WO2025140050A1 - Calibration method and calibration system for calibrating scanning imaging device - Google Patents

Abstract

Provided is a calibration method for calibrating a scanning imaging device, comprising: when a geometric calibration phantom is located in a scanning area formed by rays, executing a geometric calibration step, which comprises: collecting rays that pass through the scanning area by means of a detector to obtain detector data; performing calibration on a ray source parameter and a detector parameter by utilizing the detector data, so as to obtain an optimized ray source parameter and an optimized detector parameter, and determining the optimized ray source parameter and the optimized detector parameter as geometric calibration parameters; and when an energy spectrum calibration phantom is located in a scanning area formed by rays, executing an energy spectrum calibration step, which comprises: collecting rays that pass through the scanning area by means of the detector, and obtaining real projection data related to the energy spectrum phantom; and performing calibration on an energy spectrum parameter according to a geometric relationship and a physical attribute of the energy spectrum calibration phantom by utilizing the actual projection data, so as to obtain an optimized energy spectrum parameter, and determining the optimized energy spectrum parameter as an energy spectrum calibration parameter.

Description

Calibration method and system for calibrating scanning imaging equipment

This application claims priority to Chinese Patent Application No. 202311864101.9 filed on December 29, 2023, the contents of which are incorporated herein by reference.

Technical Field

The present disclosure relates to the field of scanning imaging technology, and more specifically, to a calibration method and a calibration system for calibrating a scanning imaging device.

Background Art

According to scanning imaging theory, if you want to accurately reconstruct the image of the scanned object, you must know the precise position of the ray source target and the detector crystal. Due to errors in mechanical manufacturing and installation, geometric calibration becomes an indispensable step in scanning imaging. In addition, when the ray is emitted from the ray source, it passes through the scanned object and then incidents on the detector. During this process, the attenuation of the ray conforms to Beer's law. Beer's law, also known as the Beer-Lambert law, is a basic law that describes the absorption of light by matter. When a beam of parallel monochromatic light passes vertically through a uniform non-scattering absorbing substance, its absorbance is proportional to the concentration of the absorbing substance and the thickness of the absorbing layer.

For example, taking static CT scanning imaging technology as an example, according to CT imaging theory, if the scanned object is to be accurately reconstructed by CT, the precise position of the ray source target and the detector crystal must be known. Due to the errors in mechanical manufacturing and installation, geometric calibration becomes an indispensable step in CT imaging. For static CT using distributed ray sources or multiple single-target ray sources, the manufacturing and installation errors will be correspondingly larger due to the large size or large number of ray sources themselves, which will have a greater impact on the imaging quality. Similarly, the detector will also have the same problem, and the geometric error needs to be corrected through geometric correction. 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 detector used for scanning imaging is required to have the same absorption energy spectrum, so that the ray attenuation 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 into which the ray is incident. In the geometric arrangement of the single-target source probe centripetal, all rays are vertically incident on the crystal, the crystal thickness through which the ray passes is the same, and the absorption energy spectrum of the detector is the same. However, in static CT scanning imaging equipment, since a single crystal needs to receive rays from different targets, the rays from different targets have different incident angles and pass through different crystal thicknesses, resulting in different absorption energy spectra. Moreover, the energy spectra of different targets may also be different. Data inconsistency caused by inconsistent energy spectra is also an important factor affecting the accuracy of reconstruction values.

The above information disclosed in this section is only for understanding of the background of the technical concept of the present disclosure and therefore, the above information may contain information that does not constitute the relevant technology.

Summary of the invention

The embodiments of the present disclosure provide a calibration method and a calibration system for calibrating a scanning imaging device.

In one aspect, a calibration method for calibrating a scanning imaging device is provided, wherein the scanning imaging device includes a radiation source for emitting radiation and a detector for receiving radiation. During the calibration process, a geometric calibration phantom or an energy spectrum calibration phantom is located in a scanning area formed by the radiation. The calibration method includes:

In the case where the geometric calibration phantom is located in the scanning area formed by the rays, a geometric calibration step is performed, wherein the geometric calibration step includes: collecting rays passing through the scanning area by the detector to obtain detector data related to the geometric calibration phantom; using the detector data, calibrating ray source parameters and detector parameters to obtain optimized ray source parameters and optimized detector parameters, and determining the optimized ray source parameters and optimized detector parameters as geometric calibration parameters, wherein the ray source parameters are used to represent the position of the ray source in the calibration system, and the detector parameters are used to represent the position of the detector in the calibration system;

In a case where the energy spectrum calibration phantom is located in a scanning area formed by the radiation, determining the relative positions among the radiation source, the energy spectrum calibration phantom and the detector according to the geometric calibration parameters to obtain a geometric relationship among the radiation source, the energy spectrum calibration phantom and the detector; and

When the energy spectrum calibration phantom is located in the scanning area formed by the rays, the energy spectrum calibration step is performed, wherein the energy spectrum calibration step includes: collecting the rays passing through the scanning area through the detector to obtain actual projection data related to the energy spectrum phantom; using the actual projection data related to the energy spectrum phantom, according to the geometric relationship and the physical properties of the energy spectrum calibration phantom, calibrating the energy spectrum parameters to obtain optimized energy spectrum parameters, and determining the optimized energy spectrum parameters as energy spectrum calibration parameters.

In another aspect, a calibration method for calibrating a scanning imaging device is provided, wherein the scanning imaging device comprises a radiation source for emitting radiation and a detector for receiving radiation. During the calibration process, both a geometric calibration phantom and an energy spectrum calibration phantom are located in a scanning area formed by the radiation. The calibration method comprises:

In the case where both the geometric calibration phantom and the energy spectrum calibration phantom are located in the scanning area formed by the rays, a geometric calibration step and an energy spectrum calibration step are performed, wherein the performing of the geometric calibration step and the energy spectrum calibration step comprises:

Collecting rays passing through the scanning area by the detector to obtain detector data related to both the geometric calibration phantom and the energy spectrum calibration phantom;

Calibrate the ray source parameters and the detector parameters by using the detector data to obtain optimized ray source parameters and optimized detector parameters, and determine the optimized ray source parameters and optimized detector parameters as geometric calibration parameters, wherein the ray source parameters are used to represent the position of the ray source in the calibration system, and the detector parameters are used to represent the position of the detector in the calibration system;

Determining the relative positions of the ray source, the energy spectrum calibration phantom, and the detector according to the geometric calibration parameters to obtain a geometric relationship between the ray source, the energy spectrum calibration phantom, and the detector; and

The detector data is used to calibrate the energy spectrum parameters according to the geometric relationship and the physical properties of the energy spectrum calibration phantom to obtain optimized energy spectrum parameters, and the optimized energy spectrum parameters are determined as energy spectrum calibration parameters.

According to some exemplary embodiments, the detector data includes an actual projection position of the ray on the detector after the ray passes through a geometric calibration phantom in the scanning area;

The calibrating of the ray source parameters and the detector parameters to obtain optimized ray source parameters and optimized detector parameters, and determining the optimized ray source parameters and optimized detector parameters as geometric calibration parameters, specifically includes: obtaining initial ray source parameters and initial detector parameters, wherein the ray source parameters are used to represent the position of the ray source in the calibration system, and the detector parameters are used to represent the position of the detector in the calibration system; obtaining the theoretical projection position of the geometric calibration phantom on the detector through geometric calculation according to the initial ray source parameters, the initial detector parameters and the positional relationship of the geometric calibration phantom relative to the ray source and the detector; calibrating the ray source parameters and the detector parameters according to the actual projection position and the theoretical projection position to obtain optimized ray source parameters and optimized detector parameters; and determining the optimized ray source parameters and optimized detector parameters as geometric calibration parameters.

According to some exemplary embodiments, the ray source parameters and the detector parameters are calibrated according to the actual projection position and the theoretical projection position to obtain optimized ray source parameters and optimized detector parameters, including: constructing an optimization function of the deviation between the actual projection position and the theoretical projection position with respect to ray source parameters and detector parameters, in which the deviation is a dependent variable, and the ray source parameters and the detector parameters are independent variables.

According to some exemplary embodiments, the ray source parameters and the detector parameters are calibrated according to the actual projection position and the theoretical projection position to obtain optimized ray source parameters and optimized detector parameters, and also include: according to the optimization function, determining the ray source parameters and the detector parameters corresponding to the minimum value of the deviation as the optimized ray source parameters and the optimized detector parameters, and determining the optimized ray source parameters and the optimized detector parameters as geometric calibration parameters.

According to some exemplary embodiments, the ray source includes N _s target points, and the N _s target points are spaced apart along a first direction, wherein N _s is a positive integer greater than or equal to 2; the ray source parameters and the detector parameters are calibrated according to the actual projection position and the theoretical projection position to obtain optimized ray source parameters and optimized detector parameters, including: constructing an optimization function, the optimization function including a projection position constraint term and a target distance constraint term, wherein the projection position constraint term is a first function of the deviation between the actual projection position and the theoretical projection position with respect to the ray source parameters and the detector parameters; the target distance constraint term is a second function of the deviation between the actual distance and the theoretical distance between two adjacent target points with respect to the ray source parameters and the detector parameters.

According to some exemplary embodiments, in the optimization function, the projection position constraint term has a first weight value, and the target point distance constraint term has a second weight value.

According to some exemplary embodiments, the ray source parameters and the detector parameters are calibrated according to the actual projection position and the theoretical projection position to obtain optimized ray source parameters and optimized detector parameters, and also include: according to the optimization function, determining the ray source parameters and the detector parameters corresponding to the minimum value of the weighted sum of the deviation between the actual projection position and the theoretical projection position and the deviation between the actual distance and the theoretical distance between two adjacent target points as the optimized ray source parameters and the optimized detector parameters, and determining the optimized ray source parameters and the optimized detector parameters as geometric calibration parameters.

According to some exemplary embodiments, the energy spectrum parameters are calibrated according to the geometric relationship and the physical properties of the energy spectrum calibration phantom to obtain optimized energy spectrum parameters, and the optimized energy spectrum parameters are determined as energy spectrum calibration parameters, specifically including: obtaining the physical properties of the energy spectrum calibration phantom, wherein the physical properties are predetermined based on the constituent materials of the energy spectrum calibration phantom; calculating theoretical projection data using a predetermined plurality of basic energy spectra based on the physical properties of the energy spectrum calibration phantom and the geometric relationship; calibrating the energy spectrum parameters according to the theoretical projection data and the actual projection data to obtain optimized energy spectrum parameters; and determining the optimized energy spectrum parameters as energy spectrum calibration parameters.

