3D image reconstruction for helical partial cone beam data

• US 6,097,784 A
• Filed: 09/30/1998
• Issued: 08/01/2000
• Est. Priority Date: 09/30/1998
• Status: Expired due to Fees

• Current Assignee: Picker International, Inc. (Marconi Holdings Company Limited)
• Original Assignee: Picker International, Inc. (Marconi Holdings Company Limited)
• Inventors: Tuy, Heang K.
• Primary Examiner(s): BRUCE, DAVID VERNON
• Application Number:
  US09/164,013
• Time in Patent Office: 671 Days
• Field of Search: 378/4, 378/8, 378/15, 378/19, 378/901
• 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: G06T 11/005 Specific pre-processing for tomographic reconstruction, e.g. calibration, source positioning, rebinning, scatter correction, retrospective gating
• CPC Class Codes: G06T 2211/432 Truncation
• CPC Class Codes: Y10S 378/901 Computer tomography program or processor

Abstract

A method of image reconstruction from partial cone beam data includes collecting the partial cone beam data in two-dimensional arrays. The collected data corresponds to rays of radiation diverging in two dimensions from a common vertex as the vertex travels along a curve. Each element of the data represents a line integral of an object being reconstructed taken along each ray. The data is then pre-weighted and a local coordinate system is defined. A one-dimensional convolution of the pre-weighted data is computed in the local coordinate system along a direction which is tangential to the curve along which the vertex travels. Finally, the convolved data is weighted and three-dimensionally backprojected. In a preferred embodiment, the curve defines a helical path, and the kernel for the one-dimensional convolution of the pre-weighted data is a ramp convolver.

Claims

1. A method of image reconstruction from partial cone beam data comprising:

(a) collecting the partial cone beam data in two-dimensional arrays, said collected data corresponding to rays of radiation diverging in two dimensions from a common vertex as the vertex travels along a curve with each element of the data related to line integrals of an object being reconstructed taken along each ray;

(b) defining a local coordinate system;

(c) pre-weighting the data;

(d) computing a one-dimensional convolution of the pre-weighted data in the local coordinate system along a direction which is tangential to the curve along which the vertex travels;

(e) weighting the convolved data; and

,

(f) three-dimensionally backprojecting the weighted convolution.

2. The method according to claim 1, wherein for each position of the vertex as it travels along the curve, the data collected is not truncated in a direction parallel to the tangent of the curve at the position of the vertex and is truncated in at least one other orthogonal direction.

3. The method according to claim 2, wherein the curve along which the vertex travels is a differentiable curve in three-dimensional space arranged such that any plane going through a point of reconstruction intersects the curve at least once.

4. The method according to claim 3, wherein the curve defines a helical path.

5. The method according to claim 4, wherein a kernel for the one-dimensional convolution of the pre-weighted data is a ramp convolver.

6. The method according to claim 5, wherein the weighting of the convolved data is proportional to a summation of values of a multiplicity function, said values corresponding to all planes going through the vertex and the point of reconstruction.

7. The method according to claim 6, wherein values of the multiplicity function are determined based on a number of intersections corresponding planes going through the vertex and the point of reconstruction have with a portion of the helical path traveled by the vertex to collect enough data for one complete reconstruction.

8. The method according to claim 7, wherein the multiplicity function includes terms corresponding to each intersection, said terms having values based on the intersections'"'"' relative level to the point of reconstruction.

9. The method according to claim 8, wherein when intersections are at a level equal to that of the point of reconstruction their corresponding terms are fully valued, and as intersections gradually go to a level one half revolution away from that of the point of reconstruction their corresponding term values gradually go to zero.

10. The method according to claim 6, wherein the weighting of the convolved data is inversely proportional to the square of the distance between the vertex and the point of reconstruction.

11. The method according to claim 1, wherein image reconstruction takes place from full cone beam data and full cone beam data is collected in step (a).

12. A CT scanner comprising:

a first gantry which defines an examination region;

a rotating gantry mounted on the first gantry for rotation about the examination region;

a source of penetrating radiation arranged on the rotating gantry for rotation therewith, said source of penetrating radiation emitting a cone-shaped beam of radiation that passes through the examination region as the rotating gantry rotates;

a subject support which holds a subject being examined at least partially within the examination region, wherein at least one of the first gantry and the subject support is translated such that the subject passes through the examination region while the rotating gantry is rotated and the source of penetrating radiation follows a helical path relative to the subject;

a two-dimensional array of radiation detectors arranged to receive the radiation emitted from the source of penetrating radiation after it has traversed the examination region;

a reconstruction processor which reconstructs images of the subject from data collected by the two-dimensional array of radiation detectors, said reconstruction processor including;

a first data processor which pre-weights the data;

a convolver which takes the data from the first data processor and performs a one-dimensional convolution on it in a local coordinate system along a direction which is tangential to the helical path;

a second data processor which takes the data from the convolver and weights it; and

,

a backprojector which takes the data from the second data processor and three-dimensionally backprojects it into an image memory; and

,

a human viewable display which accesses the image memory to display reconstructed images of the subject.

13. The CT scanner according to claim 12, wherein for each position of the penetrating radiation source along the helical path, the data collected is not truncated in a direction parallel to the tangent of the helical path at the position of the penetrating radiation source and is truncated in at least one other orthogonal direction.

14. The CT scanner according to claim 13, wherein the convolver employs a ramp function as a kernel for the one-dimensional convolution.

15. The CT scanner according to claim 14, wherein the second data processor multiplies the data by weights that are:

(i) proportional to a summation of values of a multiplicity function, said values corresponding to all planes containing a ray extending from the position of the source of penetrating radiation to a point of reconstruction, and (ii) inversely proportional to the square of the distance between the position of the source of penetrating radiation and the point of reconstruction.

16. The CT scanner according to claim 15, wherein each value of the multiplicity function is determined based on a number of intersections its corresponding plane has with an amount of the helical path followed by the source of penetrating radiation, said amount allowing enough data collection for one complete reconstruction.

17. The CT scanner according to claim 16, wherein the multiplicity function includes terms corresponding to each intersection, said terms having values based on their corresponding intersections'"'"' level relative to the point of reconstruction.

18. The CT scanner according to claim 17, wherein when intersections are at a level equal to that of the point of reconstruction, their corresponding terms are fully valued, and as intersections gradually go to a level one half revolution away from that of the point of reconstruction, their corresponding term values gradually go to zero.