System and method for spectral computed tomography using single polychromatic x-ray spectrum acquisition

1. A system for performing material decomposition using a single energy spectrum x-ray dataset, the system comprising:

a material basis generator configured to decompose the single energy spectrum x-ray dataset into at least two material basis images;

an en-chroma generator configured to regularize the material basis generator by enforcing an effective energy constraint; and

a sinogram generator configured to generate projection data from the at least two material basis images.

2. The system of claim 1 wherein the en-chroma generator is configured to extract the effective energy from each datum in the single energy spectrum x-ray dataset, including the at least two material basis images.

3. The system of claim 1 wherein the material basis generator is configured to extract energy dependent linear attenuation coefficients for each image object in the single energy spectrum dataset to decompose the single energy spectrum dataset as a linear combination of energy dependence function b k (ε), and corresponding expansion coefficients a k ({right arrow over (x)}), wherein {right arrow over (x)} is a selected spatial location, ε is an x-ray energy in the single energy spectrum x-ray dataset at the selected spatial location, and k=1, 2, . . . , K, to serve as an index that labels material basis that is selected for decomposition.

4. The system of claim 3 wherein the material basis generator is configured to decompose the single energy spectrum x-ray dataset into linear attenuation coefficients, μ( {right arrow over (x)} , ε), as follows:

μ( {right arrow over (x)} ,ε)=Σ k a k ( {right arrow over (x)} ) b k (ε).

5. The system of claim 1 wherein at least one of the material basis generator or the en-chroma generator are formed of a learning network.

6. The system of claim 1 wherein the single energy spectrum x-ray dataset is a single energy spectrum computed tomography (CT) dataset.

7. The system of claim 1 wherein the material basis generator is configured to extract energy dependent linear attenuation coefficients for each image object in the single energy spectrum x-ray dataset to decompose the single energy spectrum x-ray dataset as a linear combination of energy dependence function b k (ε), and corresponding expansion coefficients a k ({right arrow over (x)}), wherein {right arrow over (x)} is a selected spatial location, E is an x-ray energy in the single energy spectrum x-ray dataset at the selected spatial location, and k=1, 2, . . . , K, to serve as an index that labels material basis that is selected for decomposition.

8. The system of claim 7 wherein the material basis generator is configured to generate material basis images a k ({right arrow over (x)}) from the single energy spectrum x-ray dataset.

9. The system of claim 8 wherein the output of material basis generator is configured to generate energy-resolved spectral CT images, as follows: μ( {right arrow over (x)} ,ε)=Σ k a k ( {right arrow over (x)} ) b k (ε).

10. A method for performing a material decomposition using a single energy spectrum x-ray dataset, the method comprising:

accessing the single energy spectrum x-ray dataset;

decomposing the single energy spectrum x-ray dataset into a linear combination of energy dependence function, b k (ε), and corresponding expansion coefficients, a k ({right arrow over (x)});

wherein {right arrow over (x)} is a selected spatial location in the single energy spectrum x-ray dataset, ε is an x-ray energy in the single energy spectrum x-ray dataset at the selected spatial location, and, k=1, 2, . . . , K, to an index that labels material basis that is selected for decomposition;

wherein a k ( {right arrow over (x)} )=Σ j a k,j e j ({right arrow over (x)}), e j ({right arrow over (x)}) is an expanded image voxel basis function, where j∈[1,N] and N=N x N y N z is a total number of image voxels in an image formed from the single energy spectrum x-ray dataset.

11. The method of claim 10 wherein decomposing the single energy spectrum x-ray dataset includes subjecting the single energy spectrum x-ray dataset to a multi-module system.

12. The method of claim 11 wherein the multi-module system includes:

a material basis generator configured to decompose the single energy spectrum x-ray dataset into at least two material basis images;

an en-chroma generator configured to regularize the material basis generator by enforcing an effective energy constraint; and

a sinogram generator configured to generate projection data from the at least two material basis images.

13. The method of claim 10 further comprising receiving a user-selection of a desired energy for decomposition and wherein the decomposing is performed using the desired energy for decomposition.

14. A method for performing a material decomposition of a single energy spectrum x-ray dataset, the method comprising:

accessing the single energy spectrum x-ray dataset;

receiving a user-selection of a desired energy for decomposition; and

decomposing the single energy spectrum x-ray dataset into a linear combination of energy dependence function using the desired energy for decomposition.