According to some exemplary embodiments, the calibrating the energy spectrum parameters according to the geometric relationship and the physical properties of the energy spectrum calibration phantom to obtain optimized energy spectrum parameters, and determining the optimized energy spectrum parameters as energy spectrum calibration parameters specifically includes:

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

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;

Based on the physical properties of the energy spectrum calibration phantom and the geometric relationship, using a predetermined plurality of basic energy spectra to calculate theoretical projection data;

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

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

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

According to some exemplary embodiments, the calibrating the energy spectrum parameters according to 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 according to the optimization function to obtain optimized energy spectrum parameters.

According to some exemplary embodiments, the geometric calibration phantom includes at least one metal wire; or, the geometric calibration phantom includes a plurality of metal wires, and the plurality of metal wires are distributed on the rotating table with different radii and/or different angles from each other.

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

According to some exemplary embodiments, the calibration system includes a rotating table, and at least one of the geometric calibration phantom and the energy spectrum calibration phantom is located on the rotating table; 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 rotating table to rotate to drive at least one of the geometric calibration phantom and the energy spectrum calibration phantom to rotate m times, wherein m is a positive integer greater than or equal to 1; and during the process of at least one of the geometric calibration phantom and the energy spectrum calibration phantom rotating m times, the detector collects the rays emitted from the ray source and passing through the scanning area.

According to some exemplary embodiments, the calibration system includes a lifting platform, and at least one of the geometric calibration phantom 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; and controlling the lifting platform to rise and fall, so as to drive at least one of the geometric calibration phantom and the energy spectrum calibration phantom to rise and fall.

According to some exemplary embodiments, the ray source includes N _s target points, and the N _s target points are spaced apart along a first direction, wherein N _s is a positive integer greater than or equal to 2; the collecting of rays passing through the scanning area by the detector to obtain detector data includes: controlling the N _s target points to emit rays in a set order; and in the process of the N _s target points emitting rays in the set order, the detector collecting rays emitted from the ray source and passing through the scanning area.

According to some exemplary embodiments, the calibration system includes a rotating table, and at least one of the geometric calibration phantom and the energy spectrum calibration phantom is located on the rotating table; the radiation source includes _Ns target points, and the _Ns target points are spaced along a first direction, wherein _Ns is a positive integer greater than or equal to 2; the detector collects the rays passing through the scanning area to obtain the detector data, comprising: controlling the _Ns target points to emit rays in a set order; controlling the rotating table to rotate so as to drive at least one of the geometric calibration phantom and the energy spectrum calibration phantom to rotate m times, wherein m is a positive integer greater than or equal to 1; and in the process of the _Ns target points emitting rays in a set order and at least one of the geometric calibration phantom and the energy spectrum calibration phantom rotating m times, the detector collects the rays emitted from the radiation source and passing through the scanning area.

According to some exemplary embodiments, before determining the relative positions among the ray source, the energy spectrum calibration phantom and the detector, the method further comprises: calibrating the relative position of a calibration device body carrying the energy spectrum calibration phantom relative to the ray source and the detector.

According to some exemplary embodiments, the calibrating the energy spectrum parameters according to the geometric relationship and the physical properties of the energy spectrum calibration phantom to obtain optimized energy spectrum parameters, and determining the optimized energy spectrum parameters as energy spectrum calibration parameters specifically includes:

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

According to the energy spectrum information, image reconstruction is performed on the geometric calibration phantom and the energy spectrum calibration phantom to obtain a first reconstructed image; segmentation is performed on the first reconstructed image to segment the geometric calibration phantom and the energy spectrum calibration phantom to obtain a second reconstructed image; and physical properties of the energy spectrum calibration phantom are obtained according to the second reconstructed image;

Based on the physical properties of the energy spectrum calibration phantom and the geometric relationship, using a predetermined plurality of basic energy spectra to calculate theoretical projection data;

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

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

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

On the other hand, a calibration system for calibrating a scanning imaging device is provided, wherein the calibration system comprises: a calibration device body; at least one of a geometric calibration phantom and an energy spectrum calibration phantom disposed on the calibration device body; a driving member, the driving member being used to drive at least one of the geometric calibration phantom and the energy spectrum calibration phantom to move; and a controller, the controller being configured to calibrate the scanning imaging device according to the calibration method as described above.

On the other hand, a calibration system for calibrating a scanning imaging device is provided, wherein the calibration system comprises: a base; a rotating table connected to the base; at least one of a geometric calibration phantom and an energy spectrum calibration phantom disposed on the rotating table, and at least one of the geometric calibration phantom 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 so as to drive at least one of the geometric calibration phantom and the energy spectrum calibration phantom to rotate, wherein the geometric calibration phantom comprises at least one metal wire; or, the geometric calibration phantom comprises a plurality of metal wires, and the plurality of metal wires are distributed on the rotating table with different radii and/or different angles from each other; and/or, the energy spectrum calibration phantom comprises a plurality of parts respectively composed of a plurality of materials, and at least one of the following properties of any two of the plurality of materials is different: density, atomic number.

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

Additional aspects and advantages of the present disclosure will be given in part in the following description and in part will be obvious from the following description or will be learned through practice of the present disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

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:

FIG1 schematically shows a schematic diagram of the projection relationship between a ray source, a scanned object and a detector.

FIG. 2 is a schematic structural diagram of a static CT device according to some exemplary embodiments of the present disclosure.

FIG. 3A is a schematic structural diagram of a scanning stage included in a static CT device according to some exemplary embodiments of the present disclosure.

FIG. 3B is a schematic structural diagram of a scanning stage included in a static CT device according to other exemplary embodiments of the present disclosure.

FIG. 4A is a schematic diagram of the structure of a calibration system according to some exemplary embodiments of the present disclosure.

FIG. 4B is a schematic structural diagram of a calibration system according to some exemplary embodiments of the present disclosure, viewed from another angle.

FIG. 4C is a schematic diagram of the structure of a calibration system according to some exemplary embodiments of the present disclosure, which schematically shows a metal wire.

4D is a side view of the calibration system shown in FIG. 4C .

FIG. 4E is a schematic diagram of the structure of a calibration system according to some exemplary embodiments of the present disclosure, which schematically shows a plurality of metal wires.

FIG. 4F is a projection diagram of the four metal wires shown in FIG. 4E on the rotating stage.

FIG. 5 is a flow chart of a calibration method according to some exemplary embodiments of the present disclosure.

FIG. 6 is a flowchart of a calibration method according to some other exemplary embodiments of the present disclosure.

FIG. 7 is a flowchart of a geometric calibration step in a calibration method according to some exemplary embodiments of the present disclosure.

FIG8A is an exemplary flowchart of obtaining optimized ray source parameters and optimized detector parameters in a geometric calibration step in a calibration method according to some exemplary embodiments of the present disclosure.

FIG8B is an exemplary flowchart of obtaining optimized ray source parameters and optimized detector parameters in a geometric calibration step in a calibration method according to other exemplary embodiments of the present disclosure.

FIG. 9 is a flow chart of an energy spectrum calibration step in a calibration method according to some exemplary embodiments of the present disclosure.

FIG. 10 is a flow chart of energy spectrum calibration steps in a calibration method according to other exemplary embodiments of the present disclosure.

FIG. 11 is an exemplary flowchart of obtaining optimized energy spectrum parameters in a calibration method according to some exemplary embodiments of the present disclosure.

FIG. 12 schematically shows a structural block diagram of a controller of a calibration system according to an exemplary embodiment of the present disclosure.

DETAILED DESCRIPTION

Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present 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 in the present disclosure and the technical features in the embodiments can be combined with each other in any manner.

The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. In addition, the terms "including", "comprising", 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 (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having meanings consistent with the context of this specification, and should not be interpreted in an idealized or overly rigid manner.

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" and the like indicate orientations or positional relationships 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 the features. In the description of the present disclosure, unless otherwise specified, "multiple" means two or more.

In the description of the present disclosure, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present disclosure can be understood according to specific circumstances.

In the present specification, computed tomography (CT) imaging refers to the use of radiation to perform a cross-sectional scan of the object to be detected. The analog signal received by the detector is converted into a digital signal, and the attenuation coefficient of each pixel is calculated by an electronic computer. The image is then reconstructed to display the cross-sectional structure of each part of the object to be detected.

FIG1 schematically shows a schematic diagram of the projection relationship between a ray source, a scanned object, 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 scanned object OB, and rays transmitted through the scanned object OB are detected by a detector D. A spatial point X on the scanned object OB is acted upon by the ray source S to an image point Y on the detector D. In a forward projection (also called a forward projection), the pixel value of a spatial point on the scanned object OB is known, and the projection value of the image point on the detector D is obtained. In a reverse projection (also called a backward projection), the projection value of an image point on the detector D is known, and the pixel value of a spatial point on the scanned object OB is obtained.

Computer tomography technology plays an important role in security inspection, medical field and other occasions because it can eliminate the influence of overlapping objects. Traditional CT uses slip ring device to obtain projection data at different angles through the rotation of X-ray source and detector, and obtains tomographic images through reconstruction method, so as to obtain internal information of the detected luggage items. Traditional CT devices usually use slip ring rotation in the data acquisition process, which not only has limited scanning speed and large volume, but also requires high machining precision and high cost, which limits its wide application in practice. In recent years, carbon nanotube X-ray tube technology has entered the practical field. Unlike traditional ray sources, it does not need to use high temperature to generate rays, but generates cathode rays based on the principle of discharge at the tip of carbon nanotubes, and generates X-rays by hitting the target. Its advantages are that it can be turned on and off quickly and has a smaller size. By arranging this X-ray source in a ring shape and irradiating objects at different angles, a "static CT" that does not need to rotate can be made, which greatly improves the speed of ray imaging. At the same time, since the slip ring structure is omitted, the cost is saved, which is of great significance for security inspection and other fields.

Fig. 2 is a schematic diagram of the structure of a static CT device according to some exemplary embodiments of the present disclosure. Referring to Fig. 2, 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 ray source, a detector and a collection device.

For example, in an embodiment of the present disclosure, the ray source may be a distributed ray source, and the distributed ray source 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, and 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 using fewer cathode components to generate more X-ray radiation sources, improves the stability of the system, reduces the number of cathode components used, and reduces the production cost of the equipment.

In static CT devices that utilize distributed ray sources, multiple projection data sets can be acquired from various angles by combining multiple targets together and activating them in a set order at different 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, which can provide more projection angles and data, reduce artifacts in the reconstructed image, and provide 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 form helps to obtain high-quality projection data for the reconstruction of static CT images.

