CN108596967A - A kind of CT system parameter calibration and imaging algorithm - Google Patents
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Abstract
The present invention relates to CT technical applications, a kind of CT system parameter calibration and imaging algorithm are provided, to solve the predicament of CT system in practical applications：It is uniform dielectric, template geological information and in the case of absorptivity in known template, determines 180 directions of the distance and X-ray between position of the CT system rotation center in square pallet, detector cells；Using obtained calibrating parameters, the information such as position, geometry and absorptivity of the unknown medium in square pallet are determined；By known calibrating parameters, the relevant information of unknown medium is determined；The precision and stability of parameter calibration is discussed.The present invention gives certain rational hypothesis：Sample is infinitely thin, and parallel-plate is when rotated without offset.The present invention has the characteristics that with high accuracy, and obtained resultant error is small, close to actual value.
Description
Technical field
The present invention relates to CT technical applications, specifically a kind of CT system parameter calibration and imaging algorithm.
Background technology
CT is the abbreviation of Computerized Tomography, i.e. computer tomography.CT technologies refer to one kind not
Under the premise of destroying internal structure of body, by obtaining certain physical quantity (such as velocity of wave, x-ray light intensity, electron beam around object
It is strong etc.) data for projection, rebuild the X-Y scheme in the specific level of object by the processing of computer in conjunction with certain mathematical algorithm
Picture, and according to a series of technology of two dimensional images composition 3-D view.
Radon transformation is the main theoretical basis of CT technologies.Radon is converted and was proposed in 1917 by mathematician Radon,
Radon transformation is exactly the theoretical method for asking projection in simple terms.Under two-dimensional case, edge and initial point distance are d in a plane,
Deflection is that the straight line of θ does line integral to original function f (x, y), and obtained transform F (d, θ) is exactly the Radon transformation of function f.
With the development and progress of CT technologies, possessed huge advantage is increasingly prominent in terms of substance detection, makes it
It is widely used in fields such as medicine, engineering science, industry, agricultural, safety detections.But when CT system installation often
There are errors, this affects the quality of imaging.Therefore it needs to carry out parameter calibration to mounted CT system, i.e., by means of known
The parameter of sample (being known as template) calibration CT system of structure, and the sample of unknown structure is imaged accordingly.
Invention content
The invention aims to solve the deficiencies in the prior art, a kind of CT system parameter calibration and imaging are provided
Algorithm has carried out parameter calibration since to mounted CT system.
In order to achieve the above objectives, the present invention is implemented according to following technical scheme：
A kind of CT system parameter calibration and imaging algorithm, including solve problems with：
S1, the oval calibrating template that two homogeneous solid medium compositions are placed on square pallet, and demarcating
On two homogeneous solid media of template place two different unknown media object, wherein calibrating template be uniform dielectric and
The geological information and absorptivity of calibrating template are it is known that according to the calibrating template and its data information of reception CT system, then
Determine the calibrating parameters of CT system：Distance between position of the CT system rotation center in square pallet, detector cells
And 180 directions of X-ray；
S2, using two-dimentional Radon transformation and two unknown media of Radon inverse transformations pair object CT image reconstructions, really
The geometry of the object of fixed two unknown media, according to two unknown media connecing at the different location on square pallet
The data information of CT system is received to determine the absorptivity of the object of two unknown media, and then calibrating parameters and data determine two
Position of the object of unknown medium in square pallet；
Specifically, the specific solution of the S1 is as follows：
Cartesian coordinate system is established as origin using the square pallet lower left corner first, data are analyzed and are counted, are obtained
It is -90 system mode when spending to go out system mode and X-ray when X-ray and y-axis angle are 0 degree and y-axis angle, passes through statistics
Detector receives the probe unit number of information and the geological information of oval medium when direction is spent for -90, can find out probe unit
The distance between；
Secondly, detector reception information state when direction is 0 degree and direction is spent for -90 is counted respectively solves rotation center
Position, the geometry and the system for analyzing CT system rotate 180 times counterclockwise around rotation center, obtains what CT system used
180 directions of X-ray.
