NOISE SUPPRESSION FOR CONE-BEAM IMAGE RECONSTRUCTION
A method for 3-D volume image reconstruction of a subject, executed at least in part on a computer, obtains image data for 2-D projection images over a range of scan angles. For each of the plurality of projection images, a noise-corrected projection image is generated by steps of transforming the image data according to a variance-stabilizing transform to provide transformed image data, applying Gaussian based noise suppression to the transformed image data, and inverting the transformation of the noise-suppressed transformed image data to generate the noise-corrected projection image. The noise-corrected projection image is stored in a computer-accessible memory.
1 . A method for 3-D volume image reconstruction of a subject, executed at least in part on a computer, comprising:
obtaining image data for a plurality of 2-D projection images over a range of scan angles;
generating, for each of the plurality of projection images, a noise-corrected projection image by:
(i) transforming the image data according to a variance-stabilizing transform to provide transformed image data;
(ii) applying Gaussian-based noise suppression to the transformed image data; and
(iii) inverting the transformation of the noise-suppressed transformed image data to generate the noise-corrected projection image; and
storing the noise-corrected projection image in a computer-accessible memory.
2 . The method of claim 1 further comprising processing the plurality of noise-corrected projection images to reconstruct the 3-D volume image of the subject.
3 . The method of claim 2 further comprising displaying the reconstructed 3-D volume image.
4 . The method of claim 2 further comprising storing the reconstructed 3-D volume image in the computer-accessible memory.
5 . The method of claim 1 wherein transforming the image data according to a variance-stabilizing transform comprises applying an Anscombe transform.
6 . The method of claim 2 wherein processing the plurality of noise-corrected projection images comprises performing a row-wise ramp linear filtering to the projection image data without regularization of the noise suppression window.
7 . The method of claim 1 wherein obtaining image data for a plurality of 2-D projection images comprises obtaining image data from a cone-beam computerized tomography apparatus.
8 . A method for 3-D volume image reconstruction of a subject, executed at least in part on a computer, comprising:
obtaining cone-beam computed tomography image data for a plurality of 2-D projection images over a range of scan angles;
generating, for each of the plurality of projection images, a noise-corrected projection image by:
(i) transforming the image data according to a variance-stabilizing transform to provide transformed image data;
(ii) applying Gaussian based noise suppression to the transformed image data; and
(iii) inverting the transformation of the noise-suppressed transformed image data to generate the noise-corrected projection image;
processing the plurality of noise-corrected projection images to reconstruct the 3-D volume image of the subject; and
displaying the reconstructed 3-D volume image.
9 . The method of claim 8 further comprising storing the reconstructed 3-D volume image in a computer-accessible memory.
10 . The method of claim 8 wherein transforming the image data according to a variance-stabilizing transform comprises applying an Anscombe transform.
11 . The method of claim 8 wherein processing the plurality of noise-corrected projection images comprises performing a row-wise ramp linear filtering to the projection image data without regularization of the noise suppression window.
12 . The method of claim 8 further comprising performing one or more of geometric correction, scatter correction, beam-hardening correction, and gain and offset correction on the obtained image data.