Robust Estimation of Scatter and Primary Signals using Multi-View Information for Moving BlockerBased Cone-Beam Computed Tomography

The moving blocker method has been demonstrated to be effective for scatter correction (SC) of cone-beam computed tomography (CBCT). However, a fixed thresholding was usually used to detect the blocker edge in the projection images, which only works in high-contrast uniform regions. The edge detection errors, caused by low-contrast and non-uniform intensity, can lead to significant artifacts in the reconstructed images. In this work, we propose to use the projection images at multiple adjacent views to estimate the scatter signal directly without identifying the blocked regions. Subsequently, the scatter signal can serve as an adaptive threshold to locate the unblocked regions for the estimation of the primary signal. The experimental results using an anthropomorphic pelvis phantom CBCT data show that the proposed method can robustly estimate the scatter and primary signals by avoiding blocker edge detection errors and lead to much improved reconstruction images.