Calibration method and calibration system for performing energy spectrum calibration on a scan imaging device

Abstract

A calibration procedure for performing an energy spectrum calibration on a scan imaging device is provided, comprising: in a case where the energy spectrum calibration phantom is located in the scan area formed by the radiation, acquiring a geometric relationship between the radiation source, the energy spectrum calibration phantom, and the detector based on their relative positional arrangement; acquiring the radiation passing through the scan area by the detector to acquire actual projection data; acquiring physical properties of the energy spectrum calibration phantom, wherein the physical properties are predetermined based on constituent materials of the energy spectrum calibration phantom or are calculated based on an image reconstruction procedure;Calculating theoretical projection data using a plurality of predetermined base energy spectra based on the physical properties of the energy spectrum calibration phantom and the geometric relationship; calibrating an energy spectrum parameter based on the theoretical projection data and the actual projection data to capture an optimized energy spectrum parameter; and determining the optimized energy spectrum parameter as an energy spectrum calibration parameter.

Description

Calibration method and system for energy spectrum calibration of scanning imaging equipment

[0001] This application claims priority to Chinese patent application No. 202311865662.0, filed on December 29, 2023, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The present disclosure relates to the field of scanning imaging technology, and more particularly, to a calibration method and a calibration system for performing energy spectrum calibration on a scanning imaging device. Background Art

[0003] According to scanning imaging theory, when radiation is emitted from a radiation source, passes through the object being inspected, and is incident on a detector, its attenuation conforms to Beer's law. Beer's law, also known as the Beer-Lambert law, is a fundamental law describing the absorption of light by matter. When a parallel beam of monochromatic light passes perpendicularly through a uniform, non-scattering, absorbing material, its absorbance is proportional to the concentration of the absorbing material and the thickness of the absorbing layer.

[0004] For example, taking CT scanning imaging technology as an example, according to CT imaging theory, based on the fact that ray attenuation conforms to Beer's law, the detectors used for scanning imaging are required to have the same absorption energy spectrum, so that the attenuation of rays passing through objects of the same thickness from different directions can be consistent. The absorption energy spectrum of the detector is related to the thickness of the crystal on which the rays are incident. In the geometric arrangement of a single target source probe centripetal, all rays are incident vertically on the crystal, the crystal thickness through which the rays pass is the same, and the absorption energy spectrum of the detector is the same. However, in static CT scanning imaging equipment, because a single crystal needs to receive rays emitted from different targets, the incident angles of rays from different targets are different, and the crystal thicknesses they pass through are different, resulting in different absorption energy spectra. Moreover, the energy spectra of different targets may also differ. Data inconsistency caused by inconsistent energy spectra is also an important factor affecting the accuracy of reconstructed values.

[0005] The above information disclosed in this section is only for understanding of the background of the technical concept of the present disclosure and therefore may contain information that does not constitute related art. Summary of the Invention

[0006] The embodiments of the present disclosure provide a calibration method and a calibration system for performing energy spectrum calibration on a scanning imaging device.

[0007] In one aspect, a calibration method for performing energy spectrum calibration on a scanning imaging device is provided. The scanning imaging device includes a radiation source for emitting radiation and a detector for receiving radiation. During the calibration process, an energy spectrum calibration phantom is located in a scanning area formed by the radiation. The calibration method includes:

[0008] When the energy spectrum calibration phantom is located in a scanning area formed by the radiation, a geometric relationship among the radiation source, the energy spectrum calibration phantom, and the detector is acquired according to relative positions among the radiation source, the energy spectrum calibration phantom, and the detector;

[0009] collecting rays passing through the scanning area by the detector to obtain actual projection data;

[0010] Acquiring physical properties of the energy spectrum calibration phantom, wherein the physical properties are predetermined based on constituent materials of the energy spectrum calibration phantom;

[0011] Calculating theoretical projection data using a plurality of predetermined basic energy spectra based on the physical properties of the energy spectrum calibration phantom and the geometric relationship;

[0012] Calibrate energy spectrum parameters according to the theoretical projection data and the actual projection data to obtain optimized energy spectrum parameters; and

[0013] The optimized energy spectrum parameters are determined as energy spectrum calibration parameters.

[0014] In another aspect, a calibration method for performing energy spectrum calibration on a scanning imaging device is provided. The scanning imaging device includes a radiation source for emitting radiation and a detector for receiving radiation. During the calibration process, an energy spectrum calibration phantom is located in a scanning area formed by the radiation. The calibration method includes:

[0015] When the energy spectrum calibration phantom is located in a scanning area formed by the radiation, a geometric relationship among the radiation source, the energy spectrum calibration phantom, and the detector is acquired according to relative positions among the radiation source, the energy spectrum calibration phantom, and the detector;

[0016] collecting rays passing through the scanning area by the detector to obtain actual projection data;

[0017] The loop process is executed until a preset condition is met, wherein the first loop process includes:

[0018] performing image reconstruction on the energy spectrum calibration phantom according to the energy spectrum information, and obtaining physical properties of the energy spectrum calibration phantom according to a result of the image reconstruction;

[0019] Calculating theoretical projection data using a plurality of predetermined basic energy spectra based on the physical properties of the energy spectrum calibration phantom and the geometric relationship;

[0020] Calibrate energy spectrum parameters according to the theoretical projection data and the actual projection data to obtain optimized energy spectrum parameters; and

[0021] Based on the optimized energy spectrum parameters, acquiring energy spectrum information; and

[0022] The optimized energy spectrum parameters obtained for the last time during the first cycle are determined as energy spectrum calibration parameters.

[0023] According to some exemplary embodiments, the calibrating the energy spectrum parameters based on the theoretical projection data and the actual projection data to obtain optimized energy spectrum parameters includes: constructing an optimization function of the deviation between the theoretical projection data and the actual projection data with respect to the energy spectrum parameters; and calibrating the energy spectrum parameters based on the optimization function to obtain optimized energy spectrum parameters.

[0024] According to some exemplary embodiments, the method further includes: before placing the energy spectrum calibration phantom in the scanning area formed by the rays, controlling the ray source to emit rays and collecting air data of the detector; collecting the rays passing through the scanning area by the detector to obtain actual projection data, including: when the energy spectrum calibration phantom is located in the scanning area formed by the rays, controlling the ray source to emit rays, and the detector collecting the rays passing through the scanning area to obtain initial projection data; and using the air data, adopting a first correction method to correct the initial projection data to obtain first corrected projection data.

[0025] According to some exemplary embodiments, collecting rays passing through the scanning area through the detector to obtain actual projection data also includes: using the air data to correct the initial projection data using a second correction method to obtain second corrected projection data, wherein the second correction method is different from the first correction method.

[0026] According to some exemplary embodiments, the collecting of rays passing through the scanning area by the detector to obtain actual projection data further includes: classifying the first corrected projection data according to a predetermined classification standard to obtain N c The projection data of the jth category is taken as the actual projection data, wherein the projection data of the jth category is the N c One type of projection data in categories, N c is a positive integer greater than or equal to 1, 1≤j≤N c ; The predetermined classification criteria are determined based on factors that affect the absorption energy spectrum of the detector.

[0027] According to some exemplary embodiments, reconstructing an image of the energy spectrum calibration phantom according to the energy spectrum information includes: reconstructing an image of the energy spectrum calibration phantom based on the second corrected projection data according to the energy spectrum information.

[0028] According to some exemplary embodiments, the method of calculating theoretical projection data based on the physical properties of the energy spectrum calibration phantom and the geometric relationship using a predetermined plurality of basic energy spectra includes: selecting N e Basic energy spectrum {S k (E)},N e is a positive integer greater than or equal to 2; and for N e Basic energy spectrum {S k (E)}, based on the physical properties of the energy spectrum calibration phantom and the geometric relationship, calculate N e Theoretical projection data.

[0029] According to some exemplary embodiments, the optimization function includes the following function:

[0030] Among them, sprj k is the kth theoretical projection data calculated using the kth basic energy spectrum, aprj is the actual projection data, 1≤k≤N e , c k is the weight coefficient of the kth theoretical projection data.

[0031] According to some exemplary embodiments, calculating theoretical projection data using a plurality of predetermined basic energy spectra based on the physical properties of the energy spectrum calibration phantom and the geometric relationship includes:

[0032] For N c The second loop process is performed based on the projection data of each category. The second loop process includes:

[0033] For the projection data of the jth category, select N e Basic energy spectrum {S k (E)}; and

[0034] For N e Basic energy spectrum {S k (E)}, based on the physical properties of the energy spectrum calibration phantom and the geometric relationship, calculate the N corresponding to the projection data of the jth category e Theoretical projection data.

