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

Abstract

Cone-beam computed tomography (CBCT) is an important imaging modality for image-guided radiotherapy and adaptive radiotherapy. Feldkamp-Davis-Kress (FDK) method is widely adopted in clinical CBCT reconstructions due to its fast and robust application. While iterative algorithms have been shown to outperform FDK techniques in reducing noise and imaging dose, they are unable to correct projection-domain artefacts such as beam hardening and scatter. Empirical correction techniques require a holistic approach as beam hardening and scatter coexist in the measurement data. This multi-part proof of concept study conducted in MATLAB presents a novel approach to artefact reduction for CBCT image reconstruction. Firstly, we decoupled the beam hardening and scatter contributions originating from the imaging object and the bowtie filter. Next, a model was constructed to apply pixel-wise corrections to separately account for artefacts induced by the imaging object and the bowtie filter, in order to produce mono-energetic equivalent and scatter-compensated projections. Finally, the effectiveness of the correction model was tested on an offset phantom scan as well as a clinical brain scan. A conjugategradient least-squares algorithm was implemented over five iterations using FDK result as the initial input. Our proposed correction model was shown to effectively reduce cupping and shading artefacts in both phantom and clinical studies. This simple yet effective correction model could be readily implemented by physicists seeking to explore the benefits of iterative reconstruction.

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

“…The other three reconstructions compared different approaches to truncation artifact reduction: by extending the reconstruction AFOV alone, by using planning FBCT information directly in the extended AFOV, and by using preconditioned planning FBCT information in the extended AFOV. Raw CBCT projections were corrected for beam hardening and scatter artifacts using an in‐house method described in our earlier work 23 . For each reconstruction, the CGLS algorithm was run initially for 10 iterations at 2 mm resolution.…”

Feasibility evaluation of kilovoltage cone-beam computed tomography dose calculation following scatter correction: investigations of phantom and representative tumor sites

“…Their study indicates that as the image contrast improves, scatter artifacts are eliminated. Cai et al ( 30 ) outlined an approach that separately corrected for both effects in the projection domain. The model was shown to effectively reduce shading and cupping artifacts in both phantom and clinical studies.…”

Dual-domain network with transfer learning for reducing bowtie-filter induced artifacts in half-fan cone-beam CT

“…However, it can induce eclipse shape artifacts that typically have a bright ring and dark shade in the reconstructed image as shown in Fig 1 . Artifacts from the bowtie-filter may build up in various forms depending on the geometric shape of the filter and the scanning system conditions. Since the artifacts can severely degrade the soft-tissue contrast in CT images, there have been studies for reducing these artifacts and for clarifying their physical causes [1][2][3].…”

“…This spatially varying spectral incident beam, together with the nonlinear detector energy-response characteristics, can cause data inconsistencies from the linear imaging model resulting in peculiar beam-hardening artifacts such as eclipse artifacts. M. Cai et al [3] introduced a decoupling technique that decomposes the artifacts into bowtie filter-induced beam-hardening and object-induced cupping artifacts. The decoupling scheme is valid from the physical perspectives in that the artifacts originated from the bowtie-filter can be separated from the object-originated ones.…”

“…The decoupling scheme is valid from the physical perspectives in that the artifacts originated from the bowtie-filter can be separated from the object-originated ones. However, the suggested method in [3] requires heuristic parameter optimization in each case and has to handle the correction mismatch in an iterative reconstruction framework that requires heavy computational cost. A neural-network-based artifact correction method can be an alternative; a single domain network (e.g., in image-domain) may not be a suitable candidate though since physical factors are hardly incorporated in such a network, possibly resulting in residual artifacts and structural distortions.…”