In the embodiments of the present disclosure, multiple target points in the distributed ray source may be arranged along a predetermined first direction. For example, the predetermined first direction may be a straight line direction, or may be an arc direction. The embodiments of the present disclosure do not impose any particular restrictions on the arrangement of the target points in the distributed ray source.

FIG. 3A 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. FIG. 3B is a schematic diagram of the structure of a scanning stage included in a static CT device according to some other exemplary embodiments of the present disclosure. Referring to FIG. 3A and FIG. 3B, in an embodiment of the present disclosure, the static CT device includes a distributed ray source 20 and a detector 30, and the distributed ray source 20 may include a plurality of targets 210. In some embodiments, as shown in FIG. 3A, the plurality of targets 210 may be arranged in an arc shape, and accordingly, the detector 30 may include a plurality of detection units 310 arranged in an arc shape or a circle. In some embodiments, as shown in FIG. 3B, the plurality of targets 210 may be arranged along a straight line, and accordingly, the detector 30 may include a plurality of detection units 310 arranged along a straight line. It should be noted that in the embodiments of FIG. 2 to FIG. 3B, only schematic diagrams of the structure of a static CT device according to some exemplary embodiments of the present disclosure are schematically shown, rather than all embodiments of the present disclosure. In an embodiment of the present disclosure, any appropriately arranged distributed ray source and detector may be used.

In the embodiment of the present disclosure, the multiple target points 210 respectively emit radiation toward the scanned object 120, and the multiple detection units 310 are used to detect the radiation passing through the scanned object 120. For example, in the embodiment shown in FIG. 3A and FIG. 3B, the multiple target points 210 emit X-rays, and the multiple detection units 310 receive part of the X-rays emitted from the multiple target points 210 and passing through the scanned object 120. In this way, a scanning area for scanning the scanned object 120 is formed between the ray source 20 and the detector 30. In the scanning area, at least one plane located in the approximate middle position of the scanning area and perpendicular to the conveying direction of the conveying mechanism 110 can be called a scanning plane.

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 a plurality of detector crystals, and the plurality of detector crystals may be arranged along a one-dimensional direction, or the plurality of detector crystals may be arranged along a two-dimensional direction.

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 material of the detector crystal can include oxides and halides (such as iodides and fluorides), etc.

For example, in the embodiment shown in FIG2 , the transport mechanism 110 carries the scanned object 120 and drives the scanned object 120 to move in a straight line. The control device 140 controls the beam-emission sequence of the multiple target points 210 of the ray source 20, so that the detector 30 outputs a digital signal corresponding to the projection data. The imaging device 130 reconstructs a CT image of the scanned object 120 based on the digital signal.

It should be noted that in the embodiments of the present disclosure, the imaging device 130 may use various known reconstruction algorithms to reconstruct the CT image of the scanned object. For example, the reconstruction algorithm may be an iterative, analytical or other reconstruction algorithm, and the embodiments of the present disclosure do not specifically limit the reconstruction algorithm.

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 one or more continuous or discontinuous straight lines or arcs. Since the target energy can be set, a variety of scanning methods 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 the targets in the same group is adjustable, 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.

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.

The transmission mechanism 110 includes a stage or a transmission belt, and the control device 140 controls the X-ray machine and the detector frame. By controlling the beam emission mode of the distributed radiation source and the linear translation movement of the scanned object or a combination of the two, a spiral scanning track or a circular scanning track or other special tracks can be scanned. The control device 140 is responsible for completing the control of the CT system operation process, including mechanical rotation, electrical control, and safety interlock control, especially responsible for controlling the beam emission speed/frequency, beam emission energy, and beam emission sequence of the radiation source, and controlling the data reading and data reconstruction of the detector.

Static CT has gradually become a research hotspot in the field of CT due to its advantages such as high scanning speed, high stability and flexible scanning methods. However, as a new technical route, it has different requirements from the original spiral CT in many data processing methods. For example, due to the geometric correction caused by multiple targets, the spiral CT processing method cannot be used.

According to CT imaging theory, if you want to accurately reconstruct the scanned object, you must know the precise position of the radiation source target and the detector crystal. Since there are errors in mechanical manufacturing and installation, geometric calibration becomes an essential step in CT imaging. For static CT using distributed radiation sources or multiple single-target radiation sources, the radiation sources themselves are larger in size or more in number, so the manufacturing and installation errors will be correspondingly larger, which will have a greater impact on the imaging quality. Similarly, the detector will have the same problem, and the geometric error also needs to be corrected through geometric correction.

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 into which the rays are incident. In the geometric arrangement of a single target source probe centripetal, all rays are vertically incident 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 by different targets, the incident angles of rays from different targets are different, and the crystal thicknesses passed 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.

Furthermore, the inventors have also found that when different ray sources are installed, there are differences in the horizontal plane and the height direction, which will affect the clarity of the CT reconstructed image. Since the rays emitted by the ray source have a spatial distribution of energy spectra related to the direction, and the incident angles of the rays on each detector unit are also different, the energy spectra of different rays are different. During the reconstruction process, the energy spectrum error will interfere with the reconstructed values.

In addition, the above-mentioned technical problems 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.

The embodiments of the present disclosure provide a calibration method and a calibration system for calibrating a scanning imaging device, which can perform geometric calibration and energy spectrum calibration on the scanning imaging device, for example, can perform geometric calibration and energy spectrum calibration on a static CT device based on a distributed ray source.

FIG. 4A is a schematic diagram of the structure of a calibration system according to some exemplary embodiments of the present disclosure. FIG. 4B is a schematic diagram of the structure of a calibration system according to some exemplary embodiments of the present disclosure observed from another angle. FIG. 4C is a schematic diagram of the structure of a calibration system according to some exemplary embodiments of the present disclosure, schematically showing a metal wire. FIG. 4D is a side view of the calibration system shown in FIG. 4C. FIG. 4E is a schematic diagram of the structure of a calibration system according to some exemplary embodiments of the present disclosure, schematically showing multiple metal wires.

4A and 4B , the calibration system 40 may include: a base 410; a rotating table 420 connected to the base 410; at least one of a geometric calibration phantom 50 and an energy spectrum calibration phantom 60 disposed on the rotating table 420; and a driving member 430, the driving member 430 being used to drive the rotating table 420 to rotate, so as to drive at least one of the geometric calibration phantom 50 and the energy spectrum calibration phantom 60 to rotate.

For example, in the embodiments shown in FIGS. 4A and 4B , both the geometric calibration phantom 50 and the energy spectrum calibration phantom 60 are disposed on the rotating table 420. In other embodiments of the present disclosure, one of the geometric calibration phantom 50 and the energy spectrum calibration phantom 60 may be disposed on the rotating table 420. For example, in the embodiments shown in FIGS. 4C to 4E , only the geometric calibration phantom 50 is disposed on the rotating table 420.

In some exemplary embodiments, the geometric calibration phantom 50 may include at least one metal wire. For example, the geometric calibration phantom 50 includes only one metal wire, and the one metal wire is located at an eccentric position of the rotating stage 420 .

4A and 4B , the rotating table 420 rotates around the rotation axis AX1. A metal wire is vertically arranged on the rotating table 420 and is offset from the rotation axis AX1. Due to the centrifugal arrangement of the geometric calibration phantom on the rotating table 420, the geometric calibration phantom can be in different geometric positions during the rotation of the rotating table 420, which is conducive to obtaining calibration data from multiple different geometric positions, thereby improving the accuracy of calibration.

4E , the rotating stage 420 rotates around the rotation axis AX1. The geometric calibration phantom 50 may include a plurality of metal wires, which are respectively located at different centrifugal positions of the rotating stage 420, that is, the plurality of metal wires are distributed on the rotating stage 420 at different radii and/or different angles. That is, on the rotating stage 420, at least one of the radius and angle of any one of the plurality of metal wires is different from at least one of the radius and angle of another of the plurality of metal wires.

For example, in the embodiment shown in Fig. 4E, four metal wires are schematically shown, which, for the convenience of description, are respectively labeled as a first metal wire 501, a second metal wire 502, a third metal wire 503, and a fourth metal wire 504. The first metal wire 501, the second metal wire 502, the third metal wire 503, and the fourth metal wire 504 are all vertically arranged on the rotating stage 420, and the offset distances from the rotating axis AX1 are _ρ1 , _ρ2 , _ρ3 , _ρ4 , respectively.

FIG4F is a projection diagram of the four metal wires shown in FIG4E on the rotating table. Referring to FIG4E and FIG4F, a polar coordinate system is established, in which the point of the orthographic projection of the rotation axis AX1 on the rotating table 420 is taken as the pole AXO, and a ray OX starting from the pole AXO is taken as the polar axis. On this basis, the positions of the four metal wires can be represented by (ρ, θ), wherein ρ corresponds to the polar diameter, vector radius or radius in the polar coordinate system, specifically the distance of the point of the orthographic projection of the metal wire on the rotating table relative to the pole AXO; θ corresponds to the polar angle or radian in the polar coordinate system, specifically the angle of the line connecting the point of the orthographic projection of the metal wire on the rotating table and the pole relative to the polar axis OX.

Exemplarily, the positions of the first metal wire 501, the second metal wire 502, the third metal wire 503 and the fourth metal wire 504 are respectively expressed as (ρ ₁ , θ ₁ ), (ρ ₂ , θ ₂ ), (ρ ₃ , θ ₃ ), (ρ ₄ , θ ₄ ). Any two of ρ ₁ , ρ ₂ , ρ ₃ , ρ ₄ are not equal, and/or any two of θ ₁ , θ ₂ , θ ₃ , θ ₄ are not equal.

In this embodiment, multiple metal wires are arranged on the rotating table 420 and have different offset distances or offset angles from the rotation axis AX1. In this way, during the rotation of the rotating table 420, the multiple metal wires can be in different geometric positions, which is conducive to obtaining calibration data from multiple different geometric positions, thereby further improving the calibration accuracy.

In some exemplary embodiments, the metal wire may be a hard metal wire, so that the metal wire may be perpendicular to the table surface of the rotating table 420 , which is beneficial for placing the front end of the metal wire in the scanning area.

In some exemplary embodiments, the diameter of the metal wire is no greater than the width of a single detector crystal. By designing the diameter of the metal wire to be smaller, the accuracy of calibration can be improved.

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.

In some exemplary embodiments, the energy spectrum calibration phantom 60 may include a plurality of parts respectively made of a plurality of materials, and at least one of the following properties of any two of the plurality of materials is different: density, atomic number.

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

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

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.