Specifically, the specific solution of the S2 is as follows：
If f (x) is a function of two-dimensional space, Radon transformation, Rf be one in two-dimensional space along the line of straight line
Integral, R are the operator of Radon transformation, and formula is as follows：
Rf (L)=∫Lf(x)|dx|
Specifically, straight line L is replaced using length t, formula：
(x (t), y (t))=((tsin α+scos α), (- tcos α+ssin α))
Wherein, s is the distance of the L from origin to straight line, and angles of the α between straight line L normal vectors and x-axis, therefore,
Radon transformation is expressed as：
And the geometric meaning of two dimension Radon transformation is exactly function f (x, y) along the integral perpendicular to the direction of straight line L,
Radon inverse transformations are then：
Filter back-projection algorithm based on Fourier's Slice Theorem：
It is specifically described the substantive content of Fourier's Slice Theorem by defining the two-dimensional Fourier transform of object, it is as follows：
Assuming that angle, θ is projected as Pθ(t), then its Fourier transformation is：
As condition θ=0, Fourier's Slice Theorem is the simplest, and first, as V=0 in double integral, consideration is object
Body is along the Fourier transformation of straight line on frequency domain, then the Fourier transformation integral of above formula is reduced to：
According to the meaning of parallel beam projection, determine that the item inside bracket is the projection along some constant x, at this time：
From the above equation, we can see that the right of equation represents the one-dimensional Fourier transform of projection, so, in upright projection and object letter
Meet following relationship between several two-dimensional transforms：
F (u, 0)=Sθ=0(u)
In conjunction with derivation above, the mathematic(al) representation of the theorem is：
Secondly, by Fourier's Slice Theorem, the algorithm for reconstructing based on collimated beam scanning is derived, i.e. filtered back projection calculates
Method, Fourier's Slice Theorem show：The Fourier transformation once projected is straight by one of origin in two-dimentional Fourier space
Line.
Fixed coordinate system is selected in CT system, it is f (x, y) to be reconstructed image；X-ray is revolved around the object of unknown medium
Turn, therefore establish rotating coordinate system (s, t), Two coordinate system relationship is：
T=xcos θ+ysin θ
S=-xsinq+ycosq
It indicates that X-ray passes through the integral of object decaying using P (t, θ), the Fourier transformation of P (t, θ) is indicated with P (w, θ),
According to the relationship between the area element in calculus, it is shown below：
Wherein, J is Jacobi determinant, in conjunction with Fourier transformation, obtains the expression formula of P (w, θ)
Two-dimensional image Fourier transformation expression formula is：
Enabling u=wcos θ, v=wsin θ, then two formulas are equal above, and sort out f (x, y) expression formula by FBP algorithms,
It is that collimated beam scanning rebuilds mathematical formulae, is shown below：
Filter used in filter back-projection algorithm is | w |, Snic function conducts are selected in the selection of S-L filter functions
Window function obtains the system function of S-L filter functions：
Its corresponding impulse response is：
The sampling interval that d is data for projection is defined, the corresponding undistorted spatial frequency of highest is B=1/Zd, with t=1 generations
The analytical expression for entering the sample sequence that above formula obtains S-L is：
With S-L filter function reconstruction images, the geometric form of the object of unknown medium is determined to the algorithm and data mapping
Shape.
Compared with prior art, the present invention has the characteristics that with high accuracy, and obtained resultant error is small, close to actual value.
Description of the drawings
Fig. 1 shows template schematic diagram provided in an embodiment of the present invention.
Fig. 2 shows template angular distribution figures provided in an embodiment of the present invention.
Fig. 3 shows Radon Transformation Graphs provided in an embodiment of the present invention.
Fig. 4 shows geometric meaning schematic diagram provided in an embodiment of the present invention.
Fig. 5 shows Radon transformation provided in an embodiment of the present invention and inverse transformation figure.
Fig. 6 shows CT system schematic diagram provided in an embodiment of the present invention.
Fig. 7 shows FBP algorithm flow charts provided in an embodiment of the present invention.
Fig. 8 shows the geometry schematic diagram of unknown medium provided in an embodiment of the present invention.
Fig. 9 shows uniform dielectric decaying schematic diagram provided in an embodiment of the present invention.
Figure 10 shows non-uniform dielectric decaying schematic diagram provided in an embodiment of the present invention.
Figure 11 shows CT reconstructions figure provided in an embodiment of the present invention.
Specific implementation mode
With reference to specific embodiment, the invention will be further described, in the illustrative examples and explanation of the invention
For explaining the present invention, but it is not as a limitation of the invention.
