CN113237901A - Biological feature recognition system and biological feature recognition method - Google Patents
Biological feature recognition system and biological feature recognition method Download PDFInfo
- Publication number
- CN113237901A CN113237901A CN202110495666.9A CN202110495666A CN113237901A CN 113237901 A CN113237901 A CN 113237901A CN 202110495666 A CN202110495666 A CN 202110495666A CN 113237901 A CN113237901 A CN 113237901A
- Authority
- CN
- China
- Prior art keywords
- sample
- ray
- displacement table
- ray tube
- biometric identification
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 19
- 238000006073 displacement reaction Methods 0.000 claims abstract description 51
- 238000003384 imaging method Methods 0.000 claims abstract description 35
- 238000001514 detection method Methods 0.000 claims abstract description 25
- 230000001681 protective effect Effects 0.000 claims abstract description 11
- 238000004891 communication Methods 0.000 claims abstract description 5
- 238000001816 cooling Methods 0.000 claims description 9
- 238000010586 diagram Methods 0.000 claims description 7
- 238000013519 translation Methods 0.000 claims description 7
- 230000004907 flux Effects 0.000 claims description 5
- XAGFODPZIPBFFR-UHFFFAOYSA-N aluminium Chemical compound [Al] XAGFODPZIPBFFR-UHFFFAOYSA-N 0.000 claims description 4
- 229910052782 aluminium Inorganic materials 0.000 claims description 4
- 229920003229 poly(methyl methacrylate) Polymers 0.000 claims description 4
- 239000004926 polymethyl methacrylate Substances 0.000 claims description 4
- 239000000523 sample Substances 0.000 abstract description 125
- 239000012472 biological sample Substances 0.000 abstract description 14
- 238000010521 absorption reaction Methods 0.000 description 15
- 238000002591 computed tomography Methods 0.000 description 14
- 235000020234 walnut Nutrition 0.000 description 14
- 241000251468 Actinopterygii Species 0.000 description 9
- 241000758789 Juglans Species 0.000 description 9
- 235000009496 Juglans regia Nutrition 0.000 description 9
- 238000007689 inspection Methods 0.000 description 8
- 238000004445 quantitative analysis Methods 0.000 description 7
- 241000196324 Embryophyta Species 0.000 description 6
- 238000012360 testing method Methods 0.000 description 6
- 241000758791 Juglandaceae Species 0.000 description 5
- 238000000605 extraction Methods 0.000 description 5
- 238000011084 recovery Methods 0.000 description 5
- 241001465754 Metazoa Species 0.000 description 4
- 238000009826 distribution Methods 0.000 description 4
- 239000011521 glass Substances 0.000 description 4
- 239000000126 substance Substances 0.000 description 3
- 241000238631 Hexapoda Species 0.000 description 2
- 210000000988 bone and bone Anatomy 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 230000001427 coherent effect Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000001914 filtration Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000013441 quality evaluation Methods 0.000 description 2
- 230000011218 segmentation Effects 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- 230000003187 abdominal effect Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 210000004556 brain Anatomy 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 239000010794 food waste Substances 0.000 description 1
- 210000001035 gastrointestinal tract Anatomy 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 230000008676 import Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000009659 non-destructive testing Methods 0.000 description 1
- 230000005855 radiation Effects 0.000 description 1
- 241000894007 species Species 0.000 description 1
- 238000003860 storage Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N23/00—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00
- G01N23/02—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material
- G01N23/04—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material and forming images of the material
Landscapes
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Analysing Materials By The Use Of Radiation (AREA)
Abstract
The invention relates to a biological characteristic recognition system and a biological characteristic recognition method, wherein the biological characteristic recognition system comprises an X-ray detection device and a control device, the X-ray detection device is arranged in a sealed protective box and comprises a base, a guide rail is arranged on the base, a first displacement table, a second displacement table and a third displacement table are sequentially arranged in a sliding manner along the length direction of the guide rail, an X-ray tube is arranged on the first displacement table, a sample rotary table is arranged on the second displacement table, and a detector is arranged on the third displacement table; the control device comprises a main controller and an X-ray generation control assembly, wherein the main controller is connected with the X-ray generation control assembly, the sample rotary table and the three displacement tables through cables or communication respectively. The biological characteristic identification system of the invention adopts the X-ray tube with micron focus as the light source to obtain the X-ray beam with better spatial coherence, thereby realizing the imaging detection of the weakly-absorbed biological sample based on the phase contrast and improving the spatial resolution.
Description
Technical Field
The invention relates to the field of nondestructive testing equipment, in particular to a biological feature recognition system and a biological feature recognition method.
Background
National biosafety is crucial to the protection of endangered animal and plant species and the entire ecosystem, and customs is the leading position for protecting biosafety. In recent years, the number of animals and plants in import and export of China increases year by year, domestic rare animal and plant resources are rare and rare, and the task of protecting the domestic rare animal and plant special biological resources is increasingly difficult.
