IP Library Granted Patent US 8,942,452
Granted Patent B2
US 8,942,452 · App. 13/475,584 · Granted Jan 27, 2015

Apparatus and method for smoothing random event data obtained from a Positron Emission Tomography scanner

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Quick Facts
Patent No.
US 8,942,452
App. No.
13/475,584
Granted
Jan 27, 2015
Kind
B2
Abstract

A method and apparatus for smoothing random event data obtained from a Positron Emission Tomography (PET) scanner. The method includes obtaining initial random event data u(s, φ, t=0)=u 0 (s, φ), corresponding to t=0, calculating second-order central differences u ss , u φφ with respect to s, φ, calculating a gradient u t , using u t =2(u ss +u φφ )−λ(u−u 0 ), where λ is a constant parameter, and updating the random event data using u(s, φ, t 2 )=u(s, φ, t 1 )+Δt u t , where Δt=t 2 −t 1 , t 1 =0 in a first iteration, and Δt is greater than 0. The method repeats the steps of calculating the second-order central differences, calculating the gradient, and updating the random event data until a change in u(s, φ, t) from a previous iteration is less than a predetermined threshold value.

Claims (229)

1. A method for smoothing random event data obtained from a Positron Emission Tomography (PET) scanner, the method comprising:

obtaining initial random event data u(s, φ, t=0)=u 0 (s, φ), corresponding to t=0, the initial random event data corresponding to line-of-responses of the PET scanner;

calculating second-order central differences u ss , u φφ with respect to s, φ;

calculating a gradient u t , using u t =2(u ss +u φφ )−λ(u−u 0 ), where λ is a constant parameter;

updating the random event data using u(s, φ, t 2 )=u(s, φ, t 1 )+Δt u t , where Δt=t 2 −t 1 , t 1 =0 in a first iteration, and Δt is greater than 0; and

repeating the steps of calculating the second-order central differences, calculating the gradient, and updating the random event data until a change in u(s, φ, t) from a previous iteration is less than a predetermined threshold value.

2. The method according to claim 1 , wherein λ has a value between 0.05 and 2.0.

3. The method according to claim 1 , wherein λ has a value between 0 and 0.01.

4. The method according to claim 1 , wherein Δt has a value between 0.05 and 0.1.

5. The method according to claim 1 , wherein u(s, φ, t) converges when

alls

all

φ

(

u

(

s

,

φ

,

t

k

)

-

u

(

s

,

φ

,

t

k

+

1

)

)

2

is less than the predetermined threshold value.

6. An apparatus for smoothing random event data obtained from a Positron Emission Tomography (PET) scanner, the apparatus comprising:

a processing circuit configured to

obtain initial random event data u(s, φ, t=0)=u 0 (s, φ), corresponding to t=0, the initial random event data corresponding to lines-of-responses of the PET scanner,

calculate second-order central differences u ss , u φφ with respect to s, φ;

calculate a gradient u t , using u t =2(u ss +u φφ )−λ(u−u 0 ), where λ is a constant parameter,

update the random event data using u(s, φ, t 2 )=u(s, φ, t 1 )+Δt u t , where Δt=t 2 −t 1 , t 1 =0 in a first iteration, and Δt is greater than 0, and

repeat the calculating the second-order central differences, calculating the gradient, and updating the random event data until a change in u(s, φ, t) from a previous iteration is less than a predetermined threshold value.

7. The apparatus according to claim 6 , wherein λ has a value between 0.05 and 2.0.

8. The apparatus according to claim 6 , wherein λ has a value between 0 and 0.01.

9. The apparatus according to claim 6 , wherein Δt has a value between 0.05 and 0.1.

10. The apparatus according to claim 6 , wherein u(s, φ, t) converges when

alls

all

φ

(

u

(

s

,

φ

,

t

k

)

-

u

(

s

,

φ

,

t

k

+

1

)

)

2

is less than the predetermined threshold value.

