CN117929423A

CN117929423A - Calibration method and system for calibrating energy spectrum of scanning imaging equipment

Info

Publication number: CN117929423A
Application number: CN202311865662.0A
Authority: CN
Inventors: 陈志强; 沈乐; 张丽; 邢宇翔; 赵振华; 孙运达
Original assignee: Tsinghua University; Nuctech Co Ltd
Current assignee: Tsinghua University; Nuctech Co Ltd
Priority date: 2023-12-29
Filing date: 2023-12-29
Publication date: 2024-04-26

Abstract

There is provided a calibration method for performing energy spectrum calibration on a scanning imaging apparatus, including: under the condition that the energy spectrum calibration die body is positioned in a scanning area formed by rays, acquiring the geometric relationship among the ray source, the energy spectrum calibration die body and the detector according to the relative positions among the ray source, the energy spectrum calibration die body and the detector; collecting rays passing through a scanning area through a detector to obtain actual projection data; acquiring physical properties of the energy spectrum calibration module, wherein the physical properties are predetermined according to constituent materials of the energy spectrum calibration module or are calculated according to an image reconstruction method; calculating theoretical projection data by using a plurality of preset basic energy spectrums based on physical properties and geometric relations of the energy spectrum calibration module; 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 parameter as an energy spectrum calibration parameter.

Description

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

Technical Field

The present disclosure relates to the field of scanning imaging technologies, and more particularly, to a calibration method and a calibration system for performing energy spectrum calibration on a scanning imaging device.

Background

According to the scanning imaging theory, when rays are emitted from a ray source, the rays are incident on a detector after passing through an object to be inspected, and in the process, the attenuation of the rays accords with Beer's law. Beer's law, also known as Beer-lambert's law, is the basic law describing the absorption of light by a substance. When a beam of parallel monochromatic light passes perpendicularly through a uniform non-scattering light-absorbing substance, its absorbance is proportional to the concentration of the light-absorbing substance and the thickness of the absorbing layer.

For example, taking the CT scanning imaging technique as an example, according to the CT imaging theory, based on the radiation attenuation conforming to Beer's law, the detector for scanning imaging is required to have the same absorption spectrum, so that the radiation attenuation of the object passing through the same thickness from different directions can be consistent. The absorption spectrum of the detector is related to the thickness of the crystal on which the radiation is incident. In the geometrical arrangement of the single-target source detection center, all rays are vertically incident crystals, the thicknesses of the crystals through which the rays pass are the same, and the absorption energy spectrums of the detectors are the same. However, in the static CT scanning imaging device, since a single crystal needs to receive the radiation emitted by different targets, the incident angles of the radiation of the different targets are different, and the thicknesses of the passing crystals are different, so that the absorption energy spectrums are different. Moreover, the spectra of different targets may also differ. Data inconsistency caused by energy spectrum inconsistency is also an important factor affecting the accuracy of reconstructed values.

The above information disclosed in this section is only for understanding the background of the technical idea of the present disclosure, and thus, the above information may contain information that does not constitute prior art.

Disclosure of Invention

In order to solve the above problems in the prior art, an embodiment of the present disclosure provides a calibration method and a calibration system for performing energy spectrum calibration on a scanning imaging device.

In one aspect, there is provided a calibration method for energy spectrum calibration of a scanning imaging apparatus, the scanning imaging apparatus comprising a source for emitting radiation and a detector for receiving radiation, during calibration a spectrum calibration phantom being located in a scan region formed by the radiation, the calibration method comprising:

Under the condition that an energy spectrum calibration die body is positioned in a scanning area formed by the rays, acquiring geometrical relations among the ray source, the energy spectrum calibration die body and the detector according to relative positions among the ray source, the energy spectrum calibration die body and the detector;

Acquiring rays passing through the scanning area through the detector to acquire actual projection data;

Acquiring physical properties of the energy spectrum calibration die body, wherein the physical properties are predetermined according to constituent materials of the energy spectrum calibration die body;

calculating theoretical projection data by using a plurality of preset basic energy spectrums based on the physical properties of the energy spectrum calibration module body and the geometric relationship;

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

And determining the optimized energy spectrum parameter as an energy spectrum calibration parameter.

In another aspect, there is provided a calibration method for energy spectrum calibration of a scanning imaging apparatus, the scanning imaging apparatus comprising a source for emitting radiation and a detector for receiving radiation, during calibration a spectrum calibration phantom being located in a scanning area formed by the radiation, the calibration method comprising:

executing a cyclic process until a preset condition is met, wherein the first cyclic process comprises:

performing image reconstruction on the energy spectrum calibration module according to energy spectrum information, and acquiring physical properties of the energy spectrum calibration module according to the image reconstruction result;

Acquiring energy spectrum information based on the optimized energy spectrum parameters; and

And determining the optimized energy spectrum parameter obtained last time in the first cycle process as an energy spectrum calibration parameter.

According to some exemplary embodiments, the calibrating the energy spectrum parameter according to the theoretical projection data and the actual projection data to obtain the optimized energy spectrum parameter includes: constructing an optimization function of deviation between the theoretical projection data and the actual projection data with respect to 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 method further comprises: before the energy spectrum calibration die body is placed in a scanning area formed by the rays, controlling the ray source to emit rays, and collecting air data of the detector; the acquiring, by the detector, rays passing through the scan region to acquire actual projection data includes: controlling the ray source to emit rays under the condition that the energy spectrum calibration die body is positioned in a scanning area formed by the rays, and acquiring the rays passing through the scanning area by the detector to acquire initial projection data; and correcting the initial projection data by using the air data by adopting a first correction method so as to acquire first corrected projection data.

According to some exemplary embodiments, the acquiring, by the detector, radiation passing through the scan region to acquire actual projection data further comprises: and correcting the initial projection data by using the air data by using a second correction method to obtain second correction projection data, wherein the second correction method is different from the first correction method.

According to some exemplary embodiments, the acquiring, by the detector, radiation passing through the scan region to acquire actual projection data further comprises: classifying the first correction projection data according to a preset classifying standard to obtain projection data of N _c categories, and taking projection data of a j category as actual projection data, wherein the projection data of the j category is one type of projection data in N _c categories, N _c is a positive integer greater than or equal to 1, and j is greater than or equal to 1 and less than or equal to N _c; the predetermined categorization criteria are determined based on factors affecting the absorption spectrum of the detector.

According to some exemplary embodiments, the reconstructing an image of the spectrum calibration phantom according to the spectrum information includes: and carrying out image reconstruction on the energy spectrum calibration module body based on the second correction projection data according to the energy spectrum information.

According to some exemplary embodiments, the calculating theoretical projection data using a predetermined plurality of base spectra based on the physical properties of the spectral calibration phantom and the geometric relationship comprises: n _e basic energy spectrums { S _k(E)},N_e are selected to be positive integers which are more than or equal to 2; and sequentially aiming at N _e basic spectrums { S _k (E) }, calculating N _e theoretical projection data based on the physical properties of the spectrum calibration module and the geometric relationship.

According to some exemplary embodiments, the optimization function comprises the following functions:

Wherein sprj _k is the kth theoretical projection data calculated by using the kth basic energy spectrum, aprj is the actual projection data, and k is 1-N _e,c_k is the weight coefficient of the kth theoretical projection data.

According to some exemplary embodiments, the calculating theoretical projection data using a predetermined plurality of base spectra based on the physical properties of the spectral calibration phantom and the geometric relationship comprises:

Sequentially performing a second loop process for N _c categories of projection data, the second loop process comprising:

Selecting N _e base spectrums { S _k (E) } for projection data of the j-th category; and

N _e theoretical projection data corresponding to the projection data of the j-th category are calculated based on the physical properties of the spectrum calibration module body and the geometric relation for N _e basic spectrums { S _k (E) } in sequence.

