Apparatus and method for noise reduction of spectral computed tomography images and sinograms using a whitening transform
View Patent ↗A method and apparatus is provided to denoise material-decomposition data generated using projection data from a spectral computed tomography scanner. A whitening transform is used to transform the material-decomposition data into uncorrelated components and perform denoising on the uncorrelated components. Using different denoising parameters for the various uncorrelated components, a flattening can be achieved for the standard deviation of the noise as a function of X-ray energy, which can be determined using mono-energetic images derived from the material-decomposition data. The whitening transformation and the denoising can be applied the material-decomposition sinograms and/or to material-decomposition images reconstructed from the material-decomposition sinograms.
1. An apparatus, comprising:
processing circuitry configured to
obtain material-component data corresponding to a material decomposition of projection data having a plurality of energy components, the projection data representing an intensity of X-ray radiation detected at a plurality of energy-resolving detector elements;
transform the obtained material-component data to an uncorrelated basis using a whitening transform to generate a plurality of pieces of uncorrelated data, noise of the respective pieces of uncorrelated data being uncorrelated;
de-noise the generated plurality of pieces of uncorrelated data to generate denoised uncorrelated data; and
transform the denoised uncorrelated data using an inverse whitening transform to generate denoised material-component data.
2. The apparatus according to claim 1 , wherein the processing circuitry is configured to obtain the material-component data, which is one of material-component sinograms and material-component images,
the material-component sinograms being generated by the material decomposition of the projection data, and
the material-component images being reconstructed from the material-component sinograms.
3. The apparatus according to claim 1 , wherein the processing circuitry is further configured to determine the whitening transform, which includes a whitening-transform matrix, using a covariance matrix of the material-component data.
4. The apparatus according to claim 3 , wherein the processing circuitry is further configured to determine the whitening-transform matrix, which includes a matrix product of an eigenvector matrix and a square root of a diagonal eigenvalue matrix, the diagonal eigenvalue matrix and the eigenvector matrix being obtained from an eigenvalue decomposition of the covariance matrix.
5. The apparatus according to claim 3 , wherein the processing circuitry is further configured to determine the whitening-transform matrix, which includes
a first row with values respectively corresponding to absorption coefficients of material components of the material-component data at an X-ray energy corresponding to a minimum standard deviation, and
a second row orthogonal to the first row.
6. The apparatus according to claim 1 , wherein the processing circuitry is further configured to transform the material-component data to the uncorrelated basis in a piecewise manner by transforming patches of the material-component data to the uncorrelated basis using the whitening transform, which is a patchwise-dependent whitening transform.
7. The apparatus according to claim 1 , wherein the processing circuitry is further configured to denoise the plurality of pieces of uncorrelated data using a penalized weighted least square (PWLS) denoising method.
8. The apparatus according to claim 7 , wherein the processing circuitry is further configured to denoise the plurality of pieces of uncorrelated data using the PWLS denoising method, which uses one of an isotropic quadratic regularization and an anisotropic quadratic regularization.
9. The apparatus according to claim 1 , wherein the processing circuitry is further configured to denoise the plurality of pieces of uncorrelated data using different denoising parameters between components of the plurality of pieces of uncorrelated data to make noise in the denoised material-component data more uniform as a function of an X-ray energy.
10. The apparatus according to claim 1 , wherein the material-component data is material-component images, and
the processing circuitry is further configured to generate the material-component images by
obtaining the projection data,
performing material decomposition of the projection data to generate material-component sinograms, and
reconstructing, for each material-component sinogram, a corresponding material-component image.
11. The apparatus according to claim 1 , wherein the material-component data is material-component sinograms, and
the processing circuitry is further configured to generate material-component images from the material-component sinograms by reconstructing, for each material-component sinogram of the denoised material-component data, a corresponding material-component image of the material-component images.
12. An apparatus, comprising:
an X-ray source radiating X-rays;
a plurality of detector elements each configured to
detect a plurality of energy components of the X-rays that are radiated from the X-ray source,
generate projection data representing an intensity of X-ray radiation detected at a plurality of energy-resolving detector elements; and
processing circuitry configured to
obtain material-component data corresponding to a material decomposition of the projection data having a plurality,
transform the obtained material-component data to an uncorrelated basis using a whitening transform to generate a plurality of pieces of uncorrelated data, noise of the respective pieces of uncorrelated data being uncorrelated,
denoise the generated plurality of pieces of uncorrelated data to generate denoised uncorrelated data, and
transform the denoised uncorrelated data using an inverse whitening transform to generate denoised material-component data.
13. The apparatus according to claim 12 , wherein the processing circuitry is configured to obtain the material-component data, which is material-component sinograms, and
the processing circuitry further configured to
perform the material decomposition of the projection data to generate the material-component data, and
reconstruct, using the denoised material-component material, material-component images.
14. The apparatus according to claim 13 , wherein the processing circuitry further configured to
transform the material-component images to an uncorrelated basis using the whitening transform to generate uncorrelated images,
denoise the uncorrelated images, and
transform the denoised uncorrelated images using the inverse whitening transform to generate denoised material-component images.
15. The apparatus according to claim 12 , wherein the material-component data is material-component images, and
the processing circuitry further configured to
perform the material decomposition of the projection data to generate material-component sinograms, and
reconstruct, using the material-component sinograms, the material-component data.
16. A method, comprising:
obtaining material-component data corresponding to a material decomposition of projection data having a plurality of energy components, the projection data representing an intensity of X-ray radiation detected at a plurality of energy-resolving detector elements;
transforming the obtained material-component data to an uncorrelated basis using a whitening transform to generate a plurality of pieces of uncorrelated data, noise of the respective pieces of uncorrelated data being uncorrelated;
denoising the generated plurality of pieces of uncorrelated data to generate denoised uncorrelated data; and
transforming the denoised uncorrelated data using an inverse whitening transform to generate denoised material-component data.
17. The method according to claim 16 , wherein the material-component data is one of material-component sinograms and material-component images.
18. The method according to claim 17 , wherein
the material-component sinograms are generated by the material decomposition of the projection data, and
the material-component images are reconstructed using the material-component sinograms.
19. The method according to claim 16 , further comprising:
determining the whitening transform, which includes a whitening-transform matrix, using a covariance matrix of the material-component data.
20. A non-transitory computer readable storage medium including executable instruction, wherein the instructions, when executed by circuitry, cause the circuitry to perform the method according to claim 16 .