11. A method for smoothing random event data obtained from a Positron Emission Tomography (PET) scanner, the method comprising:

obtaining initial random event data u(s, φ, z, θ, t=0)=u 0 (s, φ, z, θ), corresponding to t=0, the initial random event data corresponding to lines-of-responses of the PET scanner;

calculating second-order central differences u ss , u φφ , u zz , u θθ , with respect to s, φ, z, θ;

calculating a gradient u t , using u t =2(u ss +u φφ +u zz +u θθ )−λ(u−u 0 ), where λ is a constant parameter;

updating the random event data using u(s, φ, z, θ, t 2 )=u(s, φ, z, θ, t 1 )+Δt u t , where Δt=t 2 −t 1 , t 1 =0 in a first iteration, and Δt is greater than 0; and

repeating the steps of calculating the second-order central differences, calculating the gradient, and updating the random event data until a change in u(s, φ, z, θ, t) from a previous iteration is less than a predetermined threshold value.

12. The method according to claim 11 , wherein λ has a value between 0.05 and 2.0.

13. The method according to claim 11 , wherein λ has a value between 0 and 0.01.

14. The method according to claim 11 , wherein Δt has a value between 0.05 and 0.1.

15. The method according to claim 11 , wherein u(s, φ, z, θ, t) converges when

alls

all

φ

all

z

all

θ

(

u

(

s

,

φ

,

z

,

θ

,

t

k

)

-

u

(

s

,

φ

,

z

,

θ

,

t

k

+

1

)

)

2

is less than the predetermined threshold value.

16. The method according to claim 11 , further comprising:

applying a mask so that the obtained initial random event data is restricted to a region containing all measurable line-of-responses of the PET scanner.

17. An apparatus for smoothing random event data obtained from a Positron Emission Tomography (PET) scanner, the method comprising:

a processing circuit configured to

obtain initial random event data u(s, φ, z, θ, t=0)=u 0 (s, φ, z, θ), corresponding to t=0, the initial random event data corresponding to lines-of-responses of the PET scanner;

calculate second-order central differences u ss , u φφ , u zz , u θθ , with respect to s, φ, z, θ;

calculate a gradient u t , using u t =2(u ss +u φφ +u zz +u θθ )−λ(u−u 0 ), where λ is a constant parameter;

update the random event data using u(s, φ, z, θ, t 2 )=u(s, φ, z, θ, t 1 )+Δt u t , where Δt=t 2 −t 1 , t 1 =0 in a first iteration, and Δt is greater than 0; and

repeat the calculating the second-order central differences, calculating the gradient, and updating the random event data until a change in u(s, φ, z, θ, t) from a previous iteration is less than a predetermined threshold value.

18. The apparatus according to claim 17 , wherein λ has a value between 0.05 and 2.0.

19. The apparatus according to claim 17 , wherein λ has a value between 0 and 0.01.

20. The apparatus according to claim 17 , wherein Δt has a value between 0.05 and 0.1.

21. The apparatus according to claim 17 , wherein u(s, φ, z, θ, t) converges when

alls

all

φ

all

z

all

θ

(

u

(

s

,

φ

,

z

,

θ

,

t

k

)

-

u

(

s

,

φ

,

z

,

θ

,

t

k

+

1

)

)

2

is less than the predetermined threshold value.

22. The apparatus according to claim 17 , wherein the processing circuit is further configured to apply a mask so that the obtained initial random event data is restricted to a region containing all measurable line-of-responses of the PET scanner.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 31, 2016
From: KABUSHIKI KAISHA TOSHIBA
To: TOSHIBA MEDICAL SYSTEMS CORPORATION
Reel/Frame 038891/0693 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 18, 2012
From: NIU, XIAOFENG; WANG, WENLI
To: KABUSHIKI KAISHA TOSHIBA; TOSHIBA MEDICAL SYSTEMS CORPORATION
Reel/Frame 028236/0343 →