Computed tomography approach to edge reconstruction

1. A computer-implemented method of reconstructing boundaries from a computed tomography (CT) image dataset, the method comprising:

using a number of processors to perform the steps of:

receiving CT image data;

applying a number of image filters to the CT image data;

applying a numerical derivative to the filtered CT image data to flatten and suppress non-edge regions that do not correspond to edges;

clipping numerical derivative values to a specified range to reduce artifacts and noise; and

reconstructing an X-ray image according to the image filters and clipped numerical derivative values.

2. The method of claim 1 , further comprising converting the reconstructed X-ray image into a black and white image.

3. The method of claim 1 , wherein the numerical derivative comprises one of:

four-sided derivative; or

left justified derivative.

4. The method of claim 1 , wherein non-edge regions within the X-ray image are reconstructed to zero pixel intensity.

5. The method of claim 1 , wherein edge regions within the X-ray image are reconstructed to 255 pixel intensity on a 0-255 grayscale.

6. The method of claim 1 , wherein the image filters comprise at least one of:

Prewitt;

Zerocross; or

Sobel.

7. A system for reconstructing boundaries from a computed tomography (CT) image dataset, the system comprising:

a storage device configured to store program instructions; and

one or more processors operably connected to the storage device and configured to execute the program instructions to cause the system to:

receive CT image data;

apply a number of image filters to the CT image data;

apply a numerical derivative to the filtered CT image data to flatten and suppress non-edge regions that do not correspond to edges;

clip numerical derivative values to a specified range to reduce artifacts and noise; and

reconstruct an X-ray image according to the image filters and clipped numerical derivative values.

8. The system of claim 7 , wherein the processors further execute program instructions to convert the reconstructed X-ray image into a black and white image.

9. A computer program product for reconstructing boundaries from a computed tomography (CT) image dataset, the computer program product comprising:

a non-transitory computer-readable storage medium having program instructions embodied thereon to perform the steps of:

receiving CT image data;

applying a number of image filters to the CT image data;

applying a numerical derivative to the filtered CT image data to flatten and suppress non-edge regions that do not correspond to edges;

clipping numerical derivative values to a specified range to reduce artifacts and noise; and

reconstructing an X-ray image according to the image filters and clipped numerical derivative values.

10. The computer program product of claim 9 , further comprising instructions for converting the reconstructed X-ray image into a black and white image.

11. A computer-implemented method of reconstructing boundaries from a computed tomography (CT) image dataset, the method comprising:

using a number of processors to perform the steps of:

receiving CT image data;

creating a sinogram from the CT image data;

applying a number of image filters to the sinogram;

applying a numerical derivative to the filtered sinogram to flatten and suppress non-edge regions that do not correspond to edges;

clipping numerical derivative values to a specified range to reduce artifacts and noise;

reformatting the sinogram to a radiograph; and

reconstructing an X-ray image according to the image filters and clipped numerical derivative values.

12. The method of claim 11 , further comprising converting the reconstructed X-ray image into a black and white image.

13. The method of claim 11 , wherein the numerical derivative comprises one of:

four-sided derivative; or

left justified derivative.

14. The method of claim 11 , wherein non-edge regions within the X-ray image are reconstructed to zero pixel intensity.

15. The method of claim 11 , wherein edge regions within the X-ray image are reconstructed to 255 pixel intensity on a 0-255 grayscale.

16. The method of claim 11 , wherein the image filters comprise at least one of:

Prewitt;

Zerocross; or

Sobel.

17. A system for reconstructing boundaries from a computed tomography (CT) image dataset, the system comprising:

a storage device configured to store program instructions; and

one or more processors operably connected to the storage device and configured to execute the program instructions to cause the system to:

receive CT image data;

create a sinogram from the CT image data;

apply a number of image filters to the sinogram;

apply a numerical derivative to the filtered sinogram to flatten and suppress non-edge regions that do not correspond to edges;

clip numerical derivative values to a specified range to reduce artifacts and noise;

reformat the sinogram to a radiograph; and

reconstruct an X-ray image according to the image filters and clipped numerical derivative values.

18. The system of claim 17 , wherein the processors further execute program instructions to convert the reconstructed X-ray image into a black and white image.

19. A computer program product for reconstructing boundaries from a computed tomography (CT) image dataset, the computer program product comprising:

a non-transitory computer-readable storage medium having program instructions embodied thereon to perform the steps of:

receiving CT image data;

creating a sinogram from the CT image data;

applying a number of image filters to the sinogram;

applying a numerical derivative to the filtered sinogram to flatten and suppress non-edge regions that do not correspond to edges;

clipping numerical derivative values to a specified range to reduce artifacts and noise;

reformatting the sinogram to a radiograph; and

reconstructing an X-ray image according to the image filters and clipped numerical derivative values.

20. The computer program product of claim 19 , further comprising instructions for converting the reconstructed X-ray image into a black and white image.