CN102590234B - Dual-energy under-sampling substance identification system and method based on linear track scanning - Google Patents

Abstract

Disclosed are a dual-energy undersampling substance identification system and method based on linear trajectory scanning. Use the low-energy projection data obtained by the whole layer of low-energy detector array during the straight-line trajectory scanning process to perform CT reconstruction of the detected object, and use the regional image segmentation method in the CT reconstruction image to segment and mark the tomographic image according to the attenuation coefficient . At the same time, dual-energy material identification imaging is realized by using the projection data obtained by a few high-energy detectors arranged behind some low-energy detectors. Due to the use of a straight line trajectory, no rotation is required, so the mechanical design is simple and the inspection clearance rate is high; since only a few dual-energy detectors are used, the system cost is low.

Description

System and method for dual-energy undersampling substance identification based on linear trajectory scanning

This application is a divisional application of the invention patent application 200910085923.0 filed on May 27, 2009, entitled "Dual Energy Undersampling Substance Identification System and Method Based on Linear Trajectory Scanning".

technical field

The invention relates to radiation imaging technology, in particular to a dual-energy undersampling material identification system and method based on linear trajectory scanning, which allows fast security inspection of objects.

Background technique

In recent years, due to the increasingly serious smuggling of dangerous goods such as drugs, explosives, and weapons, a security inspection system that can identify substances at low cost and quickly is of great significance in the field of combating contraband smuggling and other security fields.

At present, the dual-energy imaging system is the mainstream of the security inspection system capable of material identification, which is mainly divided into two categories. One type is a dual-energy perspective imaging system, but since the system reconstructs overlapping images of front and rear objects, it is easy to misreport or miss smuggled contraband. The other is a dual-energy CT imaging system based on circular or helical trajectories. Although this system can solve the problem of overlapping objects, it cannot be widely used due to complex system design, long scanning time, and high cost.

As shown in FIG. 1 , Patent Document 1 (CN1971620A) proposes a linear trajectory CT imaging system, which makes it possible for CT imaging technology to be used for rapid security inspection. However, due to the limitations of the CT system itself, the method proposed in this patent document can only reconstruct the shape information of the object and cannot perform material identification, so it is powerless on the issue of material identification of contraband in the suitcase. If all the detectors used for the straight-line scanning trajectory are replaced with dual-energy detectors, the system cost will be greatly increased, which is not acceptable.

Contents of the invention

The object of the present invention is to propose a dual-energy under-sampling material identification method and system based on linear trajectory scanning, which can perform dual-energy material identification at low cost and fast speed.

In one aspect of the present invention, a dual-energy undersampling material identification method based on straight-line trajectory scanning is proposed, including: performing a straight-line trajectory CT scan on the inspected object, and obtaining the first projection data through the first layer of array detectors to reconstruct The CT image of the object to be detected, and the second projection data obtained through the second layer of detector arrays arranged behind part of the first layer of array detectors; combining the first projection data and the second projection data to obtain dual can under-sampling data; according to the dual-energy under-sampling data, use the table look-up method to obtain the integral value of photoelectric coefficient and Compton coefficient; perform region segmentation on the CT image of the detected object, obtain multiple regions after segmentation and calculate the dual The length of the energy rays passing through each region; according to the length of the dual energy rays passing through each region, the integral value of the photoelectric coefficient and the integral value of the Compton coefficient, the Compton coefficient and the photoelectric coefficient are solved by using the dual-energy pre-processing double-effect decomposition and reconstruction method ; at least calculating the atomic number of the substance in each divided area based on the Compton coefficient and the photoelectric coefficient; and identifying the substance of the inspected object based on at least the atomic number.

In another aspect of the present invention, a dual-energy undersampling material identification system based on linear trajectory scanning is proposed, including: a ray generating device, which generates a ray beam to penetrate the object to be inspected; a mechanical transmission control part, including a transmission device And the control system is used to realize the linear trajectory scanning of the inspected object; the data acquisition subsystem, including the array detector, is used to obtain the transmission projection data of the ray beam penetrating the inspected object; the main control and data processing computer control The above-mentioned ray generating device, the mechanical transmission control part and the data acquisition subsystem perform straight-line trajectory CT scanning on the object to be inspected, obtain the first projection data through the first layer of array detectors to reconstruct the CT image of the object to be inspected, and set in Part of the second-layer detector array behind the first-layer array detectors obtains second projection data; wherein the main control and data processing computer includes: combining the first projection data and the second projection data to obtain dual projection data under partial angles A device capable of undersampling data; a device for obtaining the integrated value of the photoelectric coefficient and the integrated value of the Compton coefficient by using a table look-up method according to the dual-energy undersampled data; performing regional segmentation on the CT image of the detected object to obtain multiple segments after segmentation region and calculate the length of the dual-energy ray passing through each region; according to the length of the dual-energy ray passing through each region, the integral value of the photoelectric coefficient and the integral value of the Compton coefficient, the dual-energy pre-processing double-effect decomposition and reconstruction method is used to solve the Kang A device for Compton coefficient and photoelectric coefficient; a device for calculating at least the atomic number of a substance in each divided area based on the Compton coefficient and a photoelectric coefficient; a device for identifying the substance of an object under inspection based at least on the atomic number.