[0035] According to some exemplary embodiments, the optimization function includes the following function:

[0036] Among them, sprj j,k aprj is the kth theoretical projection data corresponding to the jth category projection data calculated using the kth basic energy spectrum, i is the actual projection data of the jth category, 1≤k≤N e , ck is the weight coefficient of the kth theoretical projection data.

[0037] According to some exemplary embodiments, the energy spectrum parameters are calibrated according to the optimization function to obtain the optimized energy spectrum parameters, specifically including: by solving the above optimization function, calculating N when the deviation is the minimum value e Optimize the weight coefficients, and set the N e An optimized weight coefficient is used as the optimized energy spectrum parameter.

[0038] According to some exemplary embodiments, the obtaining of energy spectrum information based on the optimized energy spectrum parameters specifically includes: e The optimized weight coefficients and the N e The energy spectrum information is obtained by calculating a basic energy spectrum using a weighted summation method.

[0039] According to some exemplary embodiments, the energy spectrum calibration phantom includes a plurality of parts respectively made of a plurality of materials, and any two of the plurality of materials have at least one of the following properties that is different: density, atomic number.

[0040] According to some exemplary embodiments, the calibration system includes a rotating table, and the energy spectrum calibration phantom is located on the rotating table; the detector collects the rays passing through the scanning area to obtain detector data, including: controlling the ray source to emit rays; controlling the rotation of the rotating table to drive the energy spectrum calibration phantom to rotate m circles, where m is a positive integer greater than or equal to 1; and during the process of the energy spectrum calibration phantom rotating m circles, the detector collects the rays emitted from the ray source and passing through the scanning area.

[0041] According to some exemplary embodiments, the calibration system includes a lifting platform, and the energy spectrum calibration phantom is located on the lifting platform; the detector collects the rays passing through the scanning area to obtain the detector data, including: controlling the ray source to emit rays; controlling the lifting platform to move up and down to drive the energy spectrum calibration phantom to move up and down.

[0042] According to some exemplary embodiments, the ray source includes N s targets, the N s Target points are spaced apart along the first direction, where N s is a positive integer greater than or equal to 2; the detector collects the rays passing through the scanning area and obtains the detector data, including: controlling the N s The target points emit rays in a set order; and in the N sIn the process of each target point emitting rays in a set order, the detector collects rays emitted from the ray source and passing through the scanning area.

[0043] According to some exemplary embodiments, the calibration system includes a rotating platform, and the energy spectrum calibration phantom is located on the rotating platform; the ray source includes N s targets, the N s Target points are spaced apart along the first direction, where N s is a positive integer greater than or equal to 2; the detector collects the rays passing through the scanning area and obtains the detector data, including: controlling the N s The target points emit radiation in a set order; the rotating stage is controlled to rotate to drive the energy spectrum calibration phantom to rotate m circles, wherein m is a positive integer greater than or equal to 1; and s During the process in which the target points emit rays in a set order and the energy spectrum calibration phantom rotates m circles, the detector collects rays emitted from the ray source and passing through the scanning area.

[0044] According to some exemplary embodiments, the preset condition includes at least one of the following conditions: during the first cycle, the deviation of energy spectrum information obtained two adjacent times is less than a preset threshold; and during the first cycle, the number of iterations reaches a preset number.

[0045] According to some exemplary embodiments, the factors affecting the absorption energy spectrum of the detector include at least one of the following factors: the exit angle of the ray; the incident angle of the ray on the detector; the energy spectrum distribution of the target point of the ray source; and the obstruction of the ray in the path from the ray source to the detector.

[0046] On the other hand, a calibration system for performing energy spectrum calibration on a scanning imaging device is provided, wherein the calibration system includes: a calibration device body; an energy spectrum calibration phantom arranged on the calibration device body; a driving member, the driving member being used to drive the energy spectrum calibration phantom to move; and a controller, the controller being configured to perform energy spectrum calibration on the scanning imaging device according to the calibration method as described above.

[0047] On the other hand, a calibration system for performing energy spectrum calibration on a scanning imaging device is provided, wherein the calibration system includes: a base; a rotating table connected to the base; an energy spectrum calibration phantom arranged on the rotating table, and the energy spectrum calibration phantom is located on the rotating table; and a driving member, wherein the driving member is used to drive the rotating table to rotate, thereby driving the energy spectrum calibration phantom to rotate, wherein the energy spectrum calibration phantom includes a plurality of parts respectively composed of a plurality of materials, and any two of the plurality of materials have at least one of the following properties that are different: density, atomic number.

[0048] According to some exemplary embodiments, the calibration system further includes: a lifting platform connected to the base, and the rotating platform is disposed on the lifting platform.

[0049] Additional aspects and advantages of the present disclosure will be given in part in the description that follows and, in part, will be obvious from the description that follows, or will be learned through practice of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] For a more complete understanding of the present disclosure and its advantages, reference will now be made to the following description taken in conjunction with the accompanying drawings, in which:

[0051] FIG1 schematically shows a schematic diagram of the projection relationship between a ray source, an object to be inspected, and a detector.

[0052] FIG2 is a schematic structural diagram of a static CT device according to some exemplary embodiments of the present disclosure.

[0053] FIG3A is a schematic structural diagram of a scanning stage included in a static CT device according to some exemplary embodiments of the present disclosure.

[0054] FIG3B is a schematic structural diagram of a scanning stage included in a static CT device according to other exemplary embodiments of the present disclosure.

[0055] FIG4A is a schematic structural diagram of a calibration system according to some exemplary embodiments of the present disclosure.

[0056] FIG4B is a schematic structural diagram of a calibration system according to some exemplary embodiments of the present disclosure, viewed from another angle.

[0057] FIG5 is a flowchart of a calibration method according to some exemplary embodiments of the present disclosure.

[0058] FIG6 is a flowchart of a calibration method according to other exemplary embodiments of the present disclosure.

[0059] FIG7 is an exemplary flowchart of obtaining optimized energy spectrum parameters in a calibration method according to some exemplary embodiments of the present disclosure.

[0060] FIG8 schematically shows a structural block diagram of a controller of a calibration system according to an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0061] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are merely illustrative and are not intended to limit the scope of the present disclosure. In addition, in the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure. In addition, the various embodiments provided below and the technical features in the embodiments may be combined with each other in any manner.

[0062] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. In addition, the terms "comprise", "include", etc. used herein indicate the presence of the features, steps, operations and / or components, but do not exclude the presence or addition of one or more other features, steps, operations or components. 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 here should be interpreted as having meanings consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0063] In the description of the present disclosure, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present disclosure and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present disclosure. In addition, features defined as "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present disclosure, unless otherwise specified, "multiple" means two or more.

[0064] In the description of this disclosure, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood broadly. For example, they may refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal connections between two components. Those skilled in the art will understand the specific meanings of the above terms in this disclosure based on the specific circumstances.

[0065] In the present disclosure, computed tomography (CT) imaging refers to the use of radiation to perform a cross-sectional scan of an object, converting the analog signal received by a detector into a digital signal, calculating the attenuation coefficient of each pixel using an electronic computer, and reconstructing the image to display the cross-sectional structure of each part of the object.

[0066] FIG1 schematically shows a schematic diagram of the projection relationship between a ray source, an object under inspection, and a detector. Referring to FIG1 , in an embodiment of the present disclosure, rays (such as X-rays, gamma rays, etc.) emitted by a ray source S are incident on the object under inspection OB, and rays transmitted through the object under inspection OB are detected by a detector D. A spatial point X on the object under inspection OB is acted upon by the ray source S to an image point Y on the detector D. In forward projection (also called forward projection), the pixel value of the spatial point on the object under inspection OB is known, and the projection value of the image point on the detector D is obtained. In reverse projection (also called backward projection), the projection value of the image point on the detector D is known, and the pixel value of the spatial point on the object under inspection OB is obtained.

[0067] Computed tomography (CT) technology, because it can eliminate the effects of overlapping objects, has played a vital role in security inspections and medical fields. Traditional CT systems use a slip-ring mechanism to acquire projection data at different angles by rotating the X-ray source and detector. Reconstruction methods produce tomographic images, thereby revealing internal information about the inspected baggage. Traditional CT systems typically rely on slip-ring rotation during data acquisition, which not only limits scanning speed and is bulky, but also requires high machining precision and is expensive, limiting their widespread practical application. In recent years, carbon nanotube X-ray tube technology has entered the practical field. Unlike traditional X-ray sources, it does not require high temperatures to generate X-rays. Instead, it generates cathode rays based on discharge at the tip of the carbon nanotube, which then strikes the target to produce X-rays. Its advantages include fast switching on and off and a smaller size. Arranging these X-ray sources in a ring shape to irradiate objects at different angles creates a "static CT" system that does not require rotation. This significantly improves X-ray imaging speed and, by eliminating the slip-ring mechanism, reduces costs. This holds significant significance for applications in security inspections and other fields.

