Method and system for correlated noise suppression in dual energy imaging

• US 8,401,266 B2
• Filed: 11/29/2010
• Issued: 03/19/2013
• Est. Priority Date: 11/29/2010
• Status: Active Grant

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Xu, Dan, Langan, David Allen, Wu, Xiaoye, Pack, Jed Douglas, Schmitz, Andrea Marie
• Primary Examiner(s): Wang, Claire X
• Assistant Examiner(s): YENTRAPATI, AVINASH
• Application Number:
  US12/955,227
• Publication Number:
  US 20120134561A1
• Time in Patent Office: 841 Days
• Field of Search: None
• US Class Current: 382/131
• 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 2211/408 Dual energy
• CPC Class Codes: G06T 5/50 using two or more images, e.g. averaging or subtraction
• CPC Class Codes: G06T 5/70 Denoising; Smoothing

Abstract

Methods and systems for correlated noise suppression are presented. The present correlated noise suppression technique estimates a correlation direction between noise values in a first and a second MD image corresponding to a first and a second basis material, respectively. The two MD images are diffused using the estimated correlation direction to generate a first and a second diffused image. Further, first and second noise masks are generated by subtracting the diffused image from the corresponding MD image. Edges in the first and the second MD images are processed with the first and second noise masks, respectively to generate a final first noise mask and a final second noise mask. The first MD image is then processed with the final second noise mask to generate a final first MD image and the second MD image is processed with the final first noise mask to generate a final second MD image.

Claims

1. A method comprising:

acquiring a first set of projection data corresponding to X-rays generated at a first energy level and a second set of projection data corresponding to X-rays generated at a second energy level;

decomposing the first set and the second set of projection data into a first set of material projection data corresponding to a first basis material and a second set of material projection data corresponding to a second basis material;

reconstructing a first materially decomposed (MD) image of the first basis material using the first set of material projection data and a second MD image of the second basis material using the second set of material projection data;

estimating a direction of correlation between noise values corresponding to the first MD image and noise values corresponding to the second MD image;

diffusing the first MD image and the second MD image to generate a first diffused image and a second diffused image based on the estimated direction of correlation;

generating a first noise mask by subtracting the first diffused image from the first MD image and generating a second noise mask by subtracting the second diffused image from the second MD image;

processing one or more edges corresponding to the first MD image with the first noise mask to generate a final first noise mask, and processing one or more edges corresponding to the second MD image with the second noise mask to generate a final second noise mask; and

processing the first MD image with the final second noise mask to generate a final first MD image and processing the second MD image with the final first noise mask to generate a final second MD image.

2. The method of claim 1, wherein estimating a direction of correlation between noise values corresponding to the first MD image and noise values corresponding to the second MD image comprises:

determining calibration information corresponding to an imaging system; and

computing the direction of correlation based on the determined system calibration information, a basis material attenuation for the first basis material, a basis material attenuation for the second basis material, or combinations thereof.

3. The method of claim 1, wherein the system calibration information comprises an X-ray spectrum corresponding to the first energy level, an X-ray spectrum corresponding to the second energy level, an efficiency of one or more detectors in the imaging system, an X-ray filtration, or combinations thereof.

4. The method of claim 1, wherein estimating a direction of correlation between noise values corresponding to the first MD image and noise values corresponding to the second MD image comprises:

determining an initial estimate of the direction of correlation based on calibration information corresponding to an imaging system;

diffusing the first MD image and the second MD image using the initial estimate of the direction of correlation to generate a first initial diffused image and a second initial diffused image;

generating a first initial noise mask by subtracting the first initial diffused image from the first MD image and generating a second initial noise mask by subtracting the second initial diffused image from the second MD image;

applying a series of window functions to the first initial noise mask and the second initial noise mask to generate a first series of windowed noise masks and a second series of windowed noise masks;

determining an optimal parameter value for each corresponding pair of windowed noise masks in the first series and the second series of windowed noise masks such that a result of mixing a first windowed noise mask and a corresponding second windowed noise mask in accordance with a value of the determined parameter results in a residual image that minimizes a norm; and

computing an estimated direction of correlation at each of a plurality of image locations based on the determined parameter for each window function in the series of window functions and the value of each window function at each of the plurality of image locations.

5. The method of claim 1, wherein diffusing the first MD image and the second MD image comprises using a correlated diffusion function that encourages a diffusion of negatively correlated points in the first MD image and the second MD image along the estimated direction of correlation and suppresses a diffusion of non-negatively correlated points in the first MD image and the second MD image.

6. The method of claim 5, wherein the correlated diffusion function comprises an anisotropic diffusion function, a non-sharp masking function, a gradient-based function or a median function.

7. The method of claim 1, wherein generating the first noise mask and the second noise mask comprises removing information corresponding to non-noise sources from the first noise mask and the second noise mask.

8. The method of claim 7, wherein removing non-noise information comprises:

segmenting the first MD image to obtain a first structure image and segmenting the second MD image to obtain a second structure image; and

subtracting the first structure image from the first noise mask and subtracting the second structure image from the second noise mask.