Compared with the traditional dual-energy perspective imaging system, the method and system of the embodiments of the present invention solve the problem of overlapping objects in perspective imaging.

Compared with the traditional circular or helical trajectory dual-energy CT imaging system, the method and system of the embodiment of the present invention utilizes straight-line trajectory scanning and only adds a small number of high-energy detectors behind the low-energy detectors for linear trajectory scanning to perform dual-energy data Sampling can realize low-cost and fast dual-energy material identification of the measured object.

At the same time, the system can also be applied in the field of non-destructive testing.

Description of drawings

From the following detailed description in conjunction with the accompanying drawings, the above-mentioned features and advantages of the present invention will be more apparent, wherein:

Fig. 1 is a schematic diagram describing a linear trajectory scanning process according to the prior art;

FIG. 2 is a schematic plan view describing the identification process of dual-energy undersampling substances based on linear trajectories according to an embodiment of the present invention;

3A is a schematic structural diagram of a dual-energy undersampling substance identification system according to an embodiment of the present invention;

3B is a schematic structural diagram of the main control and data processing computer in the dual-energy undersampling substance identification system according to an embodiment of the present invention;

4 is a detailed flow chart of a dual-energy undersampling substance identification method based on linear trajectory scanning according to an embodiment of the present invention;

Figure 5 shows a look-up table for the integral of the photoelectric coefficient and the integral of the Compton coefficient; and

FIG. 6 is a schematic diagram describing calculation of ray lengths passing through segmented regions.

Detailed ways

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the drawings, the same reference numerals are used to designate the same or similar components, although shown in different drawings. For clarity and conciseness, detailed descriptions of known functions and constructions incorporated herein will be omitted since they would otherwise obscure the subject matter of the present invention.

Fig. 2 is a schematic plan view describing the process of dual-energy undersampling substance identification based on straight-line trajectories according to an embodiment of the present invention. As shown in FIG. 2 , the dual-energy undersampling substance identification imaging system according to the embodiment of the present invention adopts a CT image-based dual-energy projection undersampling substance identification method. In the system of the embodiment of the present invention, in the data acquisition subsystem 13, a few high-energy detector units are arranged behind the entire layer of low-energy detector arrays. The inspected object moves linearly between the ray source 11 and the detector array.

In this way, the low-energy projection data obtained by the entire layer of low-energy detector arrays during the straight-line trajectory scanning process is used to perform CT reconstruction on the detected object, and the regional image segmentation method is used in the CT reconstruction image to segment the tomographic image according to the attenuation coefficient. to mark. At the same time, the projection data obtained by a few high-energy detectors arranged behind some low-energy detectors are used to realize dual-energy undersampling material identification imaging.

Fig. 3A is a schematic structural diagram of a dual-energy undersampling substance identification system according to an embodiment of the present invention. As shown in FIG. 3A , the dual-energy undersampling substance identification system of the embodiment of the present invention mainly consists of the following parts.

The ray generating device 11 includes an X-ray accelerator, an X-ray machine or a radioactive isotope, and corresponding auxiliary equipment.

The mechanical transmission control part 12 includes a transmission device and a control system for transmitting the object to be inspected (or the source and the detector). The motion of the object and the motion of the source and the detector are relative motions and are equivalent.

The data acquisition subsystem 13 mainly includes two layers of high and low energy detectors (usually arranged equidistantly, or equiangularly arranged) for acquiring low energy transmission projection data. Several high-energy detectors are placed behind the middle low-energy detectors to obtain dual-energy projection data. The subsystem 13 also includes a readout circuit and logic control unit for projection data on the detector. The detector can be a solid detector, a gas detector, or a semiconductor detector.