[0068] FIG2 is a schematic diagram of the structure of a static CT device according to some exemplary embodiments of the present disclosure. Referring to FIG2 , the static CT device according to an embodiment of the present disclosure may include a scanning stage, a transmission mechanism 110, a control device 140, and an imaging device 130. For example, the scanning stage may include a radiation source, a detector, and an acquisition device.

[0069] For example, in an embodiment of the present disclosure, the ray source may be a distributed ray source, which may include multiple target points, for example, multiple X-ray target points. In a distributed X-ray source, the target point refers to the emission point or focus of the ray source. Specifically, high-energy electrons are emitted from the cathode and bombard the metal anode target, thereby generating X-rays. The energy of the emitted X-rays depends on the material of the anode target, while the intensity of the X-rays depends on the electron flux and electron energy bombarding the anode target. In a distributed X-ray source, multiple cathodes correspond one-to-one to multiple target points, so that multiple target points receive electron beams from multiple cathodes to generate multiple beams of X-rays. This design enables the distributed X-ray source to achieve the effect of generating more X-ray radiation sources using fewer cathode components, thereby improving the stability of the system, reducing the number of cathode components used, and reducing the production cost of the equipment.

[0070] In static CT devices that utilize distributed radiation sources, multiple targets are combined and activated in a set order at different angles to obtain multiple projection data sets from various angles. These projection data sets can be used in computer reconstruction algorithms to generate high-quality cross-sectional images. One advantage of using a distributed X-ray source is that it can reduce artifacts and improve image quality. By using multiple targets, the emission positions of the X-ray beam are more evenly distributed, providing more projection angles and data, reducing artifacts in the reconstructed image, and providing more accurate anatomical information. In other words, the targets in a distributed X-ray source refer to the points or areas that emit X-ray beams, and their distribution helps to obtain high-quality projection data for the reconstruction of static CT images.

[0071] In the embodiments of the present disclosure, multiple targets in a distributed radiation source can be arranged along a predetermined first direction. For example, the predetermined first direction can be a straight line or an arc. The embodiments of the present disclosure do not impose any particular restrictions on the arrangement of the targets in the distributed radiation source.

[0072] FIG3A is a schematic diagram of the structure of a scanning stage included in a static CT device according to some exemplary embodiments of the present disclosure. FIG3B is a schematic diagram of the structure of a scanning stage included in a static CT device according to other exemplary embodiments of the present disclosure. Referring to FIG3A and FIG3B , in an embodiment of the present disclosure, the static CT device includes a distributed radiation source 20 and a detector 30. The distributed radiation source 20 may include multiple targets 210. In some embodiments, as shown in FIG3A , the multiple targets 210 may be arranged in an arc shape. Accordingly, the detector 30 may include multiple detection units 310 arranged in an arc shape or a circle. In some embodiments, as shown in FIG3B , the multiple targets 210 may be arranged along a straight line. Accordingly, the detector 30 may include multiple detection units 310 arranged along a straight line. It should be noted that the embodiments of FIG2 to FIG3B are merely schematic diagrams of the structures of static CT devices according to some exemplary embodiments of the present disclosure, and do not represent all embodiments of the present disclosure. In the embodiments of the present disclosure, any suitable arrangement of distributed radiation sources and detectors may be employed.

[0073] In the embodiment of the present disclosure, the multiple targets 210 each emit radiation toward the inspected object 120, and the multiple detection units 310 are used to detect the radiation that has passed through the inspected object 120. For example, in the embodiment shown in Figures 3A and 3B, the multiple targets 210 emit X-rays, and the multiple detection units 310 receive a portion of the X-rays emitted from the multiple targets 210 that have passed through the inspected object 120. In this way, a scanning area is formed between the radiation source 20 and the detector 30 for scanning the inspected object 120. Within this scanning area, at least one plane located approximately in the middle of the scanning area and perpendicular to the conveying direction of the conveying mechanism 110 can be referred to as a scanning plane.

[0074] For example, the detection unit 310 may include at least one detector crystal. For example, the detection unit 310 may include one detector crystal. For another example, the detection unit 310 may include multiple detector crystals, and the multiple detector crystals may be arranged along a one-dimensional direction, or the multiple detector crystals may be arranged along a two-dimensional direction.

[0075] It should be understood that each detector crystal is a basic unit of the detector, which can absorb radiation (such as X-rays) and convert it into other forms of energy, such as light or electrical signals. For example, the materials of the detector crystals can include oxides and halides (such as iodide and fluoride).

[0076] For example, in the embodiment shown in FIG2 , the transport mechanism 110 carries the subject 120 under examination and drives the subject 120 in linear motion. The control device 140 controls the beam emission sequence of the multiple target points 210 of the radiation source 20, causing the detector 30 to output digital signals corresponding to the projection data. The imaging device 130 reconstructs a CT image of the subject 120 based on the digital signals.

[0077] It should be noted that in the embodiments of the present disclosure, the imaging device 130 can use various known reconstruction algorithms to reconstruct the CT image of the object under examination. For example, the reconstruction algorithm can be an iterative, analytical, or other reconstruction algorithm. The embodiments of the present disclosure do not place any particular restrictions on the reconstruction algorithm.

[0078] In some embodiments of the present disclosure, each distributed ray source 20 has one or more targets, the energy of the targets can be set, and the order of target activation can be set. For example, the targets can be distributed on multiple scanning planes (for example, the scanning plane is perpendicular to the direction of passage). In each plane, the target distribution can be continuous or discontinuous, one or more straight lines or arcs. Since the target energy can be set, a variety of scanning modes can be achieved during the beam emission process, such as different targets having different energy spectra, or targets located in different planes having different energies. The targets can be designed in groups, such as the targets of each module as a group, or the targets of each plane as a group. The order of electronic targeting of targets in the same group can be adjusted, and sequential beam emission and alternating beam emission can be achieved. Targets in different groups can be activated at the same time for scanning to speed up the scanning speed.

[0079] The detector 30 may be a single row or multiple rows, and the detector type may be a single energy, dual energy or energy spectrum detector.

[0080] The transport mechanism 110 includes a stage or conveyor belt. The control device 140 controls the X-ray machine and detector frames. By controlling the beam emission pattern of the distributed X-ray source and the linear translation of the object, or a combination of the two, spiral scanning trajectories, circular scanning trajectories, or other special trajectories can be achieved. The control device 140 is responsible for controlling the CT system's operation, including mechanical rotation, electrical control, and safety interlocks. Specifically, it controls the X-ray source's beam emission speed / frequency, energy, and sequence, and controls detector data readout and reconstruction.

[0081] CT imaging theory is based on the fact that ray attenuation conforms to Beer's law, which requires that the detectors used for scanning imaging have the same absorption energy spectrum, so that the attenuation of rays passing through objects of the same thickness from different directions can be consistent. The inventors have found through research that the absorption energy spectrum of the detector is related to the thickness of the crystal where the rays are incident. In the geometric arrangement of a single target source probe centripetal, all rays are incident vertically on the crystal, the crystal thickness through which the rays pass is the same, and the absorption energy spectrum of the detector is the same. However, in static CT equipment, since a single crystal needs to receive rays emitted from different targets, the incident angles of rays from different targets are different, and the thickness of the crystals they pass through are different, resulting in different absorption energy spectra. On the other hand, there may also be differences in the energy spectra of different targets. Data inconsistency caused by inconsistent energy spectra is also an important factor affecting the accuracy of reconstructed values.

[0082] Furthermore, the inventors discovered that differences in the horizontal and vertical orientations of different X-ray sources can affect the clarity of CT reconstructed images. Because the radiation emitted by the X-ray source has a directionally dependent spatial distribution of its energy spectrum, and because the radiation incident on each detector unit varies at different angles, the energy spectra of different rays vary. During the reconstruction process, these energy spectrum errors can interfere with the reconstructed values.

[0083] In addition, the above-mentioned technical issues of energy spectrum accuracy will also directly affect the image color accuracy of single-view / multi-view X-ray imaging equipment, and indirectly affect the accuracy of automatic identification of some suspicious objects.

[0084] An embodiment of the present disclosure provides a calibration system for performing energy spectrum calibration on a scanning imaging device, which can perform energy spectrum calibration on a scanning imaging device, for example, can perform energy spectrum calibration on a static CT device based on a distributed ray source.

[0085] FIG4A is a schematic diagram of the structure of a calibration system according to some exemplary embodiments of the present disclosure. FIG4B is a schematic diagram of the structure of a calibration system according to some exemplary embodiments of the present disclosure, viewed from another angle. Referring to FIG4A and FIG4B , the calibration system 40 may include: a base 410; a rotating table 420 connected to the base 410; an energy spectrum calibration phantom 60 disposed on the rotating table 420; and a driving member 430, the driving member 430 being configured to drive the rotating table 420 to rotate, thereby driving the energy spectrum calibration phantom 60 to rotate.