Because the X-ray has strong penetrability, the internal structure information of samples such as insects, plants and the like can be obtained, and therefore, the security inspection equipment based on the X-ray is widely applied to various stations, ports and airports. As shown in fig. 11, the conventional X-ray security inspection apparatus includes a protective cover 100, a conveyor belt 200, an X-ray tube 300, an L-shaped detector 400, an X-ray generation device 500, a controller 600, and a computer 700, wherein the conveyor belt 200 is disposed through the protective cover 100, a sample passes through the protective cover 100 under the driving of the conveyor belt 200, the X-ray tube 300 is disposed on the top of the protective cover 100 and faces the sample on the conveyor belt 200, the L-shaped detector 400 is disposed in the protective cover 100, the X-ray tube 300 emits X-rays to the sample and forms an image on the L-shaped detector 400, the controller 600 is electrically connected to the conveyor belt 200 and the L-shaped detector 400, and the computer 700 is electrically connected to the X-ray generation device 500 and the controller 600, respectively. The existing X-ray security inspection equipment has the following defects that the existing X-ray security inspection equipment cannot detect a biological sample: firstly, the article is detected by adopting X-ray absorption imaging, and special biological resources such as insects, medicinal plants, wiggles and the like mainly comprise low-Z substances, and the X-ray absorption contrast generated by the low-Z substances is very weak, so that the imaging method based on the absorption contrast cannot effectively detect the weakly-absorbed special biological resource sample; secondly, the distances between an X-ray source, a sample and a detection system of the conventional X-ray security inspection equipment are fixed and invariable, and cannot be adjusted according to different samples, so that parameters such as imaging contrast, resolution and the like cannot be correspondingly optimized and adjusted to meet the detection requirements of different types of samples; finally, the existing security inspection equipment mainly judges the sample types based on the information of the two-dimensional absorption image, and cannot identify different producing areas or quality grades of the same sample or identify the truth of the samples belonging to different species.
Computed Tomography (CT) is an imaging technique for obtaining cross-sectional information of an object by performing X-ray projection measurements of the object at different angles, and can truly reproduce three-dimensional structural information of the inside of the object. When the existing X-ray security inspection equipment is used for detecting, the position of a sample on a conveyor belt is fixed, and 360-degree rotation cannot be performed, so that only a two-dimensional projection image of the sample at a certain angle can be shot, CT of the sample cannot be shot, and a three-dimensional structure of the sample cannot be obtained.
Disclosure of Invention
The invention aims to provide a biological characteristic identification system and a biological characteristic identification method, which are used for detecting a biological sample by adopting an X-ray phase contrast imaging method so as to realize clear imaging of a weakly-absorbed biological sample.
It is known that when X-rays pass through a substance, the absorption of X-rays is accompanied by the transmission and refraction of X-rays. The X-ray phase contrast microscopic imaging technology utilizes the change of intensity distribution caused by the phase change of X-rays after the X-rays penetrate through a sample to determine the internal structure information of the sample. That is, when the incident light satisfies a certain condition, the boundaries of different components in the sample can be directly reflected on the intensity distribution, i.e., the phase information of the sample can be detected by the spatially coherent hard X-ray. The interaction of X-rays with matter is generally expressed using a complex refractive index n:
n＝1-δ-iβ
where δ is the phase term and β is the absorption term, the phase term is typically 3 orders of magnitude greater than the absorption term. This means that the modulation effect of the object on the X-ray phase is more obvious than the absorption, and the high-sensitivity imaging of the fine structure of the weakly-absorbing sample can be obtained by utilizing the phase information carried after the X-ray penetrates through the sample.
Since the recording of the phase is achieved by local light interference, phase contrast imaging has a high requirement for the spatial coherence of the X-ray source. Ideally a parallel or point source of light is completely spatially coherent, but in practice any source has a spatial dimension. In the case of non-point source illumination, the coherence length d at the object plane can be expressed as:
wherein λ is the wavelength of the light source, Z1σ is the light source spot size, which is the distance from the light source to the sample. The smaller the light source size, the better the spatial coherence of the generated X-rays. In addition, the spatial resolution of the imaging depends largely on the size of the light source, and theoretically, the smaller the light source size, the higher the spatial resolution.
Based on this, the present invention provides in one aspect a biometric identification system comprising:
an X-ray detection device and a control device, wherein the X-ray detection device is arranged in a sealed protective box,
the X-ray detection device comprises a base, wherein a guide rail is arranged on the base, a first displacement table, a second displacement table and a third displacement table are sequentially arranged in a sliding manner along the length direction of the guide rail, an X-ray tube is arranged on the first displacement table, a sample rotary table is arranged on the second displacement table, and a detector is arranged on the third displacement table;
the control device comprises a main controller and an X-ray generation control assembly, wherein the main controller is connected with the X-ray generation control assembly, the sample rotary table, the first displacement table, the second displacement table and the third displacement table through cables or communication respectively.
