CN106821410A - Using the substance identification and system of EO-1 hyperion CT functional imagings - Google Patents
Using the substance identification and system of EO-1 hyperion CT functional imagings Download PDFInfo
- Publication number
- CN106821410A CN106821410A CN201710165177.0A CN201710165177A CN106821410A CN 106821410 A CN106821410 A CN 106821410A CN 201710165177 A CN201710165177 A CN 201710165177A CN 106821410 A CN106821410 A CN 106821410A
- Authority
- CN
- China
- Prior art keywords
- ray
- hyperion
- dimensional motion
- algorithm
- tested sample
- 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.)
- Granted
Links
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
- A61B6/02—Devices for diagnosis sequentially in different planes; Stereoscopic radiation diagnosis
- A61B6/03—Computerised tomographs
- A61B6/032—Transmission computed tomography [CT]
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
- A61B6/42—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment with arrangements for detecting radiation specially adapted for radiation diagnosis
- A61B6/4208—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment with arrangements for detecting radiation specially adapted for radiation diagnosis characterised by using a particular type of detector
- A61B6/4241—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment with arrangements for detecting radiation specially adapted for radiation diagnosis characterised by using a particular type of detector using energy resolving detectors, e.g. photon counting
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
- A61B6/44—Constructional features of apparatus for radiation diagnosis
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
- A61B6/46—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment with special arrangements for interfacing with the operator or the patient
- A61B6/467—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment with special arrangements for interfacing with the operator or the patient characterised by special input means
- A61B6/469—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment with special arrangements for interfacing with the operator or the patient characterised by special input means for selecting a region of interest [ROI]
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
- A61B6/52—Devices using data or image processing specially adapted for radiation diagnosis
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
- A61B6/52—Devices using data or image processing specially adapted for radiation diagnosis
- A61B6/5258—Devices using data or image processing specially adapted for radiation diagnosis involving detection or reduction of artifacts or noise
-
- 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
- G01N23/06—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 measuring the absorption
- G01N23/083—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 measuring the absorption the radiation being X-rays
Abstract
Using the substance identification and system of EO-1 hyperion CT functional imagings, including X-ray tube, photon counting detector, two-dimension translational platform, turntable, three-dimensional motion controller and control centre；The X-ray tube is led to be connected with high pressure generator tested sample is scanned with sending X-ray；The turntable is located at X-ray tube transmitting terminal front to place tested sample；The photon counting detector is located on two-dimension translational platform to gather high-spectral data；The three-dimensional motion controller is connected with its rotation of controller with turntable, and the three-dimensional motion device is connected to control it to translate with two-dimension translational platform；The control centre is connected to control three-dimensional motion controller and high pressure generator with three-dimensional motion controller, photon counting detector, high pressure generator, receives spectroscopic data and recognizes tested sample.The method and system in medical diagnosis on disease, food security and nondestructive testing with good application prospect.
Description
Technical field
The present invention relates to medical image field of non destructive testing, the material of particularly a kind of use EO-1 hyperion CT functional imagings is known
Other method and system.
Background technology
Medical image be study how it is noninvasive obtain human dissection and physiologic information, to diagnose and assessing offer foundation.
Can be divided into two major classes with regard to image mode：One structure imaging for being to provide anatomic information；Two functional imagings for being to provide physiologic information.