It should be noted that in the embodiments shown in FIG. 4A and FIG. 4B , the shape of the energy spectrum calibration phantom 60 is a rectangular parallelepiped, but this shape is only exemplary and is not a limitation to 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.

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

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

For example, the rotation drive mechanism for driving the rotating table 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 driving motor, a driving gear and a driven gear, and the rotational force transmission is realized by the meshing of the gears. The servo motor drive is to realize the rotation of the rotating table 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 realizes the rotation of the rotating table 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 rotating table.

For example, the mobile drive mechanism for driving the lifting platform 440 to move 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 meshing therewith. When the screw rotates, the nut moves along the spiral line of the screw, thereby realizing 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 to rotate by an electric motor, thereby pushing the lifting platform to move up and down. The gear drive mechanism uses the meshing of gears to transmit force and motion. By driving the rotation of the gear, the up and down movement of the lifting platform can be realized.

It should be noted that in the embodiments of the present disclosure, there is no particular restriction on the type and structure of the rotary drive mechanism and the mobile drive mechanism. In the absence of 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.

Some exemplary embodiments of the present disclosure also provide a calibration method for calibrating a scanning imaging device, which is suitable for performing geometric calibration and energy spectrum calibration on the scanning imaging device.

In the calibration method according to some embodiments of the present disclosure, geometric calibration may be performed first, and then energy spectrum calibration may be performed. FIG5 is a flow chart of a calibration method according to some exemplary embodiments of the present disclosure. In the calibration process of this embodiment, a geometric calibration phantom or an energy spectrum calibration phantom is located in the scanning area formed by the rays, that is, only one of the geometric calibration phantom and the energy spectrum calibration phantom is located in the scanning area. For example, the calibration method may include steps S510 to S530.

In step S510, when the geometric calibration phantom is located in the scanning area formed by the rays, a geometric calibration step is performed, wherein the geometric calibration step includes: collecting rays passing through the scanning area by the detector to obtain detector data related to the geometric calibration phantom; using the detector data, calibrating ray source parameters and detector parameters to obtain optimized ray source parameters and optimized detector parameters, and determining the optimized ray source parameters and optimized detector parameters as geometric calibration parameters, wherein the ray source parameters are used to represent the position of the ray source in the calibration system, and the detector parameters are used to represent the position of the detector in the calibration system.

In step S520, when the energy spectrum calibration phantom is located in the scanning area formed by the rays, the relative positions among the ray source, the energy spectrum calibration phantom and the detector are determined according to the geometric calibration parameters to obtain the geometric relationship among the ray source, the energy spectrum calibration phantom and the detector.

In step S530, when the energy spectrum calibration phantom is located in the scanning area formed by the rays, an energy spectrum calibration step is performed, wherein the energy spectrum calibration step includes: collecting the rays passing through the scanning area by the detector to obtain actual projection data related to the energy spectrum phantom; using the actual projection data related to the energy spectrum phantom, according to the geometric relationship and the physical properties of the energy spectrum calibration phantom, calibrating the energy spectrum parameters to obtain optimized energy spectrum parameters, and determining the optimized energy spectrum parameters as energy spectrum calibration parameters.

In the calibration method according to some other embodiments of the present disclosure, geometric calibration and energy spectrum calibration can be performed simultaneously. Figure 6 is a flow chart of the calibration method according to some exemplary embodiments of the present disclosure. In the calibration process of this embodiment, both the geometric calibration phantom and the energy spectrum calibration phantom are located in the scanning area formed by the rays. The calibration method includes: when both the geometric calibration phantom and the energy spectrum calibration phantom are located in the scanning area formed by the rays, performing a geometric calibration step and an energy spectrum calibration step. For example, the calibration method may specifically include steps S610 to S640.

In step S610, the detector collects rays passing through the scanning area to obtain detector data related to both the geometric calibration phantom and the energy spectrum calibration phantom.

In step S620, the detector data is used to calibrate the ray source parameters and the detector parameters to obtain optimized ray source parameters and optimized detector parameters, and the optimized ray source parameters and optimized detector parameters are determined as geometric calibration parameters, wherein the ray source parameters are used to represent the position of the ray source in the calibration system, and the detector parameters are used to represent the position of the detector in the calibration system.

In step S630, the relative positions among the ray source, the energy spectrum calibration phantom and the detector are determined according to the geometric calibration parameters to obtain the geometric relationship among the ray source, the energy spectrum calibration phantom and the detector.

In step S640, the energy spectrum parameters are calibrated using the detector data according to the geometric relationship and the physical properties of the energy spectrum calibration phantom to obtain optimized energy spectrum parameters, and the optimized energy spectrum parameters are determined as energy spectrum calibration parameters.

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

Below, firstly, a detailed implementation of the steps of performing geometric calibration is described in conjunction with the accompanying drawings.

FIG4D is a side view of the calibration system shown in FIG4C. Referring to FIG4A to FIG4D , when performing calibration, the calibration system 40 is placed on a conveying device (e.g., the conveying mechanism 110 shown in FIG2 ) of the scanning imaging device, and the conveying device is controlled to transport the geometric calibration phantom 50 of the calibration system 40 to the X-ray scanning plane, so that the geometric calibration phantom 50 is in the scanning plane formed by the ray source 20 and the detector 30. For example, when performing geometric calibration, only the front end of the geometric calibration phantom 50 is located in the scanning plane, and the other parts of the calibration system 40 are always outside the scanning plane. In this way, it is possible to avoid interference of other parts of the calibration system 40 with the calibration data.

FIG. 7 is a flow chart of the geometric calibration steps in the calibration method according to some exemplary embodiments of the present disclosure. With reference to FIGS. 1 to 7 , the calibration method can be used to perform geometric calibration on a scanning imaging device. For example, the calibration method can perform geometric 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 points 210, and the N _s target points are spaced apart along a first direction, wherein N _s is a positive integer greater than or equal to 2. The first direction can correspond to the straight line arrangement direction shown in FIG. 3A or the arc arrangement method shown in FIG. 3B. It should be noted that in the embodiments of the present disclosure, no special restrictions are imposed on the arrangement direction and form of the multiple target points of the distributed ray source.

In some embodiments of the present disclosure, the geometric calibration step of the calibration method may include sub-steps S710 to S750.

In sub-step S710, the detector 30 collects the rays passing through the scanning area to obtain detector data, wherein the detector data includes the actual projection position of the rays on the detector 30 after passing through the scanning area.

In some exemplary embodiments, the calibration method may include: before placing the geometric calibration phantom 50 in a scanning area or a scanning plane formed by rays, collecting air projection data p _air by the detector 30 .

It should be understood that when performing image reconstruction, it is necessary to know the detector reading in the absence of an object (i.e., only air) in order to remove this background value from the actual measured data. For example, in CT imaging, a method called line integral is often used to obtain projection data. This process involves passing rays through an 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 in the absence of an object, that is, only air. The projection data thus obtained can be used as a reference or background value, and in 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.

In sub-step S710, obtaining detector data includes: acquiring rays passing through a scanning area (where the geometric calibration phantom 50 is located) through the detector 30 to obtain initial detector data _pi ; and correcting the initial detector data _pi using air projection data p _air to obtain detector data prj _i .

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.

For example, the following formula may be used to perform air correction to obtain the detector data prj _i : prj _i = p _i / p _air .

In some exemplary embodiments of the present disclosure, the calibration system 40 includes a rotating stage 420 , and the geometric calibration phantom 50 is located on the rotating stage 420 .

In this embodiment, obtaining the initial detector data p _i may include: controlling the ray source 20 to emit rays; controlling the rotating table 420 to rotate to drive the geometric calibration phantom 50 to rotate m circles, where m is a positive integer greater than or equal to 1; and, during the process of the geometric calibration phantom 50 rotating m circles, the detector 30 collects rays emitted from the ray source 20 and passing through the scanning area.

In some exemplary embodiments of the present disclosure, the calibration system 40 includes a lifting platform 440 , and the geometric calibration phantom 50 is located on the lifting platform 440 .

In this embodiment, obtaining the initial detector data p _i 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 geometric calibration phantom 50 to move up and down.

For example, the geometric calibration phantom 50 may be driven to rise to the scanning position by the lifting and lowering motion of the lifting platform 440. During the lifting and lowering process, the detector may not collect data.

For another example, during the lifting process of the geometric calibration phantom 50, 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.

In some exemplary embodiments of the present disclosure, the ray source 20 includes N _s target points 210 , and the 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.

In this embodiment, obtaining the initial detector data _pi may include: controlling the _Ns target points 210 to emit radiation in a set order; and in the process of the _Ns target points 210 emitting radiation in the set order, the detector 30 collects radiation emitted from the radiation source 20 and passing through the scanning area.

In some exemplary embodiments of the present disclosure, the calibration system 40 includes a rotating table 420, and the geometric calibration phantom 50 is located on the rotating table 420. The radiation source 20 includes _Ns target points 210, and the _Ns target points 210 are spaced apart along the first direction, where _Ns is a positive integer greater than or equal to 2.

In this embodiment, obtaining the initial detector data p _i may include: controlling the N _s target points 210 to emit rays in a set order; controlling the rotating table 420 to rotate to drive the geometric calibration model 50 to rotate m circles, where m is a positive integer greater than or equal to 1; and in the process of the N _s target points 210 emitting rays in a set order and the geometric calibration model 50 rotating m circles, the detector 30 collects rays emitted from the ray source and passing through the scanning area.

It should be noted that in the embodiments of the present disclosure, there is no particular restriction on the movement form, setting number and target number of the geometric calibration phantom, and various situations can be combined and combined with each other without conflict. For example, in some embodiments, the geometric calibration phantom 50 can be set on a rotating table, the rotating table is set on a lifting table, and the ray source 20 can be a distributed ray source including multiple target points. In this way, the step of obtaining the detector data prj _i can be adjusted accordingly according to the setting mode, which will not be repeated here.

It should also be noted that in the embodiments of the present disclosure, the movement of the geometric calibration phantom 50 and the order of the beam emission of the radiation source may not be particularly limited. For example, the geometric calibration phantom 50 is fixed at one position, and all the targets are controlled to emit beams once in a set order, and then the rotating stage rotates to the next position, and all the targets are controlled to emit beams again, until the rotating stage rotates one circle and ends.

In sub-step S720 , initial ray source parameters and initial detector parameters are acquired, wherein the ray source parameters are used to indicate the position of the ray source 20 in the calibration system 40 , and the detector parameters are used to indicate the position of the detector 30 in the calibration system 40 .

