Image generation from limited projections in positron emission tomography using multi-slice rebinning

• US 5,744,802 A
• Filed: 10/25/1995
• Issued: 04/28/1998
• Est. Priority Date: 10/25/1995
• Status: Expired due to Term

• Current Assignee: Koninklijke Philips Electronics N.V. (Koninklijke Philips N.V.)
• Original Assignee: Adam Laboratories Inc.
• Inventors: Countryman, Peter, Muehllehner, Gerd, Braymer, William K.
• Primary Examiner(s): Porta, David P.
• Assistant Examiner(s): Bruce, David Vernon
• Application Number:
  US08/547,951
• Time in Patent Office: 916 Days
• Field of Search: 250/363.02, 250/363.03, 250/363.04, 250/370.09, 378/901, 364/413.13, 364/413.24
• US Class Current: 250/363.03
• CPC Class Codes: G01T 1/1648 Ancillary equipment for scintillation cameras, e.g. reference markers, devices for removing motion artifacts, calibration devices adapted for flow studies G01T1/1647
• CPC Class Codes: G01T 1/2985 In depth localisation, e.g. using positron emitters; Tomographic imaging (longitudinal and transverse section imaging; apparatus for radiation diagnosis sequentially in different planes, steroscopic radiation diagnosis); using external radiation sources A61B6/02
• 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: G06T 2211/436 Limited angle
• CPC Class Codes: Y10S 378/901 Computer tomography program or processor

Abstract

A method of reconstructing an image in a medical imaging system comprises the steps of detecting transverse rays and oblique rays using a limited range of projection angles. The limited range of projection angles is achieved by either limiting the range of rotation of the detectors at each position along the z axis, or by causing the detectors to trace a continuous-motion helical path along the z axis. Data is then rebinned to create a stack of partially-complete sinograms corresponding to individual transverse slice images corresponding to, in the aggregate, a three-dimensional image. Because of the limited projection angles, each sinogram represents an incomplete data set. The rebinning includes, for each oblique ray, identifying among the sinograms the images intersected by the ray, and, applying to each of the sinograms associated with the images intersected by the ray an increment that is representative of the ray. A two-dimensional iterative reconstruction algorithm is applied to each partial sinogram in order to reconstruct a three-dimensional image slice-by-slice, followed or preceded by axially filtering to reduce blurring in the z direction.

Claims

1. A method of reconstructing an image in a medical imaging system, the medical imaging system including a plurality of detectors capable of detecting a plurality of rays occurring within a range of projection angles, the rays including transverse rays and oblique rays, the method comprising the steps of:

detecting the plurality of rays using the detectors;

generating a collection of data representative of the detected rays;

rebinning the data to create a stack of two-dimensional data sets corresponding to individual transverse slice images, wherein the slice images signify in the aggregate a three-dimensional image, wherein for each data set, the data included in said data set corresponds to less than all possible projection angles for the corresponding slice image;

applying a two-dimensional iterative reconstruction algorithm to each of the data sets to reconstruct a three-dimensional image slice-by-slice from the data sets; and

axially filtering the rebinned data.

2. A method according to claim 1, wherein the step of rebinning the data comprises the steps of:

for each oblique ray, identifying among said data sets the images intersected by said ray; and

applying to each of the data sets associated with the images intersected by the ray an increment representative of the ray.

3. A method according to claim 2, each of the data sets includes data corresponding to a utilized range of projection angles of substantially less than 180°

.

4. A method according to claim 3, wherein during the step of detecting the rays, the detectors are not rotated about a z axis.

5. A method according to claim 2, wherein each of the detectors has a transverse dimension, and wherein the range of projection angles is limited to the angle subtended by the transverse dimension of one of the detectors while said one of the detectors is held stationary.

6. A method according to claim 2, wherein the data sets are sinograms, each of the sinograms corresponding to one transverse slice of the three-dimensional image.

7. A method according to claim 2, wherein the detectors are rotatable about a z axis, wherein the step of detecting the rays comprises the step of performing a first scan pass characterized by a helical path of relative motion between the detectors and an object to be imaged.

8. A method according to claim 7, wherein during the step of performing the first scan pass, each of the detectors is rotated by a total of approximately an integer multiple of 180 degrees around the z axis for the first scan pass.

9. A method according to claim 8, further comprising the step of, following completion of the first scan pass, rotating the detector approximately 90°

relative to the object to a starting position.

10. A method according to claim 9, wherein the step of detecting the rays further comprises the step of performing a second scan pass from the starting position, wherein the second scan pass is characterized by a helical path of relative motion between the detectors and the object, wherein the first scan pass and the second scan pass in aggregate result in the acquisition of sets of orthogonal data.

11. A method according to claim 3, wherein the iterative reconstruction algorithm is used to perform image-space reconstruction.

12. A method according to claim 3, wherein the iterative reconstruction algorithm is used to perform projection-space reconstruction.

13. A method according to claim 3, wherein the iterative reconstruction algorithm is a maximum-likelihood estimation (MLE) algorithm.

