CN107328798A - A kind of novel I CL systems and implementation method - Google Patents
A kind of novel I CL systems and implementation method Download PDFInfo
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- 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
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- G01N23/046—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 using tomography, e.g. computed tomography [CT]
Abstract
The present invention relates to a kind of novel I CL systems, belong to computer Stratified Imaging field.The system includes radiographic source, flat panel detector, testing sample, platform, the radiographic source is fixed on platform, flat panel detector and testing sample are moved along equidirectional parallel lines, simultaneously in scanning process middle plateform detector synchronous axial system, make system vertical with radiographic source central beam all the time in data acquisition middle plateform detector.The invention further relates to a kind of novel I CL implementation methods, this method comprises the following steps：Set up imaging model；Using iterative reconstruction algorithm.Simple in construction, inexpensive, realizability of the invention is high, Non-Destructive Testing ICL systems available for large scale tabular component.
Description
Technical field
The invention belongs to computer Stratified Imaging field, it is related to a kind of novel I CL systems and implementation method.
Background technology
Computer tomography (Computed Tomography, CT) is a more ripe non-destructive testing technology, energy
It is enough that imaging analysis effectively are carried out to internal structure of body, it is widely used to the fields such as industry, medical science and aviation.Typical
In fladellum industrial CT system, testing sample is positioned on the turntable between X-ray tube and flat panel detector, is produced by X-ray tube
Raw X rays are collected by detector after object is decayed and stored.In order to which the reconstruction image obtained through sample sheet is at least needed
Want the data for projection of 180 degree.Due to geometry limitation, obtain 180 degree data for projection for the component of oversized dimensions almost
It is impossible.Simultaneously for the length and width tabular component big more than thickness, such as multilayer board, wing or defend
Star solar panels etc., when beam and component close to it is parallel when, its intensity in transmission is very low, significantly impacts the detection effect of component
Really；On the other hand, in order to avoid collision, the distance of ray tube and rotating shaft can not be too small, so as to limit the space point of CT system
Resolution.In these cases, computer demixing scan imaging (Computed Laminography, CL) technology becomes one kind
Substitute CT possibility.
In recent years, the research and development of X ray computer demixing scan imaging technique attracts people's attention.Typical CL system masters
To include three parts：X-ray source, detector and objective table.Its feature is that the object of scanning is flat object, CL systems
System is scanned using non-coaxial mode, and X-ray is passed through along the direction angled with tabular sample plane normal, passes through X-ray
Simple relative parallel movement is done in source and the motion of detector synchronous rotary, realizes that multi-angle is scanned to sample.CL skills
Art is substantially a kind of CT technologies of the limited angle projection of non-coaxial scanning, and it belongs to non-precision reconstruction, by component
Endless full scan, realizes and the chromatography of its inner constructional form and defect is detected.
In the past few decades, it is suggested in succession for different application novel C L system or method.2013,
Sechopoulos etc. have developed a kind of chest computer Stratified Imaging system (digital breast applied to medical domain
tomosynthesis, DBT)；In industrial circle, also there are many different CL systems to be suggested.Nineteen ninety-five, Zhou etc. have developed
It is a kind of to be used to detect large-scale or planar plate members X sources CL systems, and detection printed circuit board (PCB) and weld seam are tested, preferably tied
Really；2010, Maisl etc. described applications of the CL in lightweight component context of detection；2012, Que etc. established a tackling
There are the CL systems of new Scan Architecture, and the application by the study of computer simulation algebraic reconstruction algorithm (ART) in CL imagings；It is public
The number of opening is CN1643371A, in the Chinese invention patent application of entitled " system and method for the big field-of-view objects of imaging ", is proposed
A kind of imaging device, the position for passing through mobile radiographic source and detector realizes that " scan track " scans object more, final to realize
Object more than vision detector is imaged；Yan Bin etc. solve to long materials, wide object and big object regard greatly into
As problem；2015, Liu etc., proposed in Publication No. CN105319225A Chinese invention patent a kind of industrial CL into
As system, the detection of the tabular big object of thickness of thin big to length and width yardstick the method achieve.But it comes with some shortcomings：1)
System C-arm curvature determines that ray source position immobilizes, and causes system radiographic source to flat panel detector track apart from SDNo
It is adjustable, so that visual field (Field of View, FOV) is immutable, cause system flexibility not high；2) high-precision C-arm manufacture is multiple
Miscellaneous, cost is high；Although these systems all obtain preferable result in the application of medical science and industrial circle, but they do not have
Focusing system structure complexity, cost etc..
