|
Reducing X-ray exposure to the patients is one of the major research efforts in the computed tomography (CT) field, and
one of the common strategies to achieve it is to lower the mAs setting (by lowering the X-ray tube current and/or
shortening the exposure time) in currently available CT scanners. However, the image quality from low mAs acquisition
is severely degraded due to excessive quantum noise, if no adequate noise control is applied during image
reconstruction. Different from filter-based algorithms, statistical reconstruction algorithms model the statistical property
of the noise using a cost function and minimize the cost function for an optimal solution in statistical sense. The
algorithms have shown to be feasible and effective in both sinogram and image domain. In our previous researches, we
proposed penalized reweighted least-squares (PRWLS) approaches to sinogram noise reduction and image
reconstruction for low-dose CT imaging, which are in this statistical category. This work is a continuation of the
research along this direction and aims to compare the reconstruction quality of two different PRWLS implementations
for low-dose cone-beam CT reconstruction: (1) PRWLS sinogram restoration followed by analytical Feldkamp-Davis-
Kress reconstruction, (2) fully iterative PRWLS image reconstruction. Inspired by our recent study on the variance of
low-mAs projection data in presence of electric noise background, a more accurate weight was adopted in the weighted
least-squares term. An anisotropic quadratic form penalty was utilized in both PRWLS implementations to preserve
edges during noise reduction. Experiments using the CatPhan® 600 phantom and anthropomorphic head phantom were
carried to study the relevant performance of these two implementations on image reconstruction. The results revealed
that the implementation (2) can outperform implementation (1) in terms of noise-resolution tradeoff measurement and
analysis of the reconstructed small objects due to its matched image edge-preserved penalty in the image domain.
However, those gains are offset by the cost of increased computational time. Thus, further examination of real patient
data is necessary to show the clinical significance of the iterative PRWLS image reconstruction over the PRWLS
sinogram restoration.
|
