Adaptive spatially dependent weighting scheme for tomosynthesis reconstruction

Digital Tomosynthesis (DT) is an x-ray limited-angle imaging technique. An accurate image reconstruction in tomosynthesis is a challenging task due to the violation of the tomographic sufficiency conditions. A classical "shift-and-add" algorithm (or simple backprojection) suffers from blurring artifacts, produced by structures located above and below the plane of interest. The artifact problem becomes even more prominent in the presence of materials and tissues with a high x-ray attenuation, such as bones, microcalcifications or metal. The focus of the current work is on reduction of ghosting artifacts produced by bones in the musculoskeletal tomosynthesis. A novel dissimilarity concept and a modified backprojection with an adaptive spatially dependent weighting scheme (ωBP) are proposed. Simulated data of software phantom, a structured hardware phantom and a human hand raw-data acquired with a Siemens Mammomat Inspiration tomosynthesis system were reconstructed using conventional backprojection algorithm and the new ωBP-algorithm. The comparison of the results to the non-weighted case demonstrates the potential of the proposed weighted backprojection to reduce the blurring artifacts in musculoskeletal DT. The proposed weighting scheme is not limited to the tomosynthesis limitedangle geometry. It can also be adapted for Computed Tomography (CT) and included in iterative reconstruction algorithms (e.g. SART).