9. An imaging system, comprising:

a data acquisition system that acquires a first set of projection data corresponding to X-rays generated at a first energy level and a second set of projection data corresponding to X-rays generated at a second energy level; and

an image reconstruction unit communicatively coupled to the data acquisition system, wherein the image reconstruction unit;

decomposes the first set and the second set of projection data into a first set of material projection data corresponding to a first basis material and a second set of material projection data corresponding to a second basis material;

reconstructs a first MD image of the first basis material using the first set of material projection data and a second MD image of the second basis material using the second set of material projection data;

estimates a direction of correlation between noise values corresponding to the first MD image and noise values corresponding to the second MD image;

diffuses the first MD image and the second MD image to generate a first diffused image and a second diffused image based on the estimated direction of correlation;

generates a first noise mask by subtracting the first diffused image from the first MD image and generates a second noise mask by subtracting the second diffused image from the second MD image;

processes one or more edges corresponding to the first MD image with the first noise mask to generate a final first noise mask, and processes one or more edges corresponding to the second MD image with the second noise mask to generate a final second noise mask; and

processes the first MD image with the final second noise mask to generate a final first MD image and processes the second MD image with the final first noise mask to generate a final second MD image.

10. The imaging system of claim 9, wherein the imaging system comprises a computed tomography (CT) system, a single source imaging system, a multi-source imaging system, multi-detector imaging system, a photon counting energy discriminating detector imaging system, an X-Ray system, positron emission tomography (PET) scanner, a single photon emission computed tomography (SPECT) scanner, or combinations thereof.

11. The imaging system of claim 9, wherein the image reconstruction unit estimates the direction of correlation between the first MD image and the second MD image based on the determined system calibration information, a basis material attenuation for the first basis material, a basis material attenuation for the second basis material, or combinations thereof.

12. The imaging system of claim 11, wherein the system calibration information comprises an X-ray spectrum corresponding to the first energy level, an X-ray spectrum corresponding to the second energy level, efficiency of one or more detectors in the imaging system, an X-ray filtration, or combinations thereof.

13. The imaging system of claim 9, wherein the image reconstruction unit:

determines an initial estimate of the direction of correlation based on calibration information corresponding to an imaging system;

diffuses the first MD image and the second MD image using the initial estimate of the direction of correlation to generate a first initial diffused image and a second initial diffused image;

generates a first initial noise mask by subtracting the first initial diffused image from the first MD image and generating a second initial noise mask by subtracting the second initial diffused image from the second MD image;

applies a series of window functions to the first initial noise mask and the second initial noise mask to generate a first series of windowed noise masks and a second series of windowed noise masks;

determines an optimal parameter value for each corresponding pair of windowed noise masks in the first series and the second series of windowed noise masks such that a result of mixing a first windowed noise mask and a corresponding second windowed noise mask in accordance with a value of the determined parameter results in a residual image that minimizes a norm; and

computes an estimated direction of correlation at each of a plurality of image locations based on the determined parameter for each window function in the series of window functions and the value of each window function at each of the plurality of image locations.

14. The imaging system of claim 9, wherein the image reconstruction unit diffuses the first MD image and the second MD image using a correlated diffusion function that encourages a diffusion of negatively correlated points in the first MD image and the second MD image along the estimated direction of correlation and suppresses a diffusion of non-negatively correlated points in the first MD image and the second MD image.

15. The imaging system of claim 9, wherein the image reconstruction unit:

segments the first MD image to obtain a first structure image and segmenting the second MD image to obtain a second structure image; and

subtracts the first structure image from the first noise mask and subtracting the second structure image from the second noise mask to remove information corresponding to non-noise sources from the first noise mask and the second noise mask.

16. A computed tomography (CT) system, comprising:

at least one radiation source that generates X-rays at a first energy level and at a second energy level;

a detector assembly coupled to the at least one radiation source that detects the X-rays generated from the radiation source;

an image reconstruction unit coupled to the detector assembly, wherein the image reconstruction unit;

acquires a first set of projection data corresponding to X-rays generated at the first energy level and a second set of projection data corresponding to X-rays generated at the second energy level;

decomposes the first set and the second set of projection data into a first set of material projection data corresponding to a first basis material and a second set of material projection data corresponding to a second basis material;

reconstructs a first MD image of the first basis material using the first set of material projection data and a second MD image of a second basis material using the second set of material projection data;

estimates a direction of correlation between noise values corresponding to the first MD image and noise values corresponding to the second MD image;

diffuses the first MD image and the second MD image to generate a first diffused image and a second diffused image based on the estimated direction of correlation;

generates a first noise mask by subtracting the first diffused image from the first MD image and generates a second noise mask by subtracting the second diffused image from the second MD image;

processes one or more edges corresponding to the first MD image with the first noise mask to generate a final first noise mask, and processes one or more edges corresponding to the second MD image with the second noise mask to generate a final second noise mask; and

processes the first MD image with the final second noise mask to generate a final first MD image and processes the second MD image with the final first noise mask to generate a final second MD image.