Two layers of high- and low-energy detectors (consisting of a whole layer of low-energy detector units and a few high-energy detector units) are located opposite to the ray source and parallel to the conveyor belt. The detector should have as large an angle as possible with the ray source in the horizontal direction, and cover the object in the vertical direction. For example, the detector array is placed on the opposite side of the source, and the horizontal angle θ of the rays is required to be above 90 degrees.

During data collection, the sampling interval is required to be uniform on the time axis, the object to be inspected must also move at a uniform speed, and all array detectors are required to collect synchronously.

The main control and data processing computer 14 sends and receives signals through the control signal and the data transmission line 15, and is responsible for the main control of the CT system operation process, including mechanical control, electrical control, safety chain control, etc., and the information obtained by the data acquisition subsystem 13 The projection data is processed, and the tomographic image of the object to be measured is reconstructed by the linear filter back projection method, the image is segmented, and the atomic number and electron density images of each block area are displayed on the display. Computers can be high-performance individual PCs, or workstations or clusters. The display can be either a CRT traditional display or a liquid crystal display.

FIG. 3B shows a block diagram of the main control and data processing computer 14 shown in FIG. 3A. As shown in FIG. 3B , the data collected by the data collection subsystem 13 is stored in the memory 141 . A read only memory (ROM) 142 stores configuration information and programs for the computer data processor. A random access memory (RAM) 143 is used for temporarily storing various data during the working process of the processor 146 . In addition, the memory 141 also stores computer programs for data processing and a pre-programmed database, the database stores relevant information of various known objects, photoelectric coefficient integral and Compton coefficient integral lookup table, atomic number lookup table Or the atomic number classification curve, and information such as the electron density of the substance are used for comparison with the attributes such as atomic number and electron density of each region in the inspected object calculated by the processor 146 . The internal bus 144 connects the above-mentioned memory 141 , read-only memory 142 , random access memory 143 , input device 145 , processor 146 and display device 147 .

After the operation command input by the user through the input device 145 such as keyboard and mouse, the processor 146 in the computer program executes a predetermined data processing algorithm, and after obtaining the data processing result, it is displayed on a display such as an LCD display. on the display device 147, or directly output the processing results in the form of hard copy.

The execution process of the method in the embodiment of the present invention will be described in detail below with reference to FIG. 4 . Fig. 4 is a detailed flow chart of a dual-energy undersampling substance identification method based on linear trajectory scanning according to an embodiment of the present invention.

In step S11, the main control and data processing computer 14 controls the ray generating device 11, the mechanical transmission control part 12, and the data acquisition subsystem 13, and uses the linear filter back projection method to sample the projection data obtained in the first layer of the detection array for CT Reconstruct to obtain a CT tomographic image of the detected object. At the same time, the projection data obtained by a small number of detectors in the second layer is used to realize undersampling of dual-energy projection data, and then the table can be looked up to obtain the photoelectric coefficient integral and Compton coefficient integral value A corresponding to each pair of high and low energy projections.

As shown in Figure 5, the horizontal and vertical coordinates P1 and P2 respectively represent the projections obtained under high and low energy conditions, and at each coordinate point in the table there are photoelectric coefficient integrals and Compton values corresponding to the high and low energy projection data at this time. The value of the coefficient integral A. That is, when the high and low energy projection data are known, the values of the corresponding photoelectric coefficient integral and Compton coefficient integral A can be obtained by looking up this table. The above-mentioned lookup table is disclosed in existing literature (“A Volumetric Object Detection Framework with Dual-Energy CT” IEEE NSS/MIC 2008).

In step S12, the main control and data processing computer 14 divides the CT reconstructed image into different regions according to the difference in gray level by using a method based on region segmentation and marks them. For example, the above region segmentation-based methods are improved one-way split-merge segmentation methods.

As shown in Figure 6, l _j (i) represents the length of the i-th ray passing through the j-th cut area; T(i) represents the projection data. In this way, in step S13, according to the dual-energy projection sampling information obtained in step S11, calculate the plane length l _j (i) of the beam corresponding to the i-th group of projection data passing through the j-th block area (if it is a spiral trajectory, the first The spatial length l _j (i)) of the beam corresponding to the i group of projection data passing through the jth block area.