For some cases, cannot often be diagnosed by single imaging mode, and different imaging modes tends to information
Complementation, so as to occur in that the multi-mode medical imaging technique for developing rapidly recently.The world today, biomedicine is increasingly intended to
Microcosmic point, Molecular imaging techniques are also increasingly paid attention to by people.Traditional X ray computer fault imaging (XCT) technology
Used as a kind of molecular imaging means, the diagnosis to some medical conditions plays very important effect, but it uses traditional
Detector, Object Classification ability is relatively low, limits its application in terms of 26S Proteasome Structure and Function imaging.Traditional CT belongs to typical
Structure imaging, the lesion localization to carry out non-structural change then must binding function image-forming information.The difference master of organ-tissue
If caused by the material composition difference of molecule and cell aspect, therefore multi-mode medical imaging needs to use various imaging systems
System：If various imaging modes are imaged respectively and then data fusion can bring very big difficulty to atlas registration, if all imagings are filled
Put and be integrated into set of system and can increase system complexity and operation difficulty again, reduce whole aircraft reliability with detection security.If
Only can complete structure imaging with a kind of detection means can realize lesion localization again, then can provide greatly side for clinical diagnosis
Help.CT will be extended to functional imaging field by the present invention by structure imaging field, and it can obtain each pixel (Pixel)/voxel
(Voxel) X-ray hyperspectral information, so as to judge its component/focus characteristic.Therefore it merged CT high spatial resolutions and
EO-1 hyperion detects the advantage of both strong identification capabilities.
When X-ray continuous spectrum is subsequently absorbed in the material, the absorbed degree of ray of different wave length is different, the certain ripple of correspondence
Long, absorption coefficient can undergo mutation, and these mutation are referred to as ABSORPTION EDGE, and it is discrete to there are some in ABSORPTION EDGE and its high energy extension
Peak or undulation, referred to as X-ray absorption fine structure (X-rayAbsorption Fine Structure).XAFS believes
Number determined by the Near-neighbor Structure around absorption atom, and, frequency, the amplitude of fine structure vibration sensitive to chemical environment
With shape determine that it provides the information of a small range Clusters by the arrangement of atom, including neighbour's atom is matched somebody with somebody
The geometries such as digit, atomic distance, thermal agitation and electronic structure.XAFS to valence state, do not occupy electronic state and electric charge transfer
It is sensitive etc. chemical information, the fingerprint recognition of specified chemical composition and functional group can be done, can be used to studying chemical bond, atom site and
Atomic Arrangement, oxidation state, coordination structure, the dimensional profile features of molecule, molecular configuration etc..The mechanism explanation different material of XAFS
Absorption spectrum will necessarily be otherwise varied, but XAFS to uniform material detection be effective, if will be to many kinds of substance
Labyrinth body carries out subregion detection and is but difficult to.The absorption spectrum of ray is that it passes through all decay accumulations on path
As a result, depth information is have lost, which kind of material of which section correspondence cannot judge on path, and the advantage of XCT imagings just can be with
Depth information is provided, material can be accurately positioned.The present invention distinguishes the space orientation ability for merging XCT with the material of XAFS
Knowledge ability, generates a set of new imaging system theoretical.
The high and low energy of the dual intensity CT of main flow is divided by X-ray bulb voltage now, is all broadband light, is had
Very big lap, can bring certain interference to material identification.Photon counting detector energy in theory between each passage
What amount was completely separate, in the absence of lap.But the CZT linear array detectors for being used at present can only be whole sense light
Spectrum region division is 5 wave bands, although this has been greatly improved relative to dual intensity CT, but 5 feature codings of wave band
For the focus species of numerous and complicated also very little, there is very big gap apart from clinical practice.
The content of the invention
It is a primary object of the present invention to overcome drawbacks described above of the prior art, one kind combination X ray computer is proposed
The advantage of the structural remodeling of tomography and the Object Classification of X-ray absorption spectrum so that labyrinth material identification capability is big
Width is improved.
The present invention is adopted the following technical scheme that：
Using the substance identification of EO-1 hyperion CT functional imagings, it is characterised in that comprise the following steps
1) tested sample is scanned using X-ray, high-spectral data is gathered by photon counting detector；
2) detect X-ray intensity and go background process to obtain input data with reference to high-spectral data；
3) internal structure of tested sample is rebuild using CT algorithm for reconstructing to input data, full spectral coverage fault image is obtained；
4) graphical analysis and treatment are carried out to full spectral coverage fault image, the coordinate of area-of-interest is drawn a circle to approve；
5) reuse CT algorithm for reconstructing and rebuild and obtain the coordinate open score line of area-of-interest and rebuild, obtain rebuilding light
Spectral curve；
6) the reconstruction curve of spectrum is carried out correlation contrast with the spectroscopic data in database, so as to judge tested sample
The material classification of area-of-interest.
