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Accelerated Compressed Sensing Based CT Image Reconstruction.

Hashemi S, Beheshti S, Gill PR, Paul NS, Cobbold RS - Comput Math Methods Med (2015)

Bottom Line: Therefore, the proposed method not only accelerates the reconstruction, but also removes the rebinning and interpolation errors.Simulation results are shown for phantoms and a patient.Moreover, computation times of less than 30 sec were obtained using a standard desktop computer without numerical optimization.

View Article: PubMed Central - PubMed

Affiliation: Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON, Canada M5S 3G9.

ABSTRACT
In X-ray computed tomography (CT) an important objective is to reduce the radiation dose without significantly degrading the image quality. Compressed sensing (CS) enables the radiation dose to be reduced by producing diagnostic images from a limited number of projections. However, conventional CS-based algorithms are computationally intensive and time-consuming. We propose a new algorithm that accelerates the CS-based reconstruction by using a fast pseudopolar Fourier based Radon transform and rebinning the diverging fan beams to parallel beams. The reconstruction process is analyzed using a maximum-a-posterior approach, which is transformed into a weighted CS problem. The weights involved in the proposed model are calculated based on the statistical characteristics of the reconstruction process, which is formulated in terms of the measurement noise and rebinning interpolation error. Therefore, the proposed method not only accelerates the reconstruction, but also removes the rebinning and interpolation errors. Simulation results are shown for phantoms and a patient. For example, a 512 × 512 Shepp-Logan phantom when reconstructed from 128 rebinned projections using a conventional CS method had 10% error, whereas with the proposed method the reconstruction error was less than 1%. Moreover, computation times of less than 30 sec were obtained using a standard desktop computer without numerical optimization.

No MeSH data available.


Related in: MedlinePlus

Comparison of FBP and the modified proposed method for the cardiac plaque phantom reconstructed using the protocol shown in (a), in which the projections are taken within the white areas, (b) FBP reconstructed image from the 450 projections gathered from the mask shown in image (a), and (c) image reconstructed with the modified proposed method from projections shown in image (a).
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fig11: Comparison of FBP and the modified proposed method for the cardiac plaque phantom reconstructed using the protocol shown in (a), in which the projections are taken within the white areas, (b) FBP reconstructed image from the 450 projections gathered from the mask shown in image (a), and (c) image reconstructed with the modified proposed method from projections shown in image (a).

Mentions: Current commercial CT scanners are unable to switch their X-ray sources on and off fast enough to achieve the proposed equiangular simulations. To overcome this problem, the mask used in Figure 11(a) is used that addresses this concern by turning the X-ray source off in the black areas over a range of angles and then turning it on in the white areas. To reconstruct high quality CT images scanned by this protocol, the reconstruction algorithm is modified by stacking the similar patches into 3D stacks [50]. Applying 3D wavelet thresholding/shrinkage on the 3D stacks of the similar patches increases the sparsity of the wavelet coefficients, which in turn improves the image reconstruction. The similar patches are selected from overlapped 15 × 15 neighborhoods and the patches are 6 × 6.


Accelerated Compressed Sensing Based CT Image Reconstruction.

Hashemi S, Beheshti S, Gill PR, Paul NS, Cobbold RS - Comput Math Methods Med (2015)

Comparison of FBP and the modified proposed method for the cardiac plaque phantom reconstructed using the protocol shown in (a), in which the projections are taken within the white areas, (b) FBP reconstructed image from the 450 projections gathered from the mask shown in image (a), and (c) image reconstructed with the modified proposed method from projections shown in image (a).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4489012&req=5

fig11: Comparison of FBP and the modified proposed method for the cardiac plaque phantom reconstructed using the protocol shown in (a), in which the projections are taken within the white areas, (b) FBP reconstructed image from the 450 projections gathered from the mask shown in image (a), and (c) image reconstructed with the modified proposed method from projections shown in image (a).
Mentions: Current commercial CT scanners are unable to switch their X-ray sources on and off fast enough to achieve the proposed equiangular simulations. To overcome this problem, the mask used in Figure 11(a) is used that addresses this concern by turning the X-ray source off in the black areas over a range of angles and then turning it on in the white areas. To reconstruct high quality CT images scanned by this protocol, the reconstruction algorithm is modified by stacking the similar patches into 3D stacks [50]. Applying 3D wavelet thresholding/shrinkage on the 3D stacks of the similar patches increases the sparsity of the wavelet coefficients, which in turn improves the image reconstruction. The similar patches are selected from overlapped 15 × 15 neighborhoods and the patches are 6 × 6.

Bottom Line: Therefore, the proposed method not only accelerates the reconstruction, but also removes the rebinning and interpolation errors.Simulation results are shown for phantoms and a patient.Moreover, computation times of less than 30 sec were obtained using a standard desktop computer without numerical optimization.

View Article: PubMed Central - PubMed

Affiliation: Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON, Canada M5S 3G9.

ABSTRACT
In X-ray computed tomography (CT) an important objective is to reduce the radiation dose without significantly degrading the image quality. Compressed sensing (CS) enables the radiation dose to be reduced by producing diagnostic images from a limited number of projections. However, conventional CS-based algorithms are computationally intensive and time-consuming. We propose a new algorithm that accelerates the CS-based reconstruction by using a fast pseudopolar Fourier based Radon transform and rebinning the diverging fan beams to parallel beams. The reconstruction process is analyzed using a maximum-a-posterior approach, which is transformed into a weighted CS problem. The weights involved in the proposed model are calculated based on the statistical characteristics of the reconstruction process, which is formulated in terms of the measurement noise and rebinning interpolation error. Therefore, the proposed method not only accelerates the reconstruction, but also removes the rebinning and interpolation errors. Simulation results are shown for phantoms and a patient. For example, a 512 × 512 Shepp-Logan phantom when reconstructed from 128 rebinned projections using a conventional CS method had 10% error, whereas with the proposed method the reconstruction error was less than 1%. Moreover, computation times of less than 30 sec were obtained using a standard desktop computer without numerical optimization.

No MeSH data available.


Related in: MedlinePlus