Robust artifact reduction in image reconstruction

Patent metadata

Field	Value
Publication number	US-9349198-B2
Application number	US-201313952444-A
Country	US
Kind code	B2
Filing date	Jul 26, 2013
Priority date	Jul 26, 2013
Publication date	May 24, 2016
Grant date	May 24, 2016

Abstract

Approaches are disclosed for removing or reducing metal artifacts in reconstructed images. The approaches include creating a metal mask in the projection domain, interpolating data within the metal mask, and perform a reconstruction using the interpolated data. In certain embodiments the metal structure is separately reconstructed and combined with the reconstructed volume.

First claim

The invention claimed is:

1. A computer-implemented method for processing projection image data, by way of a processing component, the method comprising:
providing an image processing system comprising a memory storing one or more routines and the processing component configured to execute the one or more routines stored in the memory, wherein the one or more routines are executed by the processing component;
accessing or acquiring projection image data from the image processing system;
generating a set of tentative two-dimensional (2D) metal masks, wherein each tentative 2D metal mask is generated based on a comparison between a respective projection image and a corresponding background image;
backprojecting each tentative 2D metal mask to generate a respective set of backprojected three-dimensional (3D) data in image space for each tentative 2D metal mask;
combining the sets of backprojected three-dimensional (3D) data in image space to generate a 3D metal mask; and
reprojecting the 3D metal mask to generate one or more metal masks in projection space.

2. The computer-implemented method of claim 1 , wherein each corresponding background image is generated by performing a weight-based smoothing of the respective projection image using a respective weight image.

3. The computer-implemented method of claim 2 , wherein each respective weight image is derived from a label image corresponding to the respective projection image.

4. The computer-implemented method of claim 3 , wherein each corresponding background image is iteratively generated or updated based on updates to the respective label image after each iteration.

5. The computer-implemented method of claim 1 , wherein generating the 3D metal mask comprises, at each voxel within the combined backprojected 3D data, determining how many tentative 2D metal masks show non-metal data at each voxel location and how many tentative 2D metal masks show the presence of a metal object at each voxel location, wherein the tentative 2D metal masks may be weighted or unweighted.

6. The computer-implemented method of claim 1 , wherein generating the 3D metal mask comprises determining, using a set of confidence weights, a confidence-weighted sum of the respective backprojected tentative metal masks at each voxel location and determining the sum of backprojected confidence-weights at each voxel location.

7. The computer-implemented method of claim 6 , wherein the confidence weights used in determining the confidence weighted sums are binary.

8. The computer-implemented method of claim 6 , wherein the confidence weights for each respective projection are derived from the local penetration or signal level in the corresponding background image.

9. The computer-implemented method of claim 6 , wherein the confidence weights for each respective projection are derived from a measure of confidence in a tentative metal label.

10. The computer-implemented method of claim 6 , wherein the confidence weights for each respective projection are derived from prior knowledge of a collimator position with the respective projection image.

11. The computer-implemented method of claim 6 , wherein the confidence weights for each respective projection are derived from prior knowledge of data points being invalid in portions of the projection image.

12. The computer-implemented method of claim 6 , wherein a voxel within the 3D metal mask is characterized as metal if the ratio of confidence weighted sums of the backprojected tentative 2D metal masks to the sum of the confidence weights exceeds a threshold that is less than 1.

13. The computer-implemented method of claim 1 , comprising expanding or dilating the tentative 2D metal masks prior to backprojection.

14. The computer-implemented method of claim 1 , comprising refining the one or more metal masks in projection space.

15. An image processing system, comprising:
a memory storing one or more routines; and
a processing component configured to execute the one or more routines stored in the memory, wherein the one or more routines, when executed by the processing component, cause acts to be performed comprising:
accessing or acquiring projection image data;
generating a set of tentative two-dimensional (2D) metal masks, wherein each tentative 2D metal mask is generated based on a comparison between a respective projection image and a corresponding background image;
backprojecting each tentative 2D metal mask to generate a respective set of backprojected three-dimensional (3D) data in image space for each tentative 2D metal mask;
combining the sets of backprojected three-dimensional (3D) data in image space to generate a 3D metal mask; and
reprojecting the 3D metal mask to generate one or more metal masks in projection space.

Assignees

• Gen Electric

Inventors

• Claus Bernhard Erich Hermann
• Langan David Allen
• Braun-Jones Taylor Robert

Classifications

• G06T12/10 Primary

  Image preprocessing, e.g. calibration, positioning of sources or scatter correction · CPC title

• A61B6/5258

  involving detection or reduction of artifacts or noise · CPC title

• A61B6/032

  Transmission computed tomography [CT] · CPC title

• G06T2200/04

  involving 3D image data · CPC title

• G06T11/005 Primary

  Physics · mapped topic