Preferably, described CT algorithm for reconstructing is filter back-projection algorithm, and it first does filtering process to input data, then does
Backprojection reconstruction.
Preferably, the CT algorithm for reconstructing is iterative algorithm.
Preferably, initial value first is assigned to unknown images vector：J=1,2,3 ... N, the iterative algorithm includes
Following steps：
3.1) i-th estimated projection value of light is calculated：WijIt is projection coefficient.
3.2) calculation error namely correction artifact：PiIt is i-th projection value of ray.
3.3) j-th correction value of pixel is calculated：Wherein NiWorn from i-th light of expression
Cross the total number of the upper pixel of image-region；
3.4) j-th correction value of pixel is calculated:
3.5) point on i-th light all adds VijIt is modified, repeats 3.2) to 3.4), until all light of all images
Line, this is an iteration；
3.6) using last round of iteration result as initial value, repeat 3.2) to K wheel results 3.4) are obtained, so as to obtain a sequence
Row
Preferably, it is described to go background process, it is as follows：
Wherein I0It is X-ray intensity, I is described high-spectral data, and μ is the attenuation coefficient of material, and L is that X-ray is passed through
The length of the material.
Preferably, in step 6) in, the standard compared as correlation using Min formula distance recognizes different materials point
Class.
A kind of EO-1 hyperion CT function imaging systems, it is characterised in that flat including X-ray tube, photon counting detector, two dimension
Moving stage, turntable, three-dimensional motion controller and control centre；The X-ray tube is logical to be connected to send X-ray pair with high pressure generator
Tested sample is scanned；The turntable is located at X-ray tube transmitting terminal front to place tested sample；The photon counting detector
Gathering high-spectral data on two-dimension translational platform；The three-dimensional motion controller is connected with its rotation of controller with turntable,
The three-dimensional motion device is connected to control it to translate with two-dimension translational platform；The control centre and three-dimensional motion controller, photon counting
Detector, high pressure generator are connected to control three-dimensional motion controller and high pressure generator, receive spectroscopic data and using above-mentioned
Any one using EO-1 hyperion CT functional imagings substance identification identification tested sample.
From the above-mentioned description of this invention, compared with prior art, the present invention has the advantages that：
1st, the method for the present invention and system, based on photon counting principle, with reference to the structure weight of X ray computer tomography
Build the advantage with the Object Classification of X-ray absorption spectrum so that labyrinth material identification capability is greatly improved,
2nd, the method for the present invention and system, rebuild belong to structure imaging for the first time, the dissection knot for observing measurand
Structure；Rebuild for second and belong to functional imaging, the X-ray absorption coefficient high-spectral data for obtaining area-of-interest material is used
In carry out material classification with reach physiological function judgement purpose.
3rd, the method for the present invention and system, the ability for possessing detection measurand internal structure, can also not damage quilt
The functional component at each position is recognized on the premise of surveying object, its recognition correct rate of empirical tests is high.The invention in medical diagnosis on disease,
In food security and nondestructive testing with good application prospect.
4th, the method for the present invention and system, spectral resolution are high, up to hundreds of even thousands of spectral coverages, and each spectral coverage it
Between be kept completely separate, there is no lap, it is more advanced than current on the market Shuan Neng multipotencys CT.
5th, the method for the present invention and system, it is only necessary to which the data acquisition of a set of imaging system can simultaneously complete three-dimensional space
Between structure imaging and functional imaging.
6th, the method for the present invention and system, by using the knot of the data analysis material with complex from X-ray absorption spectrum
Structure, with detectability higher, compared with conventional CT and dual intensity CT, EO-1 hyperion CT functional imagings can be realized more more complicated
Compound identification with identification, reach the purpose of functional imaging.