Preferably to be illustrated to the algorithm of the present invention, a kind of typical two-dimentional CT system is introduced.It puts down within the system
For the incident X-ray of row perpendicular to detector plane, each detector cells regard a receiving point, and equidistant arrangement as.X-ray
Transmitter and detector relative position immobilize, and entire emitting-receiving system rotates counterclockwise around certain fixed rotation center
180 times.To each X-ray direction, measured through the fixed two dimension in position on the detector with 512 equidistant units
Ray energy after detected medium attenuation by absorption, and 180 groups of reception information can be obtained after the processing such as gain.
In a first aspect, CT system parameter calibration provided by the invention and imaging algorithm, solve above-mentioned typical two dimension first
The problem of CT system is drawn one：The calibrating template that two homogeneous solid media composition is placed on square pallet, wherein each
The numerical value of point reflects the absorption intensity of the point, referred to herein as " absorptivity ".According to this template and its receive information, it may be determined that
The X that distance and the CT system between position of the CT system rotation center in square pallet, detector cells use is penetrated
180 directions of line.
Second aspect, CT system parameter calibration and imaging algorithm provided by the invention, can solve above-mentioned typical two dimension
The problem of CT system is drawn two：Using above-mentioned typical two-dimentional system, the reception information of certain unknown medium can be obtained.And it can lead to
After obtained calibrating parameters, the information such as position, geometry and absorptivity of the unknown medium in square pallet are determined.
The third aspect, CT system parameter calibration and imaging algorithm provided by the invention, can solve above-mentioned typical two dimension
The problem of CT system is drawn three：Using above-mentioned typical two-dimentional system, the reception information of another unknown medium can also be obtained.
And it can determine the relevant information of the unknown medium by obtained calibrating parameters.
The problem of being drawn to typical two-dimentional CT system one, is described in detail：
Descartes's rectangular coordinate system is established in the square pallet lower left corner as shown in Figure 1, believing by several picture and reception
The image procossing of breath solves.
Solution to the distance between detector cells：
The information data received from attachment two is analyzed, obtain ET arrange in have 156 be 0 data, i.e.,
There are 156 probe units to can receive data on the detector, this be all directions receive minimal data, it may be determined that at this time for
The information that X-ray is received along detector when template transverse direction is shown the data that 289 are not 0 in BF, that is, is being visited
Surveying on device has 289 probe units to can receive data, this receives most data for all directions, you can determines to be BF at this time
It is classified as the information that X-ray is received along detector when template ellipse short shaft direction.The known a length of 80mm of transverse, therefore,
If the distance between detector cells are d, then
Therefore the distance between detector cells are 0.2778mm.
Solution to CT system rotation center：
The data that information BF row are received by attachment two are corresponding transverse from detector Unit 92 to 380 red cloud data
The long information received, to there is the position of rotation center y to be
The data that information ET row are received by attachment two are corresponding ellipse short shaft from detector Unit 169 to 276 cell datas
The long information received, to there is the position of rotation center x to be
It can to sum up obtain, the position for this CT system rotation center is (40.6944,55.5556).
The solution in 180 directions of the X-ray that CT system is used：
By the data of comprehensive analysis attachment two ET and BF row, ET is classified as X-ray along detector when transverse direction
The information received, BF is classified as the information that X-ray is received along detector when template ellipse short shaft direction, it is now assumed that X-ray
180 direction X-rays and the angle of y-axis indicate that whole system rotates counterclockwise around rotation center, then the side that ET row represent
To being 0 degree, the direction that represents of BF row is -90 to spend, and check in attachment two from BF to ET row corotating 93 times.From start to
BF row corotatings 57 times, therefore direction when just starting is -145.7609 degree arranges from ET to terminating corotating 106 times, therefore knot
Direction when beam is 29.3478 degree.In conclusion 180 directions of the X-ray used to this CT system are from -145.7609
It spends to 29.3478 degree.Analog result is as shown in Figure 2.
The problem of being drawn to typical two-dimentional CT system two, is described in detail：
Using two-dimentional Radon transformation and Radon inverse transformations to image reconstruction, what Radon inverse transformations were used is based in Fu
The filtered back-projection method of leaf slice theorem, rebuilds parallel beam projection, it is determined that the geometry of unknown medium, simultaneously
Policy Shepp-Logan models are obtained, implementation model is rebuild again using algorithm after improvement.