In step S14, the main control and data processing computer 14 establishes a system of equations A=∑a·l by using the dual-energy pre-processing double-effect decomposition and reconstruction method, where a represents the Compton coefficient and the photoelectric coefficient. Let a total of M sets of DR dual-energy transmission data be obtained from the scanning angle of the second week, and the CT image is divided into N blocks of marked areas, and T _H (i) and T _L (i) are used to represent the i-th group of high-energy and low-energy projection data . The double-effect decomposition of the linear attenuation coefficient is carried out by formula (1):

μ(E)＝a ₁ f _ph (E)+a ₂ f _KN (E)...(1)

Furthermore, the high and low energy transparency can be expressed by the following formulas (2) and (3):

${\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; h</span>}}<span\; class="notranslate">\; =</span>\underset{{\mathrm{<span\; class="notranslate">\; E.</span>}}_{\mathrm{<span\; class="notranslate">\; h</span>}}}{<span\; class="notranslate">\; \&Integral;</span>}{\mathrm{<span\; class="notranslate">\; D.</span>}}_{\mathrm{<span\; class="notranslate">\; h</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; E.</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; exp</span>}<span\; class="notranslate">\; (</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; \&Integral;</span>\mathrm{<span\; class="notranslate">\; \&mu;</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; E.</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; dl</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; E</span>}<span\; class="notranslate">\; =</span>\underset{{\mathrm{<span\; class="notranslate">\; E.</span>}}_{\mathrm{<span\; class="notranslate">\; h</span>}}}{<span\; class="notranslate">\; \&Integral;</span>}{\mathrm{<span\; class="notranslate">\; D.</span>}}_{\mathrm{<span\; class="notranslate">\; h</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; E.</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; exp</span>}<span\; class="notranslate">\; (</span><span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; A</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; pH</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; E.</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; A</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; KN</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; E.</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; E</span>}<span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$

${\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; L</span>}}<span\; class="notranslate">\; =</span>\underset{{\mathrm{<span\; class="notranslate">\; E.</span>}}_{\mathrm{<span\; class="notranslate">\; L</span>}}}{<span\; class="notranslate">\; \&Integral;</span>}{\mathrm{<span\; class="notranslate">\; D.</span>}}_{\mathrm{<span\; class="notranslate">\; L</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; E.</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; exp</span>}<span\; class="notranslate">\; (</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; \&Integral;</span>\mathrm{<span\; class="notranslate">\; \&mu;</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; E.</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; dl</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; E</span>}<span\; class="notranslate">\; =</span>\underset{{\mathrm{<span\; class="notranslate">\; E.</span>}}_{\mathrm{<span\; class="notranslate">\; L</span>}}}{<span\; class="notranslate">\; \&Integral;</span>}{\mathrm{<span\; class="notranslate">\; D.</span>}}_{\mathrm{<span\; class="notranslate">\; L</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; E.</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; exp</span>}<span\; class="notranslate">\; (</span><span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; A</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; pH</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; E.</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; A</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}{\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; KN</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; E.</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; E</span>}<span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$

Among them, f _ph (E) represents the dependence of the photoelectric cross-section on the ray energy E; f _KN (E) describes the relationship between the Compton boundary cross-section and the photon energy; D _H (E) represents the X-ray machine ray measured by the high-energy detector Energy spectrum; D _L (E) represents the X-ray energy spectrum measured by the low-energy detector; a ₁ represents the photoelectric coefficient; a ₂ represents the Compton coefficient; A ₁ represents the integral of the photoelectric coefficient; A ₂ represents the Compton coefficient Integral, as shown in the following formula (4):

A=∫adl...(4)

Thus constructing the system of linear equations:

A＝∑a·l……(5)

Specifically, solve a ₁ and a ₂ with the following equations (6) and (7):

$\left[\begin{array}{ccccc}{\mathrm{<span\; class="notranslate">\; l</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>& {\mathrm{<span\; class="notranslate">\; l</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>& <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>& {\mathrm{<span\; class="notranslate">\; l</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>\\ {\mathrm{<span\; class="notranslate">\; l</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>& <span\; class="notranslate">\; .</span>& & & <span\; class="notranslate">\; .</span>\\ <span\; class="notranslate">\; .</span>& & <span\; class="notranslate">\; .</span>& & <span\; class="notranslate">\; .</span>\\ <span\; class="notranslate">\; .</span>& & & <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>\\ {\mathrm{<span\; class="notranslate">\; l</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; )</span>& <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>& {\mathrm{<span\; class="notranslate">\; l</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; )</span>\end{array}\right]\left[\begin{array}{c}{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 1,1</span>}}\\ {\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 1,2</span>}}\\ <span\; class="notranslate">\; .</span>\\ <span\; class="notranslate">\; .</span>\\ {\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; N</span>}}\end{array}\right]<span\; class="notranslate">\; =</span>\left[\begin{array}{c}{\mathrm{<span\; class="notranslate">\; A</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>\\ {\mathrm{<span\; class="notranslate">\; A</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>\\ <span\; class="notranslate">\; .</span>\\ <span\; class="notranslate">\; .</span>\\ {\mathrm{<span\; class="notranslate">\; A</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; )</span>\end{array}\right]<span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 6</span>}<span\; class="notranslate">\; )</span>$