The content of the invention
In view of this, it is an object of the invention to provide a kind of simple in construction, inexpensive, realizability it is high, for big chi
Very little tabular component Non-Destructive Testing infant industry computer Stratified Imaging (Industrial Computed Laminography,
ICL) system, and propose to be directed to CL systems image reconstruction algorithm of the present invention.
To reach above-mentioned purpose, the present invention provides following technical scheme：
A kind of novel I CL systems, including radiographic source, flat panel detector, testing sample, platform；The radiographic source, described treat
Test sample product and the flat panel detector are sequentially placed on the platform；The radiographic source is fixed on platform, is penetrated for sending
Line；The flat panel detector and the testing sample rectilinear direction along where sending ray perpendicular to the radiographic source, do in the same direction
Linear motion；In system scanning process, the radiographic source sends ray through the testing sample, and the flat panel detector is same
Step is rotated, it is ensured that it is vertical that system flat panel detector described in data acquisition sends ray with the radiographic source all the time.
A kind of novel I CL implementation methods, this method comprises the following steps：
S1：Set up imaging model；
S2：Using iterative reconstruction algorithm until image meets criterion calls.
Further, the imaging model is：
Testing sample and detector are moved all along x-axis direction synchronous parallel, take the position of any one in scanning process to visit
Study carefully angle ω sizes and testing sample maximum scan radius r sizes that detector moves track, calculation formula is：
Wherein, using x-ray source apart from the nearest point in sample track as origin, sample motion direction is that x-axis positive direction is set up
Rectangular coordinate system；It is motionless that radiographic source is fixed on a points；Object space is xp(p=1 ..., P), wherein P is the throwing that system acquisition is arrived
Shadow number, the position of detector is xD；D is the half of detector length；ω is the folder that flat panel detector panel moves track
Angle； SOFor radiographic source to the distance of testing sample track, SDFor the distance of radiographic source to flat panel detector track；
By adjusting radiographic source to testing sample track apart from SOWith radiographic source to flat panel detector track apart from SDChange
Change system angle of visual field FOV；Change the magnifying power of testing sample by moving forward and backward object, selected according to actual testing sample size
Suitable visual field and magnifying power；And in scanning process, flat panel detector synchronous axial system makes system in data acquisition
Its detector panel is vertical with radiographic source central beam all the time, reduces flat panel detector length change in scanning process.
Further, the iterative reconstruction algorithm is：First continuous image discretization, all images region is divided into limited
It is constant inside individual pixel, each pixel, constitutes a matrix to be solved, built followed by the data for projection measured
One group of algebraic equation is found, unknown images vector is tried to achieve by solving equation group；Specifically include following steps：
S201：Input data for projection piAnd assign initial value：WhereinRepresent the initial value of j-th of pixel；
S202：Calculate the estimated projection value of all rays：Wherein i=1 ..., L, L
Represent ray sum；J=1 ..., N, N represent sum of all pixels；piRepresent the projection value of i-th ray；ωijIt is projection coefficient,
Reflect contribution of j-th of pixel to i-th ray integral；
S203：Calculate correction value, the average correction term of one calculated using the correction term of all ray projections, j-th
The correction term of pixel is：
Wherein Wi,+Represent contribution of all pixels to i-th ray integral, W+,jRepresent that j-th of pixel is accumulated to all rays
The contribution divided,The projection value of i-th ray of k iteration is represented, L represents ray sum；
S204：It is modified, completes an iteration：
S205：A wheel iteration is then completed after all once being corrected to all pixels point of reconstruction image, is changed with the wheel
The result in generation is as temporary transient solution, the step of repeating S202, S203, S204, until meeting criterion calls.
