Image reconstruction system, method, and computer program

Patent metadata

Field	Value
Publication number	US-10515467-B2
Application number	US-201615546287-A
Country	US
Kind code	B2
Filing date	Jan 20, 2016
Priority date	Feb 3, 2015
Publication date	Dec 24, 2019
Grant date	Dec 24, 2019

Abstract

The present invention relates to an image reconstruction system for statistically reconstructing images from transmission measurements. The image reconstruction system comprises an update equation providing unit for providing an update equation based on an iterative statistical model. The update equation comprises a data term and a regularization term. The invention proposes to not modify the regularization term, but rather the weights with which individual measurements contribute are modified on a per image voxel and per measurement basis. This is achieved by modifying the contributions of each measurement by including an additional weight on a per image voxel/per measurement basis. The additional weight for each measurement is determined by calculating the noise perpendicular to each measurement ray at each voxel position and a voxel and measurement dependent weight for each measurement, and integrated into the update equation's data term.

First claim

The invention claimed is:

1. An image reconstruction system for statistically reconstructing images from a plurality of transmission measurements in computed tomography, comprising:
at least one processor configured to:
provide a plurality of transmission measurements;
provide an update equation based on an iterative statistical model, wherein said update equation comprises a data term and a regularization term; and
use the update equation to process the plurality of transmission measurements based on said iterative statistical model, which accounts for an energy variation of said plurality of transmission measurements, to obtain at least one final component image having reduced noise; wherein said data term comprises a counteract weighting factor that is dependent on respective voxel and measurement, and wherein said counteract weighting factor modifies a statistical weight of said respective measurement.

2. The image reconstruction system of claim 1 ,
wherein said update equation reads

μ
j

(

n
+
1

)

=

μ
j

(
n
)

+

∑

i
=
1

N
P

⁢

[

a
ij

·

ω
ij

·

1

σ
i
2

·

(

l
i

-

m
i

(
n
)

)

]

-

β
·

R
.

⁡

(

μ
j

(
n
)

)

∑

i
=
1

N
P

⁢

[

a
ij

·

ω
ij

·

1

σ
i
2

·

a
i

]

+

β
·

R
¨

⁡

(

μ
j

(
n
)

)

,

wherein μ j (n+1) corresponds to the subsequent reconstructed value of a voxel j during iteration step n+1, μ j (n) corresponds to the value of said voxel j during iteration step n, a ij corresponds to the intersection of voxel j with a ray belonging to a measurement i, ω ij corresponds to said counteract weighting factor, σ i corresponds to the variance of said measurement i, l i corresponds to a line integral measured during said measurement i, m i (n) corresponds to a line integral for said measurement i simulated during iteration step n, a i corresponds to a normalization resulting from a mathematical optimization, N P corresponds to the total number of measurements, β corresponds to a regularization parameter, and R corresponds to a regularization term, wherein {dot over (R)} corresponds to the first derivative with respect to μ j (n) , and wherein {umlaut over (R)} corresponds to the second derivative with respect to μ j (n) .

3. The image reconstruction system of claim 1 , wherein a measurement ray having a ray direction is assigned to each measurement of said plurality of transmission measurements, and wherein said counteract weighting factor is chosen to manipulate a contribution of said measurement ray depending on the respective voxel and depending

Assignees

• Koninklijke Philips Nv
• Kininklijke Philips N V

Inventors

• Bippus Rolf Dieter
• Bergner Frank

Classifications

• G06T12/20 Primary

  Inverse problem, i.e. transformations from projection space into object space · CPC title

• G06F17/18

  for evaluating statistical data {, e.g. average values, frequency distributions, probability functions, regression analysis (forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04)} · CPC title

• G06T2211/424

  Iterative · CPC title

• G06T7/0002

  Inspection of images, e.g. flaw detection · CPC title

• G06T5/002

  Physics · mapped topic