US11087508B2  Method and apparatus for acceleration of iterative reconstruction of a computed tomography image  Google Patents
Method and apparatus for acceleration of iterative reconstruction of a computed tomography image Download PDFInfo
 Publication number
 US11087508B2 US11087508B2 US16/206,922 US201816206922A US11087508B2 US 11087508 B2 US11087508 B2 US 11087508B2 US 201816206922 A US201816206922 A US 201816206922A US 11087508 B2 US11087508 B2 US 11087508B2
 Authority
 US
 United States
 Prior art keywords
 image
 subsets
 gradient
 objective function
 updating
 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.)
 Active
Links
 238000002591 computed tomography Methods 0.000 title abstract description 25
 230000001133 acceleration Effects 0.000 title description 13
 239000011159 matrix material Substances 0.000 claims description 9
 230000002829 reduced Effects 0.000 claims description 7
 230000001340 slower Effects 0.000 claims 4
 238000000638 solvent extraction Methods 0.000 claims 2
 238000005192 partition Methods 0.000 claims 1
 238000000034 method Methods 0.000 abstract description 24
 230000015654 memory Effects 0.000 description 14
 230000000875 corresponding Effects 0.000 description 6
 238000005457 optimization Methods 0.000 description 6
 230000000694 effects Effects 0.000 description 5
 238000010586 diagram Methods 0.000 description 4
 230000000670 limiting Effects 0.000 description 4
 238000002601 radiography Methods 0.000 description 4
 230000003190 augmentative Effects 0.000 description 3
 238000007781 preprocessing Methods 0.000 description 3
 230000002411 adverse Effects 0.000 description 2
 238000003384 imaging method Methods 0.000 description 2
 238000005259 measurement Methods 0.000 description 2
 238000009877 rendering Methods 0.000 description 2
 230000001960 triggered Effects 0.000 description 2
 102100015314 VSIR Human genes 0.000 description 1
 101710036075 VSIR Proteins 0.000 description 1
 238000004590 computer program Methods 0.000 description 1
 238000002939 conjugate gradient method Methods 0.000 description 1
 239000000470 constituent Substances 0.000 description 1
 238000001514 detection method Methods 0.000 description 1
 238000003745 diagnosis Methods 0.000 description 1
 238000002059 diagnostic imaging Methods 0.000 description 1
 238000001914 filtration Methods 0.000 description 1
 238000009499 grossing Methods 0.000 description 1
 230000003993 interaction Effects 0.000 description 1
 239000002184 metal Substances 0.000 description 1
 230000004048 modification Effects 0.000 description 1
 238000006011 modification reaction Methods 0.000 description 1
 230000036961 partial Effects 0.000 description 1
 229910052704 radon Inorganic materials 0.000 description 1
 SYUHGPGVQRZVTBUHFFFAOYSAN radon(0) Chemical compound data:image/svg+xml;base64,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 data:image/svg+xml;base64,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 [Rn] SYUHGPGVQRZVTBUHFFFAOYSAN 0.000 description 1
 230000035945 sensitivity Effects 0.000 description 1
 230000003068 static Effects 0.000 description 1
 238000006467 substitution reaction Methods 0.000 description 1
 238000003325 tomography Methods 0.000 description 1
 230000001702 transmitter Effects 0.000 description 1
 229910052724 xenon Inorganic materials 0.000 description 1
 FHNFHKCVQCLJFQUHFFFAOYSAN xenon(0) Chemical compound data:image/svg+xml;base64,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 data:image/svg+xml;base64,PD94bWwgdmVyc2lvbj0nMS4wJyBlbmNvZGluZz0naXNvLTg4NTktMSc/Pgo8c3ZnIHZlcnNpb249JzEuMScgYmFzZVByb2ZpbGU9J2Z1bGwnCiAgICAgICAgICAgICAgeG1sbnM9J2h0dHA6Ly93d3cudzMub3JnLzIwMDAvc3ZnJwogICAgICAgICAgICAgICAgICAgICAgeG1sbnM6cmRraXQ9J2h0dHA6Ly93d3cucmRraXQub3JnL3htbCcKICAgICAgICAgICAgICAgICAgICAgIHhtbG5zOnhsaW5rPSdodHRwOi8vd3d3LnczLm9yZy8xOTk5L3hsaW5rJwogICAgICAgICAgICAgICAgICB4bWw6c3BhY2U9J3ByZXNlcnZlJwp3aWR0aD0nODVweCcgaGVpZ2h0PSc4NXB4JyB2aWV3Qm94PScwIDAgODUgODUnPgo8IS0tIEVORCBPRiBIRUFERVIgLS0+CjxyZWN0IHN0eWxlPSdvcGFjaXR5OjEuMDtmaWxsOiNGRkZGRkY7c3Ryb2tlOm5vbmUnIHdpZHRoPSc4NScgaGVpZ2h0PSc4NScgeD0nMCcgeT0nMCc+IDwvcmVjdD4KPHRleHQgeD0nMzUuMDQ1NScgeT0nNTMuNTkwOScgY2xhc3M9J2F0b20tMCcgc3R5bGU9J2ZvbnQtc2l6ZToyM3B4O2ZvbnQtc3R5bGU6bm9ybWFsO2ZvbnQtd2VpZ2h0Om5vcm1hbDtmaWxsLW9wYWNpdHk6MTtzdHJva2U6bm9uZTtmb250LWZhbWlseTpzYW5zLXNlcmlmO3RleHQtYW5jaG9yOnN0YXJ0O2ZpbGw6IzNCNDE0MycgPlg8L3RleHQ+Cjx0ZXh0IHg9JzUxLjA0MDknIHk9JzUzLjU5MDknIGNsYXNzPSdhdG9tLTAnIHN0eWxlPSdmb250LXNpemU6MjNweDtmb250LXN0eWxlOm5vcm1hbDtmb250LXdlaWdodDpub3JtYWw7ZmlsbC1vcGFjaXR5OjE7c3Ryb2tlOm5vbmU7Zm9udC1mYW1pbHk6c2Fucy1zZXJpZjt0ZXh0LWFuY2hvcjpzdGFydDtmaWxsOiMzQjQxNDMnID5lPC90ZXh0Pgo8L3N2Zz4K [Xe] FHNFHKCVQCLJFQUHFFFAOYSAN 0.000 description 1
Images
Classifications

