Affiliations: iMinds – Vision Lab, University of Antwerp, Belgium. hilde.segers@ua.ac.be | iMinds – Vision Lab, University of Antwerp, Belgium. willemjan.palenstijn@ua.ac.be | Centrum voor Wiskunde en Informatica, Amsterdam, The Netherlands. K.J.Batenburg@cwi.nl | iMinds – Vision Lab, University of Antwerp, Belgium. jan.sijbers@ua.ac.be
Note: [] This work was financially supported by the iMinds-SuperMRI project (Interdisciplinary Institute for Technology, a research institute founded by the Flemish Government) and by the TOP BOF project Quantitative Tomographic Segmentation of Magnetic Resonance Images. Address for correspondence: iMinds – Vision Lab, University of Antwerp, Universiteitsplein 1 (N.115), B-2610 Antwerpen, Belgium
Abstract: Discrete tomography (DT) is concerned with the tomographic reconstruction of images that consist of only a small number of grey levels. Recently, DART, a practical algorithm was introduced for discrete tomography, which was validated in the domain of X-ray computed and electron tomography. In this paper, DART is introduced for magnetic resonance imaging. Using simulation experiments, it is shown that the proposed MRI-DART algorithm is capable of computing high quality reconstructions from substantially fewer data compared to state-of-the-art MRI reconstruction methods.