$\left[\begin{array}{ccccc}{\mathrm{<span\; class="notranslate">\; l</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>& {\mathrm{<span\; class="notranslate">\; l</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>& <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>& {\mathrm{<span\; class="notranslate">\; l</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>\\ {\mathrm{<span\; class="notranslate">\; l</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>& <span\; class="notranslate">\; .</span>& & & <span\; class="notranslate">\; .</span>\\ <span\; class="notranslate">\; .</span>& & <span\; class="notranslate">\; .</span>& & <span\; class="notranslate">\; .</span>\\ <span\; class="notranslate">\; .</span>& & & <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>\\ {\mathrm{<span\; class="notranslate">\; l</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; )</span>& <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>& <span\; class="notranslate">\; .</span>& {\mathrm{<span\; class="notranslate">\; l</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; )</span>\end{array}\right]\left[\begin{array}{c}{\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; 1</span>}}\\ {\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 2,2</span>}}\\ <span\; class="notranslate">\; .</span>\\ <span\; class="notranslate">\; .</span>\\ {\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; N</span>}}\end{array}\right]<span\; class="notranslate">\; =</span>\left[\begin{array}{c}{\mathrm{<span\; class="notranslate">\; A</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>\\ {\mathrm{<span\; class="notranslate">\; A</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>\\ <span\; class="notranslate">\; .</span>\\ <span\; class="notranslate">\; .</span>\\ {\mathrm{<span\; class="notranslate">\; A</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; )</span>\end{array}\right]<span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 7</span>}<span\; class="notranslate">\; )</span>$

In step S15, the least square method is used to solve the equation system constructed in step S14, and a is calculated, namely, the photoelectric coefficient X ₁ and the Compton coefficient a ₂ . Then, in step S16, calculate atomic number and electron density by formula (8) and (9):

${\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; \&ap;</span>{\mathrm{<span\; class="notranslate">\; K</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}}\frac{{\mathrm{<span\; class="notranslate">\; <figure-callout\; id="2"\; label="N\; A"\; filenames="HDA0000114669690000051.png"\; state="\{\{state\}\}">N</figure-callout></span><figure-callout\; id="2"\; label="N\; A"\; filenames="HDA0000114669690000051.png"\; state="\{\{state\}\}">\; </figure-callout>}}_{\mathrm{<span\; class="notranslate">\; </span>}}}{\mathrm{<span\; class="notranslate">\; 2</span>}}{\mathrm{<span\; class="notranslate">\; \&rho;Z</span>}}^{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; \&ap;</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 8</span>}<span\; class="notranslate">\; )</span>$

${\mathrm{<span\; class="notranslate">\; a</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; \&ap;</span>{\mathrm{<span\; class="notranslate">\; K</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}}\frac{{\mathrm{<span\; class="notranslate">\; <figure-callout\; id="2"\; label="N\; A"\; filenames="HDA0000114669690000051.png"\; state="\{\{state\}\}">N</figure-callout></span><figure-callout\; id="2"\; label="N\; A"\; filenames="HDA0000114669690000051.png"\; state="\{\{state\}\}">\; </figure-callout>}}_{\mathrm{<span\; class="notranslate">\; </span>}}}{\mathrm{<span\; class="notranslate">\; 2</span>}}\mathrm{<span\; class="notranslate">\; \&rho;</span>}<span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; \&Center\; Dot;</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 9</span>}<span\; class="notranslate">\; )</span>$

Among them, Z represents atomic number, ρ represents electron density, N _A represents Avogadro’s constant, K ₁ is a constant that includes all other coefficients that have nothing to do with ray energy and material parameters, and K ₂ is a constant that includes all other coefficients that are not related to ray energy Coefficients independent of material parameters. In this way, the atomic number and electron density of the substance in the block area can be obtained, so as to effectively identify the substance. For example, methods based on look-up tables or classification curves use atomic numbers to identify substances in various regions of the inspected object. According to another embodiment, the calculated atomic number and electron density can be used simultaneously to identify the substance.