Furthermore, a support is arranged between the first displacement table and the second displacement table, the support is arranged on the guide rail in a sliding mode, and a filtering assembly is arranged on the support.
Further, the filtering component comprises polymethyl methacrylate filters and aluminum sheet filters with different thicknesses.
Furthermore, the X-ray generation control assembly comprises a high-voltage generator, a vacuum device and a water-cooling circulating device, wherein the high-voltage generator is electrically connected with two poles of the X-ray tube, and the vacuum device and the water-cooling circulating device are connected with the X-ray tube.
Further, the focus size of the X-ray tube is in the order of micrometers.
Further, the master controller is a computer.
Further, the master controller is connected with a remote database through a network.
Another aspect of the present invention provides a biometric feature recognition method, including the steps of:
s1: constructing a biometric identification system according to any one of claims 1 to 7 and placing the sample to be tested on a sample turntable;
s2: turning on the X-ray source, and controlling the X-ray source to preheat by the control device;
s3: adjusting the distance from the sample to the X-ray tube and the distance from the detector to the sample, shooting two-dimensional projection images of the sample under different X-ray tube parameters, and then comparing to obtain the optimal contrast imaging condition;
s4: the exposure time of the projection is determined from the actual luminous flux of the biometric recognition system, and the detector is then controlled by the control device to take a two-dimensional projection of the sample.
Further, the method also comprises the following steps:
s5: the control device controls the sample rotary table to rotate 360 degrees according to a preset step length, and when the sample rotary table rotates one preset step length, the detector shoots a two-dimensional projection diagram of the sample, so that the two-dimensional projection diagram of the sample of 360 degrees is acquired;
s6: removing the sample from the sample holder, and taking a background image with the same exposure time as the two-dimensional projection image of the sample;
s7: turning off the X-ray tube, and shooting a dark current background image by using the same exposure time as the shooting of the projection image of the sample;
s8: performing three-dimensional slice reconstruction of the image by using the two-dimensional projection image, the background image and the dark current background image of the sample in the steps S5-S7;
s9: three-dimensional reconstruction is performed from the three-dimensional slice in step S8, thereby reproducing the internal structure information of the sample without loss.
Further, the preset step size in step S5 is 0.3 degrees.
According to the biological characteristic identification system, the X-ray tube with the micron focus is used as a light source, and an X-ray beam with good spatial coherence is obtained, so that the imaging detection of a weakly-absorbing biological sample based on phase contrast is realized, and the spatial resolution is improved; the distances from the sample to the X-ray tube and the sample to the detector can be adjusted by controlling the distances among the first displacement table, the second displacement table and the third displacement table, so that the optimal imaging contrast and the optimal magnification are adjusted according to different samples to meet the detection requirements of different samples; the rotation of the sample turntable and the shooting of the detector to the sample at different angles are controlled by the control device, the CT scanning of the sample can be realized, the signal stacking problem existing in a two-dimensional projection image is solved, and a high-resolution three-dimensional space structure of the biological sample can be obtained; according to the acquired CT data and the phase recovery algorithm, the extraction of the characteristic structure and the quantitative analysis of the sample are realized, and the micron-sized three-dimensional space structure of the detected sample and the quantitative information of the characteristic structure can be rapidly acquired without damage, so that the accuracy of biological safety detection is improved. The biological characteristic identification method adopts an imaging detection method based on phase contrast, and obtains the optimal contrast imaging condition by adjusting the distance from a sample to an X-ray tube and the distance from the sample to a detector; the three-dimensional space structure of the sample can be obtained through CT scanning, and the extraction, segmentation and quantitative analysis of the internal characteristic structure can be performed by combining a phase recovery algorithm, so that the identification of different varieties of samples or the quality evaluation of different samples can be realized.
Drawings
Fig. 1 is a schematic structural diagram of a biometric identification system according to an embodiment of the present invention;
FIG. 2 is an imaging schematic of the biometric identification system of the present invention;
3 a-3 d are the results of the JIMA card test at 50 times magnification, tube voltage of 60KV, and current of 100 muA, 200 muA, 300 muA, and 400 muA, respectively;
FIGS. 4 a-4 d are the results of the JIMA card test at a magnification of 100 times, a tube voltage of 60KV, and a current of 100 μ A, 200 μ A, 300 μ A, and 400 μ A, respectively;
FIGS. 5 a-5 d are the results of the JIMA card test at 150 times magnification with tube voltage of 60KV and current of 100 μ A, 200 μ A, 300 μ A, and 400 μ A, respectively;
FIGS. 6a and 6b are an absorption contrast projection and a phase contrast projection of a small fish, respectively;
fig. 7a and 7b are three-dimensional reconstruction results based on absorption contrast projection, wherein fig. 7a is a three-dimensional structure of bones and food residues in intestinal tract, and fig. 7b is an abdominal direction view; fig. 7c and 7d are three-dimensional reconstruction results based on phase contrast projections, wherein fig. 7c is a body surface structure and fig. 7d is a longitudinal sectional view;
FIG. 8 is a flowchart of a biometric identification method according to another embodiment of the invention;
fig. 9 a-9 d are three-dimensional reconstructed views of a walnut sample, wherein fig. 9a and 9b are three-dimensional rendered views, fig. 9c shows the structure of walnut shells and diaphragma, and fig. 9d shows the structure of walnut kernels;
fig. 10a and 10b are graphs of the results of three-dimensional quantitative analysis of walnuts in three different places of origin, wherein fig. 10a shows the average shell thickness and fig. 10b shows the kernel volume fraction.