15. The method of claim 14 further comprising generating a set of images specific to the desired energy for decomposition from the single energy spectrum x-ray dataset.

16. The method of claim 14 wherein decomposing includes decomposing into a linear combination of energy dependence function, b k (ε), and corresponding expansion coefficients, a k ({right arrow over (x)}), wherein {right arrow over (x)} is a selected spatial location in the single energy spectrum x-ray dataset, ε is an x-ray energy in the single energy spectrum x-ray dataset at the selected spatial location, and k=1, 2, . . . , K, to an index that labels material basis that is selected for decomposition, and wherein a k ( {right arrow over (x)} )=Σ j a k,j e j ({right arrow over (x)}), e j ({right arrow over (x)}) is an expanded image voxel basis function, where j∈[1,N] and N=N x N y N z is a total number of image voxels in an image formed from the single energy spectrum x-ray dataset.

17. The method of claim 14 wherein decomposing the single energy spectrum x-ray dataset includes subjecting the single energy spectrum x-ray dataset to a multi-module system.

18. The method of claim 17 wherein the multi-module system includes:

a material basis generator configured to decompose the single energy spectrum x-ray dataset into at least two material basis images;

an en-chroma generator configured to regularize the material basis generator by enforcing an effective energy constraint; and

a sinogram generator configured to generate projection data from the at least two material basis images.

19. The method of claim 18 wherein the material basis generator is configured to extract energy dependent linear attenuation coefficients for each image object in the single energy spectrum x-ray dataset to decompose the single energy spectrum x-ray dataset as a linear combination of energy dependence function b k (ε), and corresponding expansion coefficients a k ({right arrow over (x)}), wherein {right arrow over (x)} is a selected spatial location, ε is an x-ray energy in the single energy spectrum x-ray dataset at the selected spatial location, and k=1, 2, . . . , K, to serve as an index that labels material basis that is selected for decomposition.

20. The method of claim 19 wherein the material basis generator is configured to generate material basis images a k ({right arrow over (x)}) from the single energy spectrum x-ray dataset.

21. The method of claim 20 wherein the output of material basis generator is configured to generate energy-resolved spectral CT images, as follows:

μ( {right arrow over (x)} ,ε)=Σ k a k ( {right arrow over (x)} ) b k (ε).

22. A medical imaging system comprising:

an x-ray source configured to deliver x-rays to an imaging patient at a single, selected x-ray energy spectrum;

a controller configured to control the x-ray source to acquire a single energy spectrum x-ray dataset from the imaging patient at the single, selected x-ray energy spectrum;

a material decomposition image reconstruction system comprising:

a material basis generator configured to decompose the single energy spectrum x-ray dataset into at least two material basis images;

an en-chroma generator configured to regularize the material basis generator by enforcing an effective energy constraint; and

a sinogram generator configured to generate projection data from the at least two material basis images.

23. The system of claim 22 wherein the en-chroma generator is configured to extract the effective energy from each datum in the single energy spectrum x-ray dataset, including the at least two material basis images.

24. The system of claim 22 wherein the material basis generator is configured to extract energy dependent linear attenuation coefficients for each image object in the single energy spectrum x-ray dataset to decompose the single energy spectrum x-ray dataset as a linear combination of energy dependence function b k (ε), and corresponding expansion coefficients a k ({right arrow over (x)}), wherein ({right arrow over (x)}) is a selected spatial location, ε is an x-ray energy in the single energy spectrum x-ray dataset at the selected spatial location, and k=1, 2, . . . , K, to serve as an index that labels material basis that is selected for decomposition.

25. The system of claim 24 wherein the material basis generator is configured to generate material basis images a k ({right arrow over (x)}) from the single energy spectrum x-ray dataset.

26. The system of claim 25 wherein the output of material basis generator is configured to generate energy-resolved spectral CT images, as follows:

μ( {right arrow over (x)} ,ε)=Σ k a k ( {right arrow over (x)} ) b k (ε).

27. The system of claim 26 wherein the energy dependence functions b k (ε) are specified by the materials used in material basis generator.

28. The system of claim 22 wherein at least one of the material basis generator or the en-chroma generator are formed of a learning network.