METHOD FOR CIRCULAR SCAN RECONSTRUCTION IN COMPUTED TOMOGRAPHY AND COMPUTED TOMOGRAPHIC DEVICE

• US 20110103662A1
• Filed: 10/30/2009
• Published: 05/05/2011
• Est. Priority Date: 10/30/2009
• Status: Active Grant

• Current Assignee: Toshiba Medical Systems Corporation (Canon Inc.)
• Original Assignee: Toshiba Medical Systems Corporation (Canon Inc.), Kabushiki Kaisha Toshiba (Toshiba Corporation)
• Inventors: Akino, Naruomi, Zamyatin, Alex, Labno, Thomas, Chiang, Be-Shan, Silver, Mike, Zou, Yu
• Granted Patent: US 8,559,687 B2
• Time in Patent Office: Days
• US Class Current: 382/130
• CPC Class Codes: A61B 6/03 Computed tomography [CT] echo-tomography A61B8/14
• CPC Class Codes: A61B 6/032 Transmission computed tomography [CT]
• CPC Class Codes: A61B 6/466 adapted to display 3D data
• 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 2211/421 Filtered back projection [FBP]

Abstract

A method of computed-tomography and a computed-tomography apparatus where the portion of the field of view of a subject were full scan data is available is reconstructed using a full-scan algorithm. In the areas where full scan data is not available, half-scanning is used. Data is also extrapolated from the full scan data. The extrapolated data overlaps a portion of the half-scanning data. The extrapolated data and the overlapped portion of the half-scanning data are feathered. The image is reconstructed using the full-scan, half-scan and feathered data. Corner regions in an image are exposed and reconstructed to produce more uniform z-coverage of the reconstruction field of view.

Claims

1. A computed-tomography method, comprising:

scanning an object with x-rays to obtain projection data reconstructing a first part of an image of the object where full scan data is available;

reconstructing a second part of the image using half-scanning where full scan data is not available;

reconstructing a third part of the image using data extrapolated from the full scan data;

combining weighted sums of overlapping portions of the second and third parts; and

obtaining the image using the first to third parts and the combined weighted sums.

2. A method as recited in claim 1, wherein an angular range of the half-scanning for a pixel located at (r, φ

) is given by;

β

_start(r,φ

,z)=φ

+π

−

Δ

β

(r,z)/2

β

_end(r,φ

,z)=φ

+π

+Δ

β

(r,z)/2=β

_start(r,φ

,z)+Δ

β

(r,z)

where;

Δ

β

(r,z)=π

+2θ

3. A method as recited in claim 1, comprising:

applying redundancy weighting to each pixel.

4. A method as recited in claim 3, wherein applying redundancy weighting to said pixels comprises using:

5. A method as recited in claim 3, wherein the redundancy weighting is dependent upon angular positions of reconstruction pixels.

6. A method as recited in claim 3, wherein the redundancy weighting is dependent upon radial positions of reconstruction pixels.

7. A method as recited in claim 3, wherein the redundancy weighting is dependent upon a z-direction position of reconstruction pixels.

8. A method as recited in claim 1, comprising:

determining a first portion of the second part which overlaps a first portion of the third part;

combining weighted sums of the first portions to produce a fourth part;

determining second portions of the second and third parts which do not overlap; and

obtaining the image using the first part, second portions and the fourth part.

9. A method as recited in claim 1, wherein said combining comprises:

feathering together said second and third parts.

10. A method as recited in claim 9, comprising:

assigning a weight w=1 to data located at a first border between said first and second parts;

assigning a weight w=0 to data located at a second border between said second and third parts;

smoothly varying said weight w between 0 and 1 across said second part;

combining said second and third parts using;

Img=w×

Img2+(w−

1)×

Img3,

where Img is a combined image, Img2 is image data from said second part and Img3 is image data from said third part at a given pixel.

18. A method as recited in claim 10, comprising combining weighted sums of overlapping portions of the first and second images.

19. A method as recited in claim 18, wherein data is extrapolated over a region of said image adjacent to where said full scan data is available and which overlaps said half-scan data, said method comprising:

assigning a weight w=1 to data located at one edge of said region adjacent to said full scan data;

assigning a weight w=0 to data located at the farthest extent of said region intersecting with said half-scan data;

smoothly varying said weight w between 1 and 0 across said region;

combining said second and third parts using;

Img=w×

Img2+(w−

1)×

Img3,

where Img is a combined image, Img2 is extrapolated image data and Img3 is half-scan at a given pixel.

11. A computed tomography method, comprising:

obtaining a first image of an object using full-scan data;

obtaining a second image of said object using half-scan data;

subtracting the second image from the first image to obtain a subtracted image;

thresholding the subtracted image to obtain a thresholded image;

filtering the thresholded image to obtain a filtered image;

adding the filtered image and the second image to obtained an added image; and

feathering together portions of first image and the added image to obtain a third image.