Fig. 11 is a schematic structural diagram of a conventional X-ray security inspection apparatus.
Detailed Description
The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
Example one
As shown in fig. 1, an embodiment of the present invention provides a biological feature recognition system, which performs imaging detection on a weakly-absorbed biological sample based on X-ray phase contrast, and includes a sealed protective box 1, an X-ray detection device 2 and a control device 3, wherein the protective box 1 is used for preventing radiation of X-rays, the X-ray detection device 2 is disposed in the protective box 1, and includes a base 21, a guide rail 211 is disposed on the base 21, a first displacement table 22, a second displacement table 23 and a third displacement table 24 are sequentially disposed on the guide rail 211 along a length direction thereof, and sliders are disposed at bottoms of the three displacement tables, and are in sliding fit with the guide rail 211. Wherein the first displacement stage 22 is provided with an X-ray tube 27, the second displacement stage 23 is provided with a sample turntable 25 for supporting a sample to be measured thereon, and the third displacement stage 24 is provided with a detector 28. The control device 3 comprises a main controller 31 and an X-ray generation control assembly 32, wherein the main controller 31 is connected with the X-ray generation control assembly 32, the first displacement table 22, the second displacement table 23, the third displacement table 24 and the sample rotary table 25 through cables or communication respectively, in the embodiment, network communication connection is adopted, so that the X-ray tube 27 is controlled to emit X-rays, the displacement tables 22, 23 and 24 freely slide on the guide rail 211 and the sample table 25 rotates. Thus, X-rays from the X-ray tube 27 penetrate the sample on the sample stage 25, and a phase contrast image of the sample is obtained on the detector 28, which is transmitted back to the master 31 for analysis of the sample.
The X-ray generation control assembly 32 comprises a high-voltage generator 321, a vacuum device 322 and a water-cooling circulating device 323, the X-ray tube 27 is composed of a cathode, an anode and a high-vacuum glass tube, the cathode and the anode are fixed in the high-vacuum glass tube, the high-voltage generator 321 is connected with the cathode and the anode through high-voltage cables and used for transmitting two-pole high voltage and filament heating voltage, the vacuum device 322 is communicated with the high-vacuum glass tube and used for vacuumizing the high-vacuum glass tube, and the water-cooling circulating device 323 is connected with the X-ray tube 27 and used for cooling the X-ray tube 27 so as to ensure normal work of the X-ray tube 27 and prolong the service life of the X-ray tube 27. Preferably, the X-ray tube 27 is disposed on the first translation stage 22, and the high voltage generator 321, the vacuum device 322 and the water cooling cycle device 323 are disposed outside the shield case 1.
In order to ensure both phase contrast and high spatial resolution, the focus size of the X-ray tube 27 is in the order of microns.
The second displacement table 23 is provided with a sample turntable 25, a sample support 251 is arranged on the sample turntable 25, a sample is placed on the sample support 251, and the sample turntable 25 can drive the sample to rotate 360 degrees. The third displacement table 24 is provided with a detector 28, the X-ray emitted from the X-ray tube 27 passes through the sample and then irradiates the detector 28, the detector 28 converts the received X-ray into an image, i.e. a two-dimensional projection of the sample, and the projection information is then transmitted to the main controller 31 and displayed after being analyzed.
A support 26 is arranged between the first displacement table 22 and the second displacement table 23, the support 26 is also connected with the guide rail 211 in a sliding mode, a filter assembly 29 is fixed on the support 26, the filter assembly 29 is arranged between the X-ray tube 27 and a sample, and X-rays are filtered by the filter assembly and then irradiate the sample, so that the interference of absorption contrast can be restrained, and the phase contrast can be improved. The filter assembly consists of polymethyl methacrylate filters and aluminum sheet filters with different thicknesses, different filters are fixed on the same circular turntable, and the turntable is fixed between the X-ray tube and the sample. The filter plates with different thicknesses and materials can be selected according to different voltages of the X-ray tubes selected by different samples. For a weak absorption sample needing low-voltage imaging, a polymethyl methacrylate filter can be selected, and for a strong absorption sample needing higher-voltage imaging, an aluminum filter can be selected.
