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WE-G-18A-06: Sinogram Restoration in Helical Cone-Beam CT.

PURPOSE
To extend CT sinogram restoration, which has been shown in 2D to reduce noise and to correct for geometric effects and other degradations at a low computational cost, from 2D to a 3D helical cone-beam geometry.


METHODS
A method for calculating sinogram degradation coefficients for a helical cone-beam geometry was proposed. These values were used to perform penalized-likelihood sinogram restoration on simulated data that were generated from the FORBILD thorax phantom. Sinogram restorations were performed using both a quadratic penalty and the edge-preserving Huber penalty. After sinogram restoration, Fourier-based analytical methods were used to obtain reconstructions. Resolution-variance trade-offs were investigated for several locations within the reconstructions for the purpose of comparing sinogram restoration to no restoration. In order to compare potential differences, reconstructions were performed using different groups of neighbors in the penalty, two analytical reconstruction methods (Katsevich and single-slice rebinning), and differing helical pitches.


RESULTS
The resolution-variance properties of reconstructions restored using sinogram restoration with a Huber penalty outperformed those of reconstructions with no restoration. However, the use of a quadratic sinogram restoration penalty did not lead to an improvement over performing no restoration at the outer regions of the phantom. Application of the Huber penalty to neighbors both within a view and across views did not perform as well as only applying the penalty to neighbors within a view. General improvements in resolution-variance properties using sinogram restoration with the Huber penalty were not dependent on the reconstruction method used or the magnitude of the helical pitch.


CONCLUSION
Sinogram restoration for noise and degradation effects for helical cone-beam CT is feasible and should be able to be applied to clinical data. When applied with the edge-preserving Huber penalty, sinogram restoration leads to an improvement in resolution-variance tradeoffs.