12. A method as recited in claim 11, wherein, in obtaining said second image an angular range for a pixel located at (r, φ

) is given by;

β

_start(r,φ

,z)=φ

+π

−

Δ

β

(r,z)/2

β

_end(r,φ

,z)=φ

+π

+Δ

β

(r,z)/2=β

_start(r,φ

,z)+Δ

β

(r,z)

where;

Δ

β

(r,z)=π

+2θ

13. A method as recited in claim 11, comprising:

applying redundancy weighting to each pixel in said first and second images.

14. A method as recited in claim 13, wherein applying redundancy weighting to said pixels comprises using:

15. A method as recited in claim 13, wherein the redundancy weighting is dependent upon angular positions of reconstruction pixels.

16. A method as recited in claim 13, wherein the redundancy weighting is dependent upon radial positions of reconstruction pixels.

17. A method as recited in claim 13, wherein the redundancy weighting is dependent upon a z-direction position of reconstruction pixels.

20. A computed-tomography apparatus, comprising:

an x-ray source;

an x-ray detector; and

a reconstruction processor for reconstructing an image of an subject from data collected by said x-ray detector, wherein the processor

reconstructs a first part of the image where full scan data is available;

reconstructs a second part of the image using half-scanning data where full scan data is not available;

reconstructs a third part of the image using data extrapolated from the full scan data;

combines weighted sums of overlapping portions of the second and third parts; and

reconstructs the image using the first to third parts and combined weighted sums.

21. An apparatus as recited in claim 20, comprising:

wherein said processor applies redundancy weighting to each pixel.

22. An apparatus as recited in claim 21, wherein said processor applies redundancy weighting to said pixels comprises using:

23. An apparatus as recited in claim 22, wherein the redundancy weighting is dependent upon angular positions of reconstruction pixels.

24. An apparatus as recited in claim 22, wherein the processor applies redundancy weighting dependent upon radial positions of reconstruction pixels.

25. An apparatus as recited in claim 22, wherein the processor applies redundancy weighting dependent upon a z-direction position of reconstruction pixels.

26. An apparatus as recited in claim 22, comprising:

determining a first portion of the second part which overlaps a first portion of the third part;

combining weighted sums of the first portions to produce a fourth part;

determining second portions of the second and third parts which do not overlap; and

obtaining the image using the first part, second portions and the fourth part.

27. An apparatus as recited in claim 20, wherein said processor feathers together said second and third parts.

28. An apparatus as recited in claim 20, wherein said processor:

assigns a weight w=1 to data located at a first border between said first and second parts;

assigns a weight w=0 to data located at a second border between said second and third parts;

smoothly varies said weight w between 0 and 1 across said second part; and

combines said second and third parts using;

Img=w×

Img2+(w−

1)×

Img3,

where Img is a combined image, Img2 is image data from said second part and Img3 is image data from said third part at a given pixel.

29. A computed tomography apparatus, comprising:

an x-ray source to expose a subject with x-rays;

an x-ray detector to obtain image data of the subject; and

a reconstruction processor to reconstruct an image of the subject

obtaining a first image of an object using full-scan data;

obtaining a second image of said object using half-scan data;

subtracting the second image from the first image to obtain a subtracted image;

thresholding the subtracted image to obtain a thresholded image;

filtering the thresholded image to obtain a filtered image;

adding the filtered image and the second image to obtained an added image; and

feathering together portions of first image and the added image to obtain a third image.

30. An apparatus as recited in claim 29, wherein, in obtaining the second image an angular range for a pixel located at (r, φ

) is given by;

β

_start(r,φ

,z)=φ

+π

−

Δ

β

(r,z)/2

β

_end(r,φ

,z)=φ

+π

+Δ

β

(r,z)/2=β

_start(r,φ

,z)+Δ

β

(r,z)

where;

Δ

β

(r,z)=π

+2θ

31. An apparatus as recited in claim 29, wherein the reconstruction processor applies redundancy weighting to each pixel in said first and second images.

32. An apparatus as recited in claim 31, wherein the reconstruction processor applies redundancy weighting to the pixels comprises using:

33. An apparatus as recited in claim 31, wherein the reconstruction processor applies redundancy weighting dependent upon angular positions of reconstruction pixels.

34. An apparatus as recited in claim 31, wherein the reconstruction processor applies redundancy weighting dependent upon radial positions of reconstruction pixels.

35. An apparatus as recited in claim 31, wherein the reconstruction processor applies redundancy weighting dependent upon a z-direction position of reconstruction pixels.

36. An apparatus as recited in claim 29, wherein the reconstruction processor combines weighted sums of overlapping portions of the first and second images.

37. An apparatus as recited in claim 29, wherein data is extrapolated over a region of said image adjacent to where said full scan data is available and which overlaps said half-scan data, and the reconstruction processor:

assigns a weight w=1 to data located at one edge of said region adjacent to said full scan data;

assigns weight w=0 to data located at the farthest extent of said region intersecting with said half-scan data;

smoothly varies said weight w between 1 and 0 across said region; and

combines said second and third parts using;

Img=w×

Img2+(w−

1)×

Img3,

where Img is a combined image, Img2 is extrapolated image data and Img3 is half-scan at a given pixel.