A plurality of servo motors can be arranged on the base 21, and the main controller 31 is respectively connected with the servo motors through cables or a local area network and is used for driving the sliding of the first displacement table 22, the second displacement table 23, the third displacement table 24, the bracket 26 on the guide rail 211 and the rotation of the sample turntable 25. The main controller 31 is also connected to the high voltage generator 321, the vacuum device 322, the water cooling circulation device 323 and the detector 28 through cables or a local area network, so as to control the distance between the emission of the X-rays, the X-ray tube 27, the sample and the detector 28. The master controller 31 is preferably a computer by which a user can conveniently operate the biometric recognition system and view the two-dimensional projection information of the sample via a display. The master 31 can also transmit the collected data to a remote database 4 through the network, so as to save or realize data sharing.
The biological characteristic identification system of the invention adopts a coaxial contour method to realize X-ray phase contrast imaging, is based on Fresnel diffraction principle, has simple light path, easy realization, high photon utilization rate and low requirement on light source time coherence, and allows multicolor X-rays to be used as a light source.
As shown in fig. 2, for the case of a pure phase object and a point light source, the light intensity distribution on the image plane can be described as:
where z is the approximate optical axis, k 2 π/λ is the wavevector, λ is the wavelength, r is the optical axiseIs the classical electron radius, rho is the electron density of the sample, I0Is the light intensity value on the object plane. M ═ Z1+Z2)/Z1Is a geometric method multiple, Z, of the imaging system1And Z2The distances from the sample to the light source and the sample to the detector, respectively.
From the above equation, it can be seen that the light intensity distribution on the image plane is proportional to the second order differential of the electron density, independent of photon energy, which means that multi-color photo-phase contrast imaging can be achieved. Contrast of imaging as a function of distance Z of the sample from the light source A1And the distance Z from the sample B to the detector C2By changing and selecting proper imaging parameters, the optimal imaging contrast and the optimal magnification can be obtained. That is, the biometric authentication system of the present invention can achieve the best imaging contrast and the best magnification by adjusting the distance from the first translation stage 22 to the second translation stage 23 and the distance from the second translation stage 23 to the third translation stage 24.
The specific adjustment method is as follows: the position of the sample is first fixed (about 1cm from the X-ray tube source), then the distance from the detector 28 to the sample is adjusted from near to far, and different X-ray tube parameters are selected for shooting and comparison, so as to find out the optimal imaging conditions.
Taking a resolution plate as an example, tests were performed at three positions with 50 times, 100 times and 157 times (near, middle and far) magnification at four different currents of 100 μ a, 200 μ a, 300 μ a and 400 μ a, respectively, using a common accelerating voltage of 60KV, and the results are shown in fig. 3 a-3 d, fig. 4 a-4 d and fig. 5 a-5 d. The resolution ratio is analyzed by adopting a modulation transfer function MTF to obtain a test result: when the magnification is 100 times, namely the distance between the sample and the detector is 1m, the imaging result of the JIMA card is clearest, and the spatial resolution can reach the highest and can reach 3 micrometers.
As shown in table 1 below, where different resolutions and field sizes of the biometric identification system of the present invention were calculated at different magnifications. Different samples can select proper distance and corresponding magnification according to the characteristics of actual size, characteristic dimension and the like of the samples. For example, according to the size of a biological small fish sample, on the premise of meeting the field condition, the phase contrast structure of the small fish can be clearly obtained by selecting 10 times of magnification; for a plane resolution board sample, the magnification of 100 times is selected according to the effect of comprehensively considering the visual field and the definition, and lines of 3 microns or more on a resolution test card can be clearly presented.
Table 1: theoretical design table of magnification
| Serial number | Magnification factor | JIMA resolution (mum) | Field of view (theoretical sample size) (cm)2) |
| 1 | 1:1 | 150 | 22.8(H)*29.1(V) |
| 2 | 2:1 | 75 | 11.4(H)*14.5(V) |
| 3 | 3:1 | 50 | 7.6(H)*9.7(V) |
| 4 | 5:1 | 30 | 4.5(H)*5.8(V) |
| 5 | 10:1 | 15 | 2.2(H)*2.9(V) |
| 6 | 20:1 | 7.5 | 1.1(H)*1.4(V) |
| 7 | 50:1 | 5 | 0.4(H)*0.5(V) |
In the biological characteristic recognition system of the invention, the main controller 31 controls the rotation of the sample turntable 25 and the shooting of the detector 28 to the sample at different angles, so that the CT scanning to the sample can be realized. Preferably, software with the functions of self-defining exposure time, single-sheet shooting, single-sheet storage, real-time preview, motor control, CT scanning and the like can be developed on a computer, so that the CT of the sample can be conveniently shot.