The inventor has found through research that in a static CT scanning imaging device using a distributed radiation source, due to the large distance between the targets, especially the radiation source composed of multiple single targets, the error of each target is inconsistent. The detector crystals are densely arranged, and the error is relatively small. The error mainly comes from the installation of the entire detector arm. Therefore, the geometric calibration calibrates each target position separately, and the detector is calibrated according to the entire detector arm.

In this paper, for the convenience of description, the ray source parameters are described as s _i and the detector parameters are described as P _d .

In some exemplary embodiments, the ray source adopts a distributed ray source, the target point interval has a sufficiently high accuracy, and the error mainly comes from the overall installation of the ray source, then the target point 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 relative position relationship between two adjacent target points in the ray source is known, and the ray source parameter _si may include: the position coordinates of the first target point among the N _s target points in the calibration system, the arrangement direction of the N _s target points, and the number of each target point among the N _s target points.

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 a starting coordinate and an arrangement direction.

For example, referring to Fig. 4A to Fig. 4D, 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 relative positional relationship between two adjacent detection units is known, and the detector parameter _Pd may include: the position coordinates of the first detection unit among the plurality of detection units in the calibration system, and the arrangement direction of the plurality of detection units.

For another example, multiple detection units 310 are arranged in an arc on the detector arm, and the relative position relationship between two adjacent detection units is known. The detector parameter _Pd may include: the angle and radius of the first detection unit among the multiple detection units in the calibration system.

In sub-step S730, according to the initial ray source parameters, the initial detector parameters and the positional relationship of the geometric calibration phantom 50 relative to the ray source 20 and the detector 30, the theoretical projection position of the geometric calibration phantom 50 on the detector 30 is obtained by geometric calculation.

For example, the detector data prj _i obtained in sub-step S710 includes the actual projection position, that is, the actual projection position of the geometric calibration phantom 50 (such as a metal wire) can be extracted from the detector data prj _i , which can be described as pos(s _i , P _d ). It can be understood that the actual projection position is a function of the ray source parameters and the detector parameters.

For example, in sub-step S730, with the rotation center of the rotating stage 420 as the coordinate origin, according to the rotation speed of the rotating stage 420 and the position of the geometric calibration phantom 50, when the initial ray source parameter _si and the detector parameter _Pd are known, the theoretical projection position of the geometric calibration phantom 50 corresponding to the projection data prj _i can be obtained through geometric calculation, which is recorded as cpos( _si , _Pd ). It can be understood that the theoretical projection position cpos( _si , _Pd ) is also a function of the ray source parameter and the detector parameter.

In sub-step S740, the ray source parameters and the detector parameters are calibrated according to the actual projection position and the theoretical projection position to obtain optimized ray source parameters and optimized detector parameters.

In sub-step S750, the optimized ray source parameters and the optimized detector parameters are determined as geometric calibration parameters.

FIG8A is an exemplary flowchart of obtaining optimized ray source parameters and optimized detector parameters in a geometric calibration step in a calibration method according to some exemplary embodiments of the present disclosure.

8A , in some exemplary embodiments, sub-step S740 may include sub-steps S741 - S742 .

In sub-step S741, an optimization function of the deviation between the actual projection position and the theoretical projection position with respect to the ray source parameters and the detector parameters is constructed, in which the deviation is the dependent variable, and the ray source parameters and the detector parameters are the independent variables.

In sub-step S742, according to the optimization function, the ray source parameters and detector parameters corresponding to when the deviation takes the minimum value are determined as optimized ray source parameters and optimized detector parameters.

For example, in this embodiment, the optimized ray source parameters and the optimized detector parameters can be obtained by solving the following optimization function:

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: The ray source parameter _si and detector parameter _Pd when the minimum value is obtained; _si is the ray source parameter; _Pd is the detector parameter; _Ns is the total number of targets in the distributed ray source; i represents the number of a target in the distributed ray source, _1≤i≤Ns ; pos( _si , _Pd ) represents the actual projection position; cpos( _si , _Pd ) represents the theoretical projection position.

FIG8B is an exemplary flowchart of obtaining optimized ray source parameters and optimized detector parameters in a geometric calibration step in a calibration method according to other exemplary embodiments of the present disclosure.

8B , in some exemplary embodiments, sub-step S740 may include sub-steps S743 - S744 .

In sub-step S743, an optimization function is constructed, which includes a projection position constraint term and a target distance constraint term, wherein the projection position constraint term is a first function of the deviation between the actual projection position and the theoretical projection position with respect to the ray source parameters and the detector parameters; the target distance constraint term is a second function of the deviation between the actual distance and the theoretical distance between two adjacent target points with respect to the ray source parameters and the detector parameters.

For example, in the optimization function, the projection position constraint item has a first weight value, and the target distance constraint item has a second weight value. For example, the second weight value may be 0.

In sub-step S744, according to the optimization function, the corresponding ray source parameters and detector parameters when the weighted sum of the deviation between the actual projection position and the theoretical projection position and the deviation between the actual distance between two adjacent target points and the theoretical distance takes the minimum value are determined as the optimized ray source parameters and the optimized detector parameters.

In some exemplary implementation cases, some constraints are added to the optimization objective function according to the actual situation to make the solution of the optimization problem more stable. For example, although there is an error in the position of the target point, the deviation between the target points is within a certain range, and the following target point distance constraint term can be added to the optimization function, where dis(s _i , s _i+1 ) represents the distance between target points i and i+1, d _s represents the theoretical distance between the two target points, and λ ₁ and λ ₂ represent the weights of the two constraints.

For example, in this embodiment, the optimized ray source parameters and the optimized detector parameters can be obtained by solving the following optimization function:

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: The ray source parameter _si and detector parameter _Pd when the minimum value is obtained; _si is the ray source parameter; _Pd is the detector parameter; _Ns is the total number of targets in the distributed ray source; i represents the number of a target in the distributed ray source; pos( _si , _Pd ) represents the actual projection position; cpos( _si , _Pd ) represents the theoretical projection position; dis( _si , si ₊₁ ) represents the distance between targets i and i+1; _ds represents the theoretical spacing between two targets; _λ1 and _λ2 represent the weight values of the two constraints.

Specifically, in the above optimization function, is the projection position constraint, is the target distance constraint item. The weight value of the projection position constraint item is λ ₁ , and the weight value of the target distance constraint item is λ ₂ . For example, in some exemplary embodiments, the weight value λ ₁ of the projection position constraint item is greater than the weight value λ ₂ of the target distance constraint item, so that when performing calibration, the influencing factors of the projection position constraint are more considered.

The following describes the detailed implementation of the steps of performing energy spectrum calibration in conjunction with the accompanying drawings.

With reference to FIGS. 4A to 4B , during calibration, the calibration system 40 is placed on a conveying device (e.g., the conveying mechanism 110 shown in FIG. 2 ) of the scanning imaging device, and the conveying device is controlled to transport the energy spectrum calibration phantom 60 of the calibration system 40 to the scanning plane of the X-ray, so that the energy spectrum calibration phantom 60 is in the scanning plane formed by the ray source 20 and the detector 30. For example, during energy spectrum calibration, only the energy spectrum calibration phantom 60 is in the scanning plane; or, only the geometric calibration phantom 50 and the energy spectrum calibration phantom 60 are in the scanning plane, and the other parts of the calibration system 40 are always outside the scanning plane. In this way, it is possible to avoid interference of other parts of the calibration system 40 with the calibration data.

FIG9 is a flow chart of the energy spectrum calibration step in the calibration method according to some exemplary embodiments of the present disclosure. With reference to FIGS. 1 to 9, 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 points 210, and the N _s target points are spaced and distributed along a first direction, wherein N _s is a positive integer greater than or equal to 2. The first direction can correspond to the straight line arrangement direction shown in FIG3A or the arc arrangement method shown in FIG3B. It should be noted that in the embodiments of the present disclosure, no special restrictions are imposed on the arrangement direction and form of the multiple target points of the distributed ray source.

In some embodiments of the present disclosure, the energy spectrum calibration step in the calibration method may include sub-steps S910 to S960.

In sub-step S910, when the energy spectrum calibration phantom is located in the scanning area formed by the rays, the geometric relationship between the ray source, the energy spectrum calibration phantom and the detector is acquired according to the relative positions between the ray source, the energy spectrum calibration phantom and the detector.

In sub-step S920, the detector collects rays passing through the scanning area to obtain actual projection data.

In sub-step S930, the physical properties of the energy spectrum calibration phantom are obtained, wherein the physical properties are predetermined according to the constituent materials of the energy spectrum calibration phantom.

In sub-step S940, based on the physical properties of the energy spectrum calibration phantom and the geometric relationship, theoretical projection data are calculated using a predetermined plurality of basic energy spectra.

In sub-step S950, the energy spectrum parameters are calibrated according to the theoretical projection data and the actual projection data to obtain optimized energy spectrum parameters.

In sub-step S960, the optimized energy spectrum parameters are determined as energy spectrum calibration parameters.

In this embodiment, the energy spectrum calibration model 60 can be an object with a certain shape and composed of a known material with sufficient attenuation capability. For example, the material of the energy spectrum calibration model 60 can be selected from 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 information.

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 sub-step S930 are accurate. Accordingly, in sub-step S940, accurate theoretical projection data can be calculated based on the accurate physical properties and geometric relationship of the energy spectrum calibration phantom 60. The optimized energy spectrum parameters obtained in sub-step S950 can be used as the final energy spectrum calibration parameters without iteration.

Fig. 10 is a flow chart of an energy spectrum calibration step in a calibration method according to some other exemplary embodiments of the present disclosure. In some other embodiments of the present disclosure, the energy spectrum calibration step in the calibration method may include sub-steps S1010 to S1060.

In sub-step S1010, when the energy spectrum calibration phantom is located in the scanning area formed by the rays, the geometric relationship between the ray source, the energy spectrum calibration phantom and the detector is acquired according to the relative positions between the ray source, the energy spectrum calibration phantom and the detector.

In sub-step S1020, the detector collects rays passing through the scanning area to obtain actual projection data.

In sub-step S1030, a loop process is executed until a preset condition is met, and the first loop process includes sub-steps S1031 to S1034.

In sub-step S1031, 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.

In sub-step S1032, based on the physical properties of the energy spectrum calibration phantom and the geometric relationship, theoretical projection data are calculated using a predetermined plurality of basic energy spectra.

In sub-step S1033, the energy spectrum parameters are calibrated according to the theoretical projection data and the actual projection data to obtain optimized energy spectrum parameters.

In sub-step S1034, energy spectrum information is acquired based on the optimized energy spectrum parameters.

In sub-step S1040, the optimized energy spectrum parameters obtained last time during the first cycle are determined as energy spectrum calibration parameters.

