Decoupling of bowtie and object effects for beam hardening and scatter artefact reduction in iterative cone-beam CT

Pixel-by-pixel correction of beam hardening artifacts by bowtie filter in fan-beam CT

Objective. Beam hardening (BH) artifacts in computed tomography (CT) images originate from the polychromatic nature of x-ray photons. In a CT system with a bowtie filter, residual BH artifacts remain when polynomial fits are used. These artifacts lead to worse visuals, reduced contrast, and inaccurate CT numbers. This work proposes a pixel-by-pixel correction (PPC) method to reduce the residual BH artifacts caused by a bowtie filter.Approach. The energy spectrum for each pixel at the detector after the photons pass through the bowtie filter was calculated. Then, the spectrum was filtered through a series of water slabs with different thicknesses. The polychromatic projection corresponding to the thickness of the water slab for each detector pixel could be obtained. Next, we carried out a water slab experiment with a mono energyE= 69 keV to get the monochromatic projection. The polychromatic and monochromatic projections were then fitted with a 2nd-order polynomial. The proposed method was evaluated on digital phantoms in a virtual CT system and phantoms in a real CT machine.Main results. In the case of a virtual CT system, the standard deviation of the line profile was reduced by 23.8%, 37.3%, and 14.3%, respectively, in the water phantom with different shapes. The difference of the linear attenuation coefficients (LAC) in the central and peripheral areas of an image was reduced from 0.010 to 0.003cm-1and 0.007cm-1to 0 in the biological tissue phantom and human phantom, respectively. The method was also validated using CT projection data obtained from Activion16 (Canon Medical Systems, Japan). The difference in the LAC in the central and peripheral areas can be reduced by a factor of two.Significance. The proposed PPC method can successfully remove the cupping artifacts in both virtual and authentic CT images. The scanned object's shapes and materials do not affect the technique.

UBES: Unified scatter correction using ultrafast Boltzmann equation solver for conebeam CT

A semi-analytical solution to the unified Boltzmann equation is constructed to exactly describe the scatter distribution on a flat-panel detector for high-quality conebeam CT (CBCT) imaging. The solver consists of three parts, including the phase space distribution estimator, the effective source constructor and the detector signal extractor. Instead of the tedious Monte Carlo solution, the derived Boltzmann equation solver achieves ultrafast computational capability for scatter signal estimation by combining direct analytical derivation and time-efficient one-dimensional numerical integration over the trajectory along each momentum of the photon phase space distribution. The execution of scatter estimation using the proposed ultrafast Boltzmann equation solver (UBES) for a single projection is finalized in around 0.4 seconds. We compare the performance of the proposed method with the state-of-the-art schemes, including a time-expensive Monte Carlo (MC) method and a conventional kernel-based algorithm using the same dataset, which is acquired from the CBCT scans of a head phantom and an abdominal patient. The evaluation results demonstrate that the proposed UBES method achieves comparable correction accuracy compared with the MC method, while exhibits significant improvements in image quality over learning and kernel-based methods. With the advantages of MC equivalent quality and superfast computational efficiency, the UBES method has the potential to become a standard solution to scatter correction in high-quality CBCT reconstruction.

Reducing axial truncation artifacts in iterative cone-beam CT for radiation therapy using a priori preconditioned information

PURPOSE

Cone-beam computed tomography (CBCT) is increasingly utilized in radiation therapy for image guidance and adaptive applications. While iterative reconstruction algorithms have been shown to outperform traditional filtered back-projection methods in improving image quality and reducing imaging dose, they cannot handle data truncation in the axial view, which frequently occurs in the full-fan partial-trajectory acquisition mode. This proof-of-concept study presents a novel approach on truncation artifact reduction by utilizing a priori preconditioned information as the initial input for the iterative algorithm.

METHODS

Projections containing axial truncation were used for image reconstruction in extended axial field-of-view (AFOV) using the conjugate gradient least-squares (CGLS) algorithm. A priori information in the form of a planning fan-beam CT (FBCT) was repositioned in the expected CBCT imaging geometry, then further processed to dampen high-density features and convolved with a cubic Gaussian kernel to ensure differentiability for the gradient descent method. Anatomical and positional differences between the estimated and the actual imaging object were introduced to verify the efficacy of the proposed method.

RESULTS

Extending the reconstruction AFOV alone could partially reduce truncation artifact. Using a priori information directly resulted in ghosting artifact when there were anatomical and positional differences between the estimated and the actual imaging object. Using a priori preconditioned information was shown to effectively reduce truncation artifact and recover peripheral information.

CONCLUSIONS

Using a priori preconditioned information can effectively alleviate truncation artifact and assist recovery of peripheral information in iterative CBCT reconstruction.