 G—PHYSICS
 G06—COMPUTING; CALCULATING; COUNTING
 G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
 G06T11/00—2D [Two Dimensional] image generation
 G06T11/003—Reconstruction from projections, e.g. tomography
 G06T11/006—Inverse problem, transformation from projectionspace into objectspace, e.g. transform methods, backprojection, algebraic methods

 G—PHYSICS
 G06—COMPUTING; CALCULATING; COUNTING
 G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
 G06T2211/00—Image generation
 G06T2211/40—Computed tomography
 G06T2211/424—Iterative
Abstract
Description
Ax=y,
wherein y is the projection data, x is the image being reconstructed, and A represents a forward projection operator.
with βU(x) being the regularization term and the data fidelity term being
L(x)=½(y−Ax)^{T} W(y−Ax),
wherein the matrix W can be a diagonal matrix in which the values along the diagonal are the statistical weights. In the regularization term, the regularization function U(·) is multiplied by a regularization parameter β, which adjusts the strength of the regularization term. Finally, the symbol T denotes matrix or vector transpose.
wherein Ω_{n }is the nth subset of the entire set of projection data Ω. Often Φ_{n}(x)≈Φ(x), ∀n. When the subsets are nonoverlapping and equally sized, the total objective function Φ(x) is the average of the constituent subset objective functions Φ_{n}(x), i.e.,
{circumflex over (x)}=argmin_{x≥0}Φ(x), Φ(x)=L(x)+βU(x).
For purposes of illustration, process 130 is described using the nonlimiting example of the regularization function U(·) being the total variation functional:
Here {right arrow over (i)} and {right arrow over (j)} are threedimensional indices, and ϵ>0 is a small positive number that ensures that the TV functional is differentiable. The condition {right arrow over (i)}−{right arrow over (j)}=1=1 means that the summation inside the square root in the above expression is over the following six values {right arrow over (j)}∈{{right arrow over (i)}±(1,0,0), {right arrow over (i)}±(0,1,0)},˜0), {right arrow over (i)}±(0,0,1)}, Let x_{0 }be an initial volume (can be zero or the result of FBP reconstruction), and let P_{n }denote a preconditioner. In certain implementations, the preconditioner can change from subiteration to subiteration.
wherein A_{n }is the forward projection matrix corresponding to the views of the subset Ω_{n}, y_{n }is the projection data corresponding to the views in Ω_{n}, and ∇U(x_{n}) is the gradient of the regularization term evaluated using the current reconstructed image x_{n}.
Note that f_{1 }and f_{2 }are the OS versions of the first and second order derivatives of the data fidelity term in the direction of p_{n}. Here, as before, A_{n }is the forward projection matrix corresponding to the views in Ω_{n}, and the dot (inner) products (⋅,⋅) are computed also using the views in Ω_{n}.
x _{n+1} =x _{n}+α_{n} p _{n}.
can be applied to all the terms that make up the TV functional U(x_{n}+tp_{n}) and combining all the coefficients in front of t^{2}/2 yields an expression for d_{2}. In this case, the resulting quadratic function is a parabolic surrogate, but not a separable parabolic surrogate.
p _{n} =−Pr _{n}.
wherein u_{i }can be defined by
In certain implementations, the FletcherReeves formula is preferable when gradients are computed approximately (e.g., when using OS) because it does not use the difference of gradients at two subiterations. If different subsets are used for computing r_{n }and r_{n−1}, then the error in computing their difference may be large. If, in later iterations, the number of subsets is small, then the formulas for computing γ_{n }based on r_{n}−r_{n−1 }might be effectively used as well.
In certain implementations, a diagonal preconditioner can be used, e.g., when the diagonal entry of P^{−1 }corresponds to the i^{th }voxel is given by
In other implementations, a Fourier preconditioner can be used. Alternatively, the preconditioner can be updated every iteration e.g. using the above equation for the diagonal entries of P^{−1}, in which u_{i }and u_{j }can be updated every iteration using the equation
Claims (26)
Priority Applications (1)
Application Number  Priority Date  Filing Date  Title 

