WE-EF-207-08: Improve Cone Beam CT Using a Synchronized Moving Grid, An Inter-Projection Sensor Fusion and a Probability Total Variation Reconstruction




To present a cone beam computed tomography (CBCT) system, which uses a synchronized moving grid (SMOG) to reduce and correct scatter, an inter-projection sensor fusion (IPSF) algorithm to estimate the missing information blocked by the grid, and a probability total variation (pTV) algorithm to reconstruct the CBCT image.


A prototype SMOG-equipped CBCT system was developed, and was used to acquire gridded projections with complimentary grid patterns in two neighboring projections. Scatter was reduced by the grid, and the remaining scatter was corrected by measuring it under the grid. An IPSF algorithm was used to estimate the missing information in a projection from data in its 2 neighboring projections. Feldkamp-Davis-Kress (FDK) algorithm was used to reconstruct the initial CBCT image using projections after IPSF processing for pTV. A probability map was generated depending on the confidence of estimation in IPSF for the regions of missing data and penumbra. pTV was finally used to reconstruct the CBCT image for a Catphan, and was compared to conventional CBCT image without using SMOG, images without using IPSF (SMOG + FDK and SMOG + mask-TV), and image without using pTV (SMOG + IPSF + FDK).


The conventional CBCT without using SMOG shows apparent scatter-induced cup artifacts. The approaches with SMOG but without IPSF show severe (SMOG + FDK) or additional (SMOG + TV) artifacts, possibly due to using projections of missing data. The 2 approaches with SMOG + IPSF removes the cup artifacts, and the pTV approach is superior than the FDK by substantially reducing the noise. Using the SMOG also reduces half of the imaging dose.


The proposed technique is promising in improving CBCT image quality while reducing imaging dose.