[0086] In some exemplary embodiments, the energy spectrum calibration phantom 60 is located at the center of the rotating stage 420. For example, the geometric center of the energy spectrum calibration phantom 60 is located on the rotation axis AX1 of the rotating stage 420.

[0087] In some exemplary embodiments, the energy spectrum calibration phantom 60 may include multiple parts each made of multiple materials, and any two of the multiple materials may have different properties in at least one of the following: density and atomic number.

[0088] In some exemplary embodiments, the energy spectrum calibration phantom 60 can be a shaped object composed of a known or unknown material with sufficient attenuation capability. For example, the material of the energy spectrum calibration phantom 60 can be graphite, organic glass, polyethylene, polyoxymethylene, aluminum (alloy), magnesium (alloy), silicon dioxide, polyvinyl chloride, titanium (alloy), iron, copper, etc. The chemical composition and physical density of these materials are known. For another example, the material of the energy spectrum calibration phantom 60 can also be selected from materials with stable physical and chemical properties, but the composition ratio information of the material cannot be accurately obtained.

[0089] In some exemplary embodiments, the atomic number range of the material of the energy spectrum calibration phantom 60 should cover as wide a range as possible.

[0090] The shape of the energy spectrum calibration phantom 60 can be a cylinder, a prism, a pyramid, or an irregular shape. During the calibration process, the length of the intersection line between the ray and the energy spectrum calibration phantom 60 should cover a wide range as much as possible.

[0091] It should be noted that in the embodiments shown in Figures 4A and 4B, the energy spectrum calibration phantom 60 is in the shape of a cuboid. However, this shape is merely exemplary and does not limit the embodiments of the present disclosure. In other embodiments of the present disclosure, the energy spectrum calibration phantom 60 may adopt any other suitable shape.

[0092] 4A and 4B , the calibration system 40 may further include a lifting platform 440 connected to the base 410, and a rotating platform 420 disposed on the lifting platform 440. In this way, by controlling the lifting platform to translate up and down a fixed distance, the wire can be scanned at multiple height positions to obtain more calibration data, thereby improving calibration accuracy.

[0093] In the embodiment of the present disclosure, the base 410 is used to support other components and maintain the stability of the components installed thereon. The driving member 430 may include a movement driving mechanism for driving the lifting platform 440 to move up and down; and / or a rotation driving mechanism for driving the rotating platform 420 to rotate.

[0094] For example, the rotation drive mechanism for driving the turntable 420 to rotate may include at least one of a gear transmission mechanism, a servo motor drive mechanism, and a stepper motor drive mechanism. The gear transmission mechanism may include a drive motor, a drive gear, and a driven gear, and the rotational force is transmitted through the meshing of the gears. The servo motor drive is to achieve the rotation of the turntable by controlling the speed and position of the servo motor. The servo motor is usually used in combination with an encoder and a closed-loop control system to achieve high-precision rotation control. The stepper motor drive is to achieve the rotation of the turntable by controlling the pulse signal of the stepper motor. The stepper motor has a discrete step angle, which can accurately control the position and speed of the turntable.

[0095] For example, the mobile drive mechanism used to drive the lifting platform 440 up and down may include at least one of a screw drive mechanism, an electric screw drive mechanism, and a gear drive mechanism. The screw drive mechanism may include a screw and a nut that meshes with it. When the screw rotates, the nut moves along the screw's helical line, thereby achieving the up and down movement of the lifting platform. The electric screw drive mechanism combines screw drive and electric drive technology. The screw is driven by an electric motor to rotate, thereby driving the lifting platform up and down. The gear drive mechanism uses the meshing of gears to transmit force and motion. The up and down movement of the lifting platform can be achieved by rotating the drive gear.

[0096] It should be noted that in the embodiments of the present disclosure, there is no special restriction on the type and structure of the rotary drive mechanism and the mobile drive mechanism. Unless there is a conflict, various types of rotary drive mechanisms and mobile drive mechanisms known in the relevant field can be used in the embodiments of the present disclosure.

[0097] Some exemplary embodiments of the present disclosure further provide a calibration method for performing energy spectrum calibration on a scanning imaging device.

[0098] With reference to Figures 4A and 4B , during calibration, the calibration system 40 is placed on a conveyor mechanism (e.g., conveyor mechanism 110 shown in Figure 2 ) of the scanning imaging device. The conveyor mechanism is controlled to transport the energy spectrum calibration phantom 60 of the calibration system 40 to the X-ray scanning plane, such that the energy spectrum calibration phantom 60 is within the scanning plane formed by the X-ray source 20 and the detector 30. For example, during energy spectrum calibration, only the energy spectrum calibration phantom 60 is within the scanning plane, while the rest of the calibration system 40 remains outside of the scanning plane. This prevents interference with the calibration data from other parts of the calibration system 40.

[0099] FIG5 is a flow chart of a calibration method according to some exemplary embodiments of the present disclosure. Referring to FIG1 to FIG5 , the calibration method can be used to perform energy spectrum calibration on a scanning imaging device. For example, the calibration method can perform energy spectrum calibration on a static CT device. In the static CT device, the ray source 20 can be a distributed ray source, which includes N s Target 210, N s Target points are spaced apart along the first direction, where N s is a positive integer greater than or equal to 2. The first direction may correspond to the linear arrangement shown in FIG3A or the arc arrangement shown in FIG3B. It should be noted that in the embodiments of the present disclosure, no particular limitation is imposed on the arrangement direction and form of the multiple targets of the distributed radiation source.

[0100] In some embodiments of the present disclosure, the calibration method may include steps S510 to S560.

[0101] In step S510, when the energy spectrum calibration phantom is located in the scanning area formed by the ray, the geometric relationship between the ray source, the energy spectrum calibration phantom and the detector is obtained according to the relative positions between the ray source, the energy spectrum calibration phantom and the detector.

[0102] In step S520, the detector collects rays passing through the scanning area to obtain actual projection data.

[0103] In step S530 , the physical properties of the energy spectrum calibration phantom are acquired, wherein the physical properties are predetermined according to the constituent materials of the energy spectrum calibration phantom.

[0104] In step S540 , theoretical projection data is calculated using a plurality of predetermined basic energy spectra based on the physical properties of the energy spectrum calibration phantom and the geometric relationship.

[0105] In step S550, the energy spectrum parameters are calibrated according to the theoretical projection data and the actual projection data to obtain optimized energy spectrum parameters.

[0106] In step S560, the optimized energy spectrum parameters are determined as energy spectrum calibration parameters.

[0107] In this embodiment, the energy spectrum calibration phantom 60 can be a shaped object made of a known material with sufficient attenuation capability. For example, the material of the energy spectrum calibration phantom 60 can be graphite, organic glass, polyethylene, polyoxymethylene, aluminum (alloy), magnesium (alloy), silicon dioxide, polyvinyl chloride, titanium (alloy), iron, copper, etc. The chemical composition and physical density of these materials are known.

[0108] In this embodiment, since the physical properties of the energy spectrum calibration phantom 60 can be predetermined, the physical properties of the energy spectrum calibration phantom 60 obtained in step S530 are accurate. Accordingly, in step S540, accurate theoretical projection data can be calculated based on the accurate physical properties and geometric relationships of the energy spectrum calibration phantom 60. The optimized energy spectrum parameters obtained in step S550 can be used as the final energy spectrum calibration parameters without the need for iteration.

[0109] Fig. 6 is a flow chart of a calibration method according to some other exemplary embodiments of the present disclosure. In some other embodiments of the present disclosure, the calibration method may include steps S610 to S660.

[0110] In step S610, when the energy spectrum calibration phantom is located in the scanning area formed by the ray, the geometric relationship between the ray source, the energy spectrum calibration phantom and the detector is obtained according to the relative positions between the ray source, the energy spectrum calibration phantom and the detector.

[0111] In step S620, the detector collects rays passing through the scanning area to obtain actual projection data.

[0112] In step S630 , a loop process is executed until a preset condition is met, wherein the first loop process includes steps S631 to S634 .

[0113] In step S631, image reconstruction is performed on the energy spectrum calibration phantom according to the energy spectrum information, and physical properties of the energy spectrum calibration phantom are obtained according to the result of the image reconstruction.

[0114] In step S632 , theoretical projection data is calculated using a plurality of predetermined basic energy spectra based on the physical properties of the energy spectrum calibration phantom and the geometric relationship.

[0115] In step S633 , the energy spectrum parameters are calibrated according to the theoretical projection data and the actual projection data to obtain optimized energy spectrum parameters.

