Scatter correction for cone-beam computed tomography using simulated object models

Abstract

Scattered radiation is a major source of artifacts in flat detector based cone-beam computed tomography. In this paper, a novel software-based method for retrospective scatter correction is described and evaluated. The method is based on approximation of the imaged object by a simple geometric model (e.g., a homogeneous water-like ellipsoid) that is estimated from the set of acquired projections. This is achieved by utilizing a numerical optimization procedure to determine the model parameters for which there is maximum correspondence between the measured projections and the projections of the model. Monte-Carlo simulations of this model are used for calculation of scatter estimates for the acquired projections. Finally, using the scatter-corrected projections, tomographic reconstruction is conducted by means of cone-beam filtered back-projection. The correction method is evaluated using simulated and experimentally acquired projection data sets of geometric and physical head phantoms. It is found that the method is able to accurately estimate mean scatter levels in X-ray projections, allowing to significantly reduce scatter-caused artifacts in 3D reconstructed images.

X‐ray scattering in single‐ and dual‐source CT

“…͑2͒ In a second scenario, we assume that the contribution of scatter can be calculated precisely by other means. [13][14][15] For this case, scatter is corrected in an ideal manner by subtracting the calculated value from the measured intensity. The noise of the scatter, however, is not correctable and still superposes the total intensity.…”

Modelling the physics in the iterative reconstruction for transmission computed tomography

“…A somewhat related analytical model (Yao and Leszczynski 2009) separates the scatter distribution into object-dependent terms that are captured by the primary intensity, and terms which are independent of the object and thus can be pre-computed; primary is iteratively estimated from measured projection using this model. Other possible analytical approaches involve approximating the object by a simple ellipsoid, for which scatter can be either pre-computed or estimated at relatively low cost using MC simulations (Bertram et al 2006), a hybrid method combining this approach with scatter kernels (Meyer et al 2010), and algorithms utilising calibration scans to establish relationships between scatter properties of typical objects (e.g. spatial distribution of scatter-to-primary ratio) and some basic parameters accessible in projection images or raw reconstructions (e.g.…”

“…Potentially interesting are methods to accurately model effects of object non-uniformity on scatter re-projection S nu when low noise scatter projections of uniform objects S u are already known or can be calculated quickly and accurately with e.g. the above mentioned analytical methods (Li et al 2008, Maltz et al 2008, Sun and Star-Lack 2010, Bertram et al 2006). Using Correlated Monte Carlo methods (Spanier and Gelbard 1969), such a scatter estimate can then be rapidly transformed to the scatter projection of a non-uniform object by scaling it with a ratio of MC simulations of the non-uniform object $S_{MC}^{nu}$ and the uniform object $S_{MC}^u$, both obtained with only a very low number photon tracks ( $S^{nu}=S^u\times S_{MC}^{nu}/S_{MC}^u$), but in which correlated noise partly cancels out during division, as has been shown for SPECT scatter modelling (Beekman et al 1999).…”

Semi-empirical scattering correction model for MSCT

“…A different method is based on calculations of a single scatter process generalized to fit multiple scatter processes by an adjustment factor 3 . Other works related to cone-beam CT using flat panel detectors are reported [4][5][6][7] . Hardware solution, achieved by implementing a 2D anti-scatter grid, that reduces the scattering in both the fan beam and the longitudinal directions, is recently reported 8 .…”