Total variation regularization in measurement and image space for PET reconstruction

Beitrag in einer Fachzeitschrift

Details zur Publikation

Autorinnen und Autoren: Burger M, Mueller J, Papoutsellis E, Schoenlieb CB
Zeitschrift: Inverse Problems
Jahr der Veröffentlichung: 2014
Band: 30
ISSN: 0266-5611
Sprache: Englisch


© 2014 IOP Publishing Ltd. The aim of this paper is to test and analyse a novel technique for image reconstruction in positron emission tomography, which is based on (total variation) regularization on both the image space and the projection space. We formulate our variational problem considering both total variation penalty terms on the image and on an idealized sinogram to be reconstructed from a given Poisson distributed noisy sinogram. We prove existence, uniqueness and stability results for the proposed model and provide some analytical insight into the structures favoured by joint regularization. For the numerical solution of the corresponding discretized problem we employ the split Bregman algorithm and extensively test the approach in comparison to standard total variation regularization on the image. The numerical results show that an additional penalty on the sinogram performs better on reconstructing images with thin structures.

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Zuletzt aktualisiert 2018-03-12 um 15:53