliminate the ring artifacts caused by detector inconsistency and preliminarily eliminate the water hardening artifacts caused by the energy spectrum differences of the detection units. The projection data after the preliminary correction is then reconstructed to obtain a CT image of the photographed object. The CT image is then corrected for the second time through the image domain correction coefficient to obtain a CT image after water hardening correction. This can eliminate the cup-shaped artifacts caused by the hardening effect, the calculation time is short, and the correction effect is better.

[0219] The image correction device in the embodiment of the present application can be an electronic device, or a component in the electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal, or other devices other than a terminal. Exemplarily, the electronic device can be a mobile phone, a tablet computer, a laptop computer, a PDA, an in-vehicle electronic device, a mobile Internet device (MID), an augmented reality (AR) / virtual reality (VR) device, a robot, a wearable device, an ultra-mobile personal computer (UMPC), a netbook or a personal digital assistant (PDA), etc. It can also be a server, a network attached storage (NAS), a personal computer (PC), a television (TV), a teller machine or a self-service machine, etc., and the embodiment of the present application does not specifically limit it.

[0220] The image correction device in the embodiment of the present application may be a device having an operating system. The operating system may be an Android operating system, an iOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0221] The image correction device provided in the embodiment of the present application can achieve Figure 7 To avoid repetition, the various processes implemented in the method embodiment are not described here.

[0222] In some embodiments, as Figure 9 As shown, an embodiment of the present application further provides an electronic device 900, including a processor 901, a memory 902, and a computer program stored in the memory 902 and executable on the processor 901. When the program is executed by the processor 901, each process of the above-mentioned image calibration method and image correction method embodiments is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be described here.

[0223] It should be noted that the electronic devices in the embodiments of the present application include the mobile electronic devices and non-mobile electronic devices mentioned above.

[0224] On the other hand, the present application also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the various processes of the above-mentioned image calibration method and image correction method embodiments, and can achieve the same technical effects. To avoid repetition, they will not be repeated here.

[0225] On the other hand, the present application also provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, it is implemented to perform the various processes of the above-mentioned image calibration method and image correction method embodiments, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0226] On the other hand, an embodiment of the present application further provides a chip, which includes a processor and a communication interface, the communication interface and the processor are coupled, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned image calibration method and image correction method embodiments, and can achieve the same technical effects. To avoid repetition, they will not be repeated here.

[0227] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0228] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0229] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course, by hardware. Based on this understanding, the above technical solution, in essence, or the part that contributes to the relevant technology, can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or certain parts of the embodiments.

[0230] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. An image calibration method, characterized in that: include: Scanning the plastic phantom using a CT scanning device to obtain first projection data; performing correction calculation on the first projection data to obtain a pixel-level correction coefficient; Scanning at least two water phantoms using the CT scanning device to obtain second projection data; Correcting the second projection data using the pixel-level correction coefficient, and then reconstructing to obtain a water phantom CT image; Correction calculation is performed on the water phantom CT image to obtain an image domain correction coefficient.

2. The image calibration method according to claim 1, wherein: The correction calculation of the water phantom CT image to obtain the image domain correction coefficient includes: performing binarization processing on each of the water phantom CT images to obtain a target binarized image corresponding to each of the water phantoms; wherein the pixel values corresponding to the water region in the target binarized image are different from the pixel values corresponding to the plastic region; The image domain correction coefficient is obtained based on the target binarized image and the water phantom CT image.

3. The image calibration method according to claim 2, wherein: The binarization processing is performed on each of the water phantom CT images to obtain a target binarized image corresponding to each of the water phantoms, including: performing binarization processing on the water phantom CT image to obtain an initial binarized image; Obtaining a first attenuation coefficient of a water material under a target scanning condition and a second attenuation coefficient of a plastic material under the target scanning condition; the target scanning condition is determined based on a current average energy corresponding to the CT scanning device; The pixel values of the water area in the initial binary image are processed based on the first attenuation coefficient, and the pixel values of the plastic area in the initial binary image are processed based on the second attenuation coefficient to obtain the target binary image.