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

In this embodiment, the physical properties of the energy spectrum calibration phantom 60 can be determined by an image reconstruction method. Referring back to FIG. 1 , in reverse projection (also called back projection), the projection value of the image point on the detector D is known, and the pixel value of the spatial point on the scanned object OB is obtained. In this embodiment, in sub-step S1020, the actual projection data, i.e., the projection value on the detector, is obtained, and the image of the scanned object (i.e., the energy spectrum calibration phantom) can be calculated by a reverse projection algorithm or an image reconstruction algorithm, and the reconstructed image corresponds to the physical properties of the energy spectrum calibration phantom 60.

In the embodiments corresponding to FIG. 4A , FIG. 4B and FIG. 6 , when both the geometric calibration phantom and the energy spectrum calibration phantom are located in the scanning area formed by the rays, the geometric calibration step and the energy spectrum calibration step are performed. Specifically, in step S610, the rays passing through the scanning area are collected by the detector 30 to obtain detector data related to both the geometric calibration phantom and the energy spectrum calibration phantom. In other words, the detector data includes information of both the geometric calibration phantom 50 and the energy spectrum calibration phantom 60. In this case, when reconstructing the image of the energy spectrum calibration phantom, it is necessary to segment the image to segment the geometric calibration phantom 50 and the energy spectrum calibration phantom 60.

For example, in sub-step S1031, the geometric calibration phantom 50 and the energy spectrum calibration phantom 60 are reconstructed according to the energy spectrum information to obtain a first reconstructed image; the first reconstructed image is segmented to segment the geometric calibration phantom 50 and the energy spectrum calibration phantom 60 to obtain a second reconstructed image; and the physical properties of the energy spectrum calibration phantom 60 are obtained according to the second reconstructed image.

It should be noted that, in the embodiment corresponding to FIG. 5 , since the energy spectrum calibration is performed separately, it is not necessary to perform image segmentation processing when image reconstruction is performed during the energy spectrum calibration process.

It should also 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.

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. In this way, the accuracy of the energy spectrum calibration can be improved.

It should be noted that, unless otherwise specified or in case of conflict, the steps or methods described below can be applied to the various embodiments described above. Specifically, unless otherwise specified, the various steps described below can be applied to both the calibration methods described above for Figures 9 and 10.

In sub-step S910 or sub-step S1010, the geometric calibration steps described in the above embodiments may be used to obtain the ray source parameters _si and the detector parameters P _d .

The energy spectrum calibration phantom 60 is arranged on the rotating table 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 according to the position of the rotating table 420 in the calibration system 40 and the position of the energy spectrum calibration phantom 60 on the rotating table 420. In this way, when the energy spectrum calibration phantom 60 is located in the scanning area formed by the ray, the geometric relationship between the ray source 20, the energy spectrum calibration phantom 60 and the detector 30 can be obtained according to the relative positions among the ray source 20, the energy spectrum calibration phantom 60 and the detector 30.

Referring back to FIG. 5 , in step S510, the geometric calibration phantom 50 is placed on the rotating stage 420, and then the geometric calibration phantom 50 is moved into the scanning area. After the geometric calibration is completed, in step S520, the energy spectrum calibration phantom 60 is placed on the rotating stage 420, and then the energy spectrum calibration phantom 60 is moved into the scanning area. In this case, when performing the energy spectrum calibration, the relative position of the rotating stage 420 relative to the radiation source 20 and the detector 30 needs to be calibrated again.

In some exemplary embodiments, before determining the relative positions between the radiation source, the energy spectrum calibration phantom and the detector, the method further includes: calibrating the relative position of a calibration device body (e.g., a rotating table 420) carrying the energy spectrum calibration phantom relative to the radiation source 20 and the detector 30.

In some embodiments, the relative position of the calibration device body (eg, the rotating stage 420 ) with respect to the radiation source 20 and the detector 30 may be calibrated by calibrating the center coordinates of the calibration device body (eg, the rotating stage 420 ).

For example, in this embodiment, the center coordinates (eg, coordinates of the rotation center) for optimizing the rotating stage 420 may be obtained by solving the following optimization function:

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: The coordinate x ₀ of the rotation center of the rotating stage 420 when the minimum value is obtained; N _s is the total number of targets in the distributed ray source; i represents the number of a target in the distributed ray source, 1≤i≤N _s ; pos(s _i ,P _d ) represents the actual projection position; cpos(s _i ,P _d ) represents the theoretical projection position.

Referring back to FIG. 4A , FIG. 4B and FIG. 6 , when both the geometric calibration phantom 50 and the energy spectrum calibration phantom 60 are located in the scanning area formed by the ray, the geometric calibration step and the energy spectrum calibration step are performed. That is, the geometric calibration and the energy spectrum calibration are performed based on the same detector data. In this case, when performing the energy spectrum calibration, the center of the calibration device body (e.g., the rotating table 420) is the coordinate origin defined in the geometric calibration step, and there is no need to recalibrate the relative position of the calibration device body (e.g., the rotating table 420) relative to the ray source 20 and the detector 30.

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

In sub-step S920 or S1020, obtaining the detector data includes: collecting rays passing through a scanning area (where the energy spectrum calibration phantom 60 is located) through the detector 30 to obtain initial detector data p _i ; and correcting the initial detector data p _i using a first correction method using the air projection data p _air to obtain first corrected projection data prj _i .

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.

For example, the first correction may be performed using the following formula to obtain the first corrected projection data prj _i : prj _i = p _i / p _air .

Alternatively or additionally, in sub-step S1020, obtaining the detector data includes: acquiring, by the detector 30, rays passing through a scanning area (where the energy spectrum calibration phantom 60 is located), to obtain initial detector data p _i ; using the air projection data p _air , correcting the initial detector data p _i using a first correction method to obtain first corrected projection data prj _i ; and/or, using the air data, correcting the initial projection data p _i using a second correction method to obtain second corrected projection data pprj _i .

In some exemplary embodiments, the first correction method and the second correction method are different. For example, the first correction can be performed using the following formula to obtain the first corrected projection data prj _i : prj _i = p _i / p _air . For example, the second correction can be performed using the following formula to obtain the second corrected projection data pprj _i : pprj _i = -log(p _i / p _air ).

It should be noted that the first corrected projection data prj _i 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 is used for image reconstruction in the following steps, so it needs to take the negative value of the logarithm. For example, the logarithm here can be a logarithm with base 10.

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 .

In this embodiment, obtaining the initial detector data p _i may include: controlling the ray source 20 to emit rays; controlling the rotating table 420 to rotate to drive the energy spectrum calibration model 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 model 60 rotating m circles, the detector 30 collects rays emitted from the ray source 20 and passing through the scanning area.

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 .

In this embodiment, obtaining the initial detector data p _i 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.

For example, the energy spectrum calibration phantom 60 may be driven to rise to the scanning position by the lifting and lowering movement of the lifting platform 440. During the lifting and lowering process, the detector may not collect data.

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.

In some exemplary embodiments of the present disclosure, the ray source 20 includes N _s target points 210 , and the 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.

In this embodiment, obtaining the initial detector data _pi may include: controlling the _Ns target points 210 to emit radiation in a set order; and in the process of the _Ns target points 210 emitting radiation in the set order, the detector 30 collects radiation emitted from the radiation source 20 and passing through the scanning area.

In some exemplary embodiments of the present disclosure, the calibration system 40 includes a rotating table 420, and the energy spectrum calibration phantom 60 is located on the rotating table 420. The ray source 20 includes _Ns target _points 210, which are spaced apart along the first direction, wherein _Ns is a positive integer greater than or equal to 2.

In this embodiment, obtaining the initial detector data p _i may include: controlling the N _s target points 210 to emit rays in a set order; controlling the rotating table 420 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 in the process of the N _s target points 210 emitting rays in a set order and the energy spectrum calibration phantom 60 rotating m circles, the detector 30 collects rays emitted from the ray source and passing through the scanning area.

It should be noted that in the embodiments of the present disclosure, there is no particular restriction on the movement form, setting number and target number of the energy spectrum calibration phantom, and various situations can be combined and combined with each other without conflict. For example, in some embodiments, the energy spectrum calibration phantom 60 can be set on a rotating table, the rotating table is set on a lifting table, and the ray source 20 can be a distributed ray source including multiple target points. In this way, the step of obtaining the detector data prj _i can be adjusted accordingly according to the setting mode, which will not be repeated here.

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 of the beam emission of the radiation source may not be particularly limited. For example, the energy spectrum calibration phantom 60 is fixed at one position, and all the targets are controlled to emit beams once in a set order, and then the rotating stage rotates to the next position, and all the targets are controlled to emit beams again, until the rotating stage rotates one circle and ends.

As described 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 acquired first corrected projection data prj _i may be classified first, and then, for each type of classified projection data, energy spectrum calibration may be performed respectively.

Specifically, in sub-step S920 or sub-step S1020, collecting the rays passing through the scanning area through the detector to obtain actual projection data may also include: classifying the first corrected projection data prj _i according to a predetermined classification standard to obtain projection data of N _c categories, and taking the projection data of the jth category as actual projection data, wherein the projection data of the jth category is a category of projection data in the N _c categories, N _c is a positive integer greater than or equal to 1, 1≤j≤N _c ; and the predetermined classification standard is determined based on factors that affect the absorption energy spectrum of the detector.

In some exemplary embodiments, the factors affecting the absorption energy spectrum of the detector include at least one of the following factors: the emission angle of the ray; the incident angle of the ray incident on the detector; the energy spectrum distribution of the target point of the ray source; and the shielding of the ray in the path from the ray source to the detector. In this embodiment, energy spectra with the same or similar emission angle of the ray, the incident angle of the ray incident on the detector, and the shielding in the ray propagation path are classified into the same category, and the energy spectra of the same category are calibrated, which is conducive to improving the accuracy of energy spectrum calibration.

In sub-step S940 or sub-step S1032, the theoretical projection data is calculated using a predetermined plurality of 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 sub-step S940, 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 sub-step S1032, the physical properties of the energy spectrum calibration phantom 60 are estimated based on an image reconstruction algorithm.

It should be noted that, in this article, the “multiple basic energy spectra” can be selected from actually measured energy spectra at different energies, 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 scanned object.

In some exemplary embodiments, in sub-step S940 or sub-step S1032, the calculating theoretical projection data using a predetermined plurality of basic energy spectra based on the physical properties of the energy spectrum calibration phantom and the geometric relationship specifically includes: selecting _Ne basic energy spectra {S _k (E)}; and sequentially calculating _Ne theoretical projection data for _Ne basic energy spectra {S _k (E)} based on the physical properties and the geometric relationship of the energy spectrum calibration phantom 60. For example, _Ne is a positive integer greater than or equal to 2.