The beneficial effects of the present invention are：
(1) but CL systems proposed by the present invention solve Liu etc. system exist some shortcomings：1) arc guide rail is set
Meter is changed to relatively simple straight line and oscillatory scanning pattern, simplifies Scan Architecture and motion mode, reduces system cost.2)
C-arm curvature is determined in Liu etc. CL systems, and ray source position immobilizes, and causes system radiographic source to flat panel detector rail
Mark apart from SDIt is non-adjustable, so that visual field (Field of View, FOV) is immutable.System proposed by the present invention not only radiographic source
Distance to detection object is adjustable, and SDCan also according to detection object the need for arbitrarily change, improve system flexibility,
Different detection demands are adapted to.
(2) detector size that the present invention is selected is smaller, although reduce system cost, but visual field radius is received simultaneously
Limitation, can only partial reconstruction object, need Multiple-Scan to realize to sacrifice detection efficiency for massive plate detection.For this
One problem present invention synchronous axial system during detector scanning, makes its panel vertical with radiographic source central beam all the time.Compare
In the system for the detector that do not rotate, under identical detector length, the system can obtain larger field, so that subtracting at double
Lack the scanning times of massive plate, greatly improve detection efficiency.
Brief description of the drawings
In order that the purpose of the present invention, technical scheme and beneficial effect are clearer, the present invention provides drawings described below and carried out
Explanation：
Fig. 1 is novel I CL system structure diagrams；
Fig. 2 is novel I CL system imaging geometrical models；
Fig. 3 is the spatial resolution test card for reconstruction；
Fig. 4 is 90 degree of noiseless fladellum, 120 degree, 150 degree of finite angle image reconstructions；
Fig. 5 is the profile in y=0 directions in Fig. 4；
Fig. 6 is to have 90 degree of noise fladellum, 120 degree, 150 degree of finite angle image reconstructions；
Fig. 7 is the profile in y=0 directions in Fig. 6；
Fig. 8 is noiseless fladellum 200,300,400 projection 150 degree of finite angle image reconstructions of indexing；
Fig. 9 is the profile in y=0 directions in Fig. 8.
Embodiment
Below in conjunction with accompanying drawing, the preferred embodiments of the present invention are described in detail.
1. imaging model
Synchronous parallel linear motion of the data acquiring mode based on detector and testing sample.As shown in figure 1, radiographic source is solid
Due to motionless on platform, flat panel detector and testing sample are moved along equidirectional parallel lines, while in scanning process middle plateform
Detector synchronous axial system, makes system detector in data acquisition vertical with radiographic source central beam all the time.
As shown in Figure 2.Using x-ray source apart from the nearest point in sample track as origin, sample motion direction is x-axis positive direction
Set up rectangular coordinate system.It is motionless that radiographic source is fixed on a points.Object space is xp(p=1 ..., P), wherein P arrives for system acquisition
Projection number.The position of detector is xD, d is the half of detector length.ω is that flat panel detector panel moves track
Angle.SOFor radiographic source to the distance of testing sample track, SDFor the distance of radiographic source to flat panel detector track.Treat test sample
Product and detector are moved all along x-axis direction synchronous parallel, now take the position of any one in scanning process probe into detector with
The angle ω sizes and testing sample maximum scan radius r sizes of its movement locus.
The system motion mode is simple, cost is low, easy realization, while visual field and magnifying power are adjustable.On the one hand can be by adjusting
Radiographic source is saved to testing sample track apart from SOWith radiographic source to flat panel detector track apart from SDTo change system FOV, separately
On the one hand the magnifying power of testing sample can be changed by movable object, so as to select to close according to actual testing sample size
Suitable visual field and magnifying power.And in scanning process, flat panel detector synchronous axial system, make system in data acquisition its
Detector panel is vertical with radiographic source central beam all the time.This way makes detector length change in scanning process smaller,
So as to solve linear motion the problem of the marginal position detector demand of finite angle is excessive, the profit of detector is substantially increased
With rate, cost is reduced.Symmetrical ray structure, simplifies the calculating of the projection matrix in iterative reconstruction algorithm simultaneously, improves
Reconstruction speed.
