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One limitation of computed tomography is that no bijective relation exists between the composition of the material and the greyscale value in the reconstruction. More information on the material composition can be obtained by performing multiple scans using different X-ray energies, which in turn leads to technical issues with aligning the projections from different energies. We propose a technique based on structural similarities, which allows reconstructing the object at multiple energies without projection alignment. Additionally, we will introduce the openly available tomographic datasets from the University of Helsinki, including multi-energy CT data.
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) .