[0116] In step S634, energy spectrum information is acquired based on the optimized energy spectrum parameters.

[0117] In step S640, the optimized energy spectrum parameters obtained last time during the first cycle are determined as energy spectrum calibration parameters.

[0118] In this embodiment, the energy spectrum calibration phantom 60 can be a shaped object composed of an unknown material with sufficient attenuation capability. For example, the material of the energy spectrum calibration phantom 60 can be selected from materials with stable physical and chemical properties, but whose composition ratio information cannot be accurately obtained. In other words, the physical properties of the energy spectrum calibration phantom 60 cannot be predetermined.

[0119] In this embodiment, the physical properties of the energy spectrum calibration phantom 60 can be determined through image reconstruction. Referring back to FIG. 1 , in reverse projection (also known as back projection), the projection values ​​of image points on detector D are known, and the pixel values ​​of spatial points on the inspected object OB are calculated. In this embodiment, in step S620, actual projection data, i.e., the projection values ​​on the detector, are acquired. Using a reverse projection algorithm or an image reconstruction algorithm, an image of the inspected object (i.e., the energy spectrum calibration phantom) can be calculated. This reconstructed image corresponds to the physical properties of the energy spectrum calibration phantom 60.

[0120] It should be noted that, in this embodiment, various back-projection algorithms or image reconstruction algorithms known in the art may be used to perform image reconstruction, and the embodiments of the present disclosure do not impose any particular limitation on this.

[0121] It should be understood that the physical properties of the energy spectrum calibration phantom determined by the image reconstruction algorithm based on the actual projection data may be inaccurate. Therefore, in this embodiment, it is necessary to execute a first loop process. Through this loop process, the physical properties of the acquired energy spectrum calibration phantom can be infinitely close to the accurate physical properties of the energy spectrum calibration phantom, thereby improving the accuracy of the energy spectrum calibration.

[0122] It should be noted that, unless otherwise specified or in the event of a conflict, the steps or methods described below can be applied to the various embodiments described above. Specifically, unless otherwise specified, the steps described below can be applied to both the calibration methods described above for Figures 5 and 6.

[0123] In step S510 or S610 , ray source parameters and detector parameters may be acquired, wherein the ray source parameters are used to represent the position of the ray source 20 in the calibration system 40 , and the detector parameters are used to represent the position of the detector 30 in the calibration system 40 .

[0124] In this paper, for the convenience of description, the ray source parameters are described as s i , the detector parameters are described as P d .

[0125] For example, geometric calibration can be performed using the geometric calibration phantom 50 to obtain the ray source parameters and the detector parameters. For another example, the ray source parameters and the detector parameters can be predetermined.

[0126] In some exemplary embodiments, the ray source is a distributed ray source, and the target interval has a sufficiently high accuracy, so that the target position can be calibrated as a whole, that is, {s i :1≤i≤N s} is determined by the starting coordinates, arrangement direction and number i of the distributed ray source. In this embodiment, the ray source parameter s i Includes: N s The position coordinates of the first target point in the calibration system, N s The arrangement direction of the targets, and N s The number of each target in the target.

[0127] In some exemplary implementation cases, the detector arms are arranged in a straight line or an arc, and the parameters of the detector arms are the starting coordinates and the arrangement direction.

[0128] For example, referring to FIG4A and FIG4B , the detector 30 may include a detector arm 320 and a plurality of detection units 310 mounted on the detector arm 320. The plurality of detection units 310 are arranged in a straight line on the detector arm 320. In this embodiment, the detector parameter P d It may include: the position coordinates of the first detection unit among the multiple detection units in the calibration system, and the arrangement directions of the multiple detection units.

[0129] For another example, multiple detection units 310 are arranged in an arc on the detector arm, and the detector parameter Pd may include: the angle and radius of the first detection unit among the multiple detection units in the calibration system.

[0130] Furthermore, the energy spectrum calibration phantom 60 is disposed on the rotating stage 420, and its position in the calibration system 40 is also predetermined, or in other words, its position in the calibration system 40 is determined based on the position of the rotating stage 420 in the calibration system 40 and the position of the energy spectrum calibration phantom 60 on the rotating stage 420. In this way, when the energy spectrum calibration phantom 60 is located in the scanning area formed by the radiation, the geometric relationship between the radiation source 20, the energy spectrum calibration phantom 60, and the detector 30 can be obtained based on the relative positions among the radiation source 20, the energy spectrum calibration phantom 60, and the detector 30.

[0131] In some exemplary embodiments, the calibration method may include: before placing the energy spectrum calibration phantom 60 in the scanning area or scanning plane formed by the ray, collecting the air projection data p by the detector 30 air .

[0132] It should be understood that when performing image reconstruction, it is necessary to know the detector reading when there is no object (i.e., only air) in order to remove this background value from the actual measurement data. For example, in CT imaging, a method called line integral is often used to obtain projection data. This process involves passing rays through the object and measuring the attenuation of the rays after passing through the object. This attenuation value (or projection data) reflects the properties of the material in the ray path, such as density and composition. Similar measurements can be made when there is no object present, that is, only air. The projection data thus obtained can be used as a reference or background value. During the actual image reconstruction process, this background value is removed from the measured projection data to obtain the ray attenuation caused only by the object itself.

[0133] In step S520, the acquisition of detector data includes: collecting the rays passing through the scanning area (the energy spectrum calibration phantom 60 is located in the scanning area) through the detector 30 to obtain the initial detector data p i ; and, using the air projection data p air , use the first correction method to calibrate the initial detector data p i Correction is performed to obtain first corrected projection data prj i .

[0134] It should be noted that in this article, 1≤i≤N s , that is, i represents the number of a target point 210 in the distributed ray source.

[0135] For example, the following formula can be used to perform the first correction to obtain the first corrected projection data prj i :prj i =p i / p air .

[0136] Alternatively or additionally, in step S620, the obtaining of the detector data includes: collecting the rays passing through the scanning area (the energy spectrum calibration phantom 60 is located in the scanning area) by the detector 30 to obtain the initial detector data p i ; Using air projection data p air , use the first correction method to calibrate the initial detector data p i Correction is performed to obtain first corrected projection data prj i and / or, using the air data, adopting a second correction method to correct the initial projection data p i Correction is performed to obtain the second corrected projection data pprj i .

[0137] In some exemplary embodiments, the first correction method and the second correction method are different. For example, the following formula can be used to perform the first correction to obtain the first corrected projection data prj i :prj i =p i / p air For example, the following formula can be used to perform the second correction to obtain the second corrected projection data pprj i :pprj i =-log(p i / p air ).

[0138] It should be noted that the first corrected projection data prj i It is used as forward projection data in the following steps, so it is directly divided by the air projection data; the second corrected projection data pprj i In the following steps, it is used for image reconstruction, so it is necessary to take the negative value of the logarithm. For example, the logarithm here can be a logarithm with base 10.

[0139] In some exemplary embodiments of the present disclosure, the calibration system 40 includes a rotating stage 420 , and the energy spectrum calibration phantom 60 is located on the rotating stage 420 .

[0140] In this embodiment, the initial detector data p is obtained i It can include: controlling the ray source 20 to emit rays; controlling the rotation of the rotating table 420 to drive the energy spectrum calibration phantom 60 to rotate m circles, where m is a positive integer greater than or equal to 1; and, during the process of the energy spectrum calibration phantom 60 rotating m circles, the detector 30 collects rays emitted from the ray source 20 and passing through the scanning area.

[0141] In some exemplary embodiments of the present disclosure, the calibration system 40 includes a lifting platform 440 , and the energy spectrum calibration phantom 60 is located on the lifting platform 440 .

[0142] In this embodiment, the initial detector data p is obtained i The method may include: controlling the ray source 20 to emit rays; and controlling the lifting platform 440 to move up and down, so as to drive the energy spectrum calibration phantom 60 to move up and down.

[0143] For example, the geometric calibration phantom 50 may be moved up to the scanning position by the lifting platform 440. During the lifting process, the detector may not collect data.

[0144] For another example, during the lifting process of the energy spectrum calibration phantom 60, the detector 30 may collect radiation emitted from the radiation source 20 and passing through the scanning area. In some optional embodiments, the data collected during the lifting process may not be used for subsequent processing.

[0145] In some exemplary embodiments of the present disclosure, the ray source 20 includes N s Target 210, N s Target points 210 are spaced apart along the first direction, where N s is a positive integer greater than or equal to 2.

[0146] In this embodiment, the initial detector data p is obtained i May include: Control N s The target points 210 emit radiation in a set order; and s When each target point 210 emits radiation in a set order, the detector 30 collects radiation emitted from the radiation source 20 and passing through the scanning area.