Brief description of the drawings
Fig. 1 is system structure diagram of the invention；
Fig. 2 is vertical view index path of the invention
The tomograph of sample after Fig. 3 this reconstruction；
Fig. 4 is the workflow diagram of the inventive method；
Fig. 5 is the curve of spectrum of part sample in spectral signature storehouse；
Fig. 6 is the curve of spectrum of gained after specific sample is rebuild.
Specific embodiment
Below by way of specific embodiment, the invention will be further described.
Referring to figs. 1 to Fig. 6, a kind of EO-1 hyperion CT function imaging systems, including X-ray tube, photon counting detector, two dimension
Translation stage, turntable, three-dimensional motion controller and control centre.The X-ray tube is logical to be connected with high pressure generator, by high voltage
Drive X-ray tube to launch continuous X-ray to be scanned tested sample.The turntable be located at X-ray tube transmitting terminal front with
Place tested sample.The photon counting detector is located on two-dimension translational platform to gather high-spectral data, and it can be SDD, Si-
PIN or CdZnTe etc., for CdZnTe (Cd Te probe), using cadmium-telluride crystal as X-ray and gamma-ray detector,
Crystal is arranged on the charge sensitive preamplifier on thermoelectric (al) cooler and coupled to customization, this detector has higher
Resolution ratio and investigative range, the recordable multiple energy section number of photons of single exposure.The turntable is located at X-ray tube and photon meter
Between number detector.
The three-dimensional motion controller is connected to control its 360 ° rotations, the three-dimensional motion device and two-dimension translational platform with turntable
It is connected to control it to translate along the horizontal plane, the angle and the step number of two-dimension translational platform motion that the turntable rotates every time are based on quilt
The resolution requirement setting of the size and reconstruction image of test sample sheet, to ensure that whole sample to be tested can intactly be scanned by X-ray,
Clearly to rebuild the internal structure of tested sample.The control centre and three-dimensional motion controller, photon counting detector, height
Pressure generator is connected to control three-dimensional motion controller and high pressure generator, receives the spectroscopic data of photon counting detector and adopts
Tested sample is recognized with the substance identification of EO-1 hyperion CT functional imagings.
In addition, before measure spectrum, also needing to debug the light path of whole system.Two lasers are fixed on magnetic bases,
By adjusting two spatial attitudes of laser so that the intersection of two beam laser is also cross in detector center and x-ray source
The heart.
It is further proposed that using the substance identification of EO-1 hyperion CT functional imagings, comprising the following steps
1) tested sample is scanned using X-ray, high-spectral data is gathered by photon counting detector.
2) detect X-ray intensity and go background process to obtain input data with reference to high-spectral data.Due to being penetrated in specific X
The x-ray photon Limited Number that heat input scope is detected, can obtain inaccurate data, and this data are reconstructed image knot
Fruit can carry obvious noise, thus, it is desirable to two groups of spectroscopic datas go background process.By not placing sample to be tested, it is used for
Detection incident X-rays intensity.Background process is gone, it is as follows：
Wherein I0It is the X-ray intensity i.e. data of the air without sample to be tested, I is to place the height gathered during sample to be tested
Spectroscopic data, μ is the attenuation coefficient of material, and L is length of the X-ray through the material.
3) internal structure of tested sample is rebuild using CT algorithm for reconstructing to input data, it is all with corresponding projection measurement
Angle, high-pass filtering treatment then is carried out to the data that each is projected, finally add up all angles projection filter value, to obtain
Obtain the pad value of each pixel, the full spectral coverage fault image rebuild.The CT algorithm for reconstructing can use filter back-projection algorithm
(FBP algorithms) or iterative algorithm.Wherein, filter back-projection algorithm, to input data is first as that data for projection does filtering process,
It is specific as follows that backprojection reconstruction is done again：
Wherein, f (x, y) be density function to be asked, p (t, θ) be stepping be t, projection number of the sample to be tested in angle, θ
According to optional S-L wave filters：
After obtaining the reconstruction spectrum of full spectral coverage fault image, max-min standard normalized is carried out to spectroscopic data.