US16/206,922 US11087508B2 (en)  20181130  20181130  Method and apparatus for acceleration of iterative reconstruction of a computed tomography image 
Applications Claiming Priority (2)
Application Number  Priority Date  Filing Date  Title 

US16/206,922 US11087508B2 (en)  20181130  20181130  Method and apparatus for acceleration of iterative reconstruction of a computed tomography image 
JP2019035118A JP2020081837A (en)  20181130  20190228  Xray image processing apparatus, Xray diagnostic apparatus, and Xray image processing method 
Publications (2)
Publication Number  Publication Date 

US20200175731A1 US20200175731A1 (en)  20200604 
US11087508B2 true US11087508B2 (en)  20210810 
Family
ID=70849754
Family Applications (1)
Application Number  Title  Priority Date  Filing Date 

US16/206,922 Active US11087508B2 (en)  20181130  20181130  Method and apparatus for acceleration of iterative reconstruction of a computed tomography image 
Country Status (2)
Country  Link 

US (1)  US11087508B2 (en) 
JP (1)  JP2020081837A (en) 
Citations (2)
Publication number  Priority date  Publication date  Assignee  Title 

US20080270465A1 (en) *  20070425  20081030  Siemens Medical Solutions Usa, Inc.  NNLS Image Reconstruction 
US20140140599A1 (en)  20121121  20140522  The Regents Of The University Of Michigan  Ordered subsets with momentum for xray ct image reconstruction 

2018
 20181130 US US16/206,922 patent/US11087508B2/en active Active

2019
 20190228 JP JP2019035118A patent/JP2020081837A/en active Pending
Patent Citations (2)
Publication number  Priority date  Publication date  Assignee  Title 

US20080270465A1 (en) *  20070425  20081030  Siemens Medical Solutions Usa, Inc.  NNLS Image Reconstruction 
US20140140599A1 (en)  20121121  20140522  The Regents Of The University Of Michigan  Ordered subsets with momentum for xray ct image reconstruction 
NonPatent Citations (4)
Title 

I.K. Hong, et al. "Ultrafast Preconditioned Conjugate Gradient OSEM Algorithm for Fully 3D PET Reconstruction" published in Nuclear Science Symposium Conference Record (NSS/MIC), 2010 IEEE, Oct. 30, 2010Nov. 6, 2010, pp. 24. 
J. A. Fessler, et al. "Conjugategradient preconditioning methods for shiftvariant PET image reconstruction" IEEE Trans. Im. Proc., 8(5):68899, May 1999. 
Lin Fu, et al. "Spacevariant channelized preconditioner design for 3D iterative CT reconstruction", Proc. Intl. Mtg. on Fully 3D Image Recon. in Rad. and Nuc. Med, pp. 205208, 2013. 
Zhou Yu, et al. "Nested Loop Algorithm for Parallel Model Based Iterative Reconstruction," the proceedings of the 12th International Meeting on Fully ThreeDimensional Image Reconstruction in Radiology and Nuclear Medicine}, pp. 197200, Lake Tahoe, California, Jun. 1621, 2013. 
Also Published As
Publication number  Publication date 