[0147] In some exemplary embodiments of the present disclosure, the calibration system 40 includes a rotating stage 420, and the energy spectrum calibration phantom 60 is located on the rotating stage 420. The ray source 20 includes N s Target 210, N s Target points 210 are spaced apart along the first direction, where N s is a positive integer greater than or equal to 2.

[0148] In this embodiment, the initial detector data p is obtained i May include: Control N s The target points 210 emit radiation in a set order; the rotating stage 420 is controlled to rotate to drive the energy spectrum calibration phantom 60 to rotate m circles, where m is a positive integer greater than or equal to 1; and s During the process in which each target point 210 emits radiation in a set order and the energy spectrum calibration phantom 60 rotates m circles, the detector 30 collects radiation emitted from the radiation source and passing through the scanning area.

[0149] It should be noted that in the embodiments of the present disclosure, there is no particular restriction on the movement form, number of settings, and number of targets of the energy spectrum calibration phantom. In the absence of conflict, various situations can be combined and integrated with each other. For example, in some embodiments, the energy spectrum calibration phantom 60 can be set on a rotating table, which is set on a lifting table, and the radiation source 20 can be a distributed radiation source including multiple targets. In this way, the detector data prj is obtained. i The steps can be adjusted accordingly according to the setting method, and will not be repeated here.

[0150] It should also be noted that in the embodiments of the present disclosure, the movement of the energy spectrum calibration phantom 60 and the order in which the radiation source emits beams are not particularly limited. For example, the energy spectrum calibration phantom 60 can be fixed in one position, and all targets can be controlled to emit beams once in a set order. The rotating stage can then rotate to the next position, and all targets can be controlled to emit beams again, until the rotating stage completes one rotation.

[0151] As mentioned above, the inventors have found through research that in a static CT device, since a single crystal needs to receive rays emitted by different targets, the rays from different targets have different incident angles and pass through different crystal thicknesses, resulting in different absorption energy spectra. Therefore, in some exemplary embodiments of the present disclosure, the first corrected projection data prj can be obtained. i Classify and then perform energy spectrum calibration for each type of classified projection data.

[0152] Specifically, in step S520 or step S620, the step of collecting the rays passing through the scanning area by the detector to obtain actual projection data may further include: classifying the first corrected projection data prj according to a predetermined classification standard. i Classify to obtain N c The projection data of the jth category is taken as the actual projection data, wherein the projection data of the jth category is the N c One type of projection data in categories, N c is a positive integer greater than or equal to 1, 1≤j≤N c ; The predetermined classification criteria are determined based on factors that affect the absorption energy spectrum of the detector.

[0153] In some exemplary embodiments, the factors influencing the detector's absorption spectrum include at least one of the following: the radiation's exit angle; the radiation's incident angle on the detector; and any obstructions along the radiation path from the radiation source to the detector. In this embodiment, energy spectra with the same or similar radiation exit angles, incident angles on the detector, and any obstructions along the radiation propagation path are grouped together, and calibration is performed on energy spectra within this group, thereby improving the accuracy of energy spectrum calibration.

[0154] In step S540 or step S632, theoretical projection data is calculated using a plurality of predetermined basic energy spectra based on the physical properties of the energy spectrum calibration phantom 60 and the geometric relationship. It should be noted that in step S540, the physical properties of the energy spectrum calibration phantom 60 are predetermined based on the material and composition of the energy spectrum calibration phantom 60; and in step S632, the physical properties of the energy spectrum calibration phantom 60 are estimated based on an image reconstruction algorithm.

[0155] It should be noted that, in this article, the “multiple basic energy spectra” can be selected from the energy spectra at different energies measured, or can be obtained using Monte Carlo simulation. The multiple basic energy spectra are predetermined based on the energy spectra of interest required by the inspected object.

[0156] In some exemplary embodiments, in step S540 or step S632, the method of calculating theoretical projection data using a plurality of predetermined basic energy spectra based on the physical properties of the energy spectrum calibration phantom and the geometric relationship specifically includes: selecting N e Basic energy spectrum {S k (E)}; and successively for N e Basic energy spectrum {S k (E)}, based on the physical properties of the energy spectrum calibration phantom 60 and the geometric relationship, calculate N e Theoretical projection data. For example, N e is a positive integer greater than or equal to 2.

[0157] In the known N e Basic energy spectrum {S k (E)}, the physical properties of the energy spectrum calibration phantom 60 and the geometric relationship, various known forward projection algorithms can be used to calculate theoretical projection data.

[0158] For example, the following formula can be used to calculate the kth theoretical projection data sprj k :

[0159] In this formula, sprj k is the kth theoretical projection data calculated using the kth basic energy spectrum, 1≤k≤N e , S k (E) is the kth basic energy spectrum, Indicates location or distance The linear absorption coefficient of the inspected object at dl for rays of energy E, dl is the integral along the ray path, and dE is the integral about the energy.

[0160] For another example, as mentioned above, it is necessary to calculate the theoretical projection data for each category of actual projection data, so the above formula can be changed as follows, that is, the following formula can be used to calculate the k-th theoretical projection data sprj corresponding to the j-th category projection data calculated using the k-th basic energy spectrum: j，k :

[0161] In this formula, sprj j，k is the kth theoretical projection data corresponding to the jth category projection data calculated using the kth basic energy spectrum, 1≤k≤Ne , S k (E) is the kth basic energy spectrum, Indicates location or distance The linear absorption coefficient of the inspected object at dl for rays of energy E, dl is the integral along the ray path, and dE is the integral about the energy.

[0162] It should be noted that the above formula is only exemplary, and the embodiments of the present disclosure do not impose any particular limitation on the specific formula for calculating the theoretical projection data.

[0163] That is, in some exemplary embodiments of the present disclosure, the process of calculating theoretical projection data using a plurality of predetermined basic energy spectra based on the physical properties and the geometric relationship of the energy spectrum calibration phantom may include a cyclic process. For example, the process of calculating theoretical projection data using a plurality of predetermined basic energy spectra based on the physical properties and the geometric relationship of the energy spectrum calibration phantom may include: sequentially calculating N c The second loop process includes: for the projection data of the jth category, selecting N e Basic energy spectrum {S k (E)}; and successively for N e Basic energy spectrum {S k (E)}, based on the physical properties of the energy spectrum calibration phantom and the geometric relationship, calculate the N corresponding to the projection data of the jth category e Theoretical projection data.

[0164] In some exemplary embodiments, in step S631, the second corrected projection data pprj may be obtained based on the energy spectrum information. i , image reconstruction is performed on the energy spectrum calibration phantom 60.

[0165] Since the energy spectrum calibration phantom 60 is located in the scanning plane, the X-ray covers the entire energy spectrum calibration phantom 60, and the rotating stage 420 drives the energy spectrum calibration phantom 60 to rotate one circle. The second correction projection data pprj obtained in the above steps i CT reconstruction is complete. Combining the coordinates or relative positions of the radiation source and detector, the detector integration time, the position of the rotating stage 420, the rotation speed of the rotating stage 420, and the energy spectrum information, CT reconstruction can be performed on the energy spectrum calibration phantom 60 to obtain a reconstructed image. It will be appreciated that the reconstructed image may include an image of the energy spectrum calibration phantom 60, which reflects the physical properties of the energy spectrum calibration phantom 60.

[0166] FIG7 is an exemplary flowchart of obtaining optimized energy spectrum parameters in a calibration method according to some exemplary embodiments of the present disclosure.

[0167] 7 , in some exemplary embodiments, step S550 or step S633 may include steps S710 to S720 .

[0168] In step S710, an optimization function of the deviation between the theoretical projection data and the actual projection data with respect to energy spectrum parameters is constructed.

[0169] For example, in this optimization function, the deviation is the dependent variable and the energy spectrum parameter is the independent variable.

[0170] In step S720, the energy spectrum parameters are calibrated according to the optimization function to obtain optimized energy spectrum parameters.

[0171] For example, in some exemplary embodiments, the optimized energy spectrum parameters may be obtained by solving the following optimization function:

[0172] Among them, "argmin" is a mathematical term used to represent the parameter value (the value of the independent variable) of a function to achieve the minimum value in its domain. Specifically, in this optimization function, it means: when The energy spectrum parameter {c k};N e is the total number of basic energy spectra; k represents the kth basic energy spectrum, 1≤k≤N e ;c k represents the weight coefficient of the kth theoretical projection data, that is, the energy spectrum parameter of the kth basic energy spectrum, {c k} is a set of energy spectrum parameters; sprj k is the kth theoretical projection data calculated using the kth basic energy spectrum; aprj is the actual projection data. For example, aprj can be the first correction projection data that only passes through the energy spectrum calibration phantom. It should be noted that aprj and sprj k The two data are projection data of rays that pass through the same path and are incident on the detector.