The effect of tomograph image reconstruction is as shown in figure 3, the effect of EO-1 hyperion reconstruction is as shown in Figure 6.
Iterative algorithm comprises the following steps：Initial value first is assigned to unknown images vector：J=1,2,3 ... N.
3.1) i-th estimated projection value of light is calculated：WijIt is projection coefficient.
3.2) calculation error namely correction artifact：PiIt is i-th projection value of ray.
3.3) j-th correction value of pixel is calculated：Wherein NiWorn from i-th light of expression
Cross the total number of the upper pixel of image-region.
3.4) j-th correction value of pixel is calculated:
3.5) point on i-th light all adds VijIt is modified, i.e., the pixel value that this ray is passed through is modified,
The value that will be corrected substitutes into next equation, repeats 3.2) to 3.4), until all light of all images are disposed, this is one
Secondary iteration.
3.6) using last round of iteration result as initial value, repeat 3.2) to K wheel results 3.4) are obtained, so as to obtain a sequence
RowIf meeting convergent requirement, i.e., to the positive number ε of very little given in advance, there is positive integer K so that work as k>During K,
Have
4) graphical analysis and treatment are carried out to full spectral coverage fault image.For the data for projection of a certain section, ART algorithms are used
The faultage image for obtaining can be rebuild with SL algorithms, the seat of area-of-interest is drawn a circle to approve on the faultage image according to picture structure
Mark.
5) reuse CT algorithm for reconstructing and rebuild and obtain the coordinate open score line of area-of-interest and rebuild, obtain rebuilding light
Spectral curve.The absorption spectrum of the area-of-interest specified is rebuild using filter back-projection algorithm or iterative algorithm.To interested
Region open score line is rebuild, and then the spectral line attenuation coefficient after reconstruction is lined up, as the reconstruction spectrum in the region
Curve.Normalized is needed during spectroscopic data is rebuild so that the maximum and minimum value of all curves of spectrum are protected
Hold consistent.In order to eliminate system noise, Wavelet Denoising Method need to be introduced, the introducing of wavelet transformation reduces shadow of the noise to reconstructed results
Ring so that spectral data curve is smoother, so as to improve the accuracy of subsequent species identification.
6) the reconstruction curve of spectrum is carried out correlation contrast with the spectroscopic data in database, so as to judge tested sample
The material classification of area-of-interest.The spectral information of the respective regions obtained by reconstruction image, according to their absorption coefficient
Sample is classified, and it is matched into contrast with spectrum characteristic data storehouse, the data in the spectrum and database rebuild
Between perform correlation contrast, using Minkowski distances as dependence test standard, it is possible to identify different samples
This, Minkowski range formulas are as follows：
P=3 can be made, Minkowski distances are the popularizations of Euclidean distance, and it can describe the phase between two variables
Like property, its value two variables of smaller explanation are more similar.
After data processing, the average value of the reconstruction spectrum of every kind of material is obtained using all of pixel of each sample,
Such as Fig. 5, shown in 6, the spectroscopic data after reconstruction does correlation test with the spectroscopic data in database, it can be seen that after reconstruction
The curve of spectrum of the SG in the curve of spectrum and database coincide substantially, then it is considered that this material is SG.Demonstrate,proved through repeatedly test
Bright, system and method involved in the present invention can reach identification precision very high.
Database is made of a variety of materials, and has only arranged wherein four kinds here, (as shown in table 1), and measurement is multiple, they
Average value is stored in database.
Table 1
Specific embodiment of the invention is above are only, but design concept of the invention is not limited thereto, it is all to utilize this
Design carries out the change of unsubstantiality to the present invention, all should belong to the behavior for invading the scope of the present invention.