2. algorithm for reconstructing
2.1 tomographies are merged
X-ray source remains stationary in the system, flat panel detector and testing sample synchronized parallel movement, detector collection storage
The single projection data under each angle are deposited, the image of each layer of object is then obtained by processing, this method is referred to as tomography fusion
Technology.Its essence is exactly backprojection reconstruction, is that the fragmentary data in the case of finite angle is rebuild, the difference is that backprojection reconstruction
Method is operated to each point, and tomography fusion is that each layer (each row) is operated.
Although tomography fusion method is simple rapid but also has many deficiencies.Due to the classical fuzzy layered imaging skill of its imitation
Art, in scanning process, the point only on object focal plane can clearly be projected in the same area of detector, and object is located at
The part in the upper and lower face in focal plane can be projected in the different zones of detector, inevitably reconstruction image is caused it is fuzzy and
Artifact.And this method requirement magnifying power in scanning process can not change, and limitation is brought to Scan Architecture.Although image matter
Amount can be by being improved, even if so image of tomography fusion similar to the filtering technique in CT backprojection reconstruction methods
Quality is still not so good as CT.But, this method can be used in the object measurement with high-contrast in an x-ray projection, for example, print
Printed circuit board.
2.2 iterative reconstruction algorithm
In order to further improve picture quality, systemic resolution is improved, improves the immutable limit of magnifying power in scanning process
System, can use iterative reconstruction algorithm.Compared to by the tomography integration technology of data for projection simple superposition, iterative reconstruction algorithm elder generation handle
Continuous image discretization, it is constant that all images region, which is divided into inside limited pixel, each pixel, is so just constituted
One matrix to be solved, one group of algebraic equation is set up followed by the data for projection measured, by solving equation group
To try to achieve unknown images vector.Set forth herein system can be modeled as following linear matrix equation：
AX=b (3)
B=(b1,b2,...,bM)∈RMIt is data total amount, X=(X for data for projection wherein M1,...,XN)∈RNTo rebuild
Object wherein N is pixel sum, A=(amn) it is systematic survey matrix wherein m=1 ..., M, n=1 ..., N.
Classical iterative reconstruction algorithm be algebraic reconstruction algorithm (Algebraic Reconstruction Technique,
ART), the algorithm is in the iterative process of image reconstruction, by correcting the value of each pixel plus a correction term.
SIRT algorithms, that is, combine algebraic reconstruction technique, is the improved method to ART algorithms.Similarly SIRT algorithms are in specific projected angle
Under degree the renewal to temporarily solving is carried out by combining the method for correction term.Joint correction term, that is, by specific projection angle
Under the correction term that produces jointly of all rays.The basic process that SART algorithms are realized is as follows：
(1) the corresponding equation of first ray is calculated to the correction term of each pixel, and these correction terms are deposited with one
In individual array.Correction term of the corresponding equation of Article 2 ray to each pixel is calculated, and is added them in array.With this
Analogize, until calculated the corresponding equation of the last item ray to the correction term of each pixel and added them in array,
So far the renewal processing of the iterative solution under a projection angle is then completed.
(2) in the case of the step in (1) being applied to other projection angles, until reconstruction image meets certain criterion
It is required that.
The iterative formula of SART algorithms is as follows：
Wherein λkIt is relaxation factor, for suppressing over-correction, k is iterations.I=1 ..., L, L are ray sum.
J=1 ..., N, N are sum of all pixels.piFor the projection value of the i-th ray.ωijIt is projection coefficient, it reflects j-th of pixel pair
The contribution of i-th ray.Obvious projection coefficient is most important during equation solution, and they are by unknown image and known
Projection value is associated.Whole iterative process is as follows：
Input data for projection：piAssign initial value：
Calculate the estimated projection value of all rays.
Calculate correction value.The correction term of j-th of pixel is as follows：
The correction term is the average correction term of one calculated using the correction term of all ray projections.
It is modified, completes an iteration.
A wheel iteration is then completed after all once being corrected to all pixels point of reconstruction image, with the knot of the wheel iteration
Fruit is as temporarily solution, the step of repeating 2,3,4, until meeting certain criterion calls.