According to the acquired CT data and the phase recovery algorithm, the structures with different components and different electron densities in the same sample can be distinguished, so that the extraction and quantitative analysis of the characteristic structure are realized. By the technology, the micron-sized three-dimensional space structure of the detected sample and the quantitative information of the characteristic structure of the micron-sized three-dimensional space structure can be rapidly acquired without damage, and the accuracy of the biosafety detection work is effectively improved.
Taking the biological sample small fish as an example, the small fish is imaged based on the absorption contrast and the phase contrast, and three-dimensional reconstruction is performed, and as a result, as shown in fig. 6 a-6 b and fig. 7 a-7 d, it can be seen from the figures that the absorption contrast can only form a relatively clear image of a strongly absorbed bone, and the like, and the phase contrast can realize clear reproduction of weakly absorbed components and structures such as fish scales on the body surface, fish flesh in the body, fish brain, fish gill, and the like.
According to the biological characteristic identification system, the X-ray tube with the micron focus is used as a light source, and an X-ray beam with good spatial coherence is obtained, so that the imaging detection of a weakly-absorbing biological sample based on phase contrast is realized, and the spatial resolution is improved; by controlling the distances between the first displacement table 22, the second displacement table 23 and the third displacement table 24, the distances from the sample to the X-ray tube 27 and from the sample to the detector 28 can be adjusted, so that optimal detection parameters are provided for different samples, and the detection requirements of different samples are met; the rotation of the sample turntable 25 and the shooting of the detector 28 to the sample at different angles are controlled by the main controller 31, so that the CT scanning of the sample can be realized, the signal stacking problem existing in a two-dimensional projection image is solved, and a high-resolution three-dimensional space structure of a biological sample can be obtained; according to the acquired CT data and the phase recovery algorithm, the extraction of the characteristic structure and the quantitative analysis of the sample are realized, and the micron-sized three-dimensional space structure of the detected sample and the quantitative information of the characteristic structure can be rapidly acquired without damage, so that the accuracy of biological safety detection is improved.
Example two
As shown in fig. 8, the present embodiment provides a biometric identification method, including the following steps:
s1: a biometric identification system of the first embodiment is constructed and the sample to be tested is placed on the sample holder 251 of the second translation stage 23.
S2: the X-ray tube 27 is turned on and preheated by the main controller 31.
S3: the distance between the sample and the X-ray tube 27 and the distance between the detector 28 and the sample are adjusted, and two-dimensional projection images of the sample are taken under different X-ray tube parameters and then are compared, so that optimal contrast imaging conditions are obtained.
Taking a biological sample walnut as an example, the optimal contrast imaging conditions are as follows: the tube voltage is 80keV, the tube current is 100 muA, the target power is 6.6W, the distance from the sample to the X-ray tube 27 is 135mm, and the distance from the sample to the detector 28 is 350 mm.
S4: the exposure time of the projection is determined from the actual luminous flux of the biometric identification system and the detector 28 is then controlled by the master 31 to take a two-dimensional projection of the sample.
Since the light flux of the biometric identification system decreases with increasing distance of the X-ray tube 27 to the detector 28, the exposure time of the projection is related to the actual light flux; therefore, in the case where the X-ray tube voltage and the tube current are constant, the specific exposure time also changes with the distance from the X-ray tube 27 to the detector 28. For the walnut samples, the exposure time per projection was 500 ms.
Through the steps, a two-dimensional projection diagram of the sample can be obtained, and on the basis, CT shooting can be carried out on the sample, and the method specifically comprises the following steps:
s5: the main controller 31 controls the sample turntable 25 to rotate 360 degrees according to a preset step length, and each time the sample turntable rotates one preset step length, the detector 28 shoots a two-dimensional projection view of the sample under the angle, so that the 360-degree two-dimensional projection view of the sample is acquired.
Taking a walnut as an example of a biological sample, the preset step length is 0.3 degrees, a two-dimensional projection image is collected after the sample rotates 0.3 degrees each time, and 1200 two-dimensional projection images are collected after the sample rotates 360 degrees.
S6: the sample is removed from the sample holder 251 and a background image is taken with the same exposure time as the two-dimensional projection of the sample.
S7: the X-ray tube 27 is turned off and a dark current background image is taken with the same exposure time as the projection image of the sample.
S8: and performing three-dimensional slice reconstruction of the image by using the two-dimensional projection image, the background image and the dark current background image of the sample in the steps S5-S7.
S9: three-dimensional reconstruction is performed from the three-dimensional slice in step S8, thereby reproducing the internal structure information of the sample without loss.