Claims (7)
1. using the substance identification of EO-1 hyperion CT functional imagings, it is characterised in that comprise the following steps
1) tested sample is scanned using X-ray, high-spectral data is gathered by photon counting detector；
2) detect X-ray intensity and go background process to obtain input data with reference to high-spectral data；
3) internal structure of tested sample is rebuild using CT algorithm for reconstructing to input data, full spectral coverage fault image is obtained；
4) graphical analysis and treatment are carried out to full spectral coverage fault image, the coordinate of area-of-interest is drawn a circle to approve；
5) reuse CT algorithm for reconstructing and rebuild and obtain the coordinate open score line of area-of-interest and rebuild, obtain rebuilding light and set a song to music
Line；
6) the reconstruction curve of spectrum is carried out correlation contrast with the spectroscopic data in database, so as to judge that the sense of tested sample is emerging
The material classification in interesting region.
2. as claimed in claim 1 using the substance identification of EO-1 hyperion CT functional imagings, it is characterised in that described CT
Algorithm for reconstructing is filter back-projection algorithm, and it first does filtering process to input data, then does backprojection reconstruction.
3. as claimed in claim 1 using the substance identification of EO-1 hyperion CT functional imagings, it is characterised in that the CT weights
Algorithm is built for iterative algorithm.
4. as claimed in claim 3 using the substance identification of EO-1 hyperion CT functional imagings, it is characterised in that first to unknown
Image vector assigns initial value：J=1,2,3 ... N, the iterative algorithm comprises the following steps：
3.1) i-th estimated projection value of light is calculated：WijIt is projection coefficient.
3.2) calculation error namely correction artifact：PiIt is i-th projection value of ray.
3.3) j-th correction value of pixel is calculated：Wherein NiScheme from representing that i-th light is passed through
As the total number of the upper pixel in region；
3.4) j-th correction value of pixel is calculated:
3.5) point on i-th light all adds VijIt is modified, repeats 3.2) to 3.4), until all light of all images,
This is an iteration；
3.6) using last round of iteration result as initial value, repeat 3.2) to K wheel results 3.4) are obtained, so as to obtain a sequence
5. as claimed in claim 1 using the substance identification of EO-1 hyperion CT functional imagings, it is characterised in that described goes
Background process is as follows：
Wherein I0It is X-ray intensity, I is described high-spectral data, and μ is the attenuation coefficient of material, and L is that X-ray passes through the material
Length.
6. as claimed in claim 1 using the substance identification of EO-1 hyperion CT functional imagings, it is characterised in that in step 6)
In, the standard that is compared as correlation using Min formula distance recognizes different material classifications.
7. a kind of EO-1 hyperion CT function imaging systems, it is characterised in that including X-ray tube, photon counting detector, two-dimension translational
Platform, turntable, three-dimensional motion controller and control centre；The X-ray tube is logical to be connected to send X-ray to quilt with high pressure generator
Test sample is originally scanned；The turntable is located at X-ray tube transmitting terminal front to place tested sample；Photon counting detector position
In on two-dimension translational platform gathering high-spectral data；The three-dimensional motion controller is connected with its rotation of controller with turntable, should
Three-dimensional motion device is connected to control it to translate with two-dimension translational platform；The control centre is visited with three-dimensional motion controller, photon counting
Survey device, high pressure generator to be connected to control three-dimensional motion controller and high pressure generator, receive spectroscopic data and wanted using right
