Methods and apparatus for 3D artifact reduction

• US 6,215,841 B1
• Filed: 09/29/1998
• Issued: 04/10/2001
• Est. Priority Date: 09/29/1998
• Status: Expired due to Fees

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Hsieh, Jiang
• Primary Examiner(s): BRUCE, DAVID VERNON
• Application Number:
  US09/162,283
• Time in Patent Office: 924 Days
• Field of Search: 378/4, 378/8, 378/15, 378/99
• US Class Current: 378/8
• 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 11/008 Specific post-processing after tomographic reconstruction, e.g. voxelisation, metal artifact correction
• CPC Class Codes: G06T 2207/10081 Computed x-ray tomography [CT]
• CPC Class Codes: G06T 2207/30004 Biomedical image processing
• CPC Class Codes: G06T 5/00 Image enhancement or restoration
• CPC Class Codes: Y10S 378/901 Computer tomography program or processor

Abstract

The present invention, in one form, is a system for reducing artifacts in three-dimensional image formation. More specifically, a 3D image generation algorithm is utilized to generate a composite boundary profile of the object. In one embodiment, the composite boundary profile is determined by selecting an appropriate threshold intensity level. In another embodiment, the composite boundary profile is determined by determining the slope of the boundary, the starting angle of the data set, and the algorithm for helical computed tomography reconstruction. The composite boundary profile is then adaptively filtered to remove inconsistency and thus remove image artifacts in the 3D images.

Claims

1. An imaging system for reducing artifacts in a 3D image of an object, said system comprising an x-ray source and a detector away, said system configured to:

scan the object;

reconstruct an image of the object;

select a threshold intensity level of the reconstructed image; and

determine boundaries of the object using the reconstructed image and the selected threshold intensity.

2. A system in accordance with claim 1 wherein to scan the object, said system configured to collect a plurality of slices of object data.

3. A system in accordance with claim 2 wherein a starting angle for each of said plurality of slices of object data are substantially equal.

14. A method in accordance with claim 1 wherein scanning the object comprises the step of collecting a plurality of slices of object data.

15. A method in accordance with claim 14 wherein a starting angle for each of the plurality of slices of object data are substantially equal.

16. A method in accordance with claim 1 further comprising the step of generating a three-dimensional image of the object.

4. A method of reducing artifacts in an image of an object acquired in an imaging system, said method comprising the steps of:

scanning the object;

selecting a threshold intensity level;

determining boundaries of the object;

determining the slope of the object boundaries; and

determining a boundary error.

5. A method in accordance with claim 4 wherein said method further comprises the step of adjusting the object boundaries.

6. A method in accordance with claim 5 wherein adjusting the boundaries comprises the step of adjusting the boundaries by an amount substantially equal to the determined boundary error.

7. A method in accordance with claim 4 further comprising the step of determining a composite boundary profile of the object.

8. A method in accordance with claim 7 wherein the composite boundary profile for an axial scan is:

$g<br><br>\left(x\right)={\mathrm{\Gamma <br><br>}}_{\frac{h}{k}}\otimes <br><br>f$

where;

${\mathrm{\Gamma <br><br>}}_{\frac{h}{k}}<br><br>\left(x\right)=\{\begin{array}{cc}0& x\le <br><br>0\\ \frac{\mathrm{kx}}{h}& 0<<br><br>x<<br><br>\frac{h}{k}\\ 1& \mathrm{Other}\end{array}$

f is an edge response of an imaging system;

k is a slope of the object boundary in x-z plane;

h is a slice thickness;

x is an image index variable; and

{circle around (×

)} represents a convolution.

9. A method in accordance with claim 8 wherein the composite boundary profile for a helical scan is:

10. A method in accordance with claim 7 further comprising the step of filtering the composite boundary profile.

11. A method in accordance with claim 10 wherein said filtering the composite boundary profile comprises the step of applying a smoothing filter.

12. A method in accordance with claim 10 wherein said filtering the composite boundary profile comprises the step of applying a sharpening filter.

13. A method of seducing artifacts in an image of an object acquired in an imaging system, said method comprising the steps of:

scanning the object with an imaging system;

reconstructing an image of the object;

selecting a threshold intensity level of the reconstructed image; and

determining boundaries of the object using the reconstructed image and the selected threshold intensity.

17. A method of reducing artifacts in an image of an object acquired in an imaging system, said method comprising the steps of:

scanning the object;

selecting a threshold intensity level from a range between 30% and 70% of a maximum threshold intensity and background intensity; and

determining boundaries of the object.

18. An imaging system for reducing artifacts in a 3D image of an object, said system comprising an x-ray source and a detector array, said system configured to:

scan the object;

reconstruct an image of the object;

select a threshold intensity level;

determine boundaries of the object;

determine a slope of said object boundaries; and

determine a boundary error.

19. A system in accordance with claim 18 wherein said system further configured to adjust said object boundaries.

20. A system in accordance with claim 19 wherein to adjust said boundaries, said system configured to adjust said boundaries by an amount substantially equal to said determined boundary error.

21. A system in accordance with claim 18 further configured to determine a composite boundary profile of the object.

22. A system in accordance with claim 21 wherein said system is configured to perform an axial scan.

23. A system in accordance with claim 22 wherein said composite boundary profile is:

$g<br><br>\left(x\right)={\mathrm{\Gamma <br><br>}}_{\frac{h}{k}}\otimes <br><br>f$

where;

${\mathrm{\Gamma <br><br>}}_{\frac{h}{k}}<br><br>\left(x\right)=\{\begin{array}{cc}0& x\le <br><br>0\\ \frac{\mathrm{kx}}{h}& 0<<br><br>x<<br><br>\frac{h}{k}\\ 1& \mathrm{Other}\end{array}$

f is an edge response of an imaging system;

k is a slope of the object boundary in x-z plane;

h is a slice thickness;

x is an image index variable; and

{circle around (×

)} represents a convolution.

24. A system in accordance with claim 21 wherein said system is configured to perform a helical scan.

25. A system in accordance with claim 24 wherein said composite boundary profile is:

26. A system in accordance with claim 18 further configured to filter said composite boundary profile.

27. A system in accordance with claim 26 wherein to filter said composite boundary profile, said system configured to apply a smoothing filter.

28. A system in accordance with claim 26 wherein to filter said composite boundary profile, said system configured to apply a sharpening filter.