3. numerical simulation
In order to verify the validity of the system, at the beginning of we have done some using spatial resolution test card as testing sample
Walk emulation experiment.Because the data for projection that a linear scanning is obtained is incomplete limited angular data, therefore do not have in theory
There are exact reconstruction methods, the artifact for causing reconstructed results there are some data to cause really.It is preceding in order to improve reconstructed image quality
Many methods have been proposed in people.The data obtained herein using M-SART algorithms to system are rebuild.Fig. 3 is for rebuilding
Spatial resolution test card, its picture size be 256 × 1024, Pixel Dimensions be 1 × 1mm2.Sweep parameter is as shown in table 1.
The simulation parameter of table 1
| Parameter | Value |
| Radiographic source is to detector apart from SDD (mm) | 1800 |
| Radiographic source is to object apart from SOD (mm) | 1500 |
| Detector array length (mm) | 350 |
| Detector pixel size (mm) | 1 |
| Projection indexing | 200 300 400 |
| The radiographic source projection number of divisions P of single pass | 350 |
| Scan model | Deng angle sweep |
| Reconstruction image size | 256×1024 |
| Pixel Dimensions (mm2) | 1×1 |
| Iterations | 2000 |
The image reconstruction of 3.1 different limited angular datas
As Fig. 4 has to carry out 90 degree, 120 degree, 150 degree to spatial resolution test card using M-SIRT algorithms under fladellum
Limit angle noise-free picture to rebuild, wherein the first behavior original image, red circle mark part is effective reconstruction of partial sweep
Region.Fig. 5 gives the comparison diagram of profile gray value of the noise free data reconstruction image on y=0 straight lines under different angles.
In order to further assess listed in the quality of reconstruction image, table 2, table 3 root-mean-square error under each angle in red area and
Y-PSNR.
Reconstruction image root-mean-square error and Y-PSNR under table 2ICL systems noiseless difference finite angle
| Angle | RMSE | PSNR |
| 90 degree | 68.1281 | 11.4643 |
| 120 degree | 67.6595 | 11.5242 |
| 150 degree | 58.7665 | 12.7482 |
For test system and the noise characteristic of algorithm, we add variance for noise free data in artificial projections data
The Gaussian noise of maximum 5%.As under Fig. 6 fladellums using M-SIRT algorithms spatial resolution test card is carried out 90 degree,
120 degree, 150 degree of finite angle noise images reconstructions, wherein the first behavior original image.Fig. 7 gives reconstruction figure under different angles
As the comparison diagram of the profile gray value on y=0 straight lines.
Table 3ICL systems have reconstruction image root-mean-square error and Y-PSNR under the different finite angles of noise
| Angle | RMSE | PSNR |
| 90 degree | 68.4445 | 11.4240 |
| 120 degree | 67.9287 | 11.54897 |
| 150 degree | 59.3292 | 12.6654 |
From result above, with the increase of limited angle, the data for projection that system is obtained is more, so that obtain
Reconstruction image artifact is smaller, and picture quality is better.And the reconstructed results of lateral part are very fuzzy all the time, this is by finite angle
Degree scanning is not present what data for projection was caused in the horizontal direction.Our visual field is inside red area, outside red area
Portion also has a few rays and passed through, although the data for projection obtained in this region is seldom, but with the increase of limited angle, this portion
Low volume data is divided still to be displayed in reconstructed results.Simultaneity factor and algorithm have preferable noise characteristic.
The image reconstruction of 3.2 different projection indexing data
As Fig. 8 is thrown spatial resolution test card progress noiseless fladellum 200,300,400 using M-SIRT algorithms
Shadow indexes image reconstruction, wherein the first behavior original image.Fig. 9 gives the lower noise free data reconstruction image of projection indexing in y
Profile gray value size on=0 straight line.Each projection point is listed in the quality of reconstruction image, table 4 in order to further assess
Root-mean-square error and Y-PSNR in the lower red area of degree.