[0173] For example, optionally, the above optimization function can have the constraints: st Among them, "st" indicates that the optimization function has a constraint condition: is a specific constraint condition, which represents the 1st to Nth e Weight coefficient c k (i.e. N e Weight coefficient c k ) is approximately equal to 1. The “approximately equal to” here includes the case where it is equal to, and also includes the case where it is approximately equal to within a certain error range.

[0174] For another example, in some exemplary embodiments, the optimized energy spectrum parameters may be obtained by solving the following optimization function:

[0175] Among them, "argmin" is a mathematical term used to represent the parameter value (the value of the independent variable) of a function to achieve the minimum value in its domain. Specifically, in this optimization function, it means: when The energy spectrum parameter {c k};N e is the total number of basic energy spectra; k represents the kth basic energy spectrum, 1≤k≤N e ;c k represents the weight coefficient of the kth theoretical projection data, that is, the energy spectrum parameter of the kth basic energy spectrum, {c k} is a set of energy spectrum parameters; sprj j，k aprj is the kth theoretical projection data corresponding to the jth category projection data calculated using the kth basic energy spectrum; j is the actual projection data of the j-th category.

[0176] For example, optionally, the above optimization function can have the constraints: st Among them, "st" indicates that the optimization function has a constraint condition: is a specific constraint condition, which represents the 1st to Nth e Weight coefficient c k (i.e. N e Weight coefficient c k ) is approximately equal to 1. The “approximately equal to” here includes the case where it is equal to, and also includes the case where it is approximately equal to within a certain error range.

[0177] In the above embodiment, in step S720, the N when the deviation is the minimum value can be calculated by solving the above optimization function. e Optimized weight coefficients {c k}, the N e Optimized weight coefficients {c k} as the optimized energy spectrum parameter.

[0178] 5 , in some calibration methods according to embodiments of the present disclosure, since iterative calculation is not required, in step S560 , the optimized energy spectrum parameters may be determined as energy spectrum calibration parameters.

[0179] Referring back to Figure 6, in some other calibration methods according to the embodiments of the present disclosure, since iterative calculation is required, when the first loop process meets the preset conditions, in step S640, the optimized energy spectrum parameters obtained for the last time in the first loop process can be determined as energy spectrum calibration parameters.

[0180] 6, in step S634, according to the N e The optimized weight coefficients and the N e The energy spectrum information is obtained by calculating a basic energy spectrum using a weighted summation method.

[0181] For example, the energy spectrum information can be calculated using the following formula:

[0182] That is to say, the energy spectrum information calculated by the above formula can be matched with the actual projection data.

[0183] It should be noted that, in an embodiment of the present disclosure, the termination condition of the first cycle process (i.e., the preset condition) may include at least one of the following conditions: in the first cycle process, the deviation of the energy spectrum information obtained two adjacent times is less than a preset threshold; and in the first cycle process, the number of iterations reaches a preset number.

[0184] Referring back to Figures 4A to 4B, the calibration system 40 according to some embodiments of the present disclosure may include: a calibration device body; an energy spectrum calibration phantom 60 arranged on the calibration device body; a driving member 430, the driving member 430 is used to drive the energy spectrum calibration phantom to move; and a controller 450, the controller 450 is configured to: perform energy spectrum calibration on the scanning imaging device according to the above-mentioned calibration method.

[0185] For example, the calibration device body may include: a base 410; and a rotating platform 420 connected to the base 410. Alternatively, the calibration device body may include: a base 410; a lifting platform 440 connected to the base 410; and a rotating platform 420 connected to the base 410.

[0186] FIG8 schematically shows a structural block diagram of a controller of a calibration system according to an exemplary embodiment of the present disclosure.

[0187] As shown in Figure 8, the controller 450 of the calibration system according to an embodiment of the present disclosure may include a processor 1001, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage part 1008 into a random access memory (RAM) 1003. The processor 1001 may, for example, include a general-purpose microprocessor (such as a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (for example, an application-specific integrated circuit (ASIC)), etc. The processor 1001 may also include on-board memory for caching purposes. The processor 1001 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 disclosure.

[0188] Various programs and data required for the operation of the controller 450 are stored in the RAM 1003. The processor 1001, the ROM 1002, and the RAM 1003 are connected to each other via a bus 1004. The processor 1001 executes the various operations of the method flow according to the embodiment of the present disclosure by executing the programs in the ROM 1002 and / or the RAM 1003. It should be noted that the programs may also be stored in one or more memories other than the ROM 1002 and the RAM 1003. The processor 1001 may also execute the various operations of the method flow according to the embodiment of the present disclosure by executing the programs stored in the one or more memories.

[0189] According to an embodiment of the present disclosure, the controller 450 may further include an input / output (I / O) interface 1005, which is also connected to the bus 1004. The controller 450 may further include one or more of the following components connected to the I / O interface 1005: an input section 1006 including a keyboard, a mouse, etc.; an output section 1007 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and a speaker; a storage section 1008 including a hard disk; and a communication section 1009 including a network interface card such as a LAN card or a modem. The communication section 1009 performs communication processing via a network such as the Internet. A drive 1010 is also connected to the I / O interface 1005 as needed. A removable medium 1011, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed in the drive 1010 as needed, so that computer programs read therefrom can be installed into the storage section 1008 as needed.

[0190] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments, or may exist independently and not be incorporated into the device / apparatus / system. The computer-readable storage medium carries one or more programs, and when executed, implements the method according to the embodiments of the present disclosure.

[0191] According to an embodiment of the present disclosure, a computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, it may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, apparatus, or device. For example, according to an embodiment of the present disclosure, a computer-readable storage medium may include the ROM 1002 and / or RAM 1003 described above and / or one or more memories other than ROM 1002 and RAM 1003.

[0192] It should be noted that in the above embodiments, the calibration method is described using a static CT scanning imaging device with a distributed radiation source as an example. However, the embodiments of the present disclosure are not limited thereto. In other exemplary embodiments of the present disclosure, the calibration system and calibration method can also perform energy spectrum calibration on a spiral CT device with a single target radiation source. During the calibration process, the radiation source and detector are in a static state.

[0193] It should also be noted that the embodiments of the present disclosure can also perform energy spectrum calibration on single / multi-view X-ray imaging devices. For example, in some embodiments, the number of target points of the ray source can be N s =1. Although the single / multi-view X-ray imaging device itself is not a CT device and cannot perform CT imaging of the scanned object, when a single target point emits a beam, the data collected by the rotation of the calibration device meets the data completeness requirements of CT imaging and can also be used for CT reconstruction, and is therefore also applicable to the energy spectrum calibration process described above.

[0194] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computer 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 computing device, partially on the user device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect via the Internet).

[0195] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the above-mentioned module, program segment, or a part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0196] Throughout this specification, reference to terms such as "one embodiment," "some embodiments," "illustrative embodiments," "examples," "specific examples," or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0197] Although embodiments of the present disclosure have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations may be made to these embodiments without departing from the principles and purpose of the present disclosure, and that the scope of the present disclosure is defined by the claims and their equivalents. It will be understood by those skilled in the art that the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in the present disclosure. In particular, the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in various ways, without departing from the spirit and teachings of the present disclosure. All of these combinations and / or combinations fall within the scope of the present disclosure.

Claims

1. A calibration method for energy spectrum calibration of a scanning imaging device, the scanning imaging device including a radiation source for emitting radiation and a detector for receiving radiation. During the calibration process, an energy spectrum calibration phantom is located in the scanning area formed by the radiation, wherein, The calibration method includes: When the energy spectrum calibration phantom is located in the scanning area formed by the rays, according to the relative positions among the ray source, the energy spectrum calibration phantom, and the detector, obtain the geometric relationship among the ray source, the energy spectrum calibration phantom, and the detector; Collect the rays passing through the scanning area by the detector to obtain actual projection data; Obtain the physical properties of the energy spectrum calibration phantom, where the physical properties are pre-determined according to the constituent materials of the energy spectrum calibration phantom; Based on the physical properties of the energy spectrum calibration phantom and the geometric relationship, calculate theoretical projection data using a predetermined number of basic energy spectra; Calibrate the energy spectrum parameters according to the theoretical projection data and the actual projection data to obtain optimized energy spectrum parameters; and Determine the optimized energy spectrum parameters as the energy spectrum calibration parameters.

