Affiliations: Centrum Wiskunde en Informatica, Computational Imaging group, Science Park 123, 1098 XG Amsterdam, The Netherlands. {henri.der.sarkissian, nicola.vigano, joost.batenburg}@cwi.nl
Correspondence:
[*]
Address for correspondence: Centrum Wiskunde en Informatica, Science Park 123, 1098 XG Amsterdam, The Netherlands.
Note: [†] Also affiliated at: Leiden University, Department of Mathematics, 2300 RA Leiden, The Netherlands
Abstract: Computed Tomography (CT) is an imaging technique that allows to reconstruct volumetric information of the analyzed objects from their projections. The most popular reconstruction technique is the Filtered Back Projection (FBP). It has the advantage of being the fastest technique available, but also the disadvantage to require a high number of projections to retrieve good quality reconstructions. In this article we propose a segmentation method for tomographic volumes composed of few materials. Our method combines existing high-quality variational segmentation frameworks with the data consistency approach used in tomography and discrete tomography. We show that our algorithm performs well under high noise level and with moderately low number of projections, and that the data consistency significantly improves the segmentation, at the cost of only one FBP reconstruction and forward projection.