Radon is converted：
Data after Radon transformation are also referred to as sinogram, and the Radon of Dirac function is transformed to point of a sine wave
Cloth, therefore, the Radon transformation of object are presented as the combination of sine wave, as shown in Figure 3.
If f (x) is a function of two-dimensional space, Radon transformation, Rf be one in two-dimensional space along the line of straight line
Integral, R are the operator of Radon transformation, and formula is as follows：
Rf (L)=∫Lf(x)|dx|
Specifically, straight line L can be replaced using length t, formula：
(x (t), y (t))=((tsin α+scos α), (- tcos α+ssin α))
Wherein, s is the distance of the L from origin to straight line, and angles of the α between straight line L normal vectors and x-axis.Therefore,
Radon transformation can be expressed as：
And the geometric meaning of two dimension Radon transformation is exactly function f (x, y) along the integral perpendicular to the direction of straight line L, such as
Shown in Fig. 4.
Radon inverse transformations are then：
Accordingly, Radon transformation is interpreted as parallel beam orthographic projection, then its inverse transformation indicates parallel beam CT image reconstruction mistakes
Journey.Doing Radon transformation, the results are shown in Figure 5 with inverse transformation.
Filter back-projection algorithm based on Fourier's Slice Theorem：
First, it is specifically described the substantive content of Fourier's Slice Theorem by defining the two-dimensional Fourier transform of object,
It is as follows：
Assuming that angle, θ is projected as Pθ(t), then its Fourier transformation is：
As condition θ=0, Fourier's Slice Theorem is the simplest.First, as V=0 in double integral, consideration is object
Body is along the Fourier transformation of straight line on frequency domain, then the Fourier transformation integral of above formula can be reduced to：
According to the meaning of parallel beam projection, it may be determined that the item inside bracket is the projection along some constant x, at this time：
From the above equation, we can see that the right of equation represents the one-dimensional Fourier transform of projection, so, in upright projection and object letter
Meet following relationship between several two-dimensional transforms：
F (u, 0)=Sθ=0(u)
In conjunction with derivation above, the mathematic(al) representation of the theorem is：
Secondly, by Fourier's Slice Theorem, we can derive that the algorithm for reconstructing based on collimated beam scanning, i.e. filtering are anti-
Projection algorithm.Fourier's Slice Theorem shows：The Fourier transformation once projected is in two-dimentional Fourier space by origin
Straight line.
For the X-ray of parallel incidence perpendicular to detector plane, each detector cells regard a receiving point, and equidistant row as
Row.The transmitter and detector relative position of X-ray immobilize, and entire emitting-receiving system is around certain fixed rotation center
Rotation 180 times counterclockwise.CT system is as shown in Figure 6.
It is chosen to be fixed coordinate system, therefore it is f (x, y) to be reconstructed image；X-ray is rotated around measured object, therefore establishes rotation
Turn coordinate system (s, t).Two coordinate system relationship is：
T=xcos θ+ysin θ
S=-xsinq+ycosq
It indicates that X-ray passes through the integral of object decaying using P (t, θ), the Fourier transformation of P (t, θ) is indicated with P (w, θ).
According to the relationship between the area element in calculus, it is shown below：
Wherein, J is Jacobi determinant.In conjunction with Fourier transformation, the expression formula of P (w, θ) is obtained
Two-dimensional image Fourier transformation expression formula is：
U=wcos θ, v=wsin θ are enabled, then two formulas are equal above, and FBP algorithm flow charts are as shown in Figure 7.Sort out f
(x, y) expression formula is that collimated beam scanning rebuilds mathematical formulae, is shown below：
Filter used in filter back-projection algorithm is | w |, the selection of S-L filter functions.In order to alleviate oscillatory response,
We select Snic functions as window function, then obtain the system function of S-L filter functions：
Its corresponding impulse response is：
The sampling interval that d is data for projection is defined, the corresponding undistorted spatial frequency of highest is B=1/Zd, with t=1 generations
The analytical expression for entering the sample sequence that above formula obtains S-L is：
With S-L filter function reconstruction images, because its oscillating phase should reduce, to the reconstruction matter of noise-containing data for projection
Amount is preferable.The geometry of unknown medium is as shown in Figure 8 to be determined to the algorithm and data mapping.
By being analyzed data to obtain the geometric figure a length of 81.9510mm of elliptical long axis, short axle is a length of
43.0590mm.The position of the ellipse center of gravity in square pallet is (50,50) and long axial length and y-axis into 60 degree of angles.