The lower reconstruction image root-mean-square error of table 4ICL systems noiseless difference projection indexing and Y-PSNR
| The number of divisions | RMSE | PSNR |
| 200 | 66.8865 | 11.8966 |
| 300 | 65.3862 | 11.8211 |
| 400 | 58.7665 | 12.7482 |
From result above, with increasing for projection indexing, data for projection that system is obtained is more so as to obtaining
Reconstruction image artifact is smaller, and picture quality is better.Similarly the reconstructed results of lateral part are very fuzzy all the time, and this is by limited
Angle scanning is not present what data for projection was caused in the horizontal direction.This group experiment is all carried out under 150 degree of finite angles simultaneously,
So thering is a small amount of data for projection to be displayed in reconstructed results in visual field perimeter.
To sum up, the present invention proposes the infant industry computer that a kind of motion mode is simple, cost is low, easily realize and separated into
As (ICL) system.And innovative another detector synchronous axial system in scanning process, makes its panel in the design of system
All the time it is vertical with radiographic source central beam.The marginal position detector demand that linear motion is solved in finite angle excessive is asked
Topic, substantially increases the utilization rate of detector and the detection efficiency of system, reduces cost, simplify the meter of iterative reconstruction algorithm
Calculate, improve reconstruction speed.A kind of improved M-SIRT algorithms are proposed applied to the system.Improved M-SIRT is used simultaneously
Algorithm has carried out preliminary fladellum two-dimensional simulation experiment to system, demonstrates the feasibility of the system.In research afterwards,
We will further improve the system, carry out three-dimensional artificial experiment and actual tests research.
Finally illustrate, preferred embodiment above is merely illustrative of the technical solution of the present invention and unrestricted, although logical
Cross above preferred embodiment the present invention is described in detail, it is to be understood by those skilled in the art that can be
Various changes are made to it in form and in details, without departing from claims of the present invention limited range.
Claims (4)
1. a kind of novel I CL systems, it is characterised in that：Including radiographic source, flat panel detector, testing sample, platform；The ray
Source, the testing sample and the flat panel detector are sequentially placed on the platform；The radiographic source is fixed on platform, is used
In sending ray；The flat panel detector and the testing sample straight line side along where sending ray perpendicular to the radiographic source
To doing linear motion in the same direction；In system scanning process, the radiographic source sends ray through the testing sample, described flat
Partitioned detector synchronous axial system, it is ensured that system flat panel detector described in data acquisition is sent with the radiographic source all the time to be penetrated
Line is vertical.
2. a kind of novel I CL implementation methods, it is characterised in that：This method comprises the following steps：
S1：Set up imaging model；
S2：Using iterative reconstruction algorithm until image meets criterion calls.
3. a kind of novel I CL system imaging methods as claimed in claim 2, it is characterised in that：The imaging model is：
Testing sample and detector are moved all along x-axis direction synchronous parallel, take the position of any one in scanning process to probe into spy
Angle ω sizes and testing sample maximum scan radius r sizes that device moves track are surveyed, calculation formula is：
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Wherein, using x-ray source apart from the nearest point in sample track as origin, sample motion direction is that x-axis positive direction sets up right angle
Coordinate system；It is motionless that radiographic source is fixed on a points；Object space is xp(p=1 ..., P), wherein P is the projection that system acquisition is arrived
Number, the position of detector is xD；D is the half of detector length；ω is the angle that flat panel detector panel moves track；
SOFor radiographic source to the distance of testing sample track, SDFor the distance of radiographic source to flat panel detector track；
By adjusting radiographic source to testing sample track apart from SOWith radiographic source to flat panel detector track apart from SDChange system
The angle of visual field of uniting FOV；Change the magnifying power of testing sample by moving forward and backward object, select suitable according to actual testing sample size
Visual field and magnifying power；And in scanning process, flat panel detector synchronous axial system makes system its spy in data acquisition
Survey device panel vertical with radiographic source central beam all the time, reduce flat panel detector length change in scanning process.