2. A calibration method for energy spectrum calibration of a scanning imaging device, the scanning imaging device including a radiation source for emitting radiation and a detector for receiving radiation. During calibration, an energy spectrum calibration phantom is located in the scanning area formed by the radiation, wherein, The calibration method includes: When the energy spectrum calibration phantom is located in the scanning area formed by the rays, according to the relative positions among the ray source, the energy spectrum calibration phantom, and the detector, obtain the geometric relationship among the ray source, the energy spectrum calibration phantom, and the detector; Collect the rays passing through the scanning area by the detector to obtain actual projection data; Execute a loop process until a preset condition is met. The first loop process includes: According to the energy spectrum information, perform image reconstruction on the energy spectrum calibration phantom, and obtain the physical properties of the energy spectrum calibration phantom according to the result of the image reconstruction; Based on the physical properties of the energy spectrum calibration phantom and the geometric relationship, calculate theoretical projection data using a predetermined number of basic energy spectra; Calibrate the energy spectrum parameters according to the theoretical projection data and the actual projection data to obtain optimized energy spectrum parameters; and Obtain energy spectrum information based on the optimized energy spectrum parameters; and Determine the optimized energy spectrum parameters obtained in the last time of the first loop process as the energy spectrum calibration parameters.

3. The method according to claim 1 or 2, wherein The step of calibrating the energy spectrum parameters according to the theoretical projection data and the actual projection data to obtain optimized energy spectrum parameters includes: Construct an optimization function of the deviation between the theoretical projection data and the actual projection data with respect to the energy spectrum parameters; and Calibrate the energy spectrum parameters according to the optimization function to obtain optimized energy spectrum parameters.

4. The method according to any one of claims 1-3, wherein, The method further includes: before placing the energy spectrum calibration phantom in the scanning area formed by the rays, control the ray source to emit rays and collect the air data of the detector; The step of collecting the rays passing through the scanning area by the detector to obtain actual projection data includes: When the energy spectrum calibration phantom is located in the scanning area formed by the rays, control the ray source to emit rays, and the detector collects the rays passing through the scanning area to obtain initial projection data; and Use the air data to correct the initial projection data by a first correction method to obtain first-corrected projection data.

5. The method according to claim 4, wherein, The step of collecting the rays passing through the scanning area by the detector to obtain actual projection data further includes: Using the air data, the initial projection data is corrected by a second correction method to obtain second corrected projection data. Wherein, the second correction method is different from the first correction method.

6. The method according to any one of claims 1-5, wherein, The step of collecting, by the detector, rays passing through the scanning area to obtain actual projection data further includes: Classify the first corrected projection data according to a predetermined classification criterion to obtain projection data of N c categories of projection data, and use the projection data of the j-th category as the actual projection data Among them, the projection data of the j-th category is a kind of projection data among the N c categories, N c is a positive integer greater than or equal to 1, and 1 ≤ j ≤ N c ; the predetermined classification criterion is determined based on the factors affecting the absorption energy spectrum of the detector.

7. The method according to claim 5 or 6, wherein The step of performing image reconstruction on the energy spectrum calibration phantom according to the energy spectrum information includes: Performing image reconstruction on the energy spectrum calibration phantom based on the second corrected projection data according to the energy spectrum information.

8. The method according to any one of claims 1-5, wherein The step of calculating theoretical projection data using a predetermined number of basic energy spectra based on the physical properties and geometric relationship of the energy spectrum calibration phantom includes: Select N e basic energy spectra {S k (E)}, where N e is a positive integer greater than or equal to 2; and For each of the N in sequence e basic energy spectra {S k (E)}, based on the physical properties of the calibration phantom and the geometric relationship, calculate N e theoretical projection data.

9. The method according to claim 8, wherein The optimization function includes the following functions: Among them, sprj k is the k-th theoretical projection data calculated using the k-th basis energy spectrum, aprj is the actual projection data, where 1 ≤ k ≤ N e , c k is the weight coefficient of the k-th theoretical projection data.

10. The method according to claim 6, wherein, The step of calculating theoretical projection data using a predetermined number of basic energy spectra based on the physical properties and geometric relationship of the energy spectrum calibration phantom includes: For each of the N c categories of projection data, perform a second loop process, where the second loop process includes: For the projection data of the j-th category, select N e basic energy spectra {S k (E)}; and For N in sequence e basic energy spectra {S k (E)}, based on the physical properties of the calibration phantom and the geometric relationship, calculate N e theoretical projection data corresponding to the projection data of the j-th category.

11. The method according to claim 10, wherein, The optimization function includes the following functions: Among them, sprj j，k is the k-th theoretical projection data corresponding to the projection data of the j-th category calculated using the k-th basis energy spectrum, and aprj j is the actual projection data of the j-th category, where 1 ≤ k ≤ N e , and c k is the weight coefficient of the k-th theoretical projection data.

12. The method according to claim 9 or 11, wherein The step of calibrating energy spectrum parameters according to the optimization function to obtain optimized energy spectrum parameters specifically includes: By solving the above optimization function, calculate N when the deviation value is at its minimum e optimized weight coefficients, and use the N e optimized weight coefficients as the optimized energy spectrum parameters.

13. The method according to claim 12, wherein, The step of obtaining energy spectrum information based on the optimized energy spectrum parameters specifically includes: According to the N e optimized weight coefficients and the N e basic energy spectra, the energy spectrum information is calculated by weighted summation.

14. The method according to any one of claims 1 to 13, wherein, The energy spectrum calibration phantom includes a plurality of parts respectively composed of a variety of materials, and at least one of the following properties of any two of the variety of materials is different: density, atomic number.

15. The method according to any one of claims 1-14, wherein, The calibration system includes a turntable, and the energy spectrum calibration phantom is located on the turntable; The step of collecting, by the detector, rays passing through the scanning area to obtain detector data includes: Controlling the ray source to emit rays; Controlling the turntable to rotate to drive the energy spectrum calibration phantom to rotate m circles, where m is a positive integer greater than or equal to 1; and During the process of the energy spectrum calibration phantom rotating m circles, the detector collects rays emitted from the ray source and passing through the scanning area.

16. The method according to any one of claims 1-15, wherein, The calibration system includes a lifting table, and the energy spectrum calibration phantom is located on the lifting table; The step of collecting, by the detector, rays passing through the scanning area to obtain detector data includes: Controlling the ray source to emit rays; Controlling the lifting table to lift and lower to drive the energy spectrum calibration phantom to lift and lower.

17. The method according to any one of claims 1-16, wherein, The ray source includes N s target points, and the N s target points are spaced apart along a first direction, where N s is a positive integer greater than or equal to 2; The step of collecting, by the detector, rays passing through the scanning area to obtain detector data includes: Control the N s targets to emit rays in a set order; and During the process in which the N s targets emit rays in a set order, the detector collects the rays emitted from the ray source and passing through the scanning area.

18. The method according to any one of claims 1-13, wherein The calibration system includes a rotary table, and the energy spectrum calibration phantom is located on the rotary table; the radiation source includes N s target points, and the N s target points are spaced apart along a first direction, where N s is a positive integer greater than or equal to 2; The step of collecting, by the detector, rays passing through the scanning area to obtain detector data includes: Control the N s targets to emit rays in a set order; Controlling the turntable to rotate to drive the energy spectrum calibration phantom to rotate m circles, where m is a positive integer greater than or equal to 1; and During the process that the N s targets emit rays in a set order and the energy spectrum calibration phantom rotates m circles, the detector collects the rays emitted from the ray source and passing through the scanning area.

19. The method according to claim 2, wherein The preset conditions include at least one of the following conditions: During the first cycle, the deviation between the energy spectrum information obtained twice adjacent times is less than a preset threshold; and During the first cycle, the number of iterations reaches a preset number of times.

20. The method according to claim 6, wherein The factors affecting the absorption energy spectrum of the detector include at least one of the following factors: The exit angle of the rays; The incident angle of the rays incident on the detector; The energy spectrum distribution of the target point of the ray source; and The occlusion situation in the path of the rays from the ray source to the detector.

21. A calibration system for energy spectrum calibration of a scanning imaging device, wherein, The calibration system includes: The main body of the calibration device; The energy spectrum calibration phantom arranged on the main body of the calibration device; The driving member, and the driving member is used to drive the energy spectrum calibration phantom to move; and A controller configured to perform energy spectrum calibration on a scanning imaging device according to the calibration method as recited in any one of claims 1-20.

22. A calibration system for energy spectrum calibration of a scanning imaging device, wherein, The calibration system includes: A base; A turntable connected to the base; An energy spectrum calibration phantom disposed on the turntable, the energy spectrum calibration phantom being located on the turntable; and A driving member configured to drive the turntable to rotate so as to drive the energy spectrum calibration phantom to rotate, wherein the energy spectrum calibration phantom includes a plurality of parts made of a plurality of materials respectively, and at least one of the following properties of any two of the plurality of materials is different: density, atomic number.

23. The system according to claim 22, wherein The calibration system further includes: a lifting table connected to the base, and the turntable is disposed on the lifting table.

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