Since the CT data sources rebuild are the decaying of X-ray, exponential law is obeyed in the decaying of X-ray, and uniform dielectric declines
Subtracting schematic diagram, schematic diagram is as shown in Figure 10 as shown in figure 9, non-uniform dielectric is decayed, the incident intensity I of X-ray0, intensity in transmission I
Relationship with the thickness d of voxel is：
I=I0e-μd
Therefore, object absorbs energy IsFor：
Is=I0- I=I0-I0e-μd
However actual conditions are, what we obtained is the data for projection after decaying, and therefore, data for projection should be：
The problem of being drawn to typical two-dimentional CT system three, is described in detail：
Because object is unknown medium, absorptivity changes, the position change in square pallet.Utilize known calibration parameter
The position for determining geometry and in pallet with image, and then solve absorptivity.The geological information result of unknown medium is such as
Shown in Figure 11.
Certainly, in order to improve the precision and stability of system parameter calibration, can also use normalization average absolute value away from
From the parameter for judging evaluation calibration：
Wherein, tU, v, γU, vTest model and u rows in image after reconstruction, the absorption energy of v row are indicated respectively；For
Test model absorbs the average value of energy；The cell number of image is N × N.When r is 0, then error is zero, and precision is higher；r
Bigger, then error is bigger, and precision is lower.
Technical scheme of the present invention is not limited to the limitation of above-mentioned specific embodiment, every to do according to the technique and scheme of the present invention
The technology deformation gone out, each falls within protection scope of the present invention.
Claims (3)
1. a kind of CT system parameter calibration and imaging algorithm, which is characterized in that including：
S1, the oval calibrating template that two homogeneous solid medium compositions are placed on square pallet, and in calibrating template
Two homogeneous solid media on place two different unknown media object, wherein calibrating template be uniform dielectric and calibration
The geological information and absorptivity of template are then to be determined it is known that according to the calibrating template and its data information of reception CT system
The calibrating parameters of CT system：Distance between position of the CT system rotation center in square pallet, detector cells and X
180 directions of ray；
S2, using two-dimentional Radon transformation and two unknown media of Radon inverse transformations pair object CT image reconstructions, determine two
The geometry of the object of a unknown medium, according to reception CT of two unknown media at the different location on square pallet
The data information of system determines the absorptivity of the object of two unknown media, so calibrating parameters and data determine two it is unknown
Position of the object of medium in square pallet.
2. CT system parameter calibration according to claim 1 and imaging algorithm, which is characterized in that the specific solution of the S1
It is as follows：
Cartesian coordinate system is established as origin using the square pallet lower left corner first, data are analyzed and are counted, show that X is penetrated
System mode and X-ray when line and y-axis angle are 0 degree and y-axis angle are -90 system mode when spending, and pass through and count direction
Detector receives the probe unit number of information and the geological information of oval medium when being spent for -90, can find out between probe unit
Distance；
Secondly, detector when direction is 0 degree and direction is spent for -90 is counted respectively receives the position that information state solves rotation center
It sets, the geometry and the system for analyzing CT system rotate 180 times counterclockwise around rotation center, show that the X that CT system uses is penetrated
180 directions of line.