As mentioned above, the dual-energy undersampling material identification imaging system based on straight-line trajectory in the embodiment of the present invention adopts the dual-energy projection under-sampling material identification method based on CT images, uses straight-line trajectory scanning, and uses only a few dual-energy detection The device can realize the material identification of the detected object. Since the linear trajectory is used and no rotation is required, the mechanical design is simple and the inspection pass rate is high; since only a few dual-energy detectors are used, the system cost is low.

The above description is only used to realize the embodiment of the present invention, and those skilled in the art should understand that any modification or partial replacement that does not depart from the scope of the present invention should belong to the scope defined by the claims of the present invention. Therefore, The protection scope of the present invention should be based on the protection scope of the claims.

Claims (6)

1. the Dual-energy under-sampled matter identification method based on straight path scanning, comprising:

Inspected object is carried out to straight path CT scan, by ground floor detector array, obtain the first data for projection to rebuild the CT image of object to be detected, and obtain the second data for projection by the second layer detector array being arranged on after part ground floor detector array, wherein, ground floor detector array is low energy detector array, and second layer detector array is high energy array detector; Object to be detected between radiographic source and detector array along a direction rectilinear motion;

Combine the first data for projection and the second data for projection, to obtain the dual-energy under-sampling data under Partial angle;

According to dual-energy under-sampling data acquisition, by the method for tabling look-up, obtain photoelectric coefficient integrated value and Compton Coefficient Integrals value;

Deployment area dividing method carries out Region Segmentation and mark is carried out in the region of cutting apart the CT image of object to be detected according to the difference of attenuation coefficient or gray scale, and a plurality of regions after being cut apart and calculating dual intensity ray are through the length of regional;

Length according to dual intensity ray through regional, photoelectric coefficient integrated value and Compton Coefficient Integrals value, utilize dual intensity pre-treatment economic benefits and social benefits should decompose method for reconstructing and solve Compton coefficient and photoelectric coefficient;

Based on Compton coefficient and photoelectric coefficient, at least calculate the atomic number of material in the region of respectively cutting apart;

At least based on atomic number, the material of inspected object is identified.

2. the method for claim 1, utilizes look-up table to determine the material in each cut zone of inspected object.

3. the method for claim 1, utilizes the classification curve creating in advance to determine the material in each cut zone of inspected object.

4. the dual-energy under-sampling substance recognition system based on straight path scanning, comprising:

Ray generating device, generation will penetrate the beam of inspected object;

Mechanical drive control section, comprises gearing and control system, for realizing the straight path scanning to inspected object;

Data acquisition subsystem, comprises detector array, for obtaining the transmission projection data of the beam that penetrates inspected object;

Main control and data handling machine, control above-mentioned ray generating device, mechanical drive control section and data acquisition subsystem, inspected object is carried out to straight path CT scan, by ground floor detector array, obtain the first data for projection to rebuild the CT image of object to be detected, and obtain the second data for projection by the second layer detector array being arranged on after part ground floor detector array, wherein, ground floor detector array is low energy detector array, and second layer detector array is high energy array detector; Object to be detected between radiographic source and detector array along a direction rectilinear motion;

Wherein said main control and data handling machine comprise:

Combine the first data for projection and the second data for projection, to obtain the device of the dual-energy under-sampling data under Partial angle;

According to dual-energy under-sampling data acquisition, by the method for tabling look-up, obtain the device of photoelectric coefficient integrated value and Compton Coefficient Integrals value;

Deployment area dividing method carries out Region Segmentation and mark is carried out in the region of cutting apart the CT image of object to be detected according to the difference of attenuation coefficient or gray scale, and a plurality of regions after being cut apart and calculating dual intensity ray are through the device of the length of regional;

Length according to dual intensity ray through regional, photoelectric coefficient integrated value and Compton Coefficient Integrals value, utilize dual intensity pre-treatment economic benefits and social benefits should decompose the device that method for reconstructing solves Compton coefficient and photoelectric coefficient;

Based on Compton coefficient and photoelectric coefficient, at least calculate the device of the atomic number of material in the region of respectively cutting apart;

The device of at least based on atomic number, the material of inspected object being identified.

5. system as claimed in claim 4, wherein utilizes look-up table to determine the material in each cut zone of inspected object.

6. system as claimed in claim 4, utilizes the classification curve creating in advance to determine the material in each cut zone of inspected object.

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