US20200175731A1 (en)  20200604 
JP2020081837A (en)  20200604 
Similar Documents
Publication  Publication Date  Title 

JP5972958B2 (en)  Image processing method and Xray computed tomography apparatus  
US8958660B2 (en)  Method and apparatus for iterative reconstruction  
US9911208B2 (en)  Apparatus and method of iterative image reconstruction using regularizationparameter control  
JP6280700B2 (en)  Iterative reconstruction method, nontransitory computer readable medium and imaging system  
US6907102B1 (en)  Iterative reconstruction methods for multislice computed tomography  
US10204425B2 (en)  Fast iterative reconstruction with one backprojection and no forward projection  
JP2008006288A (en)  System and method for iterative image reconstruction  
US9600924B2 (en)  Iterative reconstruction of image data in CT  
US9449385B2 (en)  Reconstruction of computed tomography images using combined thirdgeneration and fourthgeneration projection data  
JP2016152916A (en)  Xray computer tomographic apparatus and medical image processing apparatus  
RU2598159C2 (en)  Method of images reconstruction for a filtered back projection in limited angle tomography  
JP6222813B2 (en)  Xray computed tomography apparatus, image processing apparatus and image processing method  
US10937206B2 (en)  Deeplearningbased scatter estimation and correction for Xray projection data and computer tomography (CT)  
CN110136218A (en)  CT projection denoising method for reconstructing and device based on noise generting machanism and datadriven tight frame  
US10692251B2 (en)  Efficient variancereduced method and apparatus for modelbased iterative CT image reconstruction  
JP2021013737A (en)  Xray system and imaging program  
Cierniak et al.  A practical statistical approach to the reconstruction problem using a single slice rebinning method  
US20080086052A1 (en)  Methods and apparatus for motion compensation  
US11087508B2 (en)  Method and apparatus for acceleration of iterative reconstruction of a computed tomography image  
US11060987B2 (en)  Method and apparatus for fast scatter simulation and correction in computed tomography (CT)  
JP6878147B2 (en)  Xray computed tomography equipment and medical image processing equipment  
US10307114B1 (en)  Iterative volume image reconstruction using synthetic projection images  
JP6956505B2 (en)  Image processing device, Xray CT device and image processing method  
US20190272653A1 (en)  System and method for tomographic image reconstruction  
US10515467B2 (en)  Image reconstruction system, method, and computer program 
Legal Events
Date  Code  Title  Description 

FEPP  Fee payment procedure 
Free format text: ENTITY STATUS SET TO UNDISCOUNTED (ORIGINAL EVENT CODE: BIG.); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY 

STPP  Information on status: patent application and granting procedure in general 
Free format text: NOTICE OF ALLOWANCE MAILED  APPLICATION RECEIVED IN OFFICE OF PUBLICATIONS 

AS  Assignment 
Owner name: THE UNIVERSITY OF CENTRAL FLORIDA RESEARCH FOUNDATION, INC., FLORIDA Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:KATSEVICH, ALEXANDER;REEL/FRAME:053696/0553 Effective date: 20200721 Owner name: CANON MEDICAL SYSTEMS CORPORATION, JAPAN Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:YU, ZHOU;SHI, DAXIN;SIGNING DATES FROM 20200820 TO 20200825;REEL/FRAME:053696/0528 

STCT  Information on status: administrative procedure adjustment 
Free format text: PROSECUTION SUSPENDED 

STPP  Information on status: patent application and granting procedure in general 
Free format text: NOTICE OF ALLOWANCE MAILED  APPLICATION RECEIVED IN OFFICE OF PUBLICATIONS 

STPP  Information on status: patent application and granting procedure in general 
Free format text: DOCKETED NEW CASE  READY FOR EXAMINATION 

STPP  Information on status: patent application and granting procedure in general 
Free format text: NOTICE OF ALLOWANCE MAILED  APPLICATION RECEIVED IN OFFICE OF PUBLICATIONS 

STPP  Information on status: patent application and granting procedure in general 
Free format text: PUBLICATIONS  ISSUE FEE PAYMENT RECEIVED 

STPP  Information on status: patent application and granting procedure in general 
Free format text: PUBLICATIONS  ISSUE FEE PAYMENT VERIFIED 

STCF  Information on status: patent grant 
Free format text: PATENTED CASE 