3. CT system parameter calibration according to claim 1 and imaging algorithm, which is characterized in that the specific solution of the S2
It is as follows：
If f (x) is a function of two-dimensional space, Radon transformation, Rf is one and is accumulated along the line of straight line in two-dimensional space
Point, R is the operator of Radon transformation, and formula is as follows：
Rf (L)=∫Lf(x)|dx|
Specifically, straight line L is replaced using length t, formula：
(x (t), y (t))=((tsin α+scos α), (- tcos α+ssin α))
Wherein, s is the distance of the L from origin to straight line, and angles of the α between straight line L normal vectors and x-axis, therefore,
Radon transformation is expressed as：
And the geometric meaning of two dimension Radon transformation is exactly function f (x, y) along the integral perpendicular to the direction of straight line L, Radon
Inverse transformation is then：
Filter back-projection algorithm based on Fourier's Slice Theorem：
It is specifically described the substantive content of Fourier's Slice Theorem by defining the two-dimensional Fourier transform of object, it is as follows：
Assuming that angle, θ is projected as Pθ(t), then its Fourier transformation is：
As condition θ=0, Fourier's Slice Theorem is the simplest, and first, as V=0 in double integral, consideration is that object exists
Along the Fourier transformation of straight line on frequency domain, then the Fourier transformation integral of above formula is reduced to：
According to the meaning of parallel beam projection, determine that the item inside bracket is the projection along some constant x, at this time：
From the above equation, we can see that the right of equation represents the one-dimensional Fourier transform of projection, so, in upright projection and object function
Meet following relationship between two-dimensional transform：
F (u, 0)=Sθ=0(u)
In conjunction with derivation above, the mathematic(al) representation of the theorem is：
Secondly, by Fourier's Slice Theorem, the algorithm for reconstructing based on collimated beam scanning, i.e. filter back-projection algorithm, Fu are derived
In leaf slice theorem show：The Fourier transformation once projected is the straight line by origin in two-dimentional Fourier space；
Fixed coordinate system is selected in CT system, it is f (x, y) to be reconstructed image；X-ray is rotated around the object of unknown medium, because
This establishes rotating coordinate system (s, t), and Two coordinate system relationship is：
T=xcos θ+ysin θ
S=-xsinq+ycosq
It indicates that X-ray passes through the integral of object decaying using P (t, θ), the Fourier transformation of P (t, θ) is indicated with P (w, θ), according to
The relationship between area element in calculus, is shown below：
Wherein, J is Jacobi determinant, in conjunction with Fourier transformation, obtains the expression formula of P (w, θ)
Two-dimensional image Fourier transformation expression formula is：
U=wcos θ, v=wsin θ are enabled, then two formulas are equal above, and sort out f (x, y) expression formula by FBP algorithms, are
Collimated beam scanning rebuilds mathematical formulae, is shown below：
Filter used in filter back-projection algorithm is | w |, the selection of S-L filter functions selects Snic functions as window letter
Number, obtains the system function of S-L filter functions：
Its corresponding impulse response is：
The sampling interval that d is data for projection is defined, the corresponding undistorted spatial frequency of highest is B=1/Zd, is substituted into t=1
The analytical expression that formula obtains the sample sequence of S-L is：
With S-L filter function reconstruction images, the geometry of the object of unknown medium is determined to the algorithm and data mapping.
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| CN110243847A (en) * | 2019-07-04 | 2019-09-17 | 湖南理工学院 | A kind of CT system parameter calibration and imaging method |
| CN111358465A (en) * | 2020-03-19 | 2020-07-03 | 深圳大学 | Magnetic acoustic electric imaging system and method based on filtering inverse projection |
| WO2020192265A1 (en) * | 2019-03-25 | 2020-10-01 | 同方威视技术股份有限公司 | Geometric parameter calibration piece and calibration method for ct device |
| CN112203068A (en) * | 2020-09-30 | 2021-01-08 | 中国科学院长春光学精密机械与物理研究所 | Single-pixel imaging method, system, device and medium |
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| CN109613462A (en) * | 2018-11-21 | 2019-04-12 | 河海大学 | A kind of scaling method of CT imaging |
| CN109765249A (en) * | 2018-12-26 | 2019-05-17 | 陕西师范大学 | A kind of CT system parameter calibration and imaging method based on random transformation |
| WO2020192265A1 (en) * | 2019-03-25 | 2020-10-01 | 同方威视技术股份有限公司 | Geometric parameter calibration piece and calibration method for ct device |
| US11340177B2 (en) | 2019-03-25 | 2022-05-24 | Nuctech Company Limited | Calibration assembly and method for calibrating geometric parameters of CT apparatus |
| CN110243847A (en) * | 2019-07-04 | 2019-09-17 | 湖南理工学院 | A kind of CT system parameter calibration and imaging method |
| CN111358465A (en) * | 2020-03-19 | 2020-07-03 | 深圳大学 | Magnetic acoustic electric imaging system and method based on filtering inverse projection |
| CN111358465B (en) * | 2020-03-19 | 2022-11-18 | 深圳大学 | Magnetic acoustic electric imaging system and method based on filtering inverse projection |
| CN112203068A (en) * | 2020-09-30 | 2021-01-08 | 中国科学院长春光学精密机械与物理研究所 | Single-pixel imaging method, system, device and medium |
| WO2023124452A1 (en) * | 2021-12-27 | 2023-07-06 | 同方威视技术股份有限公司 | Calibration assembly, calibration phantom, and calibration method |
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