As shown in fig. 9a and 9b, the internal structure information of the walnut sample can be reproduced without damage through three-dimensional reconstruction; as shown in fig. 9c and 9d, in combination with the phase retrieval algorithm, the internal characteristic structure of the walnut sample can be extracted, so that the internal structure can be quantitatively analyzed. As shown in FIG. 10a and FIG. 10b, the quantitative analysis structure of the walnuts in three different producing areas is shown, and it can be seen that the thickness and the kernel content of the walnut shells of the walnuts in the different producing areas are different, so that the identification of the walnuts in the different producing areas can be carried out. The method is not limited to walnuts, and is also popularized to other biological samples, so that the accuracy of biological safety detection is improved.
According to the biological characteristic identification method, the X-ray tube with the micron focus is used as a light source, and an X-ray beam with good spatial coherence is obtained, so that the imaging detection of a weakly-absorbing biological sample based on phase contrast is realized, and the spatial resolution is improved; by adjusting the distance between the sample and the X-ray tube 27 and between the sample and the detector 28, optimal contrast imaging conditions can be obtained; the three-dimensional space structure of the sample is obtained through CT scanning, and the extraction, segmentation and quantitative analysis of the internal characteristic structure can be performed by combining a phase recovery algorithm, so that the identification of different varieties of samples or the identification of production places or quality evaluation of different samples can be realized.
The above embodiments are merely preferred embodiments of the present invention, which are not intended to limit the scope of the present invention, and various changes may be made in the above embodiments of the present invention. All simple and equivalent changes and modifications made according to the claims and the content of the specification of the present application fall within the scope of the claims of the present patent application. The invention has not been described in detail in order to avoid obscuring the invention.
Claims (10)
1. A biological characteristic recognition system comprises an X-ray detection device and a control device, wherein the X-ray detection device is arranged in a sealed protective box,
the X-ray detection device comprises a base, wherein a guide rail is arranged on the base, a first displacement table, a second displacement table and a third displacement table are sequentially arranged in a sliding manner along the length direction of the guide rail, an X-ray tube is arranged on the first displacement table, a sample rotary table is arranged on the second displacement table, and a detector is arranged on the third displacement table;
the control device comprises a main controller and an X-ray generation control assembly, wherein the main controller is connected with the X-ray generation control assembly, the sample rotary table, the first displacement table, the second displacement table and the third displacement table through cables or communication respectively.
2. The biometric identification system of claim 1, wherein a support is disposed between the first and second translation stages, the support being slidably disposed on the rail, the support having a filter assembly disposed thereon.
3. The biometric identification system of claim 2, wherein the filter assembly includes polymethyl methacrylate filters and aluminum sheet filters of different thicknesses.
4. The biometric identification system of claim 1, wherein the X-ray generation control assembly includes a high voltage generator, a vacuum device, and a water-cooling circulation device, the high voltage generator being electrically connected to two poles of the X-ray tube, the vacuum device and the water-cooling circulation device both being connected to the X-ray tube.
5. The biometric identification system of claim 1, wherein a focal spot size of the X-ray tube is on the order of microns.
6. The biometric identification system of claim 1, wherein the master is a computer.
7. The biometric identification system of claim 6, wherein the master is connected to a remote database via a network.
8. A biometric identification method, comprising the steps of:
s1: constructing a biometric identification system according to any one of claims 1 to 7 and placing the sample to be tested on a sample turntable;
s2: turning on the X-ray source, and controlling the X-ray source to preheat by the control device;
s3: adjusting the distance from the sample to the X-ray tube and the distance from the detector to the sample, shooting two-dimensional projection images of the sample under different X-ray tube parameters, and then comparing to obtain the optimal contrast imaging condition;
s4: the exposure time of the projection is determined from the actual luminous flux of the biometric recognition system, and the detector is then controlled by the control device to take a two-dimensional projection of the sample.
9. The biometric identification method according to claim 8, further comprising the steps of:
s5: the control device controls the sample rotary table to rotate 360 degrees according to a preset step length, and when the sample rotary table rotates one preset step length, the detector shoots a two-dimensional projection diagram of the sample, so that the two-dimensional projection diagram of the sample of 360 degrees is acquired;
s6: removing the sample from the sample holder, and taking a background image with the same exposure time as the two-dimensional projection image of the sample;
s7: turning off the X-ray tube, and shooting a dark current background image by using the same exposure time as the shooting of the projection image of the sample;
s8: performing three-dimensional slice reconstruction of the image by using the two-dimensional projection image, the background image and the dark current background image of the sample in the steps S5-S7;
s9: three-dimensional reconstruction is performed from the three-dimensional slice in step S8, thereby reproducing the internal structure information of the sample without loss.
10. The biometric authentication method according to claim 9, wherein the preset step size in step S5 is 0.3 degrees.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110495666.9A CN113237901A (en) | 2021-05-07 | 2021-05-07 | Biological feature recognition system and biological feature recognition method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110495666.9A CN113237901A (en) | 2021-05-07 | 2021-05-07 | Biological feature recognition system and biological feature recognition method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113237901A true CN113237901A (en) | 2021-08-10 |
Family
ID=77132317
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110495666.9A Pending CN113237901A (en) | 2021-05-07 | 2021-05-07 | Biological feature recognition system and biological feature recognition method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113237901A (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102325498A (en) * | 2009-02-05 | 2012-01-18 | 中国科学院高能物理研究所 | Low dose single step grating based X-ray phase contrast imaging |
| CN104132953A (en) * | 2014-08-01 | 2014-11-05 | 中国科学技术大学 | Dual-energy X-ray phase-contrast imaging device and implementation method thereof |
| CN104569002A (en) * | 2013-10-23 | 2015-04-29 | 北京纳米维景科技有限公司 | X-ray phase contrast imaging system based on photon counting, X-ray phase contrast imaging method realized by the system, and key equipment of X-ray phase contrast imaging method |
| CN105142524A (en) * | 2014-02-10 | 2015-12-09 | 约翰斯·霍普金斯大学 | Large field of view grating interferometers for x-ray phase contrast imaging and ct at high energy |
| CN106821410A (en) * | 2017-03-20 | 2017-06-13 | 厦门大学 | Using the substance identification and system of EO-1 hyperion CT functional imagings |
-
2021
- 2021-05-07 CN CN202110495666.9A patent/CN113237901A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102325498A (en) * | 2009-02-05 | 2012-01-18 | 中国科学院高能物理研究所 | Low dose single step grating based X-ray phase contrast imaging |
| CN104569002A (en) * | 2013-10-23 | 2015-04-29 | 北京纳米维景科技有限公司 | X-ray phase contrast imaging system based on photon counting, X-ray phase contrast imaging method realized by the system, and key equipment of X-ray phase contrast imaging method |
| CN105142524A (en) * | 2014-02-10 | 2015-12-09 | 约翰斯·霍普金斯大学 | Large field of view grating interferometers for x-ray phase contrast imaging and ct at high energy |
| CN104132953A (en) * | 2014-08-01 | 2014-11-05 | 中国科学技术大学 | Dual-energy X-ray phase-contrast imaging device and implementation method thereof |
| CN106821410A (en) * | 2017-03-20 | 2017-06-13 | 厦门大学 | Using the substance identification and system of EO-1 hyperion CT functional imagings |
Non-Patent Citations (3)
| Title |
|---|
| 刘元琼等: "X射线相衬成像法在线表征冷冻靶技术", 《强激光与粒子束》 * |
| 李军等: "显微CT技术及其在生物医学领域的应用", 《现代仪器》 * |
| 高党忠等: "相衬照相法检测聚苯乙烯微球气泡缺陷", 《强激光与粒子束》 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US8488736B2 (en) | Stacked flat panel x-ray detector assembly and method of making same | |
| US6650730B2 (en) | Filter assembly for X-ray filter system for medical imaging contrast enhancement | |
| US8483352B2 (en) | Stacked x-ray detector assembly and method of making same | |
| CN106821410B (en) | Substance identification method and system adopting hyperspectral CT functional imaging | |
| CN104374783B (en) | CT system and its method | |
| EP2629083A2 (en) | 3d backscatter imaging system | |
| KR20170072170A (en) | Detector device, dual energy ct system and detection method using same | |
| US10068322B2 (en) | Inspection system | |
| Kaestner et al. | Samples to determine the resolution of neutron radiography and tomography | |
| Dudak et al. | X-ray micro-CT scanner for small animal imaging based on Timepix detector technology | |
| WO2014045045A1 (en) | A dispersive diffraction projection imaging system | |
| WO2024131089A1 (en) | Rapid low-dose x-ray multi-modal ct system and imaging method | |
| US20240044812A1 (en) | Rotational X-ray Inspection System and Method | |
| Zhang et al. | X-ray luminescence computed tomography using a focused x-ray beam | |
| Udod et al. | State-of-the art and development prospects of digital radiography systems for nondestructive testing, evaluation, and inspection of objects: a review | |
| EP3128918A2 (en) | Patient table with integrated x-ray volumetric imager | |
| CN113237901A (en) | Biological feature recognition system and biological feature recognition method | |
| Gelli et al. | The new INFN-CHNet neutron imaging facility | |
| Sharma et al. | Design and development of a high-energy gamma camera for use with NSECT imaging: feasibility for breast imaging | |
| CN107478660B (en) | Optical fiber quality detection system and method | |
| Meng et al. | X-ray fluorescence tomography using imaging detectors | |
| JP7437337B2 (en) | Internal state imaging device and internal state imaging method | |
| JP2002532713A (en) | Inspection of objects with crystal lattice by radiography | |
| Alkhateeb et al. | Energy dispersive X-ray diffraction computed tomography of breast-simulating phantoms and a tissue sample | |
| KR101231859B1 (en) | Stereo X-ray Scanning Equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20210810 |