IP Library Granted Patent US 9,390,523
Granted Patent B2
US 9,390,523 · App. 14/397,751 · Granted Jul 12, 2016

Determination of z-effective value for set of voxels using CT density image and sparse multi-energy data

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Quick Facts
Patent No.
US 9,390,523
App. No.
14/397,751
Granted
Jul 12, 2016
Kind
B2
Abstract

Z-effective (e.g., atomic number) values are generated for one or more sets of voxels in a CT density image using sparse (measured) multi-energy projection data. Voxels in the CT density image are assigned a starting z-effective value, causing a CT z-effective image to be generated from the CT density image. The accuracy of the assigned z-effective values is tested by forward projecting the CT z-effective image to generate synthetic multi-energy projection data and comparing the synthetic multi-energy projection data to the sparse multi-energy projection data. When the measure of similarity between the synthetic data and the sparse data is low, the z-effective value assigned to one or more voxels is modified until the measure of similarity is above a specified threshold (e.g., with an associated confidence score), at which point the z-effective values substantially reflect the z-effective values that would be obtained using a (more expensive) dual-energy CT imaging modality.

Claims (42)

1. A method for generating a z-effective values for a set of voxels in a CT density image for a radiography imaging modality, comprising

Acquiring the CT density image of an object;

Acquiring sparse multi-energy projection date of the object;

Wherein the sparse multi-energy projection data comprising data insufficient for generating a multi-energy image;

Identifying one or more sets of voxels in the CT density image;

Setting an initial z-effective value for respective sets of voxels to generate a CT z-effective image;

Forward projecting the CT z-effective image to generate synthetic multi-energy projection data;

Comparing the synthetic multi-energy projection data to the sparse multi-energy projection data to determine a measure of similarity between z-effective information of the synthetic multi-energy projection data and z-effective information of the sparse multi-energy projection data; and

Updating the initial z-effective value for one or more sets of voxels to update the CT z-effective image when the determined measure of similarity between the z-effective information of the synthetic multi-energy projection data and the z-effective information of the sparse multi-energy projection data is below a specific threshold.

2. The method of claim 1 , comprising computing a confidence of the determined measure of similarity when the measure of similarity between the synthetic multi-energy projection data and the sparse multi-energy projection data is greater than or equal to a specified threshold.

3. The method of claim 1 , forward projecting the CT z-effective image comprising forward projecting the CT z-effective image using a dual-energy X-ray propagation model.

4. The method of claim 1 , comprising:

identifying a first sub-object and a second sub-object in the CT density image; and

segmenting voxels of the CT density image such that a first identified set of voxels is associated with the first sub-object and a second identified set of voxels is associated with the second sub-object.

5. The method of claim 1 , setting the initial z-effective value for respective sets of voxels, comprising setting an initial z-effective value for a first set of voxels based upon a priori information about a sub-object at least partially represented by the first set of voxels.

6. The method of claim 5 , the a priori information comprising at least one of density information about the sub-object, geometric information about the sub-object, and an environment at least partially surrounding the sub-object.

7. The method of claim 1 , comprising acquiring the sparse multi-energy projection data from a dual-energy line scanner.

8. The method of claim 1 , comprising acquiring the sparse multi-energy projection data from a plurality of energy resolving detectors sparsely arranged on a CT detector array.

9. The method of claim 1 , comprising, prior to forward projecting the CT z-effective image, determining a geometry in which the sparse multi-energy projection data is acquired.

10. The method of claim 9 , forward projecting the CT z-effective image comprising forward projecting the CT z-effective image onto the geometry in which the sparse multi-energy projection data is acquired.

11. The method of claim 1 , the sparse multi-energy projection data comprising a two-dimensional projection image.

12. The method of claim 1 , the sparse multi-energy projection data comprising data insufficient for generating a multi-energy image.

13. The method of claim 1 , comprising:

identifying voxels representative of a metal sub-object in at least one of the CT density image and CT z-effective image; and

discarding the voxels representative of the metal sub-object prior to forward projecting the CT z-effective image.

14. A system for generating a z-effective value for a set of voxels in a CT density image, comprising:

A segmentation component configured to segment one or more sub-objects from the CT density image of an object under examination;

A z-effective component configured to set a first z-effective value for a first set of voxels representing a first segmented sub-object in the CT density image and a second z-effective value for a second set of voxels representing a second segmented sub-object in the CT density image to generate a CT z-effective image;

A forward projection component configured to forward project the CT z-effective image to generate synthetic multi-energy projection data; and

A comparison component configured to compare the synthetic multi-energy projection data to sparse multi-energy projection data indicative of the object to determine a measure of similarity between z-effective information of the synthetic multi-energy projection data and z-effective information of the spars multi-energy projection data,

Wherein the sparse multi-energy projection data comprising data insufficient for generating a multi-enemy image,

Where a measure of similarity that is below a specified threshold is indicative of at least one of the first z-effective value and the second z-effective value differing from an atomic number of a sub-object represented by at least a specific deviation.

15. The system of claim 14 , comprising a registration component configured to determine a geometry of an imaging modality generating the sparse multi-energy projection data.

16. The system of claim 15 , the forward projection component configured to forward project the CT z-effective image onto the determined geometry such that the synthetic multi-energy projection data and the sparse multi-energy projection data represent substantially similar ray paths.

17. The system of claim 14 , comprising a CT imaging modality configured to generate the CT density image and a line scanner configured to generate the sparse multi-energy projection data.

18. The system of claim 14 , the z-effective component configured to update at least one of the first z-effective value and the second z-effective value to update the CT z-effective image when the determined measure of similarity is below a specified threshold.

19. The system of claim 14 , comprising a confidence component configured to determine a confidence value for the determined measure of similarity, the confidence value indicative of how likely it is that the CT z-effective image represents one or more effective atomic numbers of the object.

20. A non-transitory computer-readable storage medium comprising computer executable instructions that when executed via a processor perform a method comprising:

Setting an initial z-effective value for respective voxels of a CT density image acquired from a single-energy radiography examination of an object to generate a CT z-effective image;

Forward projecting the CT z-effective image to generate synthetic multi-energy projection data; and

Comparing the synthetic multi-energy projection data to sparse multi-energy projection data indicative of the object to determine a measure of similarity between z-effective information of the synthetic multi-energy projection data and the z-effective information of the sparse multi-energy projection data,

Wherein the sparse multi-enemy projection data comprising data insufficient for generating a multi-energy image.

Assignments (3)
SECURITY INTEREST Recorded Sep 19, 2023
From: ANALOGIC CORPORATION
To: TRUIST BANK, AS COLLATERAL AGENT
Reel/Frame 064954/0027 →
RELEASE OF SECURITY INTEREST Recorded Sep 15, 2023
From: MIDCAP FINANCIAL TRUST
To: ANALOGIC CORPORATION
Reel/Frame 064917/0544 →
SECURITY INTEREST Recorded Jun 22, 2018
From: ANALOGIC CORPORATION; SOUND TECHNOLOGY, INC.
To: MIDCAP FINANCIAL TRUST
Reel/Frame 046414/0277 →