Methods, apparatus, and software for reconstructing an image

• US 7,327,822 B2
• Filed: 07/20/2005
• Issued: 02/05/2008
• Est. Priority Date: 07/20/2005
• Status: Active Grant

• Current Assignee: General Electric Company, Purdue Research Foundation (The Trustees of Purdue University (d/b/a Purdue University)), University of Notre DAME Du Lac
• Original Assignee: General Electric Company, Purdue Research Foundation (The Trustees of Purdue University (d/b/a Purdue University)), University of Notre DAME Du Lac
• Inventors: Bouman, Charles Addison, Thibault, Jean-Baptiste, Sauer, Ken David, Hsieh, Jiang
• Primary Examiner(s): Glick; Edward J.
• Assistant Examiner(s): Corbett; John M
• Application Number:
  US11/185,477
• Publication Number:
  US 20070019777A1
• Time in Patent Office: 930 Days
• Field of Search: 378/4, 378/901, 382/131
• US Class Current: 378/4
• CPC Class Codes: A61B 6/027 characterised by the use of a particular data acquisition trajectory, e.g. helical or spiral
• CPC Class Codes: A61B 6/032 Transmission computed tomography [CT]
• CPC Class Codes: G06T 11/006 Inverse problem, transformation from projection-space into object-space, e.g. transform methods, back-projection, algebraic methods
• CPC Class Codes: G06T 2211/424 Iterative
• CPC Class Codes: Y10S 378/901 Computer tomography program or processor

Abstract

A method of reconstructing an image includes combining a two-dimensional forward projection function and a three-dimensional stabilizing function to generate an iterative reconstruction algorithm, and using the obtained iterative reconstruction algorithm to perform a multislice Computed Tomography (CT) reconstruction to generate an image.

Claims

1. A method of reconstructing an image, said method comprising:

combining a two-dimensional forward projection function and a three-dimensional stabilizing function to generate an iterative reconstruction algorithm; and

using the obtained iterative reconstruction algorithm to perform a multislice Computed Tomography (CT) reconstruction to generate an image.

2. A method in accordance with claim 1 wherein combining a two-dimensional forward projection function and a three-dimensional stabilizing function to generate an iterative reconstruction algorithm further comprises combining a two-dimensional forward function of the form D_k(y_k,F(x_k)) and a three-dimensional stabilizing function of the form S(x) to generate an iterative reconstruction algorithm in the form of

3. A method in accordance with claim 2, wherein S(x) penalizes differences among spatially adjacent components of x.

4. A method in accordance with claim 2, wherein D_k(y_k,F(x_k)) is associated with a slice which is oblique to horizontal or vertical lines.

5. A method in accordance with claim 2, wherein

6. A method in accordance with claim 2, wherein D_k(y_k,F(x_k)) is a distance between y_k and F(x_k).

7. A method in accordance with claim 2, wherein D_k(y_k,F(x_k)) penalizes a function of the probability of observing y_k when x_k is the k-th slice.

8. An imaging system comprising:

a radiation source;

a detector array comprising a plurality of cells positioned to receive radiation from said source; and

a computer coupled to said detector array;

said computer configured to;

combine a two-dimensional forward projection function and a three-dimensional stabilizing function to generate an iterative reconstruction algorithm; and

use the obtained iterative reconstruction algorithm to perform a multislice Computed Tomography (CT) reconstruction to generate an image.

9. An imaging system in accordance with claim 8, wherein said computer is further configured to combine a two-dimensional forward function of the form D_k(y_k,F(x_k)) and a three-dimensional stabilizing function of the form S(x) to generate an iterative reconstruction algorithm in the form of

10. An imaging system in accordance with claim 9 wherein S(x) penalizes differences among spatially adjacent components of x.

11. An imaging system in accordance with claim 9 wherein D_k(y_k,F(x_k)) is associated with a slice which is oblique to horizontal or vertical lines.

12. An imaging system in accordance with claim 9 wherein

13. An imaging system in accordance with claim 9, wherein D_k(y_k,F(x_k)) is a distance between y_k and F(x_k).

14. An imaging system in accordance with claim 9, wherein D_k(y_k,F(x_k)) penalizes a function of the probability of observing y_k when x_k is the k-th slice.

15. A computer readable medium encoded with a program configured to instruct a computer to:

combine a two-dimensional forward projection function and a three-dimensional stabilizing function to generate an iterative reconstruction algorithm; and

use the obtained iterative reconstruction algorithm to perform a multislice Computed Tomography (CT) reconstruction to generate an image.

16. A computer readable medium in accordance with claim 15, wherein said program is further configured to instruct the computer to combine a two-dimensional forward function of the form D_k(y_k,F(x_k)) and a three-dimensional stabilizing function of the form S(x) to generate an iterative reconstruction algorithm in the form of

17. A computer readable medium in accordance with claim 15 wherein S(x) penalizes differences among spatially adjacent components of x.

18. A computer readable medium in accordance with claim 15 wherein D_k(y_k,F(x_k)) is associated with a slice which is oblique to horizontal or vertical lines.

19. A computer readable medium in accordance with claim 15, wherein

20. A computer readable medium in accordance with claim 15, wherein D_k(y_k,F(x_k)) penalizes a function of the probability of observing y_k when x_k is the k-th slice.