4. a kind of novel I CL system imaging methods as claimed in claim 2, it is characterised in that：The iterative reconstruction algorithm is：
First continuous image discretization, it is constant that all images region, which is divided into inside limited pixel, each pixel, constitutes one
Individual matrix to be solved, one group of algebraic equation is set up followed by the data for projection measured, is asked by solving equation group
Obtain unknown images vector；Specifically include following steps：
S201：Input data for projection piAnd assign initial value：WhereinRepresent the initial value of j-th of pixel；
S202：Calculate the estimated projection value of all rays：Wherein i=1 ..., L, L are represented
Ray sum；J=1 ..., N, N represent sum of all pixels；piRepresent the projection value of i-th ray；ωijIt is projection coefficient, reflection
Contribution of j-th of pixel to i-th ray integral；
S203：Calculate correction value, the average correction term of one calculated using the correction term of all ray projections, j-th of pixel
Correction term be：
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<msub>
<mi>&omega;</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
</msub>
<msub>
<mi>W</mi>
<mrow>
<mi>i</mi>
<mo>,</mo>
<mo>+</mo>
</mrow>
</msub>
</mfrac>
<mrow>
<mo>(</mo>
<msub>
<mi>p</mi>
<mi>i</mi>
</msub>
<mo>-</mo>
<msubsup>
<mi>p</mi>
<mi>i</mi>
<mi>k</mi>
</msubsup>
<mo>)</mo>
</mrow>
</mrow>
<msub>
<mi>W</mi>
<mrow>
<mo>+</mo>
<mo>,</mo>
<mi>j</mi>
</mrow>
</msub>
</mfrac>
</mrow>
Wherein Wi,+Represent contribution of all pixels to i-th ray integral, W+,jRepresent j-th of pixel to all ray integrals
Contribution,The projection value of i-th ray of k iteration is represented, L represents ray sum；
S204：It is modified, completes an iteration：
S205：A wheel iteration is then completed after all once being corrected to all pixels point of reconstruction image, with the wheel iteration
As a result as temporarily solution, the step of repeating S202, S203, S204, until meeting criterion calls.
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108535289A (en) * | 2018-05-03 | 2018-09-14 | 中国科学院高能物理研究所 | A kind of x-ray imaging device |
| CN108562598A (en) * | 2018-06-14 | 2018-09-21 | 江苏方建质量鉴定检测有限公司 | Detection device for detecting assembled architecture vertical member connecting node |
| CN110426404A (en) * | 2019-08-08 | 2019-11-08 | 蒋一鸣 | A kind of objective table and device for the imaging of computer demixing scan |
| CN111812130A (en) * | 2020-07-15 | 2020-10-23 | 深圳市金园智能科技有限公司 | X-ray-based material interior 3D imaging method and device |
| CN113125471A (en) * | 2021-03-31 | 2021-07-16 | 武汉联影生命科学仪器有限公司 | Scanning system and scanning control method |
| CN113406122A (en) * | 2021-06-15 | 2021-09-17 | 北京航星机器制造有限公司 | Double-mechanical-arm digital ray detection device and automatic detection method |
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Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1566932A (en) * | 1996-03-15 | 2005-01-19 | 迪罗格意大利公开有限公司 | X ray non-destructive testing device for food industry |
| US20060165213A1 (en) * | 2004-12-22 | 2006-07-27 | Siemens Aktiengesellschaft | X-ray system having a first and a second X-ray array |
| CN1971414A (en) * | 2005-11-21 | 2007-05-30 | 清华大学 | Imaging system |
| CN2935142Y (en) * | 2005-11-22 | 2007-08-15 | 清华大学 | Imaging equipment |
| CN101035464A (en) * | 2004-10-06 | 2007-09-12 | 皇家飞利浦电子股份有限公司 | Computed tomography method |
| CN102326182A (en) * | 2009-02-20 | 2012-01-18 | 沃思测量技术股份有限公司 | Method for measuring object |
| CN102590248A (en) * | 2012-03-13 | 2012-07-18 | 重庆大学 | Method for online detecting electronic element by translational type micro focus CT (Computerized Tomography) detection device |