4. The image calibration method according to any one of claims 1 to 3, characterized in that: The performing correction calculation on the first projection data to obtain a pixel-level correction coefficient includes: Determining projection data corresponding to different thicknesses of the plastic phantom from the first projection data; and determining, based on the relative scanning position of the CT scanning device and the plastic phantom, corresponding penetration lengths of the plastic phantom at different thicknesses; the penetration length being the length of the plastic phantom that a ray emitted from a radiation source passes through to reach each detection unit in the CT scanning device; The projection data and the penetration length corresponding to each thickness of the plastic phantom are processed by the least square method to obtain the pixel-level correction coefficient.

5. The image calibration method according to any one of claims 1 to 3, characterized in that: The at least two water phantoms include a first water phantom and a second water phantom with different diameters; the second projection data include first central projection data, first eccentric projection data, second central projection data, and second eccentric projection data; Scanning at least two water phantoms using the CT scanning device to obtain second projection data includes: When the first water phantom is located at a central position of a scanning space formed by the CT scanning device, determining projection data acquired by each detection unit in the CT scanning device at multiple acquisition angles as the first central projection data; When the first water phantom is at an eccentric position in the scanning space, determining the projection data collected by each detection unit at multiple collection angles as the first eccentric projection data; When the second water phantom is at the center of the scanning space, the projection data collected by each detection unit at multiple collection angles are determined as the second center projection data; When the second water phantom is located at an eccentric position in the scanning space, the projection data collected by each detection unit at multiple collection angles is determined as the second eccentric projection data.

6. The image calibration method according to claim 5, characterized in that: The correcting the second projection data by using the pixel-level correction coefficient and then reconstructing to obtain a water phantom CT image includes: Using the pixel-level correction coefficient, respectively correcting the first central projection data, the first eccentric projection data, the second central projection data, and the second eccentric projection data to obtain corrected first central projection data, corrected first eccentric projection data, corrected second central projection data, and corrected second eccentric projection data; The corrected first central projection data is reconstructed to obtain a first water phantom CT image corresponding to the first water phantom; the corrected first eccentric projection data is reconstructed to obtain a second water phantom CT image corresponding to the first water phantom; the corrected second central projection data is reconstructed to obtain a third water phantom CT image corresponding to the second water phantom; the corrected second eccentric projection data is reconstructed to obtain a fourth water phantom CT image corresponding to the second water phantom.

7. An image calibration device, characterized in that: include: A first processing module is configured to scan the plastic phantom using a CT scanning device to obtain first projection data; A second processing module is used to perform correction calculation on the first projection data to obtain a pixel-level correction coefficient; a third processing module, configured to scan at least two water phantoms using the CT scanning device to obtain second projection data; a fourth processing module, configured to correct the second projection data using the pixel-level correction coefficient, and then reconstruct the data to obtain a water phantom CT image; The fifth processing module is used to perform correction calculation on the water phantom CT image to obtain an image domain correction coefficient.

8. An image correction method, characterized in that: include: Use CT scanning equipment to scan the projection data of the object being photographed; Correcting the projection data of the photographed object using pixel-level correction coefficients, and then reconstructing a CT image of the photographed object; the pixel-level correction coefficients are obtained based on the image calibration method according to any one of claims 1 to 6; The CT image of the photographed object is corrected using an image domain correction coefficient to obtain a water-hardening corrected CT image, wherein the image domain correction coefficient is obtained based on the image calibration method according to any one of claims 1 to 6.

9. An image correction device, characterized in that: include: a sixth processing module, configured to scan projection data of the object using a CT scanning device; a seventh processing module, configured to correct the projection data of the photographed object using pixel-level correction coefficients, and then reconstruct a CT image of the photographed object; the pixel-level correction coefficients are obtained based on the image calibration method according to any one of claims 1 to 6; An eighth processing module is used to correct the CT image of the photographed object using an image domain correction coefficient to obtain a water-hardening corrected CT image, wherein the image domain correction coefficient is obtained based on the image calibration method according to any one of claims 1 to 6.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the image calibration method according to any one of claims 1 to 6 and the image correction method according to claim 8 are implemented.

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