Ask described in 1 to 6 any one using EO-1 hyperion CT functional imagings substance identification identification tested sample.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710165177.0A CN106821410B (en) | 2017-03-20 | 2017-03-20 | Substance identification method and system adopting hyperspectral CT functional imaging |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710165177.0A CN106821410B (en) | 2017-03-20 | 2017-03-20 | Substance identification method and system adopting hyperspectral CT functional imaging |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106821410A true CN106821410A (en) | 2017-06-13 |
| CN106821410B CN106821410B (en) | 2020-01-07 |
Family
ID=59129323
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710165177.0A Active CN106821410B (en) | 2017-03-20 | 2017-03-20 | Substance identification method and system adopting hyperspectral CT functional imaging |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106821410B (en) |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108805948A (en) * | 2018-05-24 | 2018-11-13 | 沈阳东软医疗***有限公司 | The orthographic projection method and device of image |
| CN109567838A (en) * | 2018-10-29 | 2019-04-05 | 厦门大学 | A kind of X ray absorption spectrometry lesion detector |
| CN109827979A (en) * | 2019-01-21 | 2019-05-31 | 天津三英精密仪器股份有限公司 | A kind of efficiently online CT scan imaging method and system |
| CN112784091A (en) * | 2021-01-26 | 2021-05-11 | 上海商汤科技开发有限公司 | Interest analysis method and related device and equipment |
| CN113030134A (en) * | 2021-02-26 | 2021-06-25 | 中国工程物理研究院激光聚变研究中心 | Three-axis CT imaging device and method for ICF target three-dimensional reconstruction |
| CN113237901A (en) * | 2021-05-07 | 2021-08-10 | 中国科学院上海应用物理研究所 | Biological feature recognition system and biological feature recognition method |
| CN116518879A (en) * | 2023-06-29 | 2023-08-01 | 海南大学三亚研究院 | Sample 4D reconstruction method and system based on micro CT-hyperspectral dual-mode imaging |
| CN116518878A (en) * | 2023-06-29 | 2023-08-01 | 海南大学三亚研究院 | Efficient 4D reconstruction method and efficient 4D reconstruction system based on dual-mode imaging |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8144831B2 (en) * | 2004-03-01 | 2012-03-27 | Spectramet, Llc | Method and apparatus for sorting materials according to relative composition |
| CN102462504A (en) * | 2010-11-08 | 2012-05-23 | 通用电气公司 | System and method for analyzing and visualizing spectral CT data |
| CN102507417A (en) * | 2011-11-29 | 2012-06-20 | 长春迪瑞医疗科技股份有限公司 | Method for automatically classifying particles |
| JP2013119000A (en) * | 2011-12-08 | 2013-06-17 | Tele Systems:Kk | Substance identification apparatus and substance identification method |
| 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 |
| CN106461578A (en) * | 2015-04-20 | 2017-02-22 | 株式会社蛟簿 | Data processing device and data processing method for x-ray examination, and x-ray examination apparatus provided with said device |
-
2017
- 2017-03-20 CN CN201710165177.0A patent/CN106821410B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8144831B2 (en) * | 2004-03-01 | 2012-03-27 | Spectramet, Llc | Method and apparatus for sorting materials according to relative composition |
| CN102462504A (en) * | 2010-11-08 | 2012-05-23 | 通用电气公司 | System and method for analyzing and visualizing spectral CT data |
| CN102507417A (en) * | 2011-11-29 | 2012-06-20 | 长春迪瑞医疗科技股份有限公司 | Method for automatically classifying particles |
| JP2013119000A (en) * | 2011-12-08 | 2013-06-17 | Tele Systems:Kk | Substance identification apparatus and substance identification method |
| 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 |
| CN106461578A (en) * | 2015-04-20 | 2017-02-22 | 株式会社蛟簿 | Data processing device and data processing method for x-ray examination, and x-ray examination apparatus provided with said device |
Non-Patent Citations (1)
| Title |
|---|
| 乐乐，刘琳: "CT 图像重建的迭代算法", 《长沙航空职业技术学院学报》 * |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108805948A (en) * | 2018-05-24 | 2018-11-13 | 沈阳东软医疗***有限公司 | The orthographic projection method and device of image |