When _Ne basic energy spectra {S _k (E)}, the physical properties of the energy spectrum calibration phantom 60 and the geometric relationship are known, various known forward projection algorithms can be used to calculate theoretical projection data.

For example, the k-th theoretical projection data sprj _k may be calculated using the following formula:

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 scanned object at dl for the ray of energy E, dl is the integral along the ray path, and dE is the integral about the energy.

For another example, as described above, it is necessary to calculate 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 _j,k corresponding to the j-th category of projection data calculated using the k-th basic energy spectrum:

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≤N _e , S _k (E) is the kth basic energy spectrum, Indicates location or distance The linear absorption coefficient of the scanned object at dl for the ray of energy E, dl is the integral along the ray path, and dE is the integral about the energy.

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.

That is, in some exemplary embodiments of the present disclosure, 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 may include a loop process. For example, 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 may include: executing a second loop process for N _c categories of projection data in sequence. The second loop process includes: selecting N _e basic energy spectra {S _k (E)} for the j-th category of projection data; and calculating N _e theoretical projection data corresponding to the j-th category of projection data based on the physical properties of the energy spectrum calibration phantom and the geometric relationship in sequence for the N _e basic energy spectra {S _k (E)}.

In some exemplary embodiments, in sub-step S1031, the image of the energy spectrum calibration phantom 60 may be reconstructed according to the energy spectrum information and based on the second corrected projection data pprj _i .

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 table 420 drives the energy spectrum calibration phantom 60 to rotate one circle. The second correction projection data pprj _i obtained in the above steps is complete for CT reconstruction. Combined with the coordinates or relative positions of the ray source and the detector, the integration time of the detector, the position of the rotating table 420, the rotation speed of the rotating table 420, and the energy spectrum information, the energy spectrum calibration phantom 60 can be CT reconstructed to obtain a reconstructed image. It can be understood 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.

FIG. 11 is an exemplary flowchart of obtaining optimized energy spectrum parameters in a calibration method according to some exemplary embodiments of the present disclosure.

11 , in some exemplary embodiments, sub-step S950 or sub-step S1033 may include sub-steps S1110 - S1120 .

In sub-step S1110, an optimization function of the deviation between the theoretical projection data and the actual projection data with respect to energy spectrum parameters is constructed.

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

In sub-step S1120, the energy spectrum parameters are calibrated according to the optimization function to obtain optimized energy spectrum parameters.

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

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: The energy spectrum parameter {c _k } when the minimum value is obtained; _Ne 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 are the projection data of rays that pass through the same path and are incident on the detector.

It means that the sum of the 1st to _Ne weight coefficients c _k (i.e. _Ne weight coefficients c _k ) is approximately equal to 1. Here, “approximately equal to” includes the case of being equal to and the case of being approximately equal to within a certain error range.

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

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: The energy spectrum parameter {c _k } when the minimum value is obtained; _Ne 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 is the kth theoretical projection data corresponding to the jth category projection data calculated using the kth basic energy spectrum; aprj _j is the actual projection data of the jth category.

It means that the sum of the 1st to _Ne weight coefficients c _k (i.e. _Ne weight coefficients c _k ) is approximately equal to 1. Here, “approximately equal to” includes the case of being equal to and the case of being approximately equal to within a certain error range.

In the above embodiment, in sub-step S1120, the above optimization function can be solved to calculate _Ne optimization weight coefficients {c _k } when the deviation is the minimum value, and the _Ne optimization weight coefficients {c _k } are used as the optimized energy spectrum parameters.

Referring back to FIG. 9 , in some calibration methods according to embodiments of the present disclosure, since iterative calculation is not required, in sub-step S960 , the optimized energy spectrum parameters may be determined as energy spectrum calibration parameters.

Referring back to FIG. 10 , in some other calibration methods according to the embodiments of the present disclosure, since iterative calculation is required, when the first cycle process satisfies the preset conditions, in sub-step S1040, the optimized energy spectrum parameters obtained for the last time in the first cycle process can be determined as the energy spectrum calibration parameters.

Continuing to refer to FIG. 10 , in sub-step S1034 , the energy spectrum information may be calculated by weighted summation according to the _Ne optimization weight coefficients and the _Ne basic energy spectra.

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

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

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 energy spectrum information acquired two adjacent times is less than a preset threshold; and in the first cycle process, the number of iterations reaches a preset number.

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; at least one of a geometric calibration phantom 40 and an energy spectrum calibration phantom 60 disposed on the calibration device body; a driving member 430, the driving member 430 is used to drive at least one of the geometric calibration phantom 40 and the energy spectrum calibration phantom 60 to move; and a controller 450, the controller 450 is configured to: perform geometric calibration and/or energy spectrum calibration on the scanning imaging device according to the above-mentioned calibration method.

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.

FIG. 12 schematically shows a structural block diagram of a controller of a calibration system according to an exemplary embodiment of the present disclosure.

As shown in FIG. 12 , the controller 450 of the calibration system according to an embodiment of the present disclosure may include a processor 1001, which may 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 portion 1008 into a random access memory (RAM) 1003. The processor 1001 may, for example, include a general-purpose microprocessor (e.g., a CPU), an instruction set processor and/or a related chipset and/or a dedicated microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 1001 may also include an onboard 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.

In RAM 1003, various programs and data required for the operation of controller 450 are stored. Processor 1001, ROM 1002 and RAM 1003 are connected to each other through bus 1004. Processor 1001 performs various operations of the method flow according to the embodiment of the present disclosure by executing the program in ROM 1002 and/or RAM 1003. It should be noted that the program can also be stored in one or more memories other than ROM 1002 and RAM 1003. Processor 1001 can also perform various operations of the method flow according to the embodiment of the present disclosure by executing the program stored in the one or more memories.

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 portion 1006 including a keyboard, a mouse, etc.; an output portion 1007 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 1008 including a hard disk, etc.; and a communication portion 1009 including a network interface card such as a LAN card, a modem, etc. The communication portion 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 on the drive 1010 as needed, so that a computer program read therefrom is installed into the storage portion 1008 as needed.

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 without being assembled into the device/apparatus/system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

According to an embodiment of the present disclosure, a computer-readable storage medium may be a non-volatile computer-readable storage medium, such as but 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 of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction 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.

It should be noted that in the above embodiments, the calibration method is described by taking a static CT scanning imaging device with a distributed radiation source as an example, but 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, and during the calibration process, the radiation source and the detector are in a static state.

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 _Ns = 1. Although the single/multi-view X-ray imaging device itself is not a CT device and cannot perform CT imaging on the scanned object, when a single target point emits a beam, the data collected by the calibration device in rotation meets the data completeness requirements of CT imaging, and CT reconstruction can also be performed, so it is also applicable to the energy spectrum calibration process described above.

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 computing programs can be implemented using high-level process and/or object-oriented programming languages, and/or assembly/machine languages. Programming languages include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect through the Internet).

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

In the description of this specification, the description with reference to the terms "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 schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

Although the 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 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 of the present disclosure and/or the claims may be combined in various combinations and/or combinations, even if such combinations or combinations are not explicitly described in the present disclosure. In particular, the features described in the various embodiments of the present disclosure and/or the claims may be combined in various combinations and/or combinations 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 (22)

A calibration method for calibrating a scanning imaging device, wherein the scanning imaging device comprises a ray source for emitting rays and a detector for receiving rays. During the calibration process, a geometric calibration phantom or an energy spectrum calibration phantom is located in a scanning area formed by the rays. The calibration method comprises: In the case where the geometric calibration phantom is located in the scanning area formed by the rays, a geometric calibration step is performed, wherein the geometric calibration step includes: collecting rays passing through the scanning area by the detector to obtain detector data related to the geometric calibration phantom; using the detector data, calibrating ray source parameters and detector parameters to obtain optimized ray source parameters and optimized detector parameters, and determining the optimized ray source parameters and optimized detector parameters as geometric calibration parameters, wherein the ray source parameters are used to represent the position of the ray source in the calibration system, and the detector parameters are used to represent the position of the detector in the calibration system; In a case where the energy spectrum calibration phantom is located in a scanning area formed by the radiation, determining the relative positions among the radiation source, the energy spectrum calibration phantom and the detector according to the geometric calibration parameters to obtain a geometric relationship among the radiation source, the energy spectrum calibration phantom and the detector; and When the energy spectrum calibration phantom is located in the scanning area formed by the rays, the energy spectrum calibration step is performed, wherein the energy spectrum calibration step includes: collecting the rays passing through the scanning area through the detector to obtain actual projection data related to the energy spectrum phantom; using the actual projection data related to the energy spectrum phantom, according to the geometric relationship and the physical properties of the energy spectrum calibration phantom, calibrating the energy spectrum parameters to obtain optimized energy spectrum parameters, and determining the optimized energy spectrum parameters as energy spectrum calibration parameters. A calibration method for calibrating a scanning imaging device, the scanning imaging device comprising a ray source for emitting rays and a detector for receiving rays, during the calibration process, both a geometric calibration phantom and an energy spectrum calibration phantom are located in a scanning area formed by the rays, characterized in that the calibration method comprises: In the case where both the geometric calibration phantom and the energy spectrum calibration phantom are located in the scanning area formed by the rays, a geometric calibration step and an energy spectrum calibration step are performed, wherein the performing of the geometric calibration step and the energy spectrum calibration step comprises: Collecting rays passing through the scanning area by the detector to obtain detector data related to both the geometric calibration phantom and the energy spectrum calibration phantom; Calibrate the ray source parameters and the detector parameters by using the detector data to obtain optimized ray source parameters and optimized detector parameters, and determine the optimized ray source parameters and optimized detector parameters as geometric calibration parameters, wherein the ray source parameters are used to represent the position of the ray source in the calibration system, and the detector parameters are used to represent the position of the detector in the calibration system; Determining the relative positions of the ray source, the energy spectrum calibration phantom, and the detector according to the geometric calibration parameters to obtain a geometric relationship between the ray source, the energy spectrum calibration phantom, and the detector; and The detector data is used to calibrate the energy spectrum parameters according to the geometric relationship and the physical properties of the energy spectrum calibration phantom to obtain optimized energy spectrum parameters, and the optimized energy spectrum parameters are determined as energy spectrum calibration parameters. The method according to claim 1 or 2, wherein the detector data comprises an actual projection position of the ray on the detector after the ray passes through a geometric calibration phantom in the scanning area; The calibrating of the ray source parameters and the detector parameters to obtain optimized ray source parameters and optimized detector parameters, and determining the optimized ray source parameters and optimized detector parameters as geometric calibration parameters, specifically includes: Acquire initial ray source parameters and initial detector parameters, wherein the ray source parameters are used to indicate the position of the ray source in the calibration system, and the detector parameters are used to indicate the position of the detector in the calibration system; According to initial ray source parameters, initial detector parameters and the positional relationship of the geometric calibration phantom relative to the ray source and the detector, a theoretical projection position of the geometric calibration phantom on the detector is obtained by geometric calculation; Calibrate the ray source parameters and the detector parameters according to the actual projection position and the theoretical projection position to obtain optimized ray source parameters and optimized detector parameters; and The optimized ray source parameters and the optimized detector parameters are determined as geometric calibration parameters. The method according to claim 3, wherein the ray source parameters and the detector parameters are calibrated according to the actual projection position and the theoretical projection position to obtain optimized ray source parameters and optimized detector parameters, comprising: An optimization function of the deviation between the actual projection position and the theoretical projection position with respect to ray source parameters and detector parameters is constructed, in which the deviation is a dependent variable, and the ray source parameters and the detector parameters are independent variables. The method according to claim 4, wherein the ray source parameters and the detector parameters are calibrated according to the actual projection position and the theoretical projection position to obtain optimized ray source parameters and optimized detector parameters, further comprising: According to the optimization function, the ray source parameters and the detector parameters corresponding to the minimum value of the deviation are determined as optimized ray source parameters and optimized detector parameters, and the optimized ray source parameters and optimized detector parameters are determined as geometric calibration parameters. The method according to claim 3, wherein the ray source comprises N _s target points, and the N _s target points are spaced apart along the first direction, wherein N _s is a positive integer greater than or equal to 2; Calibrate the ray source parameters and the detector parameters according to the actual projection position and the theoretical projection position to obtain optimized ray source parameters and optimized detector parameters, including: Constructing an optimization function, wherein the optimization function includes a projection position constraint term and a target distance constraint term, Among them, the projection position constraint term is a first function of the deviation between the actual projection position and the theoretical projection position with respect to the ray source parameters and the detector parameters; the target point distance constraint term is a second function of the deviation between the actual distance and the theoretical distance between two adjacent target points with respect to the ray source parameters and the detector parameters. The method according to claim 6, wherein, in the optimization function, the projection position constraint term has a first weight value, and the target distance constraint term has a second weight value. The method according to claim 6 or 7, wherein the ray source parameters and the detector parameters are calibrated according to the actual projection position and the theoretical projection position to obtain optimized ray source parameters and optimized detector parameters, further comprising: According to the optimization function, the ray source parameters and detector parameters corresponding to the minimum value of the weighted sum of the deviation between the actual projection position and the theoretical projection position and the deviation between the actual distance and the theoretical distance between two adjacent target points are determined as optimized ray source parameters and optimized detector parameters, and the optimized ray source parameters and optimized detector parameters are determined as geometric calibration parameters. The method according to any one of claims 1 to 8, wherein the calibrating the energy spectrum parameters according to the geometric relationship and the physical properties of the energy spectrum calibration phantom to obtain optimized energy spectrum parameters, and determining the optimized energy spectrum parameters as energy spectrum calibration parameters, specifically comprises: Acquiring physical properties of the energy spectrum calibration phantom, wherein the physical properties are predetermined according to constituent materials of the energy spectrum calibration phantom; Based on the physical properties of the energy spectrum calibration phantom and the geometric relationship, using a predetermined plurality of basic energy spectra to calculate theoretical projection data; Calibrate energy spectrum parameters according to the theoretical projection data and the actual projection data to obtain optimized energy spectrum parameters; and The optimized energy spectrum parameters are determined as energy spectrum calibration parameters. The method according to any one of claims 1 to 8, wherein the calibrating the energy spectrum parameters according to the geometric relationship and the physical properties of the energy spectrum calibration phantom to obtain optimized energy spectrum parameters, and determining the optimized energy spectrum parameters as energy spectrum calibration parameters, specifically comprises: The loop process is executed until a preset condition is met, wherein the first loop process includes: 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; Based on the physical properties of the energy spectrum calibration phantom and the geometric relationship, using a predetermined plurality of basic energy spectra to calculate theoretical projection data; Calibrate energy spectrum parameters according to the theoretical projection data and the actual projection data to obtain optimized energy spectrum parameters; and Based on the optimized energy spectrum parameters, acquiring energy spectrum information; and The optimized energy spectrum parameters obtained for the last time during the first cycle are determined as energy spectrum calibration parameters. The method according to claim 9 or 10, wherein the calibrating the energy spectrum parameters according to the theoretical projection data and the actual projection data to obtain the optimized energy spectrum parameters comprises: constructing an optimization function of the deviation between the theoretical projection data and the actual projection data with respect to energy spectrum parameters; and According to the optimization function, the energy spectrum parameters are calibrated to obtain optimized energy spectrum parameters. The method according to any one of claims 1 to 11, wherein the geometric calibration phantom comprises at least one metal wire; or The geometric calibration phantom includes a plurality of metal wires, and the plurality of metal wires are distributed on the rotating platform with different radii and/or different angles. The method according to any one of claims 1 to 12, wherein the energy spectrum calibration phantom comprises a plurality of parts respectively composed of a plurality of materials, and at least one of the following properties of any two of the plurality of materials is different: density, atomic number. The method according to any one of claims 1 to 13, wherein the calibration system comprises a rotating table, and at least one of the geometric calibration phantom and the energy spectrum calibration phantom is located on the rotating table; The step of collecting the rays passing through the scanning area by the detector to obtain detector data includes: Controlling the ray source to emit rays; Controlling the rotating stage to rotate so as to drive at least one of the geometric calibration phantom and the energy spectrum calibration phantom to rotate m times, wherein m is a positive integer greater than or equal to 1; and During the process in which at least one of the geometric calibration phantom and the energy spectrum calibration phantom rotates m circles, the detector collects rays emitted from the ray source and passing through the scanning area. The method according to any one of claims 1 to 14, wherein the calibration system comprises a lifting platform, and at least one of the geometric calibration phantom and the energy spectrum calibration phantom is located on the lifting platform; The step of collecting the rays passing through the scanning area by the detector to obtain detector data includes: controlling the radiation source to emit radiation; and The lifting platform is controlled to move up and down, so as to drive at least one of the geometric calibration phantom and the energy spectrum calibration phantom to move up and down. The method according to any one of claims 1 to 15, wherein the ray source comprises N _s target points, and the N _s target points are spaced apart along the first direction, wherein N _s is a positive integer greater than or equal to 2; The step of collecting the rays passing through the scanning area by the detector to obtain detector data includes: Controlling the N _s target points to emit rays in a set order; and In the process that the _Ns target points emit radiation in a set order, the detector collects radiation emitted from the radiation source and passing through the scanning area. The method according to any one of claims 1 to 13, wherein the calibration system comprises a rotating table, and at least one of the geometric calibration phantom and the energy spectrum calibration phantom is located on the rotating table; the ray source comprises N _s target points, and the N _s target points are spaced apart along the first direction, wherein N _s is a positive integer greater than or equal to 2; The step of collecting the rays passing through the scanning area by the detector to obtain detector data includes: Controlling the N _s target points to emit rays in a set order; Controlling the rotating stage to rotate so as to drive at least one of the geometric calibration phantom and the energy spectrum calibration phantom to rotate m times, wherein m is a positive integer greater than or equal to 1; and In the process that the _Ns target points emit radiation in a set order and at least one of the geometric calibration phantom and the energy spectrum calibration phantom rotates m circles, the detector collects radiation emitted from the radiation source and passing through the scanning area. According to the method of claim 1, before determining the relative positions among the ray source, the energy spectrum calibration phantom and the detector, the method further comprises: calibrating the relative position of a calibration device body carrying the energy spectrum calibration phantom relative to the ray source and the detector. The method according to claim 2, wherein the step of calibrating the energy spectrum parameters according to the geometric relationship and the physical properties of the energy spectrum calibration phantom to obtain optimized energy spectrum parameters, and determining the optimized energy spectrum parameters as energy spectrum calibration parameters, specifically comprises: The loop process is executed until a preset condition is met, wherein the first loop process includes: According to the energy spectrum information, image reconstruction is performed on the geometric calibration phantom and the energy spectrum calibration phantom to obtain a first reconstructed image; segmentation is performed on the first reconstructed image to segment the geometric calibration phantom and the energy spectrum calibration phantom to obtain a second reconstructed image; and physical properties of the energy spectrum calibration phantom are obtained according to the second reconstructed image; Based on the physical properties of the energy spectrum calibration phantom and the geometric relationship, using a predetermined plurality of basic energy spectra to calculate theoretical projection data; Calibrate energy spectrum parameters according to the theoretical projection data and the actual projection data to obtain optimized energy spectrum parameters; and Based on the optimized energy spectrum parameters, acquiring energy spectrum information; and The optimized energy spectrum parameters obtained for the last time during the first cycle are determined as energy spectrum calibration parameters. A calibration system for calibrating a scanning imaging device, wherein the calibration system comprises: Calibration device body; At least one of a geometric calibration phantom and an energy spectrum calibration phantom disposed on the calibration device body; a driving member, the driving member being used to drive at least one of the geometric calibration phantom and the energy spectrum calibration phantom to move; and A controller, wherein the controller is configured to calibrate the scanning imaging device according to the calibration method according to any one of claims 1-19. A calibration system for calibrating a scanning imaging device, wherein the calibration system comprises: Base; a rotating table connected to the base; At least one of a geometric calibration phantom and an energy spectrum calibration phantom disposed on the rotating table, wherein at least one of the geometric calibration phantom and the energy spectrum calibration phantom is located on the rotating table; and a driving member, the driving member being used to drive the rotating table to rotate, so as to drive at least one of the geometric calibration phantom and the energy spectrum calibration phantom to rotate, Wherein, the geometric calibration phantom includes at least one metal wire; or, the geometric calibration phantom includes a plurality of metal wires, and the plurality of metal wires are distributed on the rotating table with different radii and/or different angles from each other; and/or, The energy spectrum calibration phantom includes a plurality of parts respectively made of a plurality of materials, and at least one of the following properties of any two of the plurality of materials is different: density, atomic number. The system according to claim 21, wherein the calibration system further comprises: a lifting platform, the lifting platform is connected to the base, and the rotating platform is arranged on the lifting platform.