X-ray computed tomography systems typically measure attenuation along straight-line paths, with off-angle Compton-scattered photons treated as noise. We seek to improve reconstructions for few-view systems by fusing attenuation data with scatter measurements, as the broken-ray paths of scattered photons provide additional geometric views. We demonstrate a nonlinear Landweber algorithm for fusing attenuation and scatter data, yielding improved reconstructions on experimental data. Results also show benefit from optimizing weighting of attenuation vs. scatter data during reconstruction.

This presentation is part of Minisymposium “MS33 - Advances in reconstruction algorithms for computed tomography (4 parts)”
organized by: Gunay Dogan (Theiss Research, NIST) , Harbir Antil (George Mason University) , Elena Loli Piccolomini (Dept. Computer Science and Engineering, University of Bologna) , Samuli Siltanen (University of Helsinki) .

Authors:

Brian Tracey (Tufts University)

Keywords:

computed tomography, image reconstruction, inverse problems