| CN108805948B (en) * | 2018-05-24 | 2022-06-28 | 东软医疗***股份有限公司 | Image orthographic projection method and device |
| CN109567838A (en) * | 2018-10-29 | 2019-04-05 | 厦门大学 | A kind of X ray absorption spectrometry lesion detector |
| CN109827979A (en) * | 2019-01-21 | 2019-05-31 | 天津三英精密仪器股份有限公司 | A kind of efficiently online CT scan imaging method and system |
| CN112784091A (en) * | 2021-01-26 | 2021-05-11 | 上海商汤科技开发有限公司 | Interest analysis method and related device and equipment |
| CN113030134A (en) * | 2021-02-26 | 2021-06-25 | 中国工程物理研究院激光聚变研究中心 | Three-axis CT imaging device and method for ICF target three-dimensional reconstruction |
| CN113030134B (en) * | 2021-02-26 | 2022-03-01 | 中国工程物理研究院激光聚变研究中心 | Three-axis CT imaging device and method for ICF target three-dimensional reconstruction |
| CN113237901A (en) * | 2021-05-07 | 2021-08-10 | 中国科学院上海应用物理研究所 | Biological feature recognition system and biological feature recognition method |
| CN116518879A (en) * | 2023-06-29 | 2023-08-01 | 海南大学三亚研究院 | Sample 4D reconstruction method and system based on micro CT-hyperspectral dual-mode imaging |
| CN116518878A (en) * | 2023-06-29 | 2023-08-01 | 海南大学三亚研究院 | Efficient 4D reconstruction method and efficient 4D reconstruction system based on dual-mode imaging |
| CN116518878B (en) * | 2023-06-29 | 2023-10-10 | 海南大学 | Efficient 4D reconstruction method and efficient 4D reconstruction system based on dual-mode imaging |
| CN116518879B (en) * | 2023-06-29 | 2023-10-10 | 海南大学 | Sample 4D reconstruction method and system based on micro CT-hyperspectral dual-mode imaging |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106821410B (en) | 2020-01-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106821410A (en) | Using the substance identification and system of EO-1 hyperion CT functional imagings | |
| EP1324696B1 (en) | System and method for cone beam volume computed tomography using circle-plus-multiple-arc orbit | |
| JP4309760B2 (en) | Method for obtaining density and atomic number distribution in X-ray imaging inspection | |
| EP3627145A1 (en) | Data processing device and data processing method for x-ray inspection, and x-ray inspecting device with said device mounted therein | |
| Moore | Better breast cancer detection | |
| CN102488493B (en) | Small animal living body multi-mode molecule imaging system and imaging method | |
| US8008625B2 (en) | Method and apparatus for high-sensitivity single-photon emission computed tomography | |
| CN107315019A (en) | Transmission of radiation and fluorescence CT imaging systems and imaging method | |
| CN103959097B (en) | Detection apparatus comprising two scintillators for detecting x-ray radiation | |
| US11127174B2 (en) | Medical imaging system with a fixed array of x-ray detectors and a fixed array of x-ray emitters for producing a digital 3-dimensional image | |
| CN101175439B (en) | Continuous computer tomography performing super-short-scans and stronger weighting of most recent data | |
| CN105849772B (en) | Check system and method | |
| CN105182263A (en) | Accurate quantification of magnetic suceptibility in molecular mri | |
| CN103472074A (en) | CT imaging system and method | |
| CN101056582A (en) | Computer tomography apparatus and method for examining an object of interest | |
| Syryamkin et al. | Digital X-ray Tomography: Edited by VI Syryamkin | |
| CN106691487A (en) | Imaging method and imaging system | |
| US20130315453A1 (en) | System and method for wide cone helical image reconstruction | |
| US11205509B2 (en) | Image feature annotation in diagnostic imaging | |
| US20160216385A1 (en) | A tof-pet tomograph and a method of imaging using a tof-pet tomograph, based on a probability of producyion and lifetime of a positronium | |
| JP6021347B2 (en) | Medical image capturing apparatus and medical image capturing method | |
| CN105612433B (en) | X-ray tomographic compound imaging | |
| CN108280860A (en) | Reduce the spectrum channel number in the CT imagings of multipotency amount | |
| US20080095304A1 (en) | Energy-Resolved Computer Tomography | |
| CN109709127A (en) | Low scattered x-ray fluorescence CT imaging method |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |