Iterative reconstruction with system optics modeling using filters

1. A computed tomography (CT) imaging apparatus, comprising:

a processing circuit configured to

obtain projection data collected by a CT detector during a scan of an object;

perform iterative reconstruction of the projection data to generate a current image, each cycle of the iterative reconstruction including filtering the current image before forward projection with a filter that models system optics and operates on image data; and

combine the current image with a previously-obtained image to generate an updated image.

2. The CT imaging apparatus of claim 1 , wherein the processing circuit is further configured to perform the filtering using a low-pass filter in an image domain.

3. The CT imaging apparatus of claim 1 , wherein the processing circuit is further configured to perform the filtering using a spatially variant filter in an image domain.

4. The CT imaging apparatus of claim 3 , wherein the spatially variant filter includes a position-dependent Gaussian blur function that represents one or more of an X-ray source, an associated detected X-ray, and voxel contributions.

5. The CT imaging apparatus of claim 4 , wherein the processing circuit is further configured to perform the filtering using the spatially variant filter convolved with a position-dependent TopHat function that represents a gantry rotation blur.

6. The CT imaging apparatus of claim 1 , wherein in generating the current image, the processing circuit is further configured to subtract forward-projected data from the projection data.

7. The CT imaging apparatus of claim 1 , wherein the processing circuit is further configured to perform the filtering using a spatially variant filter, which is obtained by convolving a Gaussian function and a TopHat function.

8. The CT imaging apparatus of claim 1 , further comprising:

an X-ray source to emit X-rays during the scan of the object; and

the CT detector to collect the projection data.

9. A method of performing image reconstruction, comprising:

obtaining projection data collected by a computed tomography detector during a scan of an object;

performing iterative reconstruction (IR) of the projection data to generate a current image, each cycle of the iterative reconstruction including filtering the current image before forward projection with a filter that models system optics and operates on image data; and

combining the current image with a previously-obtained image to generate an updated image.

10. The method of claim 9 , further comprising:

subtracting current forward projected data from original projection data collected in a computer memory;

backprojecting a result of the subtracting to create the current image; and

adding the current image to a previously-obtained image.

11. The method of claim 10 , wherein the filtering step comprises filtering using a spatially-variant filter in a one-dimensional convolution with an image perpendicular to a ray-sum path, after each forward projection step of the IR.

12. The method of claim 11 , wherein the spatially-variant filter is in an image domain.

13. The method of claim 12 , wherein the spatially-variant filter has a position-dependent Gaussian blur function that represents one or more of the X-ray source, the detected X-ray, and voxel contributions.

14. The method of claim 11 , further comprising convolving the spatially-variant filter with a position-dependent TopHat blur function representing a gantry rotation during a data sample.

15. The method of claim 9 , further comprising:

projecting a voxel at a given location onto one or more X-ray detectors at a given view angle; and

obtaining a point spread function for the projected voxel.

16. The method of claim 15 , further comprising:

convolving a projected point voxel with a data domain low-pass filter for the given location.

17. The method of claim 16 , wherein the data domain low-pass filter is modeled as a full-width tenth max width of the Gaussian blur function convolved with a full-width tenth max width of the TopHat blur function.

18. The method of claim 9 , further comprising:

subtracting forward-projected data from the projection data.

19. A non-transitory computer-readable medium storing computer-executable instructions that, when executed by a processing circuit, cause the processing circuit to perform a method, comprising:

obtaining projection data collected by a computed tomography detector during a scan of an object;

performing iterative reconstruction of the projection data to generate a current image, each cycle of the iterative reconstruction including filtering the current image before forward projection with a filter that models system optics and operates on image data; and

combining the current image with a previously-obtained image to generate an updated image.

20. The computer-readable medium of claim 19 , wherein the filter is a spatially-variant filter in an image domain.