14. A method of reconstructing an image using a medical imaging system, the medical imaging system including a plurality of detectors capable of detecting a plurality of rays, the rays including transverse rays lying within a plurality of transverse planes and oblique rays not lying within the transverse planes, the detectors being rotatable about a z axis, the method comprising the steps of:

performing a first scan pass along the z axis using to detectors to detect the rays over a range of projection angles, wherein the first scan pass is characterized by a helical path of relative motion between the detectors and an object to be imaged wherein the range of projection angles used is substantially less than 180 degrees for each of the transverse planes;

converting the detected rays to a collection of data representative of the detected rays;

rebinning the data to create a stack of two-dimensional data sets corresponding to individual transverse slice images, wherein the slice images signify in the aggregate a three-dimensional image, wherein the step of rebinning the data comprises the steps of;

for each oblique ray, identifying among said data sets the images intersected by said ray; and

applying to each of the data sets associated with the images intersected by the ray an increment representative of the ray;

applying an iterative reconstruction algorithm to each of the data sets to reconstruct a three-dimensional image slice-by-slice from the data sets; and

axially filtering the rebinned data.

15. A method according to claim 14, wherein the iterative reconstruction algorithm is two-dimensionally iterative.

16. A method according to claim 14, wherein the iterative reconstruction algorithm is used to perform image-space reconstruction.

17. A method according to claim 14, wherein the iterative reconstruction algorithm is used to perform projection-space reconstruction.

18. A method according to claim 17, wherein the iterative reconstruction algorithm is a maximum-likelihood estimation (MLE) algorithm.

19. A method according to claim 14, wherein the data sets are sinograms, each of the sinograms corresponding to one transverse slice of the three-dimensional image.

20. An apparatus for reconstructing an image in a medical imaging system, comprising:

means for detecting both transverse and oblique rays emitted within a range of projection angles, the means for detecting including a plurality of detectors, the transverse rays lying within a plurality of transverse planes perpendicular to a z axis, the oblique rays not lying within the transverse planes, the projection angles defined within the transverse planes, wherein the range of projection angles is less than 180 degrees;

means for converting the detected rays to data;

means for collecting and assembling the data representative of the detected rays;

means for rebinning the data to create a stack of two-dimensional data sets representative of individual transverse slice images, such that the slice images signify in the aggregate a three-dimensional image, the means for rebinning the data including;

means for, for each oblique ray, identifying among said data sets the images intersected by said ray; and

means for applying to each of the data sets associated with the images intersected by the ray an increment representative of the ray;

means for applying a two-dimensional iterative reconstruction algorithm to each data set to reconstruct a three-dimensional image slice-by-slice from the data sets; and

means for axially filtering the rebinned data.

21. An apparatus according to claim 20, wherein the means for detecting comprises means for detecting rays using a range of projection angles less than 90 degrees for each data set.

22. An apparatus according to claim 20, wherein each of the detectors has a transverse dimension, and wherein the means for detecting comprises means for performing a first scan pass of an object to be imaged, such that the range of projection angles used is limited to the angle around the z axis in the transverse plane which is subtended by the transverse dimension of one of the detectors.

23. An apparatus according to claim 20, wherein the iterative reconstruction algorithm is used to perform reconstruction in image space.

24. An apparatus according to claim 20, wherein the iterative reconstruction algorithm is used to perform reconstruction in projection space.

25. An apparatus according to claim 20, wherein the data sets are sinograms, each of the sinograms corresponding to one transverse slice of the three-dimensional image.

26. An apparatus according to claim 25, wherein the means for detecting further comprises means for detecting the rays using a first scan pass characterized by a helical path of relative motion between the detectors and an object to be imaged.

27. An apparatus according to claim 26, further comprising means for rotating the detectors by a total of approximately an integer multiple of 180 degrees around the z axis during the first scan pass.

28. An apparatus according to claim 27, further comprising:

means for rotating the detectors from a first resting position approximately 90°

to a second resting position following completion of the first scan pass; and

wherein the means for detecting further comprises means for detecting rays using a second scan pass opposite in direction from the first scan pass and characterized by a helical path of relative motion between the detectors and the object to acquire sets of orthogonal data.

29. In a medical imaging system having a detector for detecting radiation emitted from an object, the detector being rotatable relative to the object about an axis of rotation, a method of performing emission computed tomography, the method comprising the steps of:

detecting radiation emitted from the object using a first scan pass characterized by a helical path of relative motion between the detector and the object;

following completion of the first scan pass, rotating the detector approximately 90°

relative to the object to a starting position; and

detecting radiation emitted from the object using a second scan pass starting from the starting position, wherein the second scan pass is opposite in direction from the first scan pass and is characterized by a helical path of relative motion between the detector and the object, such that the first scan pass and the second scan pass together result in the acquisition of orthogonal sets of data.

30. An apparatus for performing computed tomography imaging of an object, the apparatus comprising:

a radiation detector that is rotatable relative to the object about an axis of rotation;

means for controlling the radiation detector to detect radiation using a first scan pass characterized by a helical path of relative motion between the detector and the object;

means for rotating the detector, following completion of the first scan pass, approximately 90°

relative to the object to a starting position; and

means for controlling the detector to detect radiation using a second scan pass, the second scan pass starting from the starting position, wherein the second scan pass is opposite in direction from the first scan pass and is characterized by a helical path of relative motion between the detector and the object, such that the first scan pass and the second scan pass result in the acquisition of orthogonal sets of data.