| CN103196929A (en) * | 2013-04-18 | 2013-07-10 | 中国科学院高能物理研究所 | Scanning device and detection method based on computer layering scanning imaging CL (computed laminography) system |
| CN103808740A (en) * | 2014-02-20 | 2014-05-21 | 中国科学院高能物理研究所 | Detection method based on computer hierarchal scanning imaging CL (Computer Laminography) system |
| CN104809750A (en) * | 2015-05-04 | 2015-07-29 | 重庆大学 | Linear scanning CT system and image reconstructing method |
| CN105319225A (en) * | 2014-08-05 | 2016-02-10 | 中国科学院高能物理研究所 | Scanning method for achieving high-resolution large-view-field CL imaging of plate-shaped samples |
| US20160146968A1 (en) * | 2014-11-24 | 2016-05-26 | Wipotec Wiege- Und Positioniersysteme Gmbh | Apparatus for Examining Moving Products, in Particular Moving Piece Goods, by X-Ray |
-
2017
- 2017-06-21 CN CN201710475704.8A patent/CN107328798B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1566932A (en) * | 1996-03-15 | 2005-01-19 | 迪罗格意大利公开有限公司 | X ray non-destructive testing device for food industry |
| CN101035464A (en) * | 2004-10-06 | 2007-09-12 | 皇家飞利浦电子股份有限公司 | Computed tomography method |
| US20060165213A1 (en) * | 2004-12-22 | 2006-07-27 | Siemens Aktiengesellschaft | X-ray system having a first and a second X-ray array |
| CN1971414A (en) * | 2005-11-21 | 2007-05-30 | 清华大学 | Imaging system |
| CN2935142Y (en) * | 2005-11-22 | 2007-08-15 | 清华大学 | Imaging equipment |
| CN102326182A (en) * | 2009-02-20 | 2012-01-18 | 沃思测量技术股份有限公司 | Method for measuring object |
| CN102590248A (en) * | 2012-03-13 | 2012-07-18 | 重庆大学 | Method for online detecting electronic element by translational type micro focus CT (Computerized Tomography) detection device |
| CN103196929A (en) * | 2013-04-18 | 2013-07-10 | 中国科学院高能物理研究所 | Scanning device and detection method based on computer layering scanning imaging CL (computed laminography) system |
| CN103808740A (en) * | 2014-02-20 | 2014-05-21 | 中国科学院高能物理研究所 | Detection method based on computer hierarchal scanning imaging CL (Computer Laminography) system |
| CN105319225A (en) * | 2014-08-05 | 2016-02-10 | 中国科学院高能物理研究所 | Scanning method for achieving high-resolution large-view-field CL imaging of plate-shaped samples |
| US20160146968A1 (en) * | 2014-11-24 | 2016-05-26 | Wipotec Wiege- Und Positioniersysteme Gmbh | Apparatus for Examining Moving Products, in Particular Moving Piece Goods, by X-Ray |
| CN104809750A (en) * | 2015-05-04 | 2015-07-29 | 重庆大学 | Linear scanning CT system and image reconstructing method |
Non-Patent Citations (1)
| Title |
|---|
| 伍伟文 等: "相对平行直线扫描CT滤波反投影图像重建", 《光学学报》 * |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108535289A (en) * | 2018-05-03 | 2018-09-14 | 中国科学院高能物理研究所 | A kind of x-ray imaging device |
| CN108562598A (en) * | 2018-06-14 | 2018-09-21 | 江苏方建质量鉴定检测有限公司 | Detection device for detecting assembled architecture vertical member connecting node |
| CN110426404A (en) * | 2019-08-08 | 2019-11-08 | 蒋一鸣 | A kind of objective table and device for the imaging of computer demixing scan |
| CN111812130A (en) * | 2020-07-15 | 2020-10-23 | 深圳市金园智能科技有限公司 | X-ray-based material interior 3D imaging method and device |
| CN113125471A (en) * | 2021-03-31 | 2021-07-16 | 武汉联影生命科学仪器有限公司 | Scanning system and scanning control method |
| CN113406122A (en) * | 2021-06-15 | 2021-09-17 | 北京航星机器制造有限公司 | Double-mechanical-arm digital ray detection device and automatic detection method |
| CN113406122B (en) * | 2021-06-15 | 2022-11-15 | 北京航星机器制造有限公司 | Double-mechanical-arm digital ray detection device and automatic detection method |
| CN113533392A (en) * | 2021-07-12 | 2021-10-22 | 重庆大学 | Combined scanning CL imaging method |
| CN114581430A (en) * | 2022-03-15 | 2022-06-03 | 深圳中科飞测科技股份有限公司 | Edge detection method and device and storage medium |
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