Wherein sprj _j,k is the kth theoretical projection data corresponding to the projection data of the jth category calculated by using the kth basic energy spectrum, aprj _j is the actual projection data of the jth category, and 1.ltoreq.k.ltoreq.N _e,c_k is the weight coefficient of the kth theoretical projection data.

According to some exemplary embodiments, the calibrating the energy spectrum parameter according to the optimization function to obtain an optimized energy spectrum parameter specifically includes: and calculating N _e optimization weight coefficients when the deviation value is the minimum value by solving the optimization function, and taking the N _e optimization weight coefficients as the optimized energy spectrum parameters.

According to some exemplary embodiments, the acquiring energy spectrum information based on the optimized energy spectrum parameter specifically includes: and calculating the energy spectrum information by adopting a weighted summation mode according to the N _e optimized weight coefficients and the N _e basic energy spectrums.

According to some exemplary embodiments, the spectral calibration phantom comprises a plurality of portions each composed of a plurality of materials, any two of the plurality of materials differing in at least one of the following properties: density, atomic number.

According to some exemplary embodiments, the calibration system includes a rotary table on which the spectrum calibration phantom is located; the acquiring, by the detector, rays passing through the scanning area to obtain detector data includes: controlling the ray source to emit rays; controlling the rotary table to rotate so as to drive the energy spectrum calibration die body to rotate for m circles, wherein m is a positive integer greater than or equal to 1; and during the rotation of the energy spectrum calibration phantom for m turns, the detector collects radiation emitted from the radiation source and passing through the scanning area.

According to some exemplary embodiments, the calibration system includes a lift table on which the spectrum calibration phantom is located; the acquiring, by the detector, rays passing through the scanning area to obtain detector data includes: controlling the ray source to emit rays; and controlling the lifting table to lift so as to drive the energy spectrum calibration die body to lift.

According to some exemplary embodiments, the radiation source includes N _s targets, the N _s targets are spaced apart along the first direction, where N _s is a positive integer greater than or equal to 2; the acquiring, by the detector, rays passing through the scanning area to obtain detector data includes: controlling the N _s targets to emit rays according to a set sequence; and in the process that the N _s targets emit rays according to a set sequence, the detector acquires the rays emitted from the ray source and passing through the scanning area.

According to some exemplary embodiments, the calibration system includes a rotary table on which the spectrum calibration phantom is located; the ray source comprises N _s targets, the N _s targets are distributed at intervals along a first direction, wherein N _s is a positive integer greater than or equal to 2; the acquiring, by the detector, rays passing through the scanning area to obtain detector data includes: controlling the N _s targets to emit rays according to a set sequence; controlling the rotary table to rotate so as to drive the energy spectrum calibration die body to rotate for m circles, wherein m is a positive integer greater than or equal to 1; and in the process that the N _s targets emit rays according to a set sequence and the energy spectrum calibration die body rotates for m circles, the detector acquires the rays emitted from the ray source and passing through the scanning area.

According to some exemplary embodiments, the preset conditions include at least one of the following conditions: in the first cycle process, the deviation of the energy spectrum information acquired in two adjacent times is smaller than a preset threshold value; and in the first cycle process, the iteration times reach preset times.

According to some exemplary embodiments, the factors that influence the absorption spectrum of the detector include at least one of the following factors: the exit angle of the ray; the incidence angle of the radiation onto the detector; the energy spectrum distribution of a target spot of the ray source; and occlusion conditions in the path of the radiation from the source to the detector.

In yet another aspect, a calibration system for energy spectrum calibration of a scanning imaging device is provided, wherein the calibration system comprises: calibrating a device main body; the energy spectrum calibration die body is arranged on the calibration device main body; the driving piece is used for driving the energy spectrum calibration die body to move; and a controller configured to perform energy spectrum calibration of the scanning imaging device according to the calibration method as described above.

In yet another aspect, a calibration system for energy spectrum calibration of a scanning imaging device is provided, wherein the calibration system comprises: a base; a rotary table connected to the base; the energy spectrum calibration die body is arranged on the rotary table and is positioned on the rotary table; and a driving member for driving the rotation table to rotate so as to drive the spectrum calibration phantom to rotate, wherein the 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 comprises: the lifting platform is connected to the base, and the rotating platform is arranged on the lifting platform.

Additional aspects and advantages of the disclosure will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the disclosure.

Drawings

For a more complete understanding of the present disclosure and the advantages thereof, reference is now made to the following descriptions taken in conjunction with the accompanying drawings, in which:

Fig. 1 schematically shows a schematic view of a projection relationship between a radiation source, an object under examination and a detector.

Fig. 2 is a schematic structural view of a static CT apparatus according to some exemplary embodiments of the present disclosure.

Fig. 3A is a schematic structural view of a scan stage included in a static CT apparatus according to some exemplary embodiments of the present disclosure.

Fig. 3B is a schematic diagram of a structure of a scan stage included in a static CT apparatus according to other exemplary embodiments of the present disclosure.

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

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

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

FIG. 6 is a flow chart of a calibration method according to further exemplary embodiments of the present disclosure.

FIG. 7 is an exemplary flowchart of a calibration method to obtain optimized spectral parameters according to some exemplary embodiments of the present disclosure.

FIG. 8 schematically illustrates a 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. It should be understood that the description is only exemplary and is not intended to limit the scope of the present disclosure. In addition, in the following description, descriptions of well-known structures and techniques are omitted so as not to unnecessarily obscure the concepts of the present disclosure. In addition, the various embodiments provided below of the present disclosure and technical features in the embodiments may be combined with each other in any manner.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. Furthermore, the terms "comprises," "comprising," and the like, as used herein, specify the presence of stated features, steps, operations, and/or components, but do not preclude 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 same meaning as commonly understood by one of ordinary skill in the art unless otherwise defined. It should be noted that the terms used herein should be construed to have meanings consistent with the context of the present specification and should not be construed in an idealized or overly formal manner.

In the description of the present disclosure, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings are merely for convenience in describing the present disclosure and simplifying the description, and do not indicate or imply that the device or element being referred to must have a specific orientation, be configured and operated in a specific orientation, and therefore should not be construed as limiting the present disclosure. Furthermore, features defining "first", "second" may include one or more such features, either explicitly or implicitly. In the description of the present disclosure, unless otherwise indicated, the meaning of "a plurality" is two or more.

In the description of the present disclosure, it should be noted that, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the terms in this disclosure will be understood by those of ordinary skill in the art in the specific context.

In the present disclosure, computed tomography (Computed Tomography, abbreviated as CT) imaging refers to a process of performing a tomographic scan on a detection object using radiation, converting an analog signal received by a detector into a digital signal, calculating an attenuation coefficient of each pixel by an electronic computer, and reconstructing an image, thereby displaying a tomographic structure of each portion of the detection object.

Fig. 1 schematically shows a schematic view of a projection relationship between a radiation source, an object under examination and a detector. Referring to fig. 1, in an embodiment of the present disclosure, rays (e.g., X-rays, γ -rays, etc.) emitted from a ray source S are incident on an object OB to be inspected, and rays transmitted through the object OB to be inspected are detected by a detector D. The spatial point X on the object OB under examination is applied by a radiation source S to an image point Y of the detector D. In forward projection (also referred to as forward projection), the pixel values of the spatial points on the object OB under examination are known, and the projection values of the image points on the detector D are obtained. In back projection (also called back projection), the projection values of the image points on the detector D are known, and the pixel values of the spatial points on the object OB under examination are obtained.

The computerized tomography technique has an important role in security inspection, medical field, and the like, because it can eliminate the influence of object overlapping. The conventional CT acquires projection data at different angles by rotation of an X-ray source and a detector using a slip ring device, and acquires tomographic images by a reconstruction method, thereby obtaining internal information of a baggage item to be detected. The traditional CT device usually adopts a slip ring for rotation in the data acquisition process, so that the scanning speed is limited, the size is huge, the machining precision requirement is high, the cost is high, and the wide application of the CT device in practice is limited. In recent years, carbon nanotube X-ray tube technology has entered the practical field. Unlike conventional ray source, it does not need to use high temperature to generate ray, but generates cathode ray according to the principle of carbon nanotube tip discharge, and targets to generate X-ray. Its advantages are quick opening and closing, and small size. The X-ray sources are arranged in a ring shape, and the static CT without rotation can be manufactured by irradiating objects at different angles, so that the speed of ray imaging is greatly improved, and meanwhile, the structure of a slip ring is omitted, the cost is saved, and the X-ray source has very important significance in the fields of safety inspection and the like.

Fig. 2 is a schematic structural view of a static CT apparatus according to some exemplary embodiments of the present disclosure. Referring to fig. 2, a static CT apparatus according to an embodiment of the present disclosure may include a scan stage, a transfer mechanism 110, a control device 140, and an imaging device 130. For example, the scan stage may include a radiation source, a detector, and an acquisition device.

For example, in embodiments of the present disclosure, the radiation source may be a distributed radiation source, which may include multiple targets, e.g., multiple X-targets. In a distributed X-ray source, the target point refers to the emission point or focal spot of the source. Specifically, high energy electrons are emitted from the cathode and bombard a metal anode target, thereby generating X-rays. The energy of the emitted X-rays depends on the material of the anode target, while the intensity of the X-rays depends on the electron current intensity and the electron energy striking the anode target. In a distributed X-ray source, a plurality of cathodes are in one-to-one correspondence with a plurality of targets such that the plurality of targets receive electron beams from the plurality of cathodes to generate a plurality of X-rays. The design enables the distributed X-ray source to achieve the effect of generating more X-ray radiation sources by using fewer cathode assemblies, improves the stability of the system, reduces the use quantity of the cathode assemblies, and reduces the production cost of equipment.

In a static CT apparatus using a distributed radiation source, multiple projection data sets can be acquired from various angles by combining multiple targets together and activating them in a set sequence at different angles. These projection datasets can be used in a computer reconstruction algorithm to generate high quality cross-sectional images. One advantage of using a distributed X-ray source is that artifacts can be reduced and image quality improved. By using multiple targets, the emission position distribution of the X-ray beam is more uniform, more projection angles and data can be provided, artifacts in the reconstructed image are reduced, and more accurate anatomical information is provided. That is, the target point in a distributed X-ray source refers to the point or region from which the X-ray beam is emitted, and their distribution form helps to obtain high quality projection data for reconstruction of a static CT image.

In embodiments of the present disclosure, a plurality of targets in a distributed radiation source may be arranged along a predetermined first direction. For example, the predetermined first direction may be a straight direction, or may be an arc direction. Embodiments of the present disclosure are not particularly limited in terms of placement of targets in a distributed radiation source.

Fig. 3A is a schematic structural view of a scan stage included in a static CT apparatus according to some exemplary embodiments of the present disclosure. Fig. 3B is a schematic diagram of a structure of a scan stage included in a static CT apparatus according to other exemplary embodiments of the present disclosure. Referring to fig. 3A and 3B, in an embodiment of the present disclosure, the stationary CT apparatus includes a distributed radiation source 20 and a detector 30, the distributed radiation 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, and accordingly, the detector 30 may include a plurality of detection units 310 arranged in an arc or 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. Note that, in the embodiments of fig. 2 to 3B, only a structural schematic diagram of a static CT apparatus according to some exemplary embodiments of the present disclosure is schematically shown, but not all embodiments of the present disclosure. In embodiments of the present disclosure, any suitable arrangement of distributed radiation sources and detectors may be employed.

In an embodiment of the present disclosure, the plurality of targets 210 emit radiation toward the object 120 to be inspected, respectively, and the plurality of detecting units 310 are used for detecting the radiation passing through the object 120 to be inspected. For example, in the embodiment shown in fig. 3A and 3B, the plurality of targets 210 emit X-rays and the plurality of detection units 310 receive portions of the X-rays emitted from the plurality of targets 210 and passing through the object under examination 120. In this way, a scanning region for scanning the object 120 is formed between the radiation source 20 and the detector 30. In the scanning area, at least one plane located at a substantially middle position of the scanning area and perpendicular to the conveying direction of the conveying mechanism 110 may be referred to as 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 arranged in a one-dimensional direction, or a plurality of detector crystals arranged in a two-dimensional direction.

It should be understood that each detector crystal is the basic unit of a detector that can absorb radiation (e.g., X-rays) and convert it to other forms of energy, such as light or electrical signals. For example, the material of the detector crystal may include oxides and halides (e.g., iodides and fluorides), and the like.

For example, in the embodiment shown in fig. 2, the transport mechanism 110 carries the inspected object 120 and drives the inspected object 120 to make a linear motion. The control device 140 controls the beam-out sequence of the plurality of targets 210 of the radiation source 20 such that the detector 30 outputs digital signals corresponding to the projection data. The imaging device 130 reconstructs a CT image of the object under examination 120 based on the digital signals.

It should be noted that, in the embodiment of the present disclosure, the imaging apparatus 130 may reconstruct a CT image of the object under examination using various known reconstruction algorithms. For example, the reconstruction algorithm may be an iterative, analytical, or other reconstruction algorithm, and embodiments of the present disclosure are not limited in particular to reconstruction algorithms.

In some embodiments of the present disclosure, each distributed source 20 has one or more targets thereon, the energy of which can be set, and the order in which the targets are activated can be set. For example, the targets may be distributed over multiple scan planes (e.g., the scan planes are perpendicular to the direction of travel of the channel). In each plane, the target point distribution can be one or more sections of straight lines or arcs, which are continuous or discontinuous. Because the target energy can be set, various scanning modes such as different energy spectrums of different targets or different target energy in different planes can be realized in the beam outlet process. The targets can be grouped, for example, the targets of each module are used as a group, or the targets of each plane are used as a group, the sequence of electronic targeting of the targets in the same group is adjustable, sequential beam output and alternate beam output can be realized, and the targets in different groups can be simultaneously activated for scanning, so that the scanning speed is increased.

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 type detector.

The conveying mechanism 110 comprises a stage or a conveying belt, the control device 140 controls the X-ray machine and the frame of the detector, and the scanning of the spiral scanning track, the circumferential scanning track or other special tracks can be realized by controlling the beam outlet mode of the distributed ray source and the linear translation motion of the object or the combination of the two. The control device 140 is responsible for completing the control of the operation process of the CT system, including mechanical rotation, electrical control and safety interlocking control, and is especially responsible for controlling the beam-out speed/frequency, beam-out energy and beam-out sequence of the ray source, and controlling the data reading and data reconstruction of the detector.

CT imaging theory is based on the fact that the radiation attenuation accords with Beer's law, and detectors for scanning imaging are required to have the same absorption energy spectrum, so that the radiation attenuation of objects passing through the same thickness from different directions can be consistent. The inventors have found that the absorption spectrum of the detector is related to the thickness of the crystal upon which the radiation is incident. In the geometrical arrangement of the single-target source detection center, all rays are vertically incident crystals, the thicknesses of the crystals through which the rays pass are the same, and the absorption energy spectrums of the detectors are the same. However, in the static CT apparatus, since a single crystal needs to receive the radiation emitted from different targets, the incident angles of the radiation from different targets are different, and the thicknesses of the passing crystals are different, so that the absorption spectra are different. On the other hand, the spectra of different targets may also differ. Data inconsistency caused by energy spectrum inconsistency is also an important factor affecting the accuracy of reconstructed values.

Furthermore, the invention also researches and discovers that the difference between the horizontal plane and the height direction exists when different ray sources are installed, and the definition of CT reconstructed images can be influenced. Because the rays emitted by the ray source have energy spectrum space distribution related to directions, the incident angles of the rays on each detector unit are different, and the energy spectrums of different rays are different. During reconstruction, the energy spectrum error may interfere with the reconstructed values.

In addition, the technical problem of the energy spectrum accuracy can also directly influence the image color accuracy of single-view/multi-view X-ray imaging equipment, and indirectly influence the accuracy of automatic identification of some suspected articles.

Embodiments of the present disclosure provide a calibration system for performing energy spectrum calibration on a scanning imaging device, which may perform energy spectrum calibration on a scanning imaging device, for example, may perform energy spectrum calibration on a static CT device based on a distributed radiation source.

FIG. 4A is a schematic structural view of a calibration system according to some exemplary embodiments of the present disclosure. FIG. 4B is a schematic structural view of a calibration system according to some exemplary embodiments of the present disclosure, viewed from another angle. Referring to fig. 4A and 4B, the calibration system 40 may include: a base 410; a rotation table 420 connected to the base 410; a spectrum calibration phantom 60 disposed on the rotary table 420; and the driving part 430 is used for driving the rotary table 420 to rotate so as to drive the energy spectrum calibration die body 60 to rotate.

In some exemplary embodiments, the spectral calibration phantom 60 is located at a central location of the rotary stage 420. For example, the geometric center of the spectral calibration phantom 60 is located on the rotational axis AX1 of the rotary table 420.

In some exemplary embodiments, the spectral calibration phantom 60 may include a plurality of portions each composed of a plurality of materials, any two of which differ in at least one of the following properties: density, atomic number.

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

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

The shape of the spectrum calibration phantom 60 may be a cylinder, a prism, a pyramid, or an irregular shape. The length of the intersection line where the ray intersects the spectral calibration phantom 60 should cover as wide a range as possible during the calibration process.

It should be noted that, in the embodiment shown in fig. 4A and 4B, the shape of the spectrum calibration phantom 60 is a cuboid, but the shape is merely exemplary and not a limitation of the embodiments of the present disclosure. In other embodiments of the present disclosure, the spectral calibration phantom 60 may take any other suitable shape.

With continued reference to fig. 4A and 4B, the calibration system 40 may further include: the lifting table 440, the lifting table 440 is connected to the base 410, and the rotating table 420 is disposed on the lifting table 440. Therefore, the metal wire can be scanned at a plurality of height positions by controlling the lifting table to translate up and down for a fixed distance so as to obtain more calibration data, thereby being beneficial to improving the calibration precision.

In embodiments of the present disclosure, the base 410 is used to carry other components and maintain the stability of the components disposed thereon. The driving part 430 may include a movement driving mechanism for driving the elevating platform 440 to move up and down; and/or a rotation driving mechanism for driving the rotation table 420 to rotate.

For example, the rotation driving mechanism for driving the rotation stage 420 to rotate may include at least one of a gear transmission mechanism, a servo motor driving mechanism, and a stepping motor driving mechanism. The gear transmission mechanism can comprise a driving motor, a driving gear and a driven gear, and the transmission of the rotation force is realized through the meshing of the gears. The servo motor is driven to rotate the rotary table by controlling the rotating speed and the position of the servo motor. Servo motors are typically used in conjunction with encoders and closed loop control systems to achieve high precision rotational control. The stepper motor drives the pulse signal by controlling the stepper motor to realize the rotation of the rotary table. The stepping motor has discrete stepping angles, and can accurately control the position and the speed of the rotary table.

For example, the movement driving mechanism for driving the elevating platform 440 to move up and down may include at least one of a screw driving mechanism, an electric screw driving mechanism, and a gear driving mechanism. The screw drive may include a screw and a nut engaged therewith. When the screw rod rotates, the nut moves along the spiral line of the screw rod, so that the lifting table moves up and down. The electric screw drive combines screw drive and electric drive techniques. The motor drives the screw rod to rotate, so that the lifting platform is pushed to move up and down. The gear transmission uses meshing of gears to transfer force and motion. The lifting table can move up and down by the rotation of the driving gear.

It should be noted that, in the embodiments of the present disclosure, the types and structures of the rotary drive mechanism and the movement drive mechanism are not particularly limited, and various types of rotary drive mechanisms and movement drive mechanisms known in the related art may be used in the embodiments of the present disclosure without conflict.

Some exemplary embodiments of the present disclosure also provide a calibration method for performing energy spectrum calibration for a scanning imaging device.

Referring to fig. 4A-4B in combination, in performing calibration, the calibration system 40 is placed on a conveyor (e.g., conveyor 110 shown in fig. 2) of a scanning imaging apparatus, and the conveyor is controlled to convey a spectral calibration phantom 60 of the calibration system 40 to a scan plane of X-rays such that the spectral calibration phantom 60 is in the scan plane of the source 20 and detector 30. For example, in performing a spectral calibration, only the spectral calibration phantom 60 is located in the scan plane, with the remainder of the calibration system 40 always being outside of the scan plane. In this way, other parts of the calibration system 40 may be prevented from interfering with the calibration data.

FIG. 5 is a flowchart of a calibration method according to some exemplary embodiments of the present disclosure. Referring to fig. 1 to 5 in combination, the calibration method may be used for performing energy spectrum calibration on a scanning imaging device, for example, the calibration method may be used for performing energy spectrum calibration on a static CT device. In the static CT apparatus, the radiation source 20 may be a distributed radiation source, which includes N _s targets 210 and N _s targets spaced along a first direction, where N _s is a positive integer greater than or equal to 2. The first direction may correspond to a straight arrangement direction shown in fig. 3A or an arc arrangement method shown in fig. 3B. It should be noted that, in the embodiments of the present disclosure, the arrangement direction and form of the multiple targets of the distributed radiation source are not particularly limited.

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

In step S510, in the case that the spectrum calibration phantom is located in the scanning area formed by the radiation, a geometric relationship among the radiation source, the spectrum calibration phantom and the detector is obtained according to the relative positions among the radiation source, the spectrum calibration phantom and the detector.

In step S520, rays passing through the scan region are acquired by the detector to acquire actual projection data.

In step S530, physical properties of the spectrum calibration phantom are obtained, where the physical properties are predetermined according to constituent materials of the spectrum calibration phantom.

In step S540, theoretical projection data is calculated using a predetermined plurality of base spectra based on the physical properties of the spectral calibration phantom and the geometric relationship.

In step S550, the energy spectrum parameter is calibrated according to the theoretical projection data and the actual projection data, so as to obtain an optimized energy spectrum parameter.

In step S560, the optimized spectrum parameter is determined as a spectrum calibration parameter.

In this embodiment, the spectral calibration phantom 60 may be a shaped object of known material composition having sufficient attenuation capability. For example, the material of the spectral calibration phantom 60 may be selected from graphite, plexiglass, polyethylene, polyoxymethylene, aluminum (alloy), magnesium (alloy), silicon dioxide, polyvinyl chloride, titanium (alloy), iron, copper, and the like. The chemical composition and physical density of these materials are known information.

In this embodiment, since the physical properties of the spectrum calibration phantom 60 are predetermined, the obtained physical properties of the spectrum calibration phantom 60 are accurate in step S530. Accordingly, in step S540, accurate theoretical projection data may be calculated based on the accurate physical properties and geometric relationships of the spectral calibration phantom 60. The optimized energy spectrum parameter obtained in step S550 may be used as a final energy spectrum calibration parameter, without performing iteration.

FIG. 6 is a flow chart of a calibration method according to further exemplary embodiments of the present disclosure. In other embodiments of the present disclosure, the calibration method may include steps S610 to S660.

In step S610, in a case where a spectrum calibration phantom is located in a scanning area formed by the radiation, a geometrical relationship among the radiation source, the spectrum calibration phantom and the detector is acquired according to relative positions among the radiation source, the spectrum calibration phantom and the detector.

In step S620, rays passing through the scan region are acquired by the detector to acquire actual projection data.

In step S630, a cyclic process is performed until a preset condition is satisfied, the first cyclic process including steps S631 to S634.

In step S631, the spectrum calibration module is subjected to image reconstruction according to the spectrum information, and physical properties of the spectrum calibration module are obtained according to the result of the image reconstruction.

In step S632, theoretical projection data is calculated using a predetermined plurality of base spectra based on the physical properties of the spectral calibration phantom and the geometric relationship.

In step S633, the energy spectrum parameter is calibrated according to the theoretical projection data and the actual projection data, so as to obtain an optimized energy spectrum parameter.

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

In step S640, the optimized spectrum parameter obtained last in the first cycle is determined as the spectrum calibration parameter.

In this embodiment, the spectral calibration phantom 60 may be a shaped object of unknown material composition with sufficient attenuation capability. For example, the material of the spectral calibration phantom 60 may be selected from materials with stable physicochemical properties, but the component ratio information of the materials cannot be obtained accurately. That is, the physical properties of the spectral calibration phantom 60 cannot be predetermined.

In this embodiment, the physical properties of the spectral calibration phantom 60 may be determined by means of image reconstruction. Referring back to fig. 1, in back projection (also referred to as back projection), the projection values of the image points on the detector D are known, and the pixel values of the spatial points on the object OB are obtained. In this embodiment, in step S620, actual projection data, i.e. projection values on the detector, are obtained, and an image of the object under examination (i.e. the spectral calibration phantom) can be calculated by a back projection algorithm or an image reconstruction algorithm, where the reconstructed image corresponds to the physical properties of the spectral calibration phantom 60.

It should be noted that, in this embodiment, the image reconstruction may be performed using various back projection algorithms or image reconstruction algorithms known in the art, which are not particularly limited by the embodiment of the present disclosure.

It should be appreciated that the physical properties of the spectral calibration phantom determined by the image reconstruction algorithm based on the actual projection data may be inaccurate, so in this embodiment, a first cyclic process needs to be performed, by which the physical properties of the acquired spectral calibration phantom may be approximated to the exact physical properties of the spectral calibration phantom infinitely, and thus the accuracy of the spectral calibration may be improved.

It is noted that unless specifically stated otherwise or in the event of a conflict, the steps or methods described hereinafter may be applicable to the various embodiments described above. In particular, the various steps described below may be applied to both of the calibration methods described above with respect to fig. 5 and 6, unless specifically indicated.

In step S510 or S610, radiation source parameters representing the position of the radiation source 20 in the calibration system 40 and detector parameters representing the position of the detector 30 in the calibration system 40 may be acquired.

For convenience of description herein, the source parameters are described as s _i and the detector parameters are described as P _d.

For example, the geometric calibration phantom 50 may be used to perform geometric calibration to obtain source parameters and detector parameters. As another example, the source parameters and the detector parameters may be predetermined.

In some exemplary embodiments, the radiation source is a distributed radiation source, and the target interval has high enough precision to perform integral calibration on the target position, i.e., { s _i：1≤i≤N_s } is determined by the starting coordinate, the arrangement direction and the number i of the distributed radiation source. In this embodiment, the source parameters s _i include: the position coordinates of the 1st target in the N _s targets in the calibration system, the arrangement direction of the N _s targets, and the number of each target in the N _s targets.

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

For example, referring to fig. 4A through 4B, 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 detecting units 310 are arranged in a straight line on the detector arm 320. In this embodiment, the detector parameters P _d may include: the position coordinates of the 1 st detection unit in the calibration system and the arrangement direction of the plurality of detection units.

For another example, the plurality of detection units 310 may be arranged in an arc on the detector arm, and the detector parameters P _d may include: the angle and the radius of the 1 st detection unit in the calibration system are the plurality of detection units.

Further, the spectral calibration phantom 60 is arranged on the rotary table 420, the position of which in the calibration system 40 is also predetermined, or the position of which in the calibration system 40 is determined according to the position of the rotary table 420 in the calibration system 40 and the position of the spectral calibration phantom 60 on the rotary table 420. In this way, with the spectral calibration phantom 60 located in the scan region formed by the radiation, the geometric relationship between the radiation source 20, the spectral calibration phantom 60 and the detector 30 may be obtained based on the relative positions of the radiation source 20, the spectral calibration phantom 60 and the detector 30.

In some exemplary embodiments, the calibration method may include: air projection data p _air is acquired by detector 30 before the spectral calibration phantom 60 is placed in the scan region or scan plane formed by the radiation.

It will be appreciated that in performing image reconstruction, it is necessary to know the detector readings in the absence of an object (i.e. only air) in order to remove this background value from the actual measurement data. For example, in CT imaging, projection data is typically acquired using a method known as line integration, for example. This process involves passing the radiation through the object and measuring the attenuation of the radiation after it has passed through the object. This attenuation value (or projection data) reflects properties of the substance in the ray path, such as density and composition. Similar measurements can also be made in the absence of an object, i.e. only air. The projection data thus obtained can be used as a reference or background value, which background value is removed from the measured projection data during the actual image reconstruction process, in order to obtain the radiation attenuation caused only by the object itself.

In step S520, the obtaining the probe data includes: acquiring initial detector data p _i by the detector 30, which rays pass through a scanning region in which the spectral calibration phantom 60 is located; and correcting the initial detector data p _i using the air projection data p _air using a first correction method to obtain first corrected projection data prj _i.

In this context, 1.ltoreq.i.ltoreq.N _s, i.e. the number of a target 210 in the distributed radiation source denoted by i.

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 step S620, the obtaining the detector data includes: acquiring initial detector data p _i by the detector 30, which rays pass through a scanning region in which the spectral calibration phantom 60 is located; correcting the initial detector data p _i by a first correction method using the air projection data p _air to obtain first corrected projection data prj _i; and/or correcting the initial projection data p _i by using the air data and adopting a second correction method to acquire second correction projection data pprj _i.

In some exemplary embodiments, the first correction method and the second correction method are different. 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. For example, the second correction may be performed using the following formula to obtain second correction projection data pprj _i：pprj_i＝-log(p_i/p_air).

Note that, the first correction projection data prj _i is used as forward projection data in the later step, so it is directly divided by the air projection data; the second corrected projection data pprj _i is used for image reconstruction in a later step, so it needs to take the negative value of the logarithm. For example, the logarithm here may be a base 10 logarithm.

In some exemplary embodiments of the present disclosure, the calibration system 40 includes a rotary stage 420, and the spectral calibration phantom 60 is located on the rotary stage 420.

In this embodiment, obtaining initial probe data p _i may include: controlling the radiation source 20 to emit radiation; the rotary table 420 is controlled to rotate so as to drive the energy spectrum calibration die body 60 to rotate for m circles, wherein m is a positive integer greater than or equal to 1; and, during m rotations of the spectral calibration phantom 60, the detector 30 acquires radiation emanating from the radiation source 20 and passing through the scan region.

In some exemplary embodiments of the present disclosure, the calibration system 40 includes a lift table 440, and the spectral calibration phantom 60 is located on the lift table 440.

In this embodiment, obtaining initial probe data p _i may include: controlling the radiation source 20 to emit radiation; the lifting table 440 is controlled to lift so as to drive the energy spectrum calibration module 60 to lift.

For example, the geometric calibration phantom 50 may be raised to the scan position by the lifting motion of the lift table 440. During lifting, the detector may not collect data.

For another example, during the raising and lowering of the spectral calibration phantom 60, the detector 30 may acquire radiation that is emitted from the radiation source 20 and passes through the scan region. In some alternative embodiments, the data collected during lifting may not be used for subsequent processing.

In some exemplary embodiments of the present disclosure, the radiation source 20 includes N _s targets 210, N _s targets 210 spaced apart along a first direction, where N _s is a positive integer greater than or equal to 2.

In this embodiment, obtaining initial probe data p _i may include: controlling N _s targets 210 to emit rays according to a set sequence; and during the emission of radiation from the N _s targets 210 in the set order, the detector 30 collects radiation emitted from the source 20 and passing through the scan region.

In some exemplary embodiments of the present disclosure, the calibration system 40 includes a rotary stage 420, and the spectral calibration phantom 60 is located on the rotary stage 420. The radiation source 20 comprises N _s targets 210, and N _s targets 210 are distributed at intervals along a first direction, wherein N _s is a positive integer greater than or equal to 2.

In this embodiment, obtaining initial probe data p _i may include: controlling N _s targets 210 to emit rays according to a set sequence; the rotary table 420 is controlled to rotate so as to drive the energy spectrum calibration die body 60 to rotate for m circles, wherein m is a positive integer greater than or equal to 1; and during the process that the N _s targets 210 emit rays according to the set sequence and the energy spectrum calibration die body 60 rotates for m circles, the detector 30 collects the rays emitted from the ray source and passing through the scanning area.

It should be noted that, in the embodiment of the present disclosure, the movement form, the number of settings, and the number of targets of the radiation sources of the spectrum calibration phantom are not particularly limited, and various cases may be combined and combined with each other without collision. For example, in some embodiments, the spectrum calibration phantom 60 may be disposed on a rotating table, the rotating table is disposed on a lifting table, and the radiation source 20 may be a distributed radiation source including a plurality of targets, so that the step of obtaining the detector data prj _i may be adjusted accordingly according to the setting manner, which is not described herein.

It should also be noted that in embodiments of the present disclosure, the movement of the spectral calibration phantom 60 and the sequence of beam exits of the radiation sources may not be particularly limited. For example, the spectrum calibration phantom 60 is fixed in one position, controls all targets to emit beams once according to a set sequence, then the rotary table rotates to the next position, and controls all targets to emit beams again until the rotary table finishes rotating once.

As described above, the inventors have found that, in a static CT apparatus, since a single crystal is required to receive radiation emitted from different targets, the angles of incidence of the radiation from the different targets are different, and the thicknesses of the crystals passing through are different, resulting in different absorption spectra. Therefore, in some exemplary embodiments of the present disclosure, the acquired first corrected projection data prj _i may be categorized first, and then, for each type of categorized projection data, the spectrum calibration may be performed separately.

Specifically, in step S520 or step S620, the acquiring, by the detector, the radiation passing through the scanning area to acquire actual projection data may further include: classifying the first correction projection data prj _i according to a predetermined classification standard to obtain projection data of N _c categories, and taking projection data of a j category as actual projection data, wherein the projection data of the j category is one of the N _c categories, N _c is a positive integer greater than or equal to 1, and j is greater than or equal to 1 and less than or equal to N _c; the predetermined categorization criteria are determined based on factors affecting the absorption spectrum of the detector.

In some exemplary embodiments, the factors that affect the absorption spectrum of the detector include at least one of the following: the exit angle of the ray; the incidence angle of the radiation onto the detector; and occlusion conditions in the path of the radiation from the source to the detector. In the embodiment, the energy spectrums with the same or similar emission angle of the rays, the incidence angle of the rays on the detector and the shielding condition in the ray propagation path are classified into the same class, and the energy spectrums of the same class are calibrated, so that the accuracy of energy spectrum calibration is improved.

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

It should be noted that, herein, the "multiple basic energy spectrums" may be selected from energy spectrums under different measured energies, or may be obtained by using a mock simulation, where the multiple basic energy spectrums are predetermined according to the energy spectrum of interest required by the object to be inspected.

In some exemplary embodiments, in step S540 or step S632, the calculating theoretical projection data using a predetermined plurality of basic spectrums based on the physical properties of the spectrum calibration phantom and the geometric relationship specifically includes: selecting N _e basic energy spectrums { S _k (E) }; and sequentially calculating N _e theoretical projection data for N _e basic spectrums { S _k (E) } based on the physical properties of the spectrum calibration phantom 60 and the geometric relationship. For example, N _e is a positive integer of 2 or more.

With the N _e base spectra { S _k (E) }, the physical properties of the spectral calibration phantom 60, and the geometric relationships known, theoretical projection data can be calculated using various known forward projection algorithms.

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

In the formula, sprj _k is the kth theoretical projection data calculated by using the kth basic energy spectrum, 1.ltoreq.k.ltoreq.N _e,S_k (E) is the kth basic energy spectrum, Expressed in position or distance/>Where the linear absorption coefficient of the object under examination for the rays of energy E, dl is the integral along the ray path and dE is the integral for energy.

As another example, as described above, theoretical projection data needs to be calculated separately for each category of actual projection data, so the above formula may be changed such that the following formula may be used to calculate the kth theoretical projection data sprj _j,k corresponding to the jth category of projection data calculated using the kth base energy spectrum:

In the formula sprj _j,k is the kth theoretical projection data corresponding to the projection data of the jth category calculated using the kth basic energy spectrum, 1.ltoreq.k.ltoreq.N _e,S_k (E) is the kth basic energy spectrum, Expressed in position or distance/>Where the linear absorption coefficient of the object under examination for the rays of energy E, dl is the integral along the ray path and dE is the integral for energy.

It should be noted that the above formula is merely exemplary, and the embodiment of the present disclosure is not limited to a specific formula for calculating theoretical projection data.

That is, in some exemplary embodiments of the present disclosure, the calculating theoretical projection data using a predetermined plurality of base spectra based on the physical properties of the spectral calibration phantom and the geometric relationship may include a cyclic process. For example, the calculating theoretical projection data using a predetermined plurality of base spectra based on the physical properties of the spectral calibration phantom and the geometric relationship may include: the second loop process is performed sequentially for N _e categories of projection data. The second cyclic process includes: selecting N _e base spectrums { S _k (E) } for projection data of the j-th category; and sequentially aiming at N _e basic spectrums { S _k (E) }, calculating N _e theoretical projection data corresponding to the projection data of the jth category based on the physical attribute of the spectrum calibration module and the geometric relation.

In some exemplary embodiments, in step S631, the spectral calibration phantom 60 may be reconstructed from the spectral information based on the second corrected projection data pprj _i.

Since the spectrum calibration phantom 60 is located in the scan plane, the X-ray covers the entire spectrum calibration phantom 60, the rotation table 420 drives the spectrum calibration phantom 60 to rotate one revolution, the second corrected projection data pprj _i obtained in the above steps is complete for CT reconstruction, and the CT reconstruction can be performed on the spectrum calibration phantom 60 to obtain a reconstructed image in combination with the coordinates or relative positions of the radiation source and the detector, the integration time of the detector, the position of the rotation table 420, the rotation speed of the rotation table 420, and the spectrum information. It is understood that the reconstructed image may include an image of the spectral calibration phantom 60 that reflects the physical properties of the spectral calibration phantom 60.

Referring to fig. 7, in some exemplary embodiments, step S550 or step S633 may include steps S710 to S720.

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

For example, in the optimization function, the deviation is an independent variable, and the spectral parameter is an independent variable.

In step S720, the energy spectrum parameters are calibrated according to the optimization function, so as to obtain optimized energy spectrum parameters.

For example, in some exemplary embodiments, the optimized spectral parameters may be obtained by solving an optimization function as follows:

Where "argmin" is a mathematical term used to denote the value of a parameter (the value of an argument) that a function takes the smallest value in its domain of definition. Specifically, in this optimization function, it is expressed that: when (when) Obtaining the total number of energy spectrum parameters { c _k};N_e as basic energy spectrum at the minimum; k represents the kth basic energy spectrum, k is more than or equal to 1 and less than or equal to N _e;c_k represents the weight coefficient of the kth theoretical projection data, namely represents the energy spectrum parameter of the kth basic energy spectrum, and { c _k } is a group of energy spectrum parameters; sprj _k is the kth theoretical projection data calculated using the kth base energy spectrum; aprj is real projection data. For example, aprj may be the first corrected projection data that passes through only the spectral calibration phantom. Note that, aprj and sprj _k are projection data of rays having the same path passing through and incident on the detector.

For example, the optimization function described above may optionally have constraints: Where "s.t." means that the optimization function has a constraint: /(I) For a specific constraint, it means that the sum of the 1 st to N _e th weight coefficients c _k (i.e., N _e weight coefficients c _k) is approximately equal to 1, where "approximately equal to" includes the case of equal, as well as the case of approximately equal within a certain error range.

For another example, in some exemplary embodiments, the optimized spectral parameters may be obtained by solving an optimization function as follows:

Where "argmin" is a mathematical term used to denote the value of a parameter (the value of an argument) that a function takes the smallest value in its domain of definition. Specifically, in this optimization function, it is expressed that: when (when) Obtaining the total number of energy spectrum parameters { c _k};N_e as basic energy spectrum at the minimum; k represents the kth basic energy spectrum, k is more than or equal to 1 and less than or equal to N _e;c_k represents the weight coefficient of the kth theoretical projection data, namely represents the energy spectrum parameter of the kth basic energy spectrum, and { c _k } is a group of energy spectrum parameters; sprj _j,k is the kth theoretical projection data corresponding to the projection data of the jth category calculated using the kth base energy spectrum; aprj _j is the actual projection data of the j-th category.

In the above embodiment, in step S720, N _e optimization weight coefficients { c _k } when the deviation is the minimum value may be calculated by solving the optimization function, and the N _e optimization weight coefficients { c _k } are used as the optimized energy spectrum parameters.

Referring to fig. 5, in some calibration methods according to embodiments of the present disclosure, since iterative computation is not required, the optimized energy spectrum parameter may be determined as an energy spectrum calibration parameter in step S560.

Referring back to fig. 6, in other calibration methods according to embodiments of the present disclosure, since iterative computation is required, when the first cyclic process execution satisfies a preset condition, in step S640, the optimized spectrum parameter obtained last in the first cyclic process may be determined as the spectrum calibration parameter.

With continued reference to fig. 6, in step S634, the energy spectrum information may be calculated by using a weighted summation method according to the N _e optimized weight coefficients and the N _e base energy spectrums.

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

That is, the energy spectrum information calculated by the above formula may be corresponded to actual projection data.

It should be noted that, in the embodiment of the present disclosure, the termination condition of the first cyclic process (i.e., the preset condition) may include at least one of the following conditions: in the first cycle process, the deviation of the energy spectrum information acquired in two adjacent times is smaller than a preset threshold value; and in the first cycle process, the iteration times reach preset times.

Referring back to fig. 4A-4B, a calibration system 40 according to some embodiments of the present disclosure may include: calibrating a device main body; the energy spectrum calibration die body 60 is arranged on the calibration device main body; the driving piece 430 is used for driving the spectral calibration phantom to move; and a controller 450, the controller 450 configured to: according to the calibration method, the scanning imaging equipment is subjected to energy spectrum calibration.

For example, the calibration device body may include: a base 410; and a rotation table 420 coupled to the base 410. Or the calibration device body may include: a base 410; a lift table 440 coupled to the base 410; and a rotation table 420 coupled to the base 410.

As shown in fig. 8, the controller 450 of the calibration system according to the 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 section 1008 into a Random Access Memory (RAM) 1003. The processor 1001 may include, for example, a general purpose microprocessor (e.g., a CPU), an instruction set processor and/or an associated chipset and/or a special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), or the like. The processor 1001 may also comprise an on-board memory for caching purposes. The processor 1001 may comprise a single processing unit or a plurality of processing units for performing different actions of the method flow according to embodiments of the present disclosure.

In the RAM 1003, various programs and data necessary for the operation of the controller 450 are stored. The processor 1001, the ROM 1002, and the RAM 1003 are connected to each other by a bus 1004. The processor 1001 performs various operations of the method flow according to the embodiment of the present disclosure by executing programs in the ROM 1002 and/or the RAM 1003. Note that the program may be stored in one or more memories other than the ROM 1002 and the RAM 1003. The processor 1001 may also perform various operations of the method flow according to the embodiments of the present disclosure by executing programs stored in the one or more memories.

According to an embodiment of the present disclosure, the controller 450 may also include an input/output (I/O) interface 1005, the input/output (I/O) interface 1005 also being connected to the bus 1004. The controller 450 may also include one or more of the following components connected to the I/O interface 1005: an input section 1006 including a keyboard, a mouse, and the like; 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 or the like; and a communication section 1009 including a network interface card such as a LAN card, a modem, or the like. The communication section 1009 performs communication processing via a network such as the internet. The 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, or the like, is installed as needed in the drive 1010, so that a computer program read out therefrom is installed as needed in the storage section 1008.

The present disclosure also provides a computer-readable storage medium that may be embodied in the apparatus/device/system described in the above embodiments; or may exist alone without being assembled into the apparatus/device/system. The computer-readable storage medium carries one or more programs which, when executed, implement methods in accordance with embodiments of the present disclosure.

According to embodiments of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, which may include, for example, but is not limited to: portable computer diskette, hard disk, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the foregoing. In the context of this disclosure, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. For example, according to embodiments of the present disclosure, the computer-readable storage medium may include ROM 1002 and/or RAM 1003 and/or one or more memories other than ROM 1002 and RAM 1003 described above.

It should be noted that, in the above embodiment, the calibration method is described taking the static CT scanning imaging apparatus with the distributed radiation source as an example, but the embodiment of the present disclosure is not limited thereto. In other exemplary embodiments of the present disclosure, the calibration system and calibration method may also perform energy spectrum calibration on a helical CT apparatus of a single-target radiation source, during which the radiation source and detector are at rest.

It should also be noted that embodiments of the present disclosure may also be used to spectrally calibrate single/multi-view X-ray imaging devices. For example, in some embodiments, the number of targets of the radiation source may be ns=1, although the single/multi-view X-ray imaging device is not a CT device and cannot perform CT imaging on the scanned object, when the single target emits a beam, the data collected by the calibration device by rotation satisfies the data completeness requirement of CT imaging, and CT reconstruction may also be performed, so that the method is also applicable to the above-described energy spectrum calibration procedure.

According to embodiments of the present disclosure, program code for performing computer programs provided by embodiments of the present disclosure may be written in any combination of one or more programming languages, and in particular, such computer programs may be implemented in high-level procedural and/or object-oriented programming languages, and/or assembly/machine languages. Programming languages include, but are not limited to, such as Java, c++, python, "C" or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., connected via the Internet using an Internet service provider).

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

In the description of the present specification, reference to the terms "one embodiment," "some embodiments," "illustrative embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present disclosure. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

While embodiments of the present disclosure have been shown and described, it will be understood by those of ordinary skill in the art that: many changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the disclosure, the scope of which is defined by the claims and their equivalents. Those skilled in the art will appreciate that the features recited in the various embodiments of the disclosure and/or in the claims may be provided in a variety of combinations and/or combinations, even if such combinations or combinations are not explicitly recited in the disclosure. In particular, the features recited in the various embodiments of the present disclosure and/or the claims may be variously combined and/or combined without departing from the spirit and teachings of the present disclosure. All such combinations and/or combinations fall within the scope of the present disclosure.

Claims

1. A calibration method for energy spectrum calibration of a scanning imaging device, the scanning imaging device comprising a radiation source for emitting radiation and a detector for receiving radiation, during calibration a spectrum calibration phantom being located in a scanning area formed by the radiation, the calibration method comprising:

2. A calibration method for energy spectrum calibration of a scanning imaging device, the scanning imaging device comprising a radiation source for emitting radiation and a detector for receiving radiation, during calibration a spectrum calibration phantom being located in a scanning area formed by the radiation, the calibration method comprising:

3. The method according to claim 1 or 2, wherein said calibrating the energy spectrum parameters according to the theoretical projection data and the actual projection data to obtain optimized energy spectrum parameters comprises:

constructing an optimization function of deviation between the theoretical projection data and the actual projection data with respect to energy spectrum parameters; and

And calibrating the energy spectrum parameters according to the optimization function to obtain optimized energy spectrum parameters.

4. A method according to any one of claims 1-3, wherein the method further comprises: before the energy spectrum calibration die body is placed in a scanning area formed by the rays, controlling the ray source to emit rays, and collecting air data of the detector;

The acquiring, by the detector, rays passing through the scan region to acquire actual projection data includes:

Controlling the ray source to emit rays under the condition that the energy spectrum calibration die body is positioned in a scanning area formed by the rays, and acquiring the rays passing through the scanning area by the detector to acquire initial projection data; and

And correcting the initial projection data by using the air data by adopting a first correction method so as to acquire first corrected projection data.

5. The method of claim 4, wherein the acquiring, by the detector, radiation passing through the scan region to acquire actual projection data further comprises:

Correcting the initial projection data by a second correction method using the air data to obtain second corrected projection data,

Wherein the second correction method is different from the first correction method.

6. The method of any of claims 1-5, wherein the acquiring, by the detector, radiation passing through the scan region to acquire actual projection data further comprises:

classifying the first corrected projection data according to a predetermined classification criterion to obtain projection data of N _c categories, taking projection data of a j-th category as actual projection data,

The projection data of the j-th category is one of the N _c categories, N _c is a positive integer greater than or equal to 1, and j is greater than or equal to 1 and less than or equal to N _c; the predetermined categorization criteria are determined based on factors affecting the absorption spectrum of the detector.

7. The method according to claim 5 or 6, wherein the image reconstruction of the spectral calibration phantom from the spectral information comprises:

and carrying out image reconstruction on the energy spectrum calibration module body based on the second correction projection data according to the energy spectrum information.

8. The method of any of claims 1-5, wherein the calculating theoretical projection data using a predetermined plurality of base spectra based on the physical properties of the spectral calibration phantom and the geometric relationship comprises:

N _e basic energy spectrums { S _k(E)},N_e are selected to be positive integers which are more than or equal to 2; and

N _e theoretical projection data are calculated based on the physical properties of the spectrum calibration module body and the geometric relation sequentially aiming at N _e basic spectrums { S _k (E) }.

9. The method of claim 8, wherein the optimization function comprises a function of:

10. The method of claim 6, wherein the calculating theoretical projection data using a predetermined plurality of base spectra based on the physical properties of the spectral calibration phantom and the geometric relationship comprises:

11. The method of claim 10, wherein the optimization function comprises a function of:

Wherein spr _j,k is the kth theoretical projection data corresponding to the projection data of the jth category calculated by using the kth basic energy spectrum, aprj _j is the actual projection data of the jth category, and 1.ltoreq.k.ltoreq.N _e,c_k is the weight coefficient of the kth theoretical projection data.

12. The method according to claim 9 or 11, wherein the calibrating the energy spectrum parameter according to the optimization function to obtain the optimized energy spectrum parameter specifically comprises:

and calculating N _e optimization weight coefficients when the deviation value is the minimum value by solving the optimization function, and taking the N _e optimization weight coefficients as the optimized energy spectrum parameters.

13. The method according to claim 12, wherein the acquiring energy spectrum information based on the optimized energy spectrum parameters specifically comprises:

And calculating the energy spectrum information by adopting a weighted summation mode according to the N _e optimized weight coefficients and the N _e basic energy spectrums.

14. The method of any of claims 1-13, wherein the spectral calibration phantom comprises a plurality of portions each composed of a plurality of materials, any two of the plurality of materials differing in at least one of the following properties: density, atomic number.

15. The method of any of claims 1-14, wherein the calibration system comprises a rotary table on which the spectrum calibration phantom is located;

the acquiring, by the detector, rays passing through the scanning area to obtain detector data includes:

Controlling the ray source to emit rays;

controlling the rotary table to rotate so as to drive the energy spectrum calibration die body to rotate for m circles, wherein m is a positive integer greater than or equal to 1; and

During the rotation of the spectral calibration phantom m turns, the detector collects radiation emitted from the radiation source and passing through the scan region.

16. The method of any of claims 1-15, wherein the calibration system comprises a lift table on which the spectrum calibration phantom is located;

Controlling the ray source to emit rays;

And controlling the lifting table to lift so as to drive the energy spectrum calibration die body to lift.

17. The method of any of claims 1-16, wherein the radiation source comprises N _s targets, the N _s targets being spaced apart along a first direction, wherein N _s is a positive integer greater than or equal to 2;

Controlling the N _s targets to emit rays according to a set sequence; and

During the process that the N _s targets emit rays according to a set sequence, the detector collects the rays emitted from the ray source and passing through the scanning area.

18. The method of any of claims 1-13, wherein the calibration system comprises a rotary table on which the spectrum calibration phantom is located; the ray source comprises N _s targets, the N _s targets are distributed at intervals along a first direction, wherein N _s is a positive integer greater than or equal to 2;

Controlling the N _s targets to emit rays according to a set sequence;

And in the process that the N _s targets emit rays according to a set sequence and the energy spectrum calibration die body rotates for m circles, the detector acquires the rays emitted from the ray source and passing through the scanning area.

19. The method of claim 2, wherein the preset conditions include at least one of the following conditions:

In the first cycle process, the deviation of the energy spectrum information acquired in two adjacent times is smaller than a preset threshold value; and

In the first cycle, the number of iterations reaches a preset number.

20. The method of claim 6, wherein the factors that affect the absorption spectrum of the detector include at least one of the following:

The exit angle of the ray;

the incidence angle of the radiation onto the detector;

the energy spectrum distribution of a target spot of the ray source; and

Occlusion in the path of the radiation from the source to the detector.

21. A calibration system for energy spectrum calibration of a scanning imaging device, wherein the calibration system comprises:

Calibrating a device main body;

The energy spectrum calibration die body is arranged on the calibration device main body;

The driving piece is used for driving the energy spectrum calibration die body to move; and

A controller configured to perform energy spectrum calibration of a scanning imaging device according to the calibration method of any one of claims 1-20.

22. A calibration system for energy spectrum calibration of a scanning imaging device, wherein the calibration system comprises:

a base;

a rotary table connected to the base;

the energy spectrum calibration die body is arranged on the rotary table and is positioned on the rotary table; and

The driving piece is used for driving the rotary table to rotate so as to drive the energy spectrum calibration die body to rotate,

Wherein the spectral calibration phantom comprises a plurality of portions each composed of a plurality of materials, any two of the plurality of materials differing in at least one of the following properties: density, atomic number.

23. The system of claim 22, wherein the calibration system further comprises: the lifting platform is connected to the